tacit knowledge

The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion
by John Hagel Iii and John Seely Brown
Published 12 Apr 2010

In the process, they create significant new knowledge. But there is a problem—this knowledge is not easily accessible. What we’re focusing on is tacit knowledge—the “know-how” rather than the “know-what”—that we often have difficulty expressing. Much knowledge starts as tacit knowledge. A good part of it is eventually codified into explicit knowledge, although all knowledge ultimately represents some blend of explicit and tacit knowledge, for not all tacit knowledge is codifiable. Imagine instructing someone on how to ride a bike—something that you learn by doing, rather than by reading a set of instructions.

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We post difficult research problems and give rewards to those who can offer solutions. But what about tacit knowledge? How do we access it? Accessing this kind of knowledge typically requires long-term trust-based relationships. Trust is necessary because of the inevitable fumbling that occurs as we try to express and share tacit knowledge. Without trust we may lack the respect for the other needed to stay with them as they fumble. Trust also fosters the shared understanding that makes it easier to access tacit knowledge. This suggests that one key dimension of the Big Shift is a movement from a world where value is concentrated in transactions to one where it resides in large networks of long-term relationships.

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We not only have the opportunity to access the tacit knowledge other people have gained from their experiences—and to share our own—but can begin to create relationships that may themselves spawn new tacit knowledge as we begin to collaborate on areas of shared interest. Serendipity becomes much more than a one-time encounter or an end in itself: It becomes the crucial means of access to rich flows of tacit knowledge both now and in the future. From our perspective, attraction is particularly powerful when it leads to serendipitous encounters with people on the edge—and then to long-term relationships with them. This form of attraction offers privileged access to tacit knowledge and rare insight into new opportunities. It also lowers our risk.

Business Metadata: Capturing Enterprise Knowledge
by William H. Inmon , Bonnie K. O'Neil and Lowell Fryman
Published 15 Feb 2008

See Chapter 8 for examples of business metadata delivery (or as knowledge management folks say, dissemination.) 264 Chapter 15 15.4 Knowledge Management and Business Metadata Business Metadata and Tacit Knowledge The relationship between knowledge management and business metadata becomes a little weak and tenuous when the discussion turns to tacit knowledge, however. Tacit knowledge does not easily lend itself to articulation and transformation into business metadata. Here’s part of Wikipedia’s formal definition of tacit knowledge: Tacit knowledge consists often of habits and culture that we do not recognize in ourselves. In the field of knowledge management the concept of tacit knowledge refers to a knowledge which is only known to you and hard to share with someone else, which is the opposite of the concept of explicit knowledge.

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In the field of knowledge management the concept of tacit knowledge refers to a knowledge which is only known to you and hard to share with someone else, which is the opposite of the concept of explicit knowledge. (Wikipedia, “Tacit Knowledge,” 2006) Later, the same article states that tacit knowledge “involves learning and skill but not in a way that can be written down.” Business metadata is the result of articulating knowledge so that it can be disseminated to a user; it is stored as data, usually in a DBMS (but can also be stored in groupware like wikis). Since tacit knowledge typically isn’t written down, it cannot be stored as business metadata unless it is made explicit knowledge. The knowledge management field is highly concerned with the transmission of tacit knowledge in face-to-face interactions.

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So there appears to be a facet of knowledge management that cannot be articulated as business metadata. 15.4.1 Making Tacit Knowledge Explicit Tacit knowledge is therefore “know-how.” It is the ability to just know how to do something, perform a job, or notice when something does not look quite right—without being able to explain it. Perhaps one of the biggest challenges for knowledge management and the attempt to capture business metadata is to get expert employees to be able to express tacit knowledge; if it can be articulated, it can be put in a business metadata knowledge base. Sometimes just the act of socialization can drive out tacit knowledge, concretize it, and create the necessary artifacts to add to a knowledge base.

The Connected Company
by Dave Gray and Thomas Vander Wal
Published 2 Dec 2014

Tacit and Explicit Knowledge Knowledge can be classified into two categories: explicit knowledge, which can be counted, quantified, documented, and easily shared, and tacit knowledge, which includes things that are difficult to measure and share, like expertise, technical know-how, informal relationships, intuition, mental models, beliefs, and trust. It is tacit knowledge that constitutes our understanding of reality, and tacit knowledge makes up the bulk of the knowledge in most organizations. As the saying goes, the company’s intellectual property walks out the door every evening. The learning challenge for the company comes from the dynamic relationship between the two forms of knowledge. Tacit knowledge is where the action is, and in most cases, it’s the people with the tacit knowledge that deliver the results.

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Reflection can be a very personal, individual process. An apprenticeship is a way for the master and apprentice to share the growth spiral, by making tacit knowledge explicit and then translating it back into tacit knowledge again. When the journalist comes to the editor with a story, she has represented her “reporting knowledge” explicitly, in the form of a document. When the editor and reporter sit down together to review and rewrite the story, the editor is making his tacit knowledge explicit in the form of the rewrite and the questions he asks. When the journalist goes out in the field again to write her next story, she will try to internalize that knowledge and write a better story, and the cycle begins again.

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Tacit knowledge is where the action is, and in most cases, it’s the people with the tacit knowledge that deliver the results. But the only way tacit knowledge can be broadly shared is by translating it into explicit knowledge—a very difficult task that very few companies have mastered. One way to solve this problem is apprenticeship. Consider the newspaper business: when a rookie journalist is assigned a story, she will go out, do the legwork, and come up with a first draft. Then she will sit down with an editor (a former journalist) who goes through the story, line by line—usually at the same terminal at the same time—asking questions that he feels are unanswered by the story.

Why Information Grows: The Evolution of Order, From Atoms to Economies
by Cesar Hidalgo
Published 1 Jun 2015

For those familiar with the literature, I will be building on the distinction between explicit and tacit knowledge advanced half a century ago by Michael Polanyi. I will be using the word knowhow to describe tacit knowledge, as I prefer using two distinct nouns to denote two different concepts instead of using the same noun and adding an adjective (explicit or tacit). For a summary of the concepts of tacit and explicit knowledge I recommend Harry Collins, Tacit and Explicit Knowledge (Chicago: University of Chicago Press, 2010). There, Collins divides tacit knowledge into relational tacit knowledge, which includes what we could describe in principle but often fail to describe; somatic tacit knowledge, which relates to things we can do with our bodies but cannot describe (such as riding a bike); and collective tacit knowledge, which involves knowledge that draws meaning from social interactions, such as the rules for language. 4.

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There, Collins divides tacit knowledge into relational tacit knowledge, which includes what we could describe in principle but often fail to describe; somatic tacit knowledge, which relates to things we can do with our bodies but cannot describe (such as riding a bike); and collective tacit knowledge, which involves knowledge that draws meaning from social interactions, such as the rules for language. 4. This quote can be found in the biography of Marvin Minsky on the Computer History Museum’s website: www.computerhistory.org/fellowawards/hall/bios/Marvin,Minsky. CHAPTER 2: THE BODY OF THE MEANINGLESS 1. My friend and undergraduate advisor Francisco Claro suggested this calculation to me a few years ago. His example at that time was a fighter jet. 2.

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Hence, the people making these products need to have access to the knowledge and knowhow required to make them in their “raw” form—that is, the knowledge and knowhow embodied in human flesh, not the practical uses of knowledge and knowhow embodied implicitly in items. In academic circles this humanly embodied knowledge is referred to as “tacit” knowledge when it involves knowhow that cannot be explicitly described. As the Hungarian polymath Michael Polanyi cleverly noted, often “we know more than we can tell.”3 The separation between the practical uses of knowledge and knowhow and the knowledge and knowhow embodied in people implies that making products will be more difficult in the places where obtaining access to people with specific forms of knowledge and knowhow is more difficult.

The Glass Cage: Automation and Us
by Nicholas Carr
Published 28 Sep 2014

The sophisticated jobs Levy and Murnane identified as lying beyond the reach of computers—in addition to driving, they pointed to teaching and medical diagnosis—were a mix of the mental and the manual, but they all drew on tacit knowledge. Google’s car resets the boundary between human and computer, and it does so more dramatically, more decisively, than have earlier breakthroughs in programming. It tells us that our idea of the limits of automation has always been something of a fiction. We’re not as special as we think we are. While the distinction between tacit and explicit knowledge remains a useful one in the realm of human psychology, it has lost much of its relevance to discussions of automation. THAT DOESN’T mean that computers now have tacit knowledge, or that they’ve started to think the way we think, or that they’ll soon be able to do everything people can do.

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It seemed a sure bet, to them and to pretty much everyone else, that steering wheels would remain firmly in the grip of human hands.4 In assessing computers’ capabilities, economists and psychologists have long drawn on a basic distinction between two kinds of knowledge: tacit and explicit. Tacit knowledge, which is also sometimes called procedural knowledge, refers to all the stuff we do without thinking about it: riding a bike, snagging a fly ball, reading a book, driving a car. These aren’t innate skills—we have to learn them, and some people are better at them than others—but they can’t be expressed as a simple recipe.

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When you make a turn through a busy intersection in your car, neurological studies show, many areas of your brain are hard at work, processing sensory stimuli, making estimates of time and distance, and coordinating your arms and legs.5 But if someone asked you to document everything involved in making that turn, you wouldn’t be able to, at least not without resorting to generalizations and abstractions. The ability resides deep in your nervous system, outside the ambit of your conscious mind. The mental processing goes on without your awareness. Much of our ability to size up situations and make quick judgments about them stems from the fuzzy realm of tacit knowledge. Most of our creative and artistic skills reside there too. Explicit knowledge, which is also known as declarative knowledge, is the stuff you can actually write down: how to change a flat tire, how to fold an origami crane, how to solve a quadratic equation. These are processes that can be broken down into well-defined steps.

User Stories Applied: For Agile Software Development
by Mike Cohn
Published 1 Mar 2004

Further, as users learn how to characterize their needs in stories that are directly useful to developers, developers more actively engage the users. This virtuous cycle benefits everyone involved in developing or using the software. Stories Build Up Tacit Knowledge Because of the emphasis placed on face-to-face communication, stories promote the accumulation of tacit knowledge across the team. The more often developers and customers talk to each other and among themselves, the more knowledge builds up within the team. Why Not Stories? Having looked at a number of reasons why stories are a preferred approach to agile requirements, let’s also consider their drawbacks.

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Stories encourage opportunistic development, in which the team readily shifts focus between high and low levels of detail as opportunities are discovered. Stories enhance the level of tacit knowledge on the team. User stories encourage participatory, rather than empirical, design, in which users become active and valued participants in designing the behavior of the software. While there are many reasons to use stories, they do have some drawbacks: on large projects it can be difficult to keep hundreds or thousands of stories organized; they may need to be augmented with additional documents for traceability; and, while great at improving tacit knowledge through face–to–face communication, conversations do not scale adequately to entirely replace written documents on large projects.

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Answer: User stories emphasize verbal communication, are comprehensible by everyone, are the right size for planning, support iterative development, encourage deferring detail, support opportunistic design, encourage participatory design and build up tacit knowledge. 13.2 What can be two drawbacks to using user stories? Answer: On large projects it can be difficult to keep hundreds or thousands of stories organized; stories may need to be augmented with additional documents for traceability; and, while great at improving tacit knowledge through face-to-face communication, conversations do not scale adequately to entirely replace written documents on large projects. 13.3 What is the key difference between participatory and empirical design?

The Intelligence Trap: Revolutionise Your Thinking and Make Wiser Decisions
by David Robson
Published 7 Mar 2019

506. 55 Sternberg, R.J. (2000), Practical Intelligence in Everyday Life, Cambridge: Cambridge University Press, pp. 144?200. See also Wagner, R.K. and Sternberg, R.J. (1985), ‘Practical Intelligence in Real-world Pursuits: The Role of Tacit Knowledge’, Journal of Personality and Social Psychology, 49(2), 436?58. See also Cianciolo, A.T., et al. (2006), ‘Tacit Knowledge, Practical Intelligence and Expertise’, in Ericsson, K.A. (ed.), Cambridge Handbook of Expertise and Expert Performance, Cambridge: Cambridge University Press. For an independent discussion of Sternberg’s studies, see Perkins, D. (1995), Outsmarting IQ: The Emerging Science of Learnable Intelligence, New York: Free Press, pp. 83?

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Practical intelligence, meanwhile, concerns a different kind of innovation: the ability to plan and execute an idea, and to overcome life’s messy, ill-defined problems in the most pragmatic way possible. It includes traits like ‘metacognition’ – whether you can judge your strengths and your weaknesses and work out the best ways to overcome them, and the unspoken, tacit knowledge that comes from experience and allows you to solve problems on the fly. It also includes some of the skills that others have called emotional or social intelligence – the ability to read motives and to persuade others to do what you want. Among the Termites, Shelley Smith Mydans’ quick thinking as a war reporter, and her ability to navigate her escape from a Japanese prison camp, may best personify this kind of intelligence.

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In the military, meanwhile, Sternberg examined various measures of leadership performance among platoon commanders, company commanders and battalion commanders. They were asked how to deal with soldier insubordination, for instance – or the best way to communicate the goals of a mission. Again, practical intelligence – and tacit knowledge, in particular – predicted their leadership ability better than traditional measures of general intelligence.55 Sternberg’s measures may lack the elegance of a one-size-fits-all IQ score, but they are a step closer to measuring the kind of thinking that allowed Jess Oppenheimer and Shelley Smith Mydans to succeed where other Termites failed.56 ‘Sternberg’s on the right track,’ Flynn told me.

Kanban: Successful Evolutionary Change for Your Technology Business
by David J. Anderson
Published 6 Apr 2010

If a team is co-located and always available to each other, this memory loss can be corrected through repeated discussion or tapping the shared memory of a group of people. So agile teams co-located in a shared workspace are more likely to retain tacit knowledge longer. Regardless of this, tacit knowledge depreciates with time, so shorter lead times are essential for tacit knowledge processes. We know that reducing work-in-progress is directly related to reducing lead times. Hence, we can infer that there will be lower tacit-knowledge depreciation when we have less work-in-progress, resulting in higher quality. In summary, reducing work-in-progress improves quality and enables more frequent releases.

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High quality in the released code builds trust with downstream partners such as operations, technical support, field engineering, and sales. Tacit Knowledge It’s quite easy to speculate why small batches of code improve quality. Complexity in knowledge-work problems grows exponentially with the quantity of work-in-progress. Meanwhile, our human brains struggle to cope with all this complexity. So much of knowledge transfer and information discovery in software development is tacit in nature and is created during collaborative working sessions, face-to-face. The information is verbal and visual but it’s in a casual format like a sketch on a whiteboard. Our minds have a limited capacity to store all this tacit knowledge and it degrades while we store it.

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Kanban as a Complex Adaptive System for Lean Emergent Behavior with Kanban Kanban as a Permission Giver Takeaways Part Two: Benefits of Kanban Chapter 3: A Recipe for Success Implementing the Recipe Focus on Quality Reduce Work-in-Progress and Deliver Often WIP, Lead Time, and Defects Who’s better? Frequent Releases Build Trust Tacit Knowledge Balance Demand against Throughput Create Slack Prioritize Influence Building Maturity Attack Sources of Variability to Improve Predictability Recipe for Success and Kanban Takeaways Chapter 4: From Worst to Best in Five Quarters The Problem Visualize the Workflow Factors Affecting Performance Make Process Policies Explicit Estimation Was a Waste Limit Work-in-Progress Implementing Changes Adjusting Policies Takeaways Chapter 5: A Continuous Improvement Culture Kaizen Culture Kanban Accelerates Organizational Maturity and Capability Sociological Change Takeaways Part Three: Implementing Kanban Chapter 6: Mapping the Value Stream Defining a Start and End Point for Control Work Item Types Drawing a Card Wall Demand Analysis Allocating Capacity According to Demand Anatomy of a Work Item Card Electronic Tracking Setting Input and Output Boundaries Coping with Concurrency Coping with Unordered Activities Takeaways Chapter 7: Coordination with Kanban Systems Visual Control and Pull Electronic Tracking Daily Standup Meetings Release Planning Meetings Triage Issue Log Review and Escalation Sticky Buddies Synchronizing across Geographic Locations Takeaways Chapter 8: Establishing a Delivery Cadence Transaction Costs of Delivery Agreeing a Delivery Cadence Improve Efficiency to Increase Delivery Cadence Making On-Demand or Ad Hoc Deliveries Takeaways Chapter 9: Establishing an Input Cadence Coordination Costs of Prioritization Agreeing on a Prioritization Cadence Efficiency of Prioritization Transaction Costs of Prioritization Improve Efficiency to Increase Prioritization Cadence Making On-Demand or Ad Hoc Prioritization Takeaways Chapter 10: Setting Work-in-Progress Limits Limits for Work Tasks Buffer Bottlenecks Input Queue Size Unlimited Sections of Workflow Don’t Stress Your Organization Capacity Allocation Takeaways Chapter 11: Establishing Service Level Agreements Typical Class-of-Service Definitions Expedite Fixed Delivery Date Standard Class Intangible Class Policies for Class of Service Expedite Policies Fixed Delivery Date Policies Standard Class Policies Intangible Class Determining a Service Delivery Target Assigning a Class of Service Putting Classes of Service to Use Allocate Capacity to Classes of Service Takeaways Chapter 12: Metrics and Management Reporting Tracking WIP Due Date Performance Throughput Issues and Blocked Work Items Flow Efficiency Takeaways Chapter 13: Scaling Kanban Hierarchical Requirements Decouple Value Delivery from Work Item Variability Introducing Swim Lanes Alternative Approach to Size Variability Incorporating Classes of Service Systems Integration Managing Shared Resources Takeaways Chapter 14: Operations Review Ante Meeting Set a Business Tone from the Beginning Inviting Guests Broadens the Audience and Adds Value Main Agenda Keystone of Lean Transition Appropriate Cadence Demonstrating the Value of Managers Organizational Focus Fosters Kaizen An Earlier Example Takeaways Chapter 15: Starting a Kanban Change Initiative The Primary Goal for Our Kanban System Secondary Goals for Our Kanban System Know the Goals and Articulate the Benefits Steps to Get Started WIP Limits Prioritization Delivery/Release Lead Time and Classes of Service Takeaways Part Four: Making Improvements Chapter 16: Three Types of Improvement Opportunity Bottlenecks, Waste Elimination, and Reduction of Variability Theory of Constraints Five Focusing Steps Lean, TPS, and Waste Reduction Deming and Six Sigma Fitting Kanban to Your Company Culture Takeaways Chapter 17: Bottlenecks and Non-Instant Availability Capacity-Constrained Resources Elevation Actions Exploitation/Protection Actions Subordination Actions Non-Instant Availability Resources Exploitation/Protection Actions Subordination Actions Elevation Actions Takeaways Chapter 18: An Economic Model for Lean Redefining “Waste” Transaction Costs Coordination Costs How Do You Know if an Activity Is a Cost?

In the Age of the Smart Machine
by Shoshana Zuboff
Published 14 Apr 1988

Inferential linkages between actions and their consequences need not be made explicit in order for skill to be learned or enacted. Action-centered skills are so called in part because their development, execution, and memory can remain confined to the sphere of tacit knowledge. Ulric Neisser's discussion of skill development supports the notion of a linkage between action-centered skill and tacit knowledge. 11 Ac- cording to Neisser, action skills depend upon a detailed understanding of the physical medium to which the skills are applied. These properties of a medium have been called "affordances"-the physical properties of the local environment that make a difference by shaping or con- straining what an organism can do. 12 In Neisser's view, action skills develop based upon an increasing knowledge of the "affordances" of the medium to which one's skills apply.

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These materials, while not definitive, suggest the distinguishing characteristics of each skill do- main and provide a basis for additional speculation, discussion, and research. First, what is the quality of knowledge associated with action- centered skill? According to the scientist and philosopher Michael Pola- nyi, know-how that cannot be verbalized is possible in part because of what he called "tacit knowledge." He began with the need to explain how it is that humans know more than they can say: "This fact seems obvious enough; but it is not easy to say exactly what it means. . . . We know a person's face, and can recognize it among a thousand, indeed among a million. Yet we usually cannot tell how we recognize a face we know.

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It is essential to skilled practice: the carpenter uses what he knows with every stroke of his tool." 1 3 It would seem from this description that explicit awareness has a relatively minor role in the performance of action-centered skills. We might imagine that such awareness could be invoked in order to com- 188 KNOWLEDGE AND COMPUTER-MEDIATED WORK municate or teach skills, or when a particularly problematic situation arises. It is likely, though, that attempts at explication of such tacit knowledge must always be incomplete. The knowledge is too layered and subtle to be fully articulated. That is why action-centered skill has always been learned through experience (on-the-job-training, appren- ticeships, sports practice, and so forth). Actions work better than words when it comes to learning and communicating these skills.

The Gated City (Kindle Single)
by Ryan Avent
Published 30 Aug 2011

Among the firms and individuals within the innovative city circulates a large body of knowledge of what has worked and failed so far, and what is likely to bear fruit in the future. Transplant that technology to a tabula rasa at this stage, and it will be nearly useless. As the technology matures, the importance of the technological community wanes. Much of the tacit knowledge is written down, codified, and taught in schools or training programs. Processes become standardized and easier to explain to newcomers. Consequently, it becomes easier to shift use of the technology abroad. This is a key way in which the city fuels growth across the economy, by domesticating new technologies and making them accessible enough for deployment outside the initial all-important technological community.

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Most of the technology the world has is fairly simple to use and reproduce (if not for you and I then for trained engineers), and yet there are massive wealth disparities across the world. Some of the gap is due to institutional differences and variation in education. But history is also littered with examples of economies that tried and failed to import and develop around existing technologies. Local populations unfamiliar with the deep (and often tacit) knowledge underlying the original process of innovation struggle to successfully deploy even basic technologies. Take the experience of the American South. For much of America's history, the South was an economy apart from the rest of America. Labor movement between the South and other American regions was limited.

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When northern producers attempted to develop more sophisticated industries in the South, they found their new factories in constant need of talent imported from the North. Southern engineers struggled to work around even minor technical challenges. This wasn't due to any special incompetence or laziness on the part of southern workers. They weren't stupid. They simply lacked the skills and the tacit knowledge of industrial processes to make skill-dependent industry work on a large scale. They needed to have been there for part of the earlier conversation, but they missed it. That shortcoming turned out to have significant consequences. It meant, first, that southern wage growth lagged that of the rest of the country for much of the last century.

Democracy and Prosperity: Reinventing Capitalism Through a Turbulent Century
by Torben Iversen and David Soskice
Published 5 Feb 2019

One way of reading our book is therefore to see it as tying together economic geography, national and regional systems of innovation, and political economy. As is increasingly understood in contemporary economic geography, the topographical distribution of knowledge competences is of hills and peaks rather than of a flat earth. This reflects the combination of the importance of tacit knowledge (even if partly codifiable), and of the need for colocation in the generation of tacit knowledge. Educated workers colocate in skill-clustered networks (which for them is valuable social capital) and therefore cannot be transported abroad, and companies cannot typically find alternative specialized knowledge competences elsewhere; thus, in business school jargon, “Capital chases skills.”

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The first key point is again the limited mobility of skilled knowledge-based workforces in the advanced economies. Nor can companies usually replicate the skills of the workforce elsewhere because training in tacit skills depends largely on new employees working with existing ones who can impart the tacit knowledge. Nearly always companies or skilled educated employees depend on other companies or other facilities (including research) in the area. This is strongly reinforced by and reinforces geographical specialization. 2. Not only can the advanced company not move, but it cannot seldom threaten credibly to do so.

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Companies within these skill clusters can of course be bought and sold, but the value-adding resources are much more immobile: largely because they consist of high-skilled workers who are themselves dependent on other high-skilled workers. Patents and intellectual property is only an exception to this in the rare cases in which it is not complementary with tacit knowledge—as is the case for some pharmaceutical patents. All this comes with major regulatory changes toward greater openness, both in terms of trade—including sophisticated high value-added services—but even more so in terms of capital mobility. Many of these changes took place in the second half of the 1980s (including the Single European Act).

The New Division of Labor: How Computers Are Creating the Next Job Market
by Frank Levy and Richard J. Murnane
Published 11 Apr 2004

If the seat problem is caused by one of these interactions, the factory-programmed rules will detect no error and the technician will be on his own. The second, more profound limit is summarized in Michael Polanyi’s felicitous phrase, “We can know more than we can tell.”9 Polanyi is referring to what psychologists call intuitive or tacit knowledge—knowledge that we use but cannot articulate. To grasp Polanyi’s idea, we can contrast what in essence are two extremes: a student adding a column of numbers and a bakery truck driver making a left turn against traffic. 20 CHAPTER 2 The student doing addition is processing a set of numbers by consciously applying rules: 7  3
10.

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But executing a left turn across oncoming traffic involves so many factors that it is hard to imagine discovering the set of rules that can replicate the driver’s behavior. There are, of course, many cases between these extremes, a point we shall return to shortly. In the early days of computer science, the obstacle of tacit knowledge was not so apparent. By the mid-1960s, a computer using rules-based logic could play competent chess—a difficult task for humans. Based on this success, many researchers thought software replicating human visual recognition and motor control would come easily. Recall the example from chapter 1—a four-year-old child walking across a crowded room to pick an apple from a bowl of fruit.

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We don’t know what kind of bowl we are looking for or where the apple will be in the bowl. In the absence of predictability, the number of contingencies explodes as does the knowledge required to deal with them. The required rules are very hard to write. Giving an inspiring speech, designing a new chair, administering anesthesia to a patient—these and many other tasks rely on tacit knowledge and pose limits on computer substitution. There are some strategies for pushing back on these limits. In chapter 1, we cited Herbert Simon’s prescient 1960 essay on how computers would affect occupations. In the essay, Simon observed that it is possible to extend the range of computer substitution by simplifying the task.

How Big Things Get Done: The Surprising Factors Behind Every Successful Project, From Home Renovations to Space Exploration
by Bent Flyvbjerg and Dan Gardner
Published 16 Feb 2023

So although the instructions are helpful, the only way for the child to learn how to ride a bike is to try, fail, and try again. That is, she needs to develop experience and get that tacit knowledge for herself. This is obvious in the case of physical activities such as riding a bicycle or playing golf, but it applies to so much more. Polanyi actually developed the concept of tacit knowledge in an exploration of how scientists do science. Highly experienced project leaders like Frank Gehry and Pete Docter overflow with tacit knowledge about the many facets of the big projects they oversee. It improves their judgment profoundly. Often, they will feel that something is wrong or that there is a better way without quite being able to say why.

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You don’t actually need experience to get that sort of knowledge. Someone can just tell you, or you can find it in a manual; it is “explicit knowledge.” But as the scientist and philosopher Michael Polanyi showed, much of the most valuable knowledge we can possess and use isn’t like that; it is “tacit knowledge.” We feel tacit knowledge. And when we try to put it into words, the words never fully capture it. As Polanyi wrote, “We can know more than we can tell.”21 When an adult gives a child what she thinks are complete instructions on how to ride a bike (“Put your foot on the pedal, push off, press down on the other pedal”), the child typically falls on her first tries, because the instructions are not complete.

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INDEX AC/DC, ref1 Academia, ref1 Adele, ref1 adjustments, ref1, ref2, ref3, ref4, ref5 airports, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Amazon, ref1, ref2 Amazon Fire Phone, ref1 Amazon Prime, ref1 American Civil War, ref1 American Institute of Architects, ref1 anchoring, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Apple, ref1, ref2, ref3, ref4, ref5, ref6 archaeology, ref1, ref2 Aristotle, ref1, ref2, ref3, ref4, ref5 Arlington Farm, ref1, ref2, ref3, ref4 Arlington National Cemetery, ref1 artificial intelligence, ref1 arXiv, ref1 Atomic Energy Agency, Japan, ref1 Auken, Svend, ref1 Aurora Place skyscraper, Australia, ref1 Australia, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13, ref14, ref15, ref16, ref17, ref18, ref19, ref20 availability bias, ref1, ref2, ref3 averages, ref1 Bach, Steven, ref1 backcasting, ref1 Bangladesh, ref1 bankruptcy, ref1, ref2, ref3 Barcelona Olympic Games (1992), ref1 Barnard, Michael, ref1 BART system, San Francisco, ref1 base rates for cost risk, ref1 Basic and Primary Education Project (BPEP), Nepal, ref1, ref2, ref3 Basque Country, ref1 behavioral bias, ref1, ref2 behavioral science, ref1, ref2, ref3 bell curve, ref1, ref2 Bergendahl, Anders, ref1 bespokeness, ref1, ref2, ref3, ref4 best-case scenario, ref1, ref2 Bezos, Jeff, ref1, ref2, ref3 bias, ref1 for action, ref1 anchoring, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 availability, ref1, ref2, ref3 base rate neglect, ref1, ref2 behavioral, ref1, ref2 cognitive, ref1, ref2, ref3, ref4, ref5 escalation of commitment, ref1, ref2 optimism, ref1, ref2, ref3, ref4, ref5, ref6 overconfidence, ref1 planning fallacy, ref1 planning fallacy writ large, ref1 power, ref1, ref2, ref3 survivorship, ref1 against thinking, ref1 strategic misrepresentation, ref1, ref2, ref3, ref4, ref5, ref6, ref7 uniqueness, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 “Big Dig,” Boston, ref1 Bilbao, Spain, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Bilbao effect, ref1 Bill & Melinda Gates Foundation, ref1 Birol, Fatih, ref1 Biskind, Peter, ref1 black swan management, ref1 black swans, ref1, ref2, ref3, ref4 Blackberry, ref1 Boeing, ref1 boring machines, ref1, ref2, ref3, ref4, ref5, ref6 Bornu Railway, Nigeria, ref1 Boston, Massachusetts, ref1 Bowie, David, ref1 Box, The: How the Shipping Container Made the World Smaller and the World Economy Bigger (Levinson), ref1 Brandenburg Airport, Germany, ref1 break-fix cycle, ref1, ref2 bridges, ref1, ref2, ref3 British Airports Authority (BAA), ref1, ref2 Brockner, Joel, ref1 Brookings Institution, ref1 Brown, Gordon, ref1, ref2, ref3 Brown, Willie, ref1, ref2 Bryar, Colin, ref1 budgets and cost overruns, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13, ref14, ref15, ref16, ref17, ref18, ref19, ref20, ref21, ref22, ref23, ref24, ref25, ref26, ref27, ref28, ref29, ref30, ref31, ref32, ref33, ref34, ref35, ref36, ref37, ref38, ref39, ref40, ref41, ref42, ref43, ref44, ref45, ref46, ref47, ref48, ref49 Buehler, Roger, ref1 Buffett, Warren, ref1 building phase, ref1 Caesar Augustus, Emperor, ref1 Cahill, Joe, ref1 California High-Speed Rail, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 California High-Speed Rail Peer Review Group, ref1 Cambridge Analytica, ref1 Canada, ref1, ref2 Capitol, Washington, D.C., ref1, ref2 carbon capture, ref1 Caro, Ina, ref1 Caro, Robert, ref1, ref2, ref3, ref4 Carr, Bill, ref1 Carreyrou, John, ref1, ref2 cars, ref1, ref2 CATIA software, ref1, ref2, ref3, ref4 Catmull, Ed, ref1, ref2, ref3 Chan, Edwin, ref1 Channel Tunnel, ref1 Chernobyl, ref1 China, ref1, ref2, ref3, ref4, ref5 Chrysler Building, New York City, ref1 Churchill, Winston, ref1 Cimino, Michael, ref1 Clapton, Eric, ref1 Clash, ref1 climate crisis, ref1, ref2, ref3, ref4, ref5, ref6 cognitive bias, ref1, ref2, ref3, ref4, ref5 Cohn, Harry, ref1 Colosseum, Rome, ref1 Columbia Pictures, ref1 commitment, escalation of, ref1, ref2 commitment fallacy, ref1 containerization, ref1, ref2 contingency plans, ref1, ref2, ref3, ref4 (see also schedules) Cook, Tim, ref1 Copenhagen Infrastructure Partners (CIP), ref1 Copenhagen Opera House, ref1 cost overruns, ref1 (see also budgets and cost overruns) cost risk, ref1 Covid-19 pandemic, ref1, ref2, ref3, ref4 creativity, ref1, ref2, ref3 Crowe, Frank, ref1, ref2 CubeSat modules, ref1 Cupertino, California, ref1 Daft Punk, ref1 dams, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10 Dassault Systèmes, ref1, ref2 data in reference class forecasting, ref1 vs. stories, ref1 decision theory, ref1 defense, ref1, ref2 Del Ray, Lana, ref1 Denmark, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 design for manufacture and assembly, ref1, ref2 Development Projects Observed (Hirschman), ref1, ref2 Digital Project, ref1 digital simulation, ref1, ref2, ref3 digitalization, ref1 Disney, Lillian, ref1 Disney, Walt, ref1, ref2 Disney Animation, ref1 Disney (see Walt Disney Company, The) Disney family, ref1, ref2 Docter, Pete, ref1, ref2, ref3, ref4, ref5 Drapeau, Jean, ref1, ref2, ref3 driving into the blizzard, ref1, ref2 droughts, ref1 Drummond, Helga, ref1 earthquakes, ref1, ref2, ref3, ref4, ref5 Easy Rider (movie), ref1 Easy Riders, Raging Bulls: How the Sex-Drugs-and-Rock ’n’ Roll Generation Saved Hollywood (Biskind), ref1 Edison, Thomas, ref1, ref2 Edmondson, Amy, ref1 education, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 Egan, Sir John, ref1 Eiffel Tower, Paris, ref1 8 Spruce Street, New York City, ref1 Eldrup, Anders, ref1 Electric Lady Studios, New York City, ref1, ref2, ref3, ref4, ref5, ref6 Electric Ladyland (Hendrix), ref1 electricity transmission, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, ref11, ref12, ref13 electrification, ref1, ref2 electrolyzer capacity, ref1 Elizabeth II, Queen of England, ref1, ref2 emotions, distinguished from intuitive judgments, ref1 Empire State Building, New York City, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 Empire State Inc., ref1, ref2 escalation of commitment, ref1, ref2 estimates, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 European Union, ref1 Ever Given (container ship), ref1 experience, ref1, ref2, ref3, ref4, ref5, ref6 being first and, ref1 Empire State Building example, ref1 frozen and unfrozen, ref1, ref2 of Gehry and Utzon, ref1, ref2 marginalizing, ref1 Olympic Games example, ref1 quest for superlatives, ref1, ref2 tacit knowledge and, ref1 experiential learning, ref1 experimentation, ref1, ref2, ref3, ref4, ref5, ref6, ref7 experiri, ref1, ref2, ref3, ref4 Facebook, ref1 fat-tailed distribution, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 fat-tailed projects, ref1 feasibility studies, ref1 Final Cut: Art, Money, and Ego in the Making of Heaven’s Gate, the Film That Sank United Artists (Bach), ref1 Finding Nemo (movie), ref1 firearms registry, ref1 first-mover advantage, ref1 floods, ref1, ref2, ref3, ref4 flowcharts, ref1, ref2, ref3 Flyvbjerg, Bent, further readings by, ref1 Football Association (FA) Cup Final, United Kingdom, ref1 forecasting, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9 foreign aid, ref1 Forster, Danny, ref1 fossil thermal power, ref1, ref2, ref3 Foster, Norman, ref1 France, ref1, ref2 Franklin, Benjamin, ref1, ref2 freight shipping, ref1 frozen and unfrozen experience, ref1, ref2, ref3 Fukushima disaster, ref1, ref2 Galton, Sir Francis, ref1 Gates, Bill, ref1, ref2 Gaussian distribution, ref1, ref2 Gehry, Frank, ref1 8 Spruce Street, New York City, designed by, ref1 experience of, ref1, ref2 Guggenheim Museum Bilbao designed by, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 questioning by, ref1, ref2, ref3 Simpsons, guest appearance on, ref1, ref2 simulation and models used by, ref1, ref2, ref3, ref4, ref5 teams led by, ref1, ref2, ref3 Walt Disney Concert Hall designed by, ref1, ref2 General Motors, ref1 Generation nightclub, New York City, ref1 Germany, ref1, ref2, ref3, ref4 Gigafactory 1 (Giga Nevada), ref1 Gigerenzer, Gerd, ref1, ref2 Gino, Francesca, ref1 Giroux, Yves, ref1 Gladwell, Malcolm, ref1, ref2 goals, ref1, ref2 Goldberger, Paul, ref1, ref2 Google, ref1 Google Scholar, ref1 Grand Central Terminal, New York City, ref1 Great Belt project, Denmark, ref1 Great Chicago Fire Festival, ref1, ref2 Great Depression, ref1 Great Wall of China, ref1 Green, Mike, ref1, ref2 greenhouse gases, ref1 Guangzhou, China, ref1 Guardian, The, ref1 Guggenheim Museum Bilbao, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10 Hall, Peter, ref1 Harper, Richard, ref1 Harvard Business Review, ref1 HealthCare.gov website, ref1 heat waves, ref1, ref2 Heathrow Airport, United Kingdom, ref1, ref2, ref3, ref4, ref5 Heaven’s Gate (movie), ref1 height, ref1 Hendrix, Jimi, ref1, ref2, ref3, ref4, ref5 Hero’s Journey, ref1 heuristics, ref1, ref2, ref3 heuristics and biases school, ref1 heuristics for better leadership, ref1 Hiding (Hidden) Hand, ref1, ref2 High Speed 2 (HS2), United Kingdom, ref1, ref2 Hirschman, Albert O., ref1, ref2, ref3, ref4, ref5 Hofstadter, Douglas, ref1 Hofstadter’s Law, ref1 Holland Tunnel, New York, ref1 Holm, Mette K.

Exploring the World of Lucid Dreaming
by Stephen Laberge, Phd and Howard Rheingold
Published 8 Feb 2015

Furthermore, as we will discuss in the next section, the tools available in that workshop may be far more versatile than those we are familiar with in the waking world. Tacit Knowledge The most important idea behind our belief that lucid dreaming can help boost the illumination phase of the creative process is the concept of ““tacit” knowledge. The things you know that you know and can spell out explicitly, such as your street address or how to tie your shoe, are called ““explicit” knowledge. Tacit knowledge, on the other hand, includes what you know but can’t explain (how to walk or talk), and what you know but don’t think you do (say, the color of your firstgrade teacher’s eyes).

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Of the two kinds of knowledge, the tacit variety is by far the more extensive: we know more than we realize. In dreams we have greater contact with our tacit knowledge than we do while awake. If you remember your dreams, you can surely recall having had one in which the likeness of a person whom you have met only once was reproduced with amazing detail in comparison to any description you could have made of him or her while awake. The explanation for this phenomenon is our access to tacit knowledge in dreams. In dreams we have conscious access to the contents of our unconscious minds. Therefore, in our dreams we are not limited, as we are while awake, to working with only that tiny portion of our accumulated experience to which we normally have conscious access.

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Without lucidity, it seems we have no way to determine when, or even if, a creative dream might occur. However, through lucid dreaming we may be able bring the extraordinary creativity of the dream state under conscious control. Consider this next example, in which an oneironaut managed to find a specific piece of tacit knowledge in the form of a book. In this instance, the dreamer did not find the specific solution in the dreamed book, but upon awakening he did find it in the real book. The knowledge discovered in this case was that this book contained a clue to the problem –– a good example of something you can know without knowing you do: I recently pulled second place in a math competition.

The Tyranny of Metrics
by Jerry Z. Muller
Published 23 Jan 2018

There is an elective affinity between a democratic society with substantial social mobility and greater ethnic heterogeneity, and the culture of measured accountability. In societies with an established, transgenerational upper class, the members of that class are more likely to feel secure in their positions, to trust one another, and to have imbibed a degree of tacit knowledge about how to govern from their families, giving them a high degree of confidence in their judgments (whether or not that confidence is justified).1 By contrast, in meritocratic societies with more open and changing elites, those who reach positions of authority are less likely to feel secure in their judgments, and more likely to seek seemingly objective criteria by which to make decisions.

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THE RATIONALIST ILLUSION There are also powerful dissections of accountability-as-measurement from conservative and classical liberal thinkers, such as Michael Oakeshott, Michael Polanyi, and Friedrich Hayek, whose analysis has recently been rediscovered by James C. Scott, a Yale anthropologist with self-described anarchist predilections. They have all distinguished between two forms of knowledge, one abstract and formulaic, the other more practical and tacit. Practical or tacit knowledge is the product of experience: it can be learned, but cannot be conveyed in general formulas. Abstract knowledge, by contrast, is a matter of technique, which, it is assumed, can be easily systematized, conveyed, and applied. In Oakeshott’s famous example, there is the sort of abstract, recipe knowledge conveyed by cookbooks; but actually knowing how to make use of such knowledge (“beat an egg,” “whisk the mixture”) requires practical knowledge, based upon experience, that cannot be learned from books.

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Accountability metrics are less likely to be effective when they are imposed from above, using standardized formulas developed by those far from active engagement with the activity being measured. Measurements are more likely to be meaningful when they are developed from the bottom up, with input from teachers, nurses, and the cop on the beat. That means asking those with the tacit knowledge that comes from direct experience to provide suggestions about how to develop appropriate performance standards.2 Try to involve a representative group of those who will have a stake in the outcomes.3 In the best of cases, they should continue to be part of the process of evaluating the measured data.

Track Changes
by Matthew G. Kirschenbaum
Published 1 May 2016

If I tried hard, there was always a logic to discover, an internal order and consistency … I could produce these harmonies, test them, see them work.”29 Martin’s intimate knowledge of WordStar’s functions and keyboard patterns might be best characterized as tacit knowledge, the extraordinary combination of muscle memory and unarticulated experience that enables us to perform very complex tasks without conscious effort or consciously knowing how to do them. Tacit knowledge is necessary for the flow states many writers cite as characteristic of their most productive sessions, and they deeply resent anything that jolts them out of that zone.30 (Thus Martin’s comment about autocorrect, for example.)

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In the wake of the widespread adoption of word processing by writers in the 1980s, composition researchers such as Daniel Chandler and Christina Haas worked to articulate the specific components of tacit knowledge in computing in order to better understand the new realities of the writing process.31 Haas found, for example, that screen size and other aspects of the graphical interface had a measurable impact on what she termed an author’s “sense of the text,” his or her ability to conceive of it as a whole, a gestalt—and that this in turn had implications for how the writer approached the task of revision.32 Chandler, meanwhile, called such tacit knowledge “resonance,” the way in which small, seemingly insignificant details of a particular technology ended up mattering a great deal to a writer, often for inexplicable or inarticulate reasons.

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Her reply: “You can just mark those pages off and copy them over to another disk, then take the later chapter put that in the computer and then copy those pages into the later chapter, you can move them anywhere you want, you can swap them around. That’s what I mean by once you work this way, nothing stands between you and what you want to do.”81 The casual reference to “marking pages off” coupled with the tacit knowledge necessary for swapping around the disks to effect the transfer speaks volumes about the casual mastery of a new way of working. It also testifies to a new way of writing that nonetheless has its roots in office technologies of the previous decade, which placed a premium on precisely such a modularized view of text—merging it, flowing it, retrieving it, and outputting it.

The Structure of Scientific Revolutions
by Thomas S. Kuhn and Ian Hacking
Published 1 Jan 1962

Rather it comes as one is given words together with concrete examples of how they function in use; nature and words are learned together. To borrow once more Michael Polanyi’s useful phrase, what results from this process is “tacit knowledge” which is learned by doing science rather than by acquiring rules for doing it. 4. Tacit Knowledge and Intuition That reference to tacit knowledge and the concurrent rejection of rules isolates another problem that has bothered many of my critics and seemed to provide a basis for charges of subjectivity and irrationality. Some readers have felt that I was trying to make science rest on unanalyzable individual intuitions rather than on logic and law.

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For its effects on Boyle’s chemistry, see T. S. Kuhn, “Robert Boyle and Structural Chemistry in the Seventeenth Century,” Isis, XLIII (1952), 12–36. V. The Priority of Paradigms 1. Michael Polanyi has brilliantly developed a very similar theme, arguing that much of the scientist’s success depends upon “tacit knowledge,” i.e., upon knowledge that is acquired through practice and that cannot be articulated explicitly. See his Personal Knowledge (Chicago, 1958), particularly chaps. v and vi. 2. Ludwig Wittgenstein, Philosophical Investigations, trans. G. E. M. Anscombe (New York, 1953), pp. 31–36. Wittgenstein, however, says almost nothing about the sort of world necessary to support the naming procedure he outlines.

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W., 53, 55, 70 Schlick, Moritz, xx scholastic criticism, 67, 104, 105, 110, 120, 124 Schrödinger equation, 186 science: defined, 159–60; historiographic revolution in study of, 3–4; history of, xxxix, 138; nature of, 206–8; relation to arts during Renaissance, 160–61; sociological study of, xxxvi; tendency to link with progress, 159, 161 science-as-cumulation, 2–3, 96, 108, 138, 139–40 scientific fields, transitions to maturity, 21 scientific law, 28–29, 40 shared values, 184–86, 198–99 Smith, Norman Kemp, xiin10 social sciences: debates about as sciences, 159–60; need for defense of choice of research problem, 163–64 Society of Fellows, xli specialization, xxxii–xxxiii, 19–20, 171–72 specific heats, 68, 89 Spencer, Herbert, 170 Stanford Encyclopedia of Philosophy, viii statistical thermodynamics, laws of, 40 stimulus-to-sensation, 191–97 Stokes, George Gabriel, 73 structure: of scientific communities, 19–20, 175–86; of scientific revolutions, x–xi sunspots, 116 Sutton, Francis X., xli symbolic generalizations, 182–83, 187–88, 189 Symmer, Robert, 18n9 tacit knowledge, 44n1, 190, 195 Tarski, Alfred, xxxvii textbooks, science, 1–2, 10, 20, 47, 136; application given in, 80–81; bases for new tradition of normal science, 143; chemical elements attributed to Robert Boyle, 141; increasing reliance on concomitant with first paradigm of a field of science, 136; mistaken version of Boyle’s contribution to elements, 141–42; postrevolutionary reconstruction of history, 136–37, 139; refer to work easily viewed as contributing to solution of paradigm problems, 137; reliance on, in science education, 164–65; and science-as-cumulation, 139–40; tendency to describe linear development of science, 139 theories, scientific: articulation of, xvi; change in, 97–98; emergence from revolutionary reformulation of preceding scientific tradition, 140; process of learning dependent on study of applications, 47; restricted conception of, 98–103; as used in philosophy of science, 181; verification of, 144, 146.

The Wealth of Humans: Work, Power, and Status in the Twenty-First Century
by Ryan Avent
Published 20 Sep 2016

Human capital, for example, is valuable knowledge, accumulated through the investment of personal time and energy, but which is not especially context-dependent: a clear understanding of algebra, say, is useful in many different contexts. Tacit knowledge, meanwhile, is human capital that cannot easily be shared with others: how to juggle or ride a bicycle, for example. Tacit knowledge is useful knowledge that might only be shared through close and repeated contact, but it is not context-dependent. Trade secrets, however, are forms of knowledge kept within certain organizations or firms, but the value of which is also not especially context-dependent: if one firm discovered the code another used to solve a knotty computational problem, it would find that knowledge of use without needing to bring on board the culture of the firm that wrote the useful code.

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These cities also became a magnet for other skilled workers.5 Over the last generation, places that had lots of highly educated workers a few decades ago have seen a rise in their share of college graduates, while cities that began with low levels of educated workers have often seen their share of those with college degrees stagnate or decline.6 The economic importance of two sorts of information (both of which were discussed in Chapter 6) drives the success of the modern city. One is tacit knowledge: human capital that cannot easily be transferred without repeated, personal interactions. Tacit knowledge includes particular skills – such as how to manage a complex global business – which can be learned by watching others do their jobs, or through trial and error, with feedback. It also consists of critical details about the nature of local technological change.

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Today, more than 80 per cent of the value of Standard & Poor’s 500* firms is ‘dark matter’: the intangible secret sauce of success; the physical stuff companies own and their wage bill accounts for less than 20 per cent: a reversal of the pattern that prevailed in the 1970s.27 A large proportion of that dark matter is an amorphous ‘know-how’: the culture, incentives and tacit knowledge that make a modern company tick. The Economist is like that; our journalists gather information from all over the world, analyse it, and filter it through our editorial structures in order to generate pieces of journalism people want to buy. So is the (somewhat more profitable) Apple. Apple’s phenomenal riches are built not just on the talent of its workforce, but on a particular internal culture and workflow, which prioritizes design and relentlessly improves on products until they are near-perfect: a culture that competitors find impossible to imitate.

The Happiness Hypothesis: Finding Modern Truth in Ancient Wisdom
by Jonathan Haidt
Published 26 Dec 2005

But wisdom is b a s e d — a c c o r d i n g to Robert Sternberg,46 a leading wisdom researcher—on "tacit knowledge." Tacit knowledge is procedural (it's "knowing how" rather than "knowing that"), it is acquired without direct help from others, and it is related to goals that a person values. Tacit knowledge resides in the elephant. It's the skills that the elephant acquires, gradually, from life experience. It d e p e n d s on context: There is no universal set of best practices for ending a romantic relationship, consoling a friend, or resolving a moral disagreement. Wisdom, says Sternberg, is the tacit knowledge that lets a person balance two sets of things.

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This second balance corresponds roughly to the famous "serenity prayer": " G o d , grant me the serenity to accept the things I cannot change, courage to change the things I can, and wisdom to know the difference."47 If you already know this prayer, your rider knows it (explicitly). If you live this prayer, your elephant knows it, too (tacitly), and you are wise. Sternberg's ideas show why parents can't teach their children wisdom directly. T h e best they can do is provide a range of life experiences that will help their children acquire tacit knowledge in a variety of life domains. Parents can also model wisdom in their own lives and gently encourage children to think about situations, look at other viewpoints, and achieve balance in challenging times. Shelter your children when young, but if the sheltering goes on through the child's teens and twenties, it may keep out wisdom and growth as well as pain.

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T h e y all knew that training takes daily practice and a great deal of repetition. T h e rider must take part in the training, but if moral instruction imparts only explicit knowledge (facts that the rider can state), it will have no effect on the elephant, and therefore little effect on behavior. Moral education must also impart tacit knowledge—skills of social perception and social emotion so finely tuned that one automatically feels the right thing in each situation, knows the right thing to do, and then wants to do it. Morality, for the ancients, was a kind of practical wisdom. H o w T H E W E S T W A S L O S T T h e Western approach to morality got off to a great start; as in other ancient cultures, it focused on virtues.

The 100-Year Life: Living and Working in an Age of Longevity
by Lynda Gratton and Andrew Scott
Published 1 Jun 2016

In part, the value of experiential learning will increase as simple knowledge acquisition becomes so much easier because of the developments of web and online learning. So what will separate people is not what they know, but rather what they have experienced using this knowledge. This is a consequence of the two paradoxes (Polyani and Moravec) that we discussed earlier and the increasing importance of tacit knowledge – that which cannot be codified. This tacit knowledge, though hard to build, is very valuable. It is the basis of wisdom, insight and intuition and is built through practice, repetition and observation. It is also likely that what is valuable from an employer’s perspective is not simply being ‘book smart’ but also having real world savvy.

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Clearly, measuring your health and vitality is reasonably straightforward and the health checks most of us have are designed to do just that and remind us whether our health has increased or depleted over a period of time. The same is true of some forms of skills and knowledge. The examinations we sit and certificates we receive are a measure of our explicit knowledge, although tacit knowledge is inherently more difficult to measure. What of friendships and relationships? Most people have some understanding of the health of their most important relationships, though would struggle to quantify this understanding. There are also growing attempts by network analysts to measure the size, variety and interconnectedness of an individual’s network and, over time, to track the extent by which these are growing or depleting.1 Rapid developments in augmented technology – which measure many aspects of daily behaviour such as miles walked, time spent talking with friends and so forth – will add to the sophistication with which intangible assets can be measured.

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After her initial law training, let’s imagine that she wants to take a more flexible approach to her work, perhaps because she has small children. Very soon she will find that if she is not available to meet a client when the client needs her, then at that point her value to the firm begins to decline. She may also find that her intangible assets, such as tacit knowledge, begins to erode because she is not constantly in the office to interact with her colleagues and clients in meetings or through random exchanges. So if she is not around, she will be excluded from the ideas that are bouncing around in conversation. As Goldin shows, these types of knowledge-rich occupations (such as law, consultancy, investment banking) impose heavy penalties on people who want to work fewer hours and have more flexible employment.

No Such Thing as a Free Gift: The Gates Foundation and the Price of Philanthropy
by Linsey McGoey
Published 14 Apr 2015

In The Road to Serfdom and influential essays such as ‘On the Use of Knowledge in Society’, Hayek, inspired by Michael Polanyi’s work on tacit knowledge and Karl Popper’s work on the open society, made an argument that was then radical for its time. He believed that much formal economic theory represented ‘only the visible tip of the vast submerged fund of tacit knowledge, much of which is entirely beyond our powers of articulation’.1 Because of the inaccessibility of the ‘tacit knowledge’ that affects individual decision-making, it is impossible, he argued, for a central planner to respond to the needs of different market actors.

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B., 46, 47 Duncan, Arne: and charter schools, 139; and No Child Left Behind, 121; and performance pay for teachers, 139; and Race to the Top, 144 Duti, Vida, 177–8 Dvorak, John, 183–4 economics: and agricultural commodities, 212–3; and capital gains tax, 22; and commodities markets, 210–4; and currency speculation, 22; and economic development, 30, 38–9; and global financial markets, 27, 86; and governmental and philanthropic aid, 38–9, 84–7; and Henry George, 115; and impact investing, 80–1; and income inequality, 24, 39; and laissez-faire policies, 51, 93, 179, 236–8; and Ludwig von Mises, 236; and microfinance, 7–8, 21, 63, 68, 77–81, 83–4; and patents, 180; and positive capacity of business, 17, 86–7; and pro-market solutions, 86; and social entrepreneurs, 63, 66–72, 86–7; and state planning, 235–6; and supply-side economics, 111–2; and tacit knowledge, 235–6; and tax cuts for the wealthy in the UK, 76; and treatment of poor countries by IMF and World Bank, 171–2; and virtues of free-market, 239 education: and African Americans, 10, 54, 118; and American Legislative Exchange Council’s conservative agenda, 132; and Arne Duncan, 139; and Broad Foundation, 9, 122, 139; and charter schools, 118, 123–8, 131; and college acceptance rates, 134; and Common Core, 137–8; and debate over class size, 127–8; and efforts of Carnegie and Rockefeller, 27–8; and evaluation of teachers using value-added modelling, 140–2, 144; and firing of teachers, 139; and for-profit schooling, 133; and funding for the Measure of Effective Teaching study, 140–1; and Gates Foundation, 27–8, 121–2, 132–47; and gathering of data on students, 133–4; governmental spending on, 8–9; and growth of charity schools, 92; and higher education, 121, 242; and John Dewey, 72; and Michigan’s schools, 133; and No Child Left Behind programme, 118–22, 139, 240; and online schools, 129–31; and Peer Assistance and Review programme, 144; and performance pay for teachers, 139, 145; and poverty, 7, 128–9; and primary and secondary schools, 9, 24, 115, 122, 129–30; and privatization of public education, 116; and Progress in International Reading Literacy Study, 128; and public education, 109; and public shaming of teachers, 142, 144–5; and Race to the Top, 139, 144; and standardized testing for students, 134, 139; and teacher effectiveness, 134, 139, 140–2, 144; and teacher performance, 132, 138–42, 144, 145; and teachers’ remuneration, 127, 134, 139; and US students compared to international peers, 128; and value of teachers, 126–7, 140; and views of Maria Montessori, 72; and William Bennett, 130 Edwards, Michael, 8–9, 229, 241 Eisenberg, Pablo, 229–30, 234 Eli Lilly, 104–5 Elkington, John, 66–7 Emerson, Jed, 80–1 Emerson, Ralph Waldo, 11–12, 245 Ford, Henry: business practices of, 56–8; and the Dearborn Independent, 57; and employees’ productivity, 56; as an opponent of labour unions, 56; and philanthropy, 11, 56, 117; and shorter work week, 56; as supporter of high wages, 56–7 Ford, Henry, II, 60–1 Ford Foundation: establishment of, 56; and McGeorge Bundy, 61; money of, 22; and philanthropy, 28; projects of, 58 Ford Motor Company, 56–7, 60–1 Foucault, Michel, 114, 147 Foundation for Excellence in Education, 132, 133 Foundation Strategy Group, 89–90 France, 220, 237 Freeland, Chrystia, 64, 108, 199–200 Frick, Henry Clay, 10–11, 42–3 Fries, Foster, 108, 109, 111 Galbraith, James, 24, 111 Gandhi, Mahatma, 68, 72 Gates, Bill: as a businessman, 246; and campaign for a global tax on currency speculation, 22; and Coca-Cola, 174, 222; and Common Core, 137; donations of, 22–3, 85, 108, 117; and efficiency of philanthropic spending, 24; and ethical investing, 175; and favoring increase in class size, 127–8; and fight against AIDS, 193; and fight against polio, 154, 155, 157, 159; and focus on Africa, 223–4; fortune of, 9, 177, 183; and funding for Purchase for Progress programme, 207–8; and the Giving Pledge, 24, 117; and global health issues, 177, 192; as head of Gates Foundation, 21, 107, 244; and home in Seattle, WA, 134, 245–6; and interest in Carnegie’s writings, 41, 111; and intervening to try to delay guidance on antiretrovirals, 196–7; and investment in companies with bad records on health issues, 173; and patent rules, 205; philanthropic ethos of, 183, 245; and philanthropy, 5–7, 9–10, 23–4, 26, 116–7, 146, 159; and position on intellectual property, 198–9; and pre-exposure prophylactic treatments for HIV, 194; and presence at G20 consultations, 154; and primary and secondary schools, 9, 24; and public shaming of teachers, 142, 144–5; and science grants for minority students, 59; and small schools, 134–6; and support for HIV prevention, 193; and support for increasing the capital gains tax, 22; and support of charter school movement, 125–6; and support of tighter firearms controls in WA, 23; and taxes paid by Gates Foundation, 85; and teacher performance, 126; and teachers’ remuneration, 127; and time at Harvard, 63, 181, 182, 183; as trustee of Gates Foundation, 8, 174; and views on foreign aid, 27; and views on patents, 26, 181, 186; and wealth tax, 24; and William H.

Fewer, Better Things: The Hidden Wisdom of Objects
by Glenn Adamson
Published 6 Aug 2018

Chapter 11 COMMUNITIES OF RESPECT Thinking back to my grandfather’s business card, the way he applied his farm boy’s curiosity to both jet engines and wood carvings simultaneously, I am struck by the way that he intuitively grasped the idea that making is a continuum. It binds different kinds of people together, and that is true no matter how the making is done. For those who lack the skills or the firsthand experience, this can all seem a rather mysterious business. People often speak of the “tacit knowledge” of craftsmanship, and for good reason. What happens when a maker, a tool, and a material come together is difficult to grasp from the outside, because it is intuitive and embodied. That makes it difficult to see the sophistication involved. By crossing this gap in understanding and becoming more respectful of the intelligence that is embodied in making, we inevitably find ways to live in a more integrated way.

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In her research, Smith often found it necessary to ask questions about practice that were not easy to answer on the basis of surviving documents. What was it actually like for an artisan in the laboratory? How difficult were the processes involved? What was the sensory aspect of the experience of research like—the way it looked, felt, and smelled? What equipment was required? “Lacking written documents about this tacit knowledge,” Smith asks, “how then do we go about building up a picture of artisanal knowledge and theorizing?”2 She decided there was only one way to proceed: She would actually re-create the experience of the alchemists. Smith chose a particularly informative manuscript, a French “book of secrets” that probably dates from the sixteenth century.

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Things can function as powerful exemplars and guides. Like rocks in a swift current, even when they sit perfectly still, they shape the course of our experience. ACKNOWLEDGMENTS I’m a person who feels most at home when thinking and writing. But making is what I like to think and write about best. What’s often called “tacit knowledge,” which I prefer to call “material intelligence,” has a profound appeal for me. Many others feel the same, I know. Yet this fundamental human faculty does not get enough respect. This is partly because it is difficult to grasp making from the outside. If you haven’t done something yourself, then the depth involved may well remain lost on you.

The Tyranny of Experts: Economists, Dictators, and the Forgotten Rights of the Poor
by William Easterly
Published 4 Mar 2014

Even more inaccessible to conscious designers is tacit knowledge, which cannot be communicated as a list of instructions from one individual to another. Tacit knowledge is the kind of trained and mostly unconscious knowledge needed, for example, to ride a bicycle—it does not work to follow a recipe on how to balance and turn the pedals. Economics examples include on-the-job learning, which is the main reason workers’ earnings rise with experience. Even purely technical solutions often require experience with that technology, in particular times and places, to fix the bugs. Tacit knowledge can only be gained through what Kenneth Arrow later called “learning by doing.”

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Tacit knowledge can only be gained through what Kenneth Arrow later called “learning by doing.” Tacit knowledge can certainly not be accessed by centralized problem-solvers. For Hayek, the advantages of a spontaneous order of free individuals is that it creates the incentives for individuals to utilize their own localized or tacit knowledge, without any need for anyone else to access it. For private goods, the prices and markets coordinate all the decisions of individuals based on their idiosyncratic knowledge in a way that top-down plans could never do. In any given area, the individual who has the knowledge to produce what customers want most is the one chosen through market competition to be the producer.

The Wisdom of Crowds
by James Surowiecki
Published 1 Jan 2004

And it increases the scope and the diversity of the opinions and information in the system (even if each individual person’s interests become more narrow). Decentralization is also crucial to what the economist Friedrich Hayek described as tacit knowledge. Tacit knowledge is knowledge that can’t be easily summarized or conveyed to others, because it is specific to a particular place or job or experience, but it is nonetheless tremendously valuable. (In fact, figuring out how to take advantage of individuals’ tacit knowledge is a central challenge for any group or organization.) Connected with this is the assumption that is at the heart of decentralization, namely that the closer a person is to a problem, the more likely he or she is to have a good solution to it.

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But boundarylessness was one of the things that allowed GE, unlike most old-line American industrial corporations, to flourish. V So what would the wider distribution of real decision-making power look like? To begin with, decisions about local problems should be made, as much as possible, by people close to the problem. Friedrich Hayek, as we’ve seen, emphasized that tacit knowledge—knowledge that emerged only from experience—was crucial to the efficiency of markets. It is just as important to the efficiency of organizations. Instead of assuming that all problems need to be filtered up the hierarchy and every solution filtered back down again, companies should start with the assumption that, just as in the marketplace, people with local knowledge are often best positioned to come up with a workable and efficient solution.

A World Without Work: Technology, Automation, and How We Should Respond
by Daniel Susskind
Published 14 Jan 2020

At the moment, many economists believe their mistake was a failure to see that new technologies would turn many “non-routine” tasks into “routine” ones. Remember that “non-routine” tasks are defined as those requiring “tacit” knowledge, the sort of knowledge that human beings struggle to articulate. What is happening, the economists argue, is that new technologies are simply uncovering some of this tacit knowledge that human beings rely upon. The “routine” versus “non-routine” distinction is still useful, they maintain; new technologies are simply shifting the boundary between the two, a boundary that the economists once (mistakenly, they admit) thought was fixed.

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By “routine,” they did not mean that the task was necessarily boring or dull. Rather, a task was regarded as “routine” if human beings found it straightforward to explain how they performed it—if it relied on what is known as “explicit” knowledge, knowledge which is easy to articulate, rather than “tacit” knowledge, which is not.23 Autor and his colleagues believed that these “routine” tasks must be easier to automate. Why? Because when these economists were trying to determine which tasks machines could do, they imagined that the only way to automate a task was to sit down with a human being, get her to explain how she would perform that task, and then write a set of instructions based on that explanation for machines to follow.24 For a machine to accomplish a task, Autor wrote, “a programmer must first fully understand the sequence of steps required to perform that task, and then must write a program that, in effect, causes the machine to precisely simulate these steps.”

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See Big State; government state bonus status steam engine Stiglitz, Joseph stock plans structural technological unemployment complementing force weakening and lump of labor fallacy and overview of remaining tasks and superiority assumption and timing of world with less work and substituting force ALM hypothesis and complementing force and defined education and frictional technological unemployment and misplaced anxiety and strengthening of task encroachment and Summers, Larry superintelligence superiority assumption supermanagers superstar firms Supplemental Nutrition Assistance Program (SNAP) supply, price and Supreme Court decision prediction Susskind, Jamie Susskind, Richard Suzman, James synthetic media tacit knowledge Tantalus task complexity task encroachment affective capabilities and cognitive capabilities and manual capabilities and overview of regional differences in skepticism and weakening complementing force and tasks, jobs vs. taxation Tay (chatbot) technological unemployment. See also frictional technological unemployment; structural technological unemployment future of inequality and Keynes and television Temple of Heaven Park Tennyson, Alfred territorial dividends Tesla Thebes A Theory of Justice (Rawls) Thiel, Peter Thiel Foundation 3-D printing techniques Thrun, Sebastian timing toilet paper top-down creation top income inequality tractors Trades Union Congress (TUC) traditional capital transparency tribal sovereignty Trump, Donald TUC.

A Culture of Growth: The Origins of the Modern Economy
by Joel Mokyr
Published 8 Jan 2016

A key to the understanding of the emergence of modern economic growth can be gained by recognizing that both the technology of the Industrial Revolution and its subsequent development and the propositional knowledge underpinning it were cultural phenomena subject to evolutionary forces. Technological or prescriptive knowledge, which is partially tacit knowledge, is passed among individuals who teach one another how to make things or produce a service, from music lessons to apprenticeships. The propositional knowledge (science) on which techniques are based is taught as well, although typically in a somewhat different settings and not always to the same people (although all engineers and technicians need to be trained in mathematics and physics).

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Intelligent and creative artisans invented, improved, and tinkered with tools and techniques. Many improvements came about through small, cumulative improvements made by unknown craftsmen and diffused through the networks of technically literate masters and journeymen who became increasingly adept at disseminating tacit knowledge. Yet all told, these groups remained a small minority, and economic development in these areas can be viewed as their actions eventually affecting the economic status of the rest of the population, not so much a trickle-down as a dragging-along. The exact modus operandi of this top-down mechanism could vary from situation to situation, but historical outcomes can be analyzed using the various cultural evolution biases delineated in chapter 5.

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But it seems exaggerated to argue that without the printing press, modern science would not have arrived and that “printing created the modern world” (Perkinson, 1995, p. 63). For one thing, printing could disseminate and preserve only codified knowledge, and while that clearly had big consequences, codifiable knowledge was not all there was to know. Artisanal knowledge was still predominantly tacit knowledge, and its transmission required personal contact. Codified technological knowledge, as embodied in the many books about machinery and engineering that were published in this age, did not have much of a direct impact on technological practices (Cipolla, 1972). The same was true for large parts of natural history and experimental philosophy, which needed other means of communication such as personal interaction.

Exodus: How Migration Is Changing Our World
by Paul Collier
Published 30 Sep 2013

Migrants seldom compete head-to-head with indigenous workers, because, through a combination of tacit knowledge, accumulated experience, and discrimination, indigenous workers have a substantial advantage over migrants. Migrants compete head-to-head not with low-skill indigenous workers but with each other. Migrants are not in close competition with indigenous workers, even in respect to those indigenous workers who have a similar level of education.1 The indigenous advantage may be that they have better command of the language or that their greater tacit knowledge of social conventions makes them more productive. Or it may be because employers discriminate against immigrant workers.

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The taxation of migrants would be the surest way of making them second-class citizens, making integration more difficult. Even without migrant-specific taxation, in some host societies immigrants tend to become an underclass due to a combination of less education than the indigenous population, a lack of the tacit knowledge that contributes to productivity, and discrimination. Where this happens it is rightly seen as a social problem to which major resources must be devoted. Imposing a tax on immigrants with one hand while attempting to undo its consequences with the other would be an incoherent policy. Further, if the revenue from an immigrant tax accrued to the indigenous population, it could have the paradoxical effect of deepening the hostility of the indigenous population toward immigrants.

Obliquity: Why Our Goals Are Best Achieved Indirectly
by John Kay
Published 30 Apr 2010

It would be different if the people who had such intuitions had an established record of being proved right in establishing other similar medico-technical relationships. By lumping a bundle of things together under the headings of instinct and intuition and contrasting them with a particular kind of rationality, by failing to acknowledge the central role that tacit knowledge plays in daily life, we not only fail to see how good judgments are arrived at and good decisions made, but we also open the door to much unscientific nonsense. If we were to insist that Beckham give an account of why he proposed to kick the ball in that particular way before he were allowed to do so, we would quickly lose faith in him.

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James Scott’s superb Seeing Like a State is a fertile source of both ideas and examples of the failure of directness and modernism in economic affairs, and I have borrowed both the ideas and the examples shamelessly. The maxim “We know more than we can tell,” which is fundamental to obliquity, encapsulates Michael Polanyi’s exposition of tacit knowledge, an idea that many have had but few have so well expressed. Richard Sennett’s The Craftsman has recently provided an elegant exposition of related theories. Matt Ridley’s Origins of Virtue introduced me to the idea that many of our social and economic institutions can best be explained with the aid of evolutionary psychology; in a very different style, Ken Binmore and Herbert Gintis explore similar themes.

Everything Is Obvious: *Once You Know the Answer
by Duncan J. Watts
Published 28 Mar 2011

Coleman, James S., and Thomas J. Fararo. 1992. Rational Choice Theory: Advocacy and Critique. Thousand Oaks, CA: Sage. Coleman, James Samuel. 1993. “The Impact of Gary Becker’s Work on Sociology.” Acta Sociologica 36:169–78. Collins, Harry. 2007. “Bicycling on the Moon: Collective Tacit Knowledge and Somatic-Limit Tacit Knowledge.” Organization Studies 28 (2):257. Cook, Karen S., Richard M. Emerson, Mary R. Gillmore, and Toshio Yamagishi. 1983. “The Distribution of Power in Exchange Networks: Theory and Experimental Results.” American Journal of Sociology 89:275–305. Cook, Karen S., Linda D. Molm, and Toshio Yamagishi. 1993.

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It is simply what any reasonable person would do if they had grown up in that culture. What these results reveal is that common sense is “common” only to the extent that two people share sufficiently similar social and cultural experiences. Common sense, in other words, depends on what the sociologist Harry Collins calls collective tacit knowledge, meaning that it is encoded in the social norms, customs, and practices of the world.10 According to Collins, the acquisition of this type of knowledge can be learned only by participating in society itself—and that’s why it is so hard to teach to machines. But it also means that even among humans, what seems reasonable to one might seem curious, bizarre, or even repugnant to another.

The World Beyond Your Head: On Becoming an Individual in an Age of Distraction
by Matthew B. Crawford
Published 29 Mar 2015

This restricts the range of diffusion to that of personal contacts, and we find accordingly that craftsmanship tends to survive in closely circumscribed local traditions.”7 Polanyi is here talking about craft knowledge, but he was seeking a larger epistemological point. Polanyi was one of the most prominent physical chemists of the middle of the twentieth century. In the second half of his life he took up philosophy in an effort to understand his own experience of scientific discovery. His elaboration of “tacit knowledge” entailed a criticism of the then-prevailing ideas of how science proceeds, tied to wider claims about the nature of reason. The logical positivists conceived reason to be rulelike, whereas according to Polanyi, a scientist relies on a lot of knowledge that can’t be rendered explicit, and an inherent feature of this kind of knowledge is that it is “personal.”

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There is, then, a certain harmony between these institutional developments and our deep supposition that the ideal of perfect “clarity”—of precise formalization—is both possible and desirable and that, if realized, it would make any field transmissible by impersonal means. But let us heed Polanyi’s warning that “the ideal of eliminating all personal elements of knowledge would, in effect, aim at the destruction of all knowledge.” Polanyi’s argument about the role of unspecifiable, tacit knowledge in expertise; his elaboration of personal commitment as the core of intellectual inquiry, understood as a craft skill; his demonstration that scientific competence is transmitted through apprenticeship to authoritative teachers—from all of this, “it follows that an art which has fallen into disuse for the period of a generation is altogether lost.”

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and inheritance of past maintaining of as result of historical polemics right vs. left politics and scientific method and situated statistical in West self-absorption self-awareness self-control self-criticism self-discipline self-doubt self-driving cars self-knowledge self-motion self-protection “Self-Reliance” (Emerson) self-responsibility self-sufficiency self-understanding Sennett, Richard sensorimotor contingency sensorimotor experience Seoul sequences Sesame Street sex, Kinsey Reports on sex addicts Sexual Behavior studies (Kinsey) Shapiro, Lawrence Sharon (gambler) Sheba (chimpanzee) Shop Class as Soulcraft (Crawford) short-order cooks background jig of jigging of environment by kitchen-self relationship of as “machine” silence, importance of Simmel, Georg situatedness situated self affordances and situation defining features of pragmatic criteria of propositional knowledge and role of risk in comprehending role of skill in comprehending 60 Minutes skateboarders, world-historical significance of skepticism skill acquisition of and perception of affordances skilled action, contingent facts in skilled practices see also specific skilled practices Sleeper (film) slot machines autoplay see also machine gambling smart technology Smith, Christian “smooth coping” social capital social engineering gambling addiction as nudging and social media social mobility social nature Socrates South Korea sovereign, relationship of citizens to sovereignty, absolute Soviet Union five-year plan in spatial categories speed, judgment and Spiegel, Bernt spontaneous encounters Springsteen, Bruce stackable self Stahl, Lesley state of nature steering head bearings stereotyping stimulation Stoicism stories Stowe, Doug Stradivari, Antonio subjectivism Kant and submission suicide Sunstein, Cass supermarket Supersizing the Mind (Clark) suppression of environment suspension Sweden symbolic representation tacit knowledge tactical flight suit Tagliapietra, Lino Tannenberg, David tannic acid tapered roll bearings taxes, taxation filing of gambling as Taylor, Charles Taylor, George reverse engineering by Taylor and Boody Tea Party technology automaticity and television children’s and orienting response in public spaces Terror (French Revolution) texting Thaler, Richard Thatcher, Margaret “thing in itself” things attention structured by encountering of thought Descartes’s belief in certainty of explicit thrift tipping Tocqueville, Alexis de toddlers mastery of body gained by will of “To Each His Own” (Fleming) tools totalitarianism Toyota recall (2008) toys agency and traction traders tradition as authority vs. self-responsibility traffic lights transvestites Trilling, Lionel truth as representation standard for TRW Turkle, Sherry Two Treatises of Government (Locke) United Kingdom United States apprenticeships criticized in belief in meritocracy of massification in science in social mobility in Upper Half of the Motorcycle, The (Spiegel) value ventilation systems Verizon Vico, Giambattista video gambling violins virtual reality virtual reel mapping, in slot machines virtual stops, in slot machines visual demand visual perception von Hebenstreit, Benedikt walking Wallace, David Foster walls, colored Wampole, Christy “war of all against all” (Hobbes) water wealth Weariness of the Self, The (Ehrenberg) Weber, Max weight lifting Weil, Simone welfare reform Whitman, Walt Who Owns the Future?

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
by Thomas H. Davenport and Julia Kirby
Published 23 May 2016

And note here that, not long ago, we would not have said the ability to study an X-ray or MRI and render a diagnosis could be codified. This is, after all, the profession that loves its “Aunt Minnie.” That’s a term, reportedly first used by a Cincinnati radiologist named Ben Felson in the 1940s, that honors tacit knowledge. As a radiologist gains practical experience, some diagnoses become possible at a glance, because the same image has come up so many times before. In Felson’s words, the radiologist is presented with “a case with radiologic findings so specific and compelling that no realistic differential diagnosis exists.”

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Many of these activities are supported and accelerated by computers, but none are driven by them.” There is a common thread in all these thinkers’ categories, and it has everything to do with the codification mentioned earlier. The moment a realm of intellectual activity is codifiable, it ceases to be uniquely human. The human strengths they point to all involve tacit knowledge and judgment calls that can’t be specified in an algorithm—at least, not yet. But what the past sixty years have shown us is that, as soon as a realm of knowledge can be made explicit, the algorithm becomes possible. At that point, no decisions requiring judgment need to be made—or the few that still do are considered acceptable casualties, because there are only small consequences and costs associated with them if the decisions are made poorly.

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Summing it up: “Look for high-character, unselfish guys who are tough, physical, and play the right way, who care more about winning than paychecks and stats.” It’s interesting to note here that these keys to success are themselves traits that wouldn’t show up in a player’s stats—and would therefore be invisible to the analytics. In McDonough’s appreciation of the tacit knowledge he gained from mentors—he also says “working under (Celtics president of basketball operations and former player) Danny Ainge was the best thing that happened in my career”—is a lesson for anyone who wants to win by stepping aside. It also didn’t hurt that his dad was sports reporter Will McDonough, whom Dan Shaughnessy of the Boston Globe (no slouch himself) describes as “the toughest, most street-smart and knowledgeable of all-time.”15 The first way to soak up deeply human strengths is to spend time with the humans who already have them.

Human + Machine: Reimagining Work in the Age of AI
by Paul R. Daugherty and H. James Wilson
Published 15 Jan 2018

In other words, they are exactly the kind of technology that is enabling the third wave of business process improvement—adaptable processes—that we discussed in the introduction chapter. These applications are more transformational and typically require human employees to actively participate, applying a kind of tacit knowledge or expertise that is difficult to explain or model. Think of the global bank’s anti-money-laundering system that we discussed earlier. A complicated financial transaction is processed; an automated system flags it as being suspicious; and a human expert exercises the judgment to decide whether it warrants further investigation.

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Thus far, they have developed an algorithm that can detect sarcasm on social media and websites with an accuracy of at least 80 percent.3 As AI creeps across industries, more businesses will need trainers for their physical and software-based systems. As a first step, consider using expert employees who already work closely with AI or with the systems that will integrate AI as initial trainers. Their tacit knowledge can often make the difference in a system that works well and one that is prone to failure. Then, after a system has learned the fundamentals, consider next-level training, which can provide further nuance and resilience—as demonstrated in the following examples. An empathy trainer is an individual who will teach AI systems to display compassion.

Working Identity, Updated Edition, With a New Preface: Unconventional Strategies for Reinventing Your Career
by Herminia Ibarra
Published 17 Oct 2023

Just like guiding figures, new communities play a number of important roles: They offer inclusion, provide a safe base, and replace the community that is being lost. Communities of practice are an integral part of the test-and-learn method because we need a context in which to learn both the substance and style of the new self we are trying to become. Some of us, like Ben Forrester, are lucky enough to find a guiding figure who can also teach us the tacit knowledge of the occupation we are trying to enter; more often than not, however, we have to learn by doing and participating in whatever limited way we can in the life of the group we’d like to join. Consider how a person moves into a career the first time around, as a young adult. Apprentices work with their mentors and learn craftsmanship by observation, imitation, and practice.

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Newcomers to a profession or organization are socialized by old-timers, meaning that they are taught not only the required skills and rules but also how to acquire the right look and feel—the social norms that govern how they should conduct themselves so as to become true members.15 In the same way, reinventing oneself as a member of a new occupational world is a process of becoming an insider to that world, learning its subjective viewpoint, language, demeanor, and outlook. But since apprenticeships and internships typically exist in institutional form for only the young, at midcareer we are left to our own devices when it comes to picking up the tacit knowledge of the new work we wish to do. It is up to us to create or find our own community. If we are free to try out any identity we like, it is also true that we must rely on others to complete the picture of which we are only allowed to paint certain parts.16 The desired identity remains incomplete and tentative without the stamp of approval of a new peer group, mentor, or community.

Our Own Devices: How Technology Remakes Humanity
by Edward Tenner
Published 8 Jun 2004

Try, without manipulating an actual pair of laces on shoes, to write a paragraph explaining to a novice—and there must be at least a billion or two around the world—how to tie the knot. If you can do that in your mother tongue and are proficient in another, try to explain the procedure in your second language. You will probably find it easier to restate the ontological argument for the existence of God, or any other philosophical or theological idea. Tacit knowledge, what we can do but seldom explain, is essential. The special vocabulary of the everyday is obscure. How many people know the proper words for the plastic- or metal-bound ends of shoelaces, aglets or tags?3 Baker’s narrator could have discovered even more about shoelace technique. Simple objects can call for a surprising level of skill.

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Thus the thumb may be the best symbol for a new technological optimism based on user self-reliance, a proletarian digit resurgent in the digital age. The index finger signifies authority, marking regulations and warnings in texts, wagging and lecturing in person: the Rules. The thumb connotes the practical knowledge men and women have worked out for themselves: the Rules of Thumb. And it represents tacit knowledge, the skills we can’t always explain: as in the Green Thumb. Most of all, when extended in the almost lost art of hitchhiking, the thumb shows the right attitude toward the future, open and cooperative but with a firm sense of direction. Notes PREFACE 1. Michael M. Weinstein, “A Test You’re Apt to Flunk,” New York Times, March 28, 1993. 2.

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Norman, The Psychology of Everyday Things (New York: Basic Books, 1988); Henry Petroski, The Evolution of Useful Things (New York: Alfred A. Knopf, 1993). 3. Dave Duehls, “Fit to Be Tried,” Runner’s World, vol. 28, no. 10 (October 1993), 26–27; Nicholson Baker, The Mezzanine (New York: Vintage Books, 1990), 16–18; Jerry Fodor, “The Appeal to Tacit Knowledge in Psychological Explanation,” Journal of Philosophy, vol. 65, no. 20 (October 24, 1968), 627–28. 4. Robert D. Richardson, Jr., Henry Thoreau: A Life of the Mind (Berkeley: University of California Press, 1986), 290–91; Geoffrey Wolff, The Duke of Deception: Memories of My Father (New York: Vintage Books, 1990), 52; Ed Dentry, “Hikers Need Lessons in Tying the Knot,” Rocky Mountain News, August 1, 1997; Melvyn P.

The Knowledge Economy
by Roberto Mangabeira Unger
Published 19 Mar 2019

Moreover, the businesses of the knowledge economy can thrive only by creating around themselves a wide penumbra of people, institutions, practices, and ideas conducive to their work. All this embodied or tacit knowledge represents what economists have called a “non-rivalrous” good: its use by some fails to deplete its use by others except to the extent that the law of intellectual property intervenes to limit access to it, making a non-rivalrous good “excludable.” The proliferation of shared tacit knowledge and capabilities in the knowledge economy will not only foster the development of advanced firms and advanced parts of the production system; it will also make it easier for the successful to flourish yet more, widening their lead.

Piracy : The Intellectual Property Wars from Gutenberg to Gates
by Adrian Johns
Published 5 Jan 2010

tacit property Claims that research is intrinsically inhospitable to rules and doctrines therefore emerged repeatedly in the midcentury furor over patents, science, and the public good. Shorn of their ties to intellectual property anxieties, such claims today bring to mind the work of the chemist and philosopher Michael Polanyi, who maintained that research rested on tacit knowledge and therefore could not be subjected to planning. But his work should not be shorn from those ties. A chemist and refugee from Nazism, in Manchester Polanyi had become increasingly exercised by the questions of the nature and public role of science, and devoted years to answering them. His principal target at first was the crystallographer and Marxist, J.

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Their conduct in such roles corresponded to no articulable principle or method beyond the practice itself, and must be unpredictable. But their freedom in those roles redounded to the benefit of all. Polanyi insisted that research itself was similarly not a matter of methodological rules, but rather of “tacit knowledge.” That is, it rested on ineffable techniques, preferences, and norms that together resembled a tradition more than a rational system. For that reason, while Hayek warned that planned research was tyrannical, Polanyi believed it impossible. Research, to be genuine science, must play out in something like a marketplace, characterized by “the Liberal conception” of freedom.

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Inventors would be left at the mercy of rapacious corporations, and could not afford to seek backing for fear of seeing their creations expropriated. Research would stagnate amid a reversion to craft secrecy. Polanyi thus recognized the strength of the assumption that “pioneer” inventions needed patents. But that assumption, he insisted, was false. If research was truly a matter of tacit knowledge, then no algorithm could exist to predict even probabilistically which candidate discoveries or inventions would succeed. There was no such thing as “commercially justified” investment in pioneer ventures, therefore, with or without a patent system. This being so, there was nothing to offset the “grave difficulty” of patenting, namely, the truism that “the full benefit of knowledge is only reaped when its circulation is free.”

The Facebook era: tapping online social networks to build better products, reach new audiences, and sell more stuff
by Clara Shih
Published 30 Apr 2009

Traditionally, people relied on tacit, anecdotal knowledge about who knows what and who used to work where to track down internal expertise. This is extremely difficult, however, in organizations that are larger, geographically dispersed, or have high employee turnover—the trend most companies are headed in. Also, the desired expertise often lies across organizational and functional boundaries where tacit knowledge and regular communication links are weakest. Online social networking offers an easier, more systematic way to find experts and knowledge. Public social networking sites like Facebook and LinkedIn are helpful for finding external expertise. Corporate social networking solutions, such as Connectbeam and IBM’s Lotus Connections, are ideal for locating internal expertise.

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Active Candidates Increasingly, people who are actively seeking jobs are looking to LinkedIn and to a lesser extent, Doostang. There are a few reasons people might prefer to find jobs using social networking sites. First, there is a greater sense of trust within one’s social network. Job seekers can see exactly how they might be connected to a prospective job and employer, perform better due diligence, and gain tacit knowledge about the people and opportunity at hand. Trust and familiarity are paramount in job seeking; as mentioned earlier, people’s careers are a major, intensely personal life decision. Second, the candidates with whom I spoke complained about the overwhelming number of junk listings on traditional job sites that were irrelevant, redundant, or out of date.

Essential Scrum: A Practical Guide to the Most Popular Agile Process
by Kenneth S. Rubin
Published 19 Jul 2012

In aggregate, if the team has roughly 200 points of work to complete and velocity declines by one-half, what would have cost $200K to complete will now cost $400K. So, using velocity, we can clearly see the financial cost of the interest payments on the accrued technical debt. Make Technical Debt Visible at the Technical Level Technical people often have tacit knowledge of where at least the most egregious technical debt is located in the product. However, that understanding may not be visible in a way that it can be analyzed, discussed, and acted upon. Figure 8.9 illustrates three ways of making technical debt visible at the technical level. Figure 8.9. Ways to make technical debt visible at the technical level First, technical debt could be logged like defects into an existing defect-tracking system (left side of Figure 8.9).

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A behavior whereby team members with available capacity and appropriate skills collectively work (swarm) on an item to finish what has already been started before moving ahead to begin work on new items. See also T-shaped skills. synchronization. Causing multiple events to happen at the same time. Frequently used to ensure that multiple Scrum teams work together in a coordinated way by starting and ending their sprints on the same days. See also cadence. T tacit knowledge. Unwritten and unspoken knowledge (including insights, intuitions, and hunches) that is hard, but not impossible, to articulate with formal language. The opposite of explicit or formal knowledge. Sometimes referred to as “know-how.” targeted technical debt. A status category for technical debt that represents debt that is known and has been targeted for servicing by the development team.

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See also Component teams Succeeding with Agile (Cohn), xxv, 397 Summarization aspect, of sprint review, 369–370 Sustainable pace defined, 418 of development team in performance of work, 56, 208–209 Sutherland, Jeff, xxix–xxx, 3 Swarming defined, 418 sprint execution and, 351–352 T-shaped skills, 201–203 Synchronization defined, 418 of multiple teams, 220, 222 System system-level constraints expressed via nonfunctional requirements, 93 system-level focus in sprint retrospective, 385 testing in definition of done, 75 Systems perspective, of managers, 235 T T-shaped skills choosing who does the work and, 354 defined, 420 diversity of development team and, 201–203 finding balance in utilization of, 351 Tacit knowledge defined, 419 of technical debt, 154 Takeuchi, Hirotaka, 3 Targeted technical debt defined, 419 servicing, 155 Task board for communicating sprint execution progress, 356–357 defined, 419 Tasks defined, 419 during sprint planning, 22 estimating sprint backlog, 122 organizing task work, 352–353 technical practices for performance of, 355–356 TDD (test-driven development), 378, 419–420 Team structures coordinating multiple teams using release train approach (Leffingwell), 220–223 coordinating multiple teams using scrum of scrums, 218–220 feature teams vs. component teams, 213–218 multiple team coordination, 218 overview of, 213 Teams compared with groups, 209–210 coordinating multiple, 218–220 cross-functional.

The Rise of the Network Society
by Manuel Castells
Published 31 Aug 1996

What he labels “the knowledge-creating company” is based on the organizational interaction between “explicit knowledge” and “tacit knowledge” at the source of innovation. He argues that much of the knowledge accumulated in the firm comes from experience, and cannot be communicated by workers under excessively formalized management procedures. And yet the sources of innovation multiply when organizations are able to establish bridges to transfer tacit into explicit knowledge, explicit into tacit knowledge, tacit into tacit, and explicit into explicit. By so doing, not only is worker experience communicated and amplified to increase the formal body of knowledge in the company, but also knowledge generated in the outside world can be incorporated into the tacit habits of workers, enabling them to work out their own uses and to improve on the standard procedures.

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In an economic system where innovation is critical, the organizational ability to increase its sources from all forms of knowledge becomes the foundation of the innovative firm. This organizational process, however, requires the full participation of workers in the innovation process, so that they do not keep their tacit knowledge solely for their own benefit. It also requires stability of the labor force in the company, because only then does it become rational for the individual to transfer his/her knowledge to the company, and for the company to diffuse explicit knowledge among its workers. Thus, this apparently simple mechanism, the dramatic effects of which in enhancing productivity and quality are shown in a number of case studies, in fact engages a profound transformation of management–labor relationships.

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Although information technology does not play a prominent role in Nonaka’s “explicit analysis,” in our personal conversations we shared the thought that on-line communication and computerized storage capacity have become powerful tools in developing the complexity of organizational links between tacit and explicit knowledge. Yet this form of innovation preceded the development of information technologies, and was, in fact, for the past two decades “tacit knowledge” of Japanese management, removed from the observation of foreign managerial experts, but truly decisive in improving the performance of the Japanese firms. Inter-firm networking Let us now turn to consider two other forms of organizational flexibility in the international experience, characterized by inter-firm linkages.

Capitalism Without Capital: The Rise of the Intangible Economy
by Jonathan Haskel and Stian Westlake
Published 7 Nov 2017

Computerized information Software development Patent, copyright, design IPR, trademark, other Yes, since early 2000s Database development Copyright, other Recommended in SNA 1993, but OECD suggests uneven implementation Innovative Property R&D Patents, design IPR Yes, recommended in SNA 2008, introduced gradually since then Mineral exploration Patents, other Yes Creating entertainment and artistic originals Copyright, design IPR Yes in EU, in US since 2013 Design and other product development costs Copyright, design IPR, trademark No Economic Competencies Training Other No Market research and branding Copyright, trademark No Business process re-engineering Patent, copyright, other No Note: R&D should be thought of, in line with official definitions, as scientific-oriented spending as distinct from, say, artistic or design endeavors. “Other” in column 3 refers to things like trade secrets, contracts, etc. Column 3 refers to formal intellectual property: we would expect all intangible investment to produce tacit knowledge as well. Source: Columns 1 and 2 from Corrado, Hulten, and Sichel 2005, column 3 based on Corrado 2010, column 4 from Corrado et al. 2013. Computerized information is the clearest: it is any investment that involves putting information into computers to make them useful in the long run.

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K., 131 rules and norms, 211–14 Sadun, Rafaella, 53, 82 Salter, Ammon, 197 Sampson, Rachelle, 168 Samsung, 73, 112 Sanders, Bernie, 223 Santa Fe Institute, 80 scalability, 9–10, 58, 60, 87, 101–2; definition of, 246n2; importance of, 67–68; income inequality and, 133–34; and increased investment, 110; and intangibles, 65–67; secular stagnation and, 103–5 Schreyer, Paul, 40 Schwarzenegger, Arnold, 16 Science: The Endless Frontier (Bush), 232 Second Machine Age, 30 secular stagnation, 91, 116; explanation for, 101–16; and intangibles investment, 102–3; profits and productivity differences and, 103–7; relationship of scalability and spillovers to, 109–16; symptoms of, 92–96 Shankar, Ravi, 61 Shi, Yuan, 168 Shih, Willy, 85 Shinoda, Yukio, 42 short-termism, 161, 168–69 Sichel, Dan, 4, 5, 39, 42, 43, 45 Siemens, 60–61, 204 single-factor productivity, 98–101 Six Sigma, 51 Skype, 217 Slack, 152, 217 smartphones, 72–73, 81 Smil, Vaclav, 146 Smith, Adam, 36, 188 social capital, 156, 236 soft infrastructure, 156 solar energy, 85 Solow, Robert, 39, 125 Song, Jae, 129, 131, 135 South Wales Institution of Engineers, 83 speculation, 249n1 spending, 46–47, 54; on assets, 20; rent-seeking, 113 Spenser, Percy, 80 spillovers, 9, 58, 61, 87, 102; contestedness and, 87; importance of, 77–79; and intangibles, 72–77, 109–16; Jacobs, 138; Marshall-Arrow-Romer, 62, 138; physical infrastructure and, 147–51; secular stagnation and, 103–4; slowing TFP growth and, 107–9; venture capital and, 178 Spotify, 18 Stack Overflow, 29 Stansted Airport, 1–2, 3–4 Starbucks, 34, 52, 65, 140, 183, 195, 197; scalability of, 67 start-up ecosystems, 222 Statute of Anne (1709), 76 stock markets, 167–68, 205–6; IPOs and, 171–72 stock of intangible assets, 56–57 Summers, Larry, 93 sunkenness, 8–9, 58, 60, 87, 246n5; as characteristic of intangibles, 68–70; importance of, 70–72; venture capital and, 175–76 sustained advantage, 250n2 Sutton, John, 67 symbolic analysis, 132–34 synergies, 10, 58, 61, 87–88, 213; and intangible assets, 80–83, 83–86; among investments, 110; maximizing the benefits of, 214–18; physical infrastructure and, 147–51; venture capital and, 176 System of National Accounts, 20, 43, 51 systems innovation, 198 tacit knowledge, 65 tangible investments, differences between intangible and, 7–10, 58 taxes, 139–40, 235; and financing, 166, 219 technology: and cost of intangible investment, 28; inequality as result of improvements in, 123–24, 126–27; and productivity of intangibles, 28–30; and spillovers, 151–52 Tesla Motors, 24, 111, 209 Thatcher, Margaret, 127 Theory of Moral Sentiments, The (Smith), 188 Thiel, Peter, 78, 175, 184–85, 187, 223 3M, 194 Toffler, Alvin, 4 Tonogi, Konomi, 42 total factor productivity (TFP), 96, 98, 102; poor performance of, 109–9, 114 Toyota, 29, 51 trade and inequality, 124 trademarks, 76 training and education, 51–52, 170, 228–30 Trajtenberg, Manuel, 106 Trump, Donald, 122, 141–42, 143 trust, 156 23andMe, 152 Twitter, 185, 187 Uber, 24, 28, 51; building of driver network by, 112–13; contestedness and, 115; legal travails of, 187; scalability of, 67, 101–2, 105; and synergies, 82; venture capital and, 174, 175 uncertainty, 87 Ure, Andrew, 126 Ur-Nammu, 75 US Federal Reserve, 4, 40, 41, 42, 165 US Food and Drug Administration, 154 Van Reenen, John, 82, 136, 173, 195 venture capital (VC) funding, 154–55, 161, 166, 174–75; problems with, 177–79; and intangibles, 175–77 Vlachos, Jonas, 131 Volcker, Paul, 165 von Mises, Ludwig, 38 von Wachter, Till, 129 Wallis, Gavin, 42, 223–24 Walmart, 81, 187 Warsh, David, 62 Wasmer, Etienne, 128 Watt, James, 78 wealth, 119–20, 121; housing and, 122, 128–29, 136–39; inequality of, 139–40; intangibles’ effects on, 129–40 Wealth of Nations, The (Smith), 36 Weightless World, The (Coyle), 4 Weitzman, Martin L., 195 Welch, Jack, 184 Whalley, Alexander, 224 “What Is the U.S.

The Great Convergence: Information Technology and the New Globalization
by Richard Baldwin
Published 14 Nov 2016

When Carrier announced in 2016 that it would close its facility in Indianapolis and move production to Mexico, it was implicitly saying that it was going to use some of its tax-break-subsidized R&D to create jobs abroad. That does not mean that the offshoring is wrong. And it does not mean that the R&D subsidy is wrong. What it illustrates is the fact that the nature of and justification for R&D subsidies should be refined to encompass the nature of the New Globalization. Tacit knowledge is the next in the schematic diagram. It is defined as knowledge that seems to encourage spatial clustering of production. Such knowledge is difficult to promote directly, but it has the great advantage of being unlikely to leave the nation once it is created. This unique combination explains why so many nations are trying to create industrial clusters or hubs.

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See also developing nations; North Africa Against the Tide: An Intellectual History of Free Trade (Irwin), 119 Age of Discovery, European, 38, 39–40, 46 agglomeration (industrial clustering)/dispersion: cities and, 26; coordination and, 203, 204; free trade and, 129, 136, 194–196; future and, 290, 292–293; geographical distance and, 267; globalization and, 2, 19, 77, 127–130, 136, 140, 143; human capital and, 235; innovation and, 116, 123, 124; jobs and, 232; New Economic Geography and, 186–196, 189f, 194f, 214; Old Globalization (first unbundling) and, 122–124, 123f, 124f; specialization and, 202, 208; stickiness and, 231, 233, 235; tacit knowledge and, 230; transport costs and, 212; wages and, 114–115, 214–215. See also offshoring; reshoring; specialization; stickiness agriculture and food: bubonic plague and, 36; China and, 44; climate change and, 22f; first bundling and, 24–46; migration and, 138; multiple equlibria and, 255f–256; New Globalization/poverty line and, 242; New vs.

The End of Accounting and the Path Forward for Investors and Managers (Wiley Finance)
by Feng Gu
Published 26 Jun 2016

Finally, business enterprises accumulate considerable organizational knowledge through learning and experience. Essentially, they figure out how to do things, big and small, in the most efficient way. Most of this knowledge is tacit, residing with employees. Some companies attempt to make such tacit knowledge explicit with formal “knowledge management systems.” For example, consulting firms formally debrief managers at the end of consulting engagements to preserve the main lessons drawn from the engagement. The fight against organizational amnesia should therefore be an important element of the resource preservation efforts of the company.13 This all leads us to the third usefulness attribute of the proposed information system: ■ Usefulness attribute no. 3: Articulate the major risks to the company’s strategic assets from infringement by competitors, disruptions by new technologies, and regulatory moves, as well as the measures taken by management to mitigate these risks.

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You should inquire: Does management regularly monitor its competitors and alliance partners to make sure that its patents, brands, and know-how are not infringed upon, and does management act vigorously when they are? Are disruption threats—a new technology developed elsewhere that threatens incumbent’s technology—monitored continuously and effectively?11 Is the obsolescence of know-how—employee skills, 236 PRACTICAL MATTERS key business processes—avoided by remedial measures (training)? Is tacit knowledge of employees, particularly those soon to retire, made explicit by regular debriefing and knowledge management systems? Are the company’s mineral assets threatened by regulators or environmental activists? In brief, has management instituted effective systems to protect and preserve the strategic assets of the company?

Fully Grown: Why a Stagnant Economy Is a Sign of Success
by Dietrich Vollrath
Published 6 Jan 2020

Whatever the decision, does this represent a necessary action by Apple to defend the innovation of rounded edges and gridded icons, or was it an attempt by the firm to kneecap a potential competitor? Would Apple have gone out of business without those patents? Partly on the basis of such examples, Michelle Boldrin and David Levine have argued for the abolition of IPRs. Their argument is that nonrival ideas are excludable through either training (e.g., as with a surgeon) or the tacit knowledge required to use them (e.g., manufacturing a car). In the case of Apple, they might argue that its intellectual property was protected by Apple’s own brand, marketing, customer service, and better software, and that the patents themselves were just a way of extorting payments from Samsung. A different example in support of their case against IPRs is Tesla, the electric car company, which gave away all of its patents.

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You could go out and build yourself an exact replica of a Tesla right now if you wanted to. To Boldrin and Levine’s point, though, while in theory you could build your own Tesla, in reality you can’t. You don’t have the requisite knowledge, training, and capital to reproduce a Tesla in your own garage. That tacit knowledge and specialized equipment mean that the nonrival idea of a Tesla is effectively excludable, even with no legal protections in place. That illustrates, I think, the need to think of IPRs and market power on a case-by-case basis. For Tesla, IPRs are unnecessary for the reasons Boldrin and Levine suggest.

What Algorithms Want: Imagination in the Age of Computing
by Ed Finn
Published 10 Mar 2017

ORION and its 1,000-page “solution” to this tangled problem is, of course, a process or system in continued evolution rather than an elegant equation for the balletic coordination of brown trucks. Its equations and computational models of human behavior are just one example among millions of algorithms attempting to regularize and optimize complex cultural systems. The pragmatist’s definition achieves clarity by constructing an edifice (a cathedral) of tacit knowledge, much of it layered in systems of abstraction like the traveling salesman problem. At a certain level of cultural success, these systems start to create their own realities as well: various players in the system begin to alter their behavior in ways that short-circuit the system’s assumptions.

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Like every romance, the attraction is based on both familiarity and foreignness—the recognition of ourselves in another as well as the mystery of that other. As technical systems, algorithms have always embodied fragments of ourselves: our memories, our structures of knowledge and belief, our ethical and philosophical foundations. They are mirrors for human intention and progress, reflecting back the explicit and tacit knowledge that we embed in them. At the same time they provide the essential ingredient of mystery, operating according to the logics of the database, complexity, and algorithmic iteration, calculating choices in ways that are fundamentally alien to human understanding. On the surface, it may seem as if the apotheosis of the algorithm in contemporary culture has not brought us any closer to the consummation of our twinned desires for perfect knowledge of the world and perfect knowledge of ourselves.

Lying for Money: How Fraud Makes the World Go Round
by Daniel Davies
Published 14 Jul 2018

He thought it was insoluble, because most of the information that you would need to plan an economy was ‘tacit’ – embodied in personal experience, spread out across the production units themselves and not available, even in principle, to any information-collecting authority. Although this very strong version of tacit knowledge is controversial, a weaker version of the idea has been very influential indeed. And that’s the concept of private information, which the planner doesn’t have, either because it’s too costly to collect or because the people who generate the information don’t want to share it. The great thing about the market economy is that the information itself can stay private – all the disaggregated system needs to know about it can be summarised in its effect on market prices.

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A. 201–3,205 Henry VIII 216 high-net worth investors tendency to have time on hands 109 tax strategies of a proportion of 266–8 Hippocratic Oath 134 hire purchase scam (Leslie Payne) 36, 39–40 homomorphism 209, 212 Hooley, Ernest ‘The Millionaire’ 230 hotel bills 37 House of Commons 1 Howe, Sarah 90, 116–19, 222 HSBC 188, 189, 280 Hudson Oil 249, 251 Humphery, John Stanley 228 I IBM 64–8 Iceland 218–22 Inca Empire 226–7 Incentives 13, 22, 62, 74, 115, 135, 159, 165, 174, 185–6, 205, 210 incidental fraud vs entrepreneurial 213, 215, 287, 288 Infinity Game 92–9 information 24, 71, 199–208, 211–15, 238 control of by fraudsters 41, 65, 71, 115, 173 insider, securities fraud 23, 239–42, 260 inheritance 117, 217, 218–22, 235, 266 insider dealing 23, 106, 129, 241–43, 260 insurance 36, 39–40, 65, 163–4, 171, 225, 228 medical 74–7, 84 Payment Protection Insurance (PPI) 187–97 insurance scam (Leslie Payne) 40–41 International Reply Coupons see Ponzi, Charles investors 1, 16 in OPM leases 65–7, 69–71 Charles Ponzi’s 86–9 hedge fund 96, 104–9, 113 in pigeons 100, 103 institutional 104 nineteenth century female 118–20 mining 126–30 reliance on accounts 142–54 expectations of UK banks 188 Victorian 228, 231 Retail 240–43 in Piggly Wiggly 256–61 IRS vs UBS 263–4 Israel, Sam see Bayou Capital drug habit of as potential indicator something was wrong 116 J Jehoash (high priest) 217 John Bull 230 K Keating Five 182 Keating, Charles 177–83, 214 Kennedy, John Fitzgerald 61 Kerviel, Jerome 165 King, Don 163 Knights of Industry 234, 237 Kolnische Volkszeitung 232, 234, 236, 237 KPMG 150 Kray, Ronnie and Reggie 26–7, 31, 36, 39, 41 Kutz Method 152–3 KYC (know your customer) 281 L Lab fraud anaemia 74 Ladies’ Deposit Bank (Boston) 116–19 lawyers 19, 27, 33–4, 39, 45, 71, 115, 117, 161, 180, 182, 194, 196, 225, 267, 271, 272, 281 (they’re usually in the background even when not specifically mentioned) professional qualifications of 114 extreme expensiveness of 234 leasing tax advantages of 64 see also OPM Leasing importance of residual value 66 accountancy issues 152 Leeson, Nick 17, 165–73, 285 Lehman Brothers collapse 13 relationship with OPM Leasing 65, 71 Lehnert, Lothar 235–7 Lernout & Hauspie 150 Let’s Gowex see Gowex letterhead 31, 70, 80, 122 Levi, Michael 81, 216, 283 Levy, Jonathan 224 libel 77, 236–8 LIBOR 1–4, 12–16, 193, 205, 215, 244 Liman & Co 235–6 limited liability 34, 225, 231 Lincoln Savings & Loan 177–8, 180, 182–3 livestock 100 Livingstone, Jesse 259 Lloyd’s of London 164, 225 Lomuscio, Joe 59 Long firms 21, 23, 27, 29, 35, 41–2, 43–50, 61, 63, 72, 73–5, 77, 79–82, 96, 141, 142, 163, 164, 212, 224, 283, 284 ‘sledge-drivers’ 232–4 against government 271–4 Lucifer’s Banker 263 M MacGregor, Gregor 5, 8, 9, 17, 77, 78, 214 dubious knighthood of 7, 162 military career 7 previous frauds 18 Madden, Steve 147 Madoff, Bernard 96, 104–5, 113 Mafia 41, 253 Mahler, Russ 249–53 management scientific 19, 200, 206–12, 215 risk management 212–13, 287 strategic 248 public sector 264 marginal cost pricing 248 Marino, Dan (fraudster) 107–9, 113, 115 Marino, Dan (quarterback) 107 maritime capitalism 34, 224–6 market corner 259 market crimes 23, 24, 58, 194, 239–62, 271, 282, 289 markets general characteristics of 23, 197, 201–4, 208, 278, 289 financial 3, 4, 8, 13, 26, 58–60, 99, 100, 107–8, 129, 132, 142–5, 147–8, 149, 150–56, 161, 163, 166, 171–2, 176, 195, 230–31, 239–40, 242–4, 256–61 pharmaceutical, ‘grey’ 136–7 drugs, illegal 43–50 prime bank securities 110–11, 184 real estate 179–80 supermarkets 213, 255 Marx, Groucho 66 Marx, Karl 84, 232, 247 McGregor, Ewan 165, 173 McVitie, Jack ‘The Hat’ 26, 41 Medicare 73–6,134–5, 199, 289 Merchant of Venice 34 Merck Pharmaceuticals 138–40 Michaela, Maria 215, 222 military planning 204, 207, 211 Milken, Michael 177, 183 Miller, Norman 52 mis-selling 194–6 money laundering 278–82 Monopolies Commission (UK) 247 mortgages 38, 77, 101, 175–9, 188, 191, 194, 215, 238 multi-level marketing 94–5 N New England Journal of Medicine 139 New Zealand 9, 172, 241 newspapers 9, 125, 152, 230, 237, 252, 262 Nichols, Robert Booth 110–12 Nikkei index 170–71, 173 nobility Scottish 7 phony scottish 5–9, see Gregor MacGregor phony 223 North Wales Railway Company 229 notaries 114, 125, 133 indiscriminate stamping of documents by in 1920s Portugal 121–2 O ODL Securities 112–13 OECD 268 oil recycling 249–54 OODA loop 208 operations research 204, 208–10, 289 OPM Leasing 63–72 snowball effect of interest expense 98 accounting trick 152–3 options markets 163–4, 171–2 Optitz, Gustav 235–7 Opus Dei 53, 57 Original Dinner Party 92 Other People’s Money 63, 285 P Paddington Buys A Share 20, 43 Parmalat 155 Patsies see fronts Payment Protection Insurance (PPI) 187–97 Payne, Leslie 26–8, 30, 33–6, 39–42, 67, 73, 98, 163, 237, 283 petrol stations 190, 247–8 pharmaceutical industry 133–41 track and trace 136 Philadelphia Savings Fund 70–71 Pigeon King International see Galbraith, Arlan pigeons, racing 100–103 Piggly Wiggly 255–61 Ponzi, Charles 84–90, 96, 109, 116 trial of 90 takeover of Hanover Trust 88–9 launch of scheme 86 Portuguese Banknote Affair 120–25 Powers, Austin 263 Poyais 5–9, 15, 78, 121, 162, 215, 219, 287, 297 prime bank securities 110–13, 122, 184 Prince 135 Prince Albert 228 Princess Caraboo see Baker, Mary Princesses 6, 223 Principles of Scientific Management 206 Prison 18, 61, 112, 119, 125, 173, 208, 252, 270 debtor’s 34, 225 private equity 144 psychology 17, 87 public choice theory 210–11 pump and dump 147 pyramid schemes 91–5, 116, 184, 222 Q Quakers 118 quality control 184, 207, 213–15, 287 Quanta Resources 251–2 Quarterly Review 162 Queen Victoria 228 Queenan, Joe 10 Qwest 150 R Rabelais, Francois 120 Railway Mania 176, 231 Ranbaxy Laboratories 137 Reagan, Ronald 174–5, 251 real estate 89, 177–81, 214, 281 Reddit 48 regulators financial 2, 4, 14, 18, 99, 165, 177–83, 194–5, 240, 260–61, 280–81, 289 softness of in 1960s London 40 environmental 250–51 pharmaceutical 136, 137, 140 Reuschel, Rollo (Stanislaus Reu) 232–8 libel case 237 Richmond-Fairfield 107 Robb, George 228 Rockwell Industries 66–71 Rogers, Will 283 rogue traders 98, 165–73, 215 Royal Canadian Mounted Police 129 S salting (mining fraud technique) 127 Sarbanes-Oxley 194, 202 Saunders, Clarence 255–61 Savings and Loans 174–84, 185, 196, 285, 289 economic theories of failure 174 business model 175 settlement, securities 60, 107, 108, 112, 163, 257, 261 Sherman Antitrust Act 246 shipowners 10, 116, 117, 164, 224–6 ships 164, 207, 221, 224–6 US Navy 89, 249 short firm 73–5, 93 short selling 147, 258–9, 261, 283 shotgun/rifle technique 76–7, 134 signatures, forged 67, 123 Silk Road (online market) 44, 47–8, 50 simplified summary which hopefully captures the important structural features see homomorphism Sketch of the Mosquito Shore 8, 162 Skilling, Jeff 17, 142, 153 slaves 34, 219–21, 225 ‘sledge-drivers’ 232–8 SLK Securities 108, 115 Smith, Adam 11, 213 on cartels 246 snowball effect see compound interest societies, high and low trust 10, 16, 62, 125, 166–7, 264, 287 Soviet planning 204, 208, 227 Sparrow, Malcolm 74, 76 St Joseph (fictitious city) 5 stock exchanges Alberta 11, 129 Toronto 129 Vancouver 11, 126 London 9, 117 New York 59–60,147, 228–31, 256–61 Chicago 59–60, 256 Singapore 170–72 Osaka 170 Tokyo in general 142–5, 147, 163–4,241–2 NASDAQ 240 Strangeways, Thomas 162, see also Gregor MacGregor Strathclyde Genetics see Galbraith, Arlan Stratton Oakmont 145–8 Sufficient Variety, Law of 209 Sullivan, Scott 154 Susquehanna River 251, 252 T tacit knowledge 202–3 Tarantino, Quentin 105 tax 32, 64, 69, 98, 155, 159, 177, 191, 263–71 value added see VAT Taylor, F. W. 206 Taylorism 206 Ten Commandments 14, 23 Tennessee Valley Authority 244 Thackeray, W. M. 229 The Economist 125 The Great Salad Oil Scandal 52 The Sting 17 The Uses of Knowledge in Society 202, 203 The Wolf of Wall Street 145–7 Thomas Jenkins & Co 5 Thorolf (saga character) 218–22 Times, The (newspaper) 230 Times Beach (polluted town) 252 toxic waste 249–54 Toyoda, Sakichi and Kiichio 256 traders, financial 2–3, 59, 98, 107, 116, 163, 242, 258 rogue 165–8, 172–3 Trainspotting 280 trust 10–12, 15–17, 20–24, 38–9, 49, 62, 75, 125, 131, 134, 141, 180, 211, 222, 233, 254, 264, 286 circles of 113–16, 137, 280–82 Tupperware 95 TVA see Tennessee Valley Authority Tyson, Mike 101 U UBS 263, 266–70 Kweku Adoboli scandal 215 UK banking sector unusual conditions of at end of 1990s 188–90 Ulfar (saga character) 218–22 unprotected females 117 V VAT 271–8 Victorian era 117, 176. 227–31, 232 VIGOR (research study) 138–40 Vioxx 137–41 Volkswagen 253 W Walsh, David 128–9 warehouse lending 54 Waterlow & Sons 121, 123–5 Wealth of Nations 246 Weil, Raoul 269 Weiner, Norbert 208 Weissman, Mordecai 63–72, 153 West Diddlesex see West Middlesex Life and Fire Assurance Company West Middlesex Life and Fire Assurance Company 229 Westinghouse 244 White Collar Crime in Modern England 228 women 91, 94, 118–19, 122 Women Empowering Women 94, 222 World of Giving (pyramid scheme) 92 Worldcom 152, 154–5 wrongful trading 35–6 Footnotes * Bloomberg terminals, the $50,000/year news and financial data servers that every trader uses, have a chatroom function as well as being able to give you prices and transmit news.

The Warhol Economy
by Elizabeth Currid-Halkett
Published 15 Jan 2020

The same galleries that hold art openings also provide employment and economic security in a very tangible sense to those who work on the openings, curate the exhibitions, and run administration and management. Formal institutions operate as hybrids because they are the centers of official economic transactions (the selling of art, the hiring of a labor force) but also lend themselves to tacit knowledge exchange and informal collaborations and social networks that emerge as a part of a broader phenomenon that these formal and informal nodes of creative exchange offer, otherwise known as the “scene.” The Importance of Scenes It was a cold evening in the early days of March when I met Lee Quinones outside a Cuban restaurant in SoHo.

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Such regional agglomerations appear to sustain themselves not only due to physical resources but also the success of informational and institutional spillovers that allow firms and people to share relevant knowledge and inputs that can be applied in different ways (Piore and Sabel 1984; Saxenian 1994; Castells and Hall 1994; Scott 1993, 2000; Storper 1997). The Marshall-Arrow-Romer (MAR) framework (Mathur 1999) argues that knowledge-intensive industries, in particular, rely on the informal economies of face-to-face interaction, tacit knowledge, and information spillovers that are constantly used and permutated by different actors. In this web of people and firms, the contradictory notions of complements and competition spur a strange brew of constant innovation that is fueled by networks of knowledge and ideas. (See Romer 1990 for a discussion of knowledge spillovers and Saxenian 1994 for a look at rivalry and collaboration.)

An Economist Gets Lunch: New Rules for Everyday Foodies
by Tyler Cowen
Published 11 Apr 2012

A lot of old recipes were this simple, as you’ll see in old cookbooks. It’s not that all the food was unsophisticated, but rather the cooks were operating with a lot of background knowledge, including an understanding of the proper raw materials, or what it meant when you read “srv w soup or gravy.” In economics this is sometimes called “tacit knowledge” and it is an important part of how business firms succeed. Here’s a Thai recipe from her site: “Yam Khao Pot: Thailand. Blend t rdcurrypaste/2T cocontmilk& peanut&lime&cilantro/T fishsauce&dryshrimp(opt). Toss+2c sweetcorn/¼c tstdcocont.” I’ve cooked a lot of Thai food so I have a good sense of the proper portions on the items where it is not indicated.

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See also shipping and transportation infrastructure and the Aztecs, 143 and barbecue, 89 and chili peppers, 207 and cities, 143–44 and cross-subsidies, 65 and French food, 226–27, 229 and Genetically Modified Organisms, 165 historical influences on, 36 and home cooking, 245–46 and immigrants, 28–29 impact on quality of American food, 17–19 and Mexican food, 196, 210 and Nicaraguan food, 5 and poverty, 155–56 and Singaporean foods, 221–22 sushi, 58, 118, 122–23, 216, 218, 258 Susur: A Culinary Life (Lee), 249 Swanson, 35 sweets shops, 224, 240 Switzerland, 222, 235–37 Syngenta, 162 Syria, 157 tacit knowledge, 251 Taco Bell, 188 tacos, 190 Tad’s, 17 Taino culture, 89–90 Taiwanese restaurants, 136 tamales, 7 Tanzania, 129–30 tapas, 20, 239–40 taquerías, 188 Tarahumaras, 251 tariffs, 192 tar sands, 181 Tastee Chinese Food, 52 tastes of consumers, 183–84 taxi drivers, 3–4, 216–17 tax policy, 149, 158, 178–80 teas, 49 technological progress and agricultural revolutions, 146 changing pace of, 13 and home cooking, 258–59 and hunger and malnutrition, 151–52 and kitchen appliances, 35 mechanization of food production, 96, 100–107, 143–44, 154, 203, 205–6 and Mexican food, 209 and modern food market, 154 telegraph, 144 television, 18, 33–37 Teochew food, 221 teosinte, 143 Texas and barbecue, 12, 88, 105–7, 109, 111, 259 and food trucks, 76 and immigration restrictions, 31 and liquor laws, 25–26 and Mexican food, 189, 190, 192, 195, 199, 203, 206 and oil, 181 and perceptions of American food, 19 Texas de Brazil, 111 Texas Monthly, 88 Tex-Mex food, 31, 188 Thai Food (Thompson), 118–19 Thailand and Thai food and agricultural revolutions, 146 described, 116–22 and ethnic supermarkets, 50 and influential cookbooks, 251 in London, 232 and low-rent areas, 75 and seafood, 59 Thai Street Food (Thompson), 119 Thai X-ing, 119–20 Thermomix, 255–56 Thompson, David, 118–19 Ticciati, Laura, 164 Ticciati, Robin, 164 Tijuana, Mexico, 195 Time Out, 237 Tim Hortons, 94 Tlaxcala, Mexico, 98 tofu, 217 Tokyo, Japan, 214–19 tomatoes, 90, 206, 208–10, 246 Tony Roma’s, 96 torta sandwich, 202 tortillas, 141–42, 201–6, 246 tort law, 197 tourism and foods of Istanbul, 241 and foods of London, 231 and French food, 226, 229, 231 and Italian food, 237 and rules for finding good food, 70, 73, 74 traffic patterns, 74 trains, 193 transportation.

The Knowledge: How to Rebuild Our World From Scratch
by Lewis Dartnell
Published 15 Apr 2014

The results from these investigative efforts provide the clues for reaching a diagnosis. After the apocalypse not only will you lose the advanced tests and scanning equipment, but much of the medical expertise itself will also be lost. Medicine and surgery, more than many other areas covered in this book, rely heavily on implicit or tacit knowledge—something you have learned how to do but would find extremely difficult to successfully convey to someone else in just words or pictures. In Britain, it takes up to a decade of medical school and on-the-job learning in a hospital to achieve competency as a registrar doctor (the equivalent of a US fellow in a subspecialty), all of this with training and hands-on demonstrations provided by someone already proficient.

…

Clews, Henry. 1974. Electric Power from the Wind. (ATL 21-466) Norwich, VT: Enertech Corporation. Cohen, Laurie P. 2000. “Many Medicines Are Potent Years Past Expiration Dates.” Wall Street Journal, March 28. http://online.wsj.com/article/SB954201508530067326.html. Collins, H. M. 1974. “The TEA Set: Tacit Knowledge and Scientific Networks.” Science Studies 4 (2): 165–86. Conant, Jeff. 2005. Sanitation and Cleanliness for a Healthy Environment. Berkeley, CA: The Hesperian Foundation. Connolly, Kate. 2001. “Human Flesh On Sale in Land the Cold War Left Behind.” The Observer, April 7. http://www.theguardian.com/world/2001/apr/08/russia.kateconnolly.

Messy: The Power of Disorder to Transform Our Lives
by Tim Harford
Published 3 Oct 2016

A grizzled market participant might have looked at rapidly inflating house prices and mused that a house price crash was possible, even though the United States had not experienced a nationally synchronized crash before. And if that grizzled market participant had been able to talk to the computers, the computers would have been able to demonstrate the catastrophic impact of such a crash on the value of CDOs. Unfortunately, there was no meeting of minds: the computers didn’t have the tacit knowledge of the experienced humans, so they didn’t process the idea that a crash was plausible, while the experienced humans didn’t understand what their intuition would imply for the value of CDOs. It is possible to resist the siren call of the algorithms. Rebecca Pliske, a psychologist, found that veteran meteorologists would make weather forecasts first by looking at the data and forming an expert judgment; only then would they look at the computerized forecast to see if the computer had spotted anything that they had missed.

…

In 2009, Air France 447 was one of just eight crashes, a safety record. The cost-benefit analysis seems clear: freakish accidents like Flight 447 are a price worth paying, as the steady silicon hand of the computer has prevented many others. Still, one cannot help but wonder if there is a way to combine the adaptability, judgment, and tacit knowledge of humans with the reliability of computers, reducing the accident rate even further. One priority could be to make semi-automated systems give feedback in a way that humans feel more viscerally. The crew of Air France 447 were told seventy-five times that they were stalling—STALL STALL STALL—but they didn’t feel it instinctively.

Nervous States: Democracy and the Decline of Reason
by William Davies
Published 26 Feb 2019

It is knowledge that sits closely to the person who possesses it, and can’t be shared with the public in any straightforward way, by publishing, statistics, or public debate. The knowledge of a successful entrepreneur, like that of a skilled mechanic or military commander, doesn’t consist of a set of findings or facts. It isn’t a representation of the world, but an ability to manipulate it. It’s what is sometimes called “embodied knowledge” or “tacit knowledge”—a knowing how, not a knowing that. At a time when business schools and vocational qualifications were still almost unknown in universities (especially in Europe), Hayek believed that this type of know-how was denigrated by intellectuals for lacking objectivity. But in its humility and limitations, he deemed it far less politically dangerous than the knowledge of experts seeking to put their factual and theoretical knowledge to public use.

…

Kennedy International Airport, New York, x, xiii, 41 Johns Hopkins University, 176 Jones, Alexander, 131 Kant, Immanuel, 128, 130 Kemelmacher-Shlizerman, Ira, 188 Kennedy Jr., Robert, 23 Kepler, Johannes, 35 Keynes, John Maynard, 165 King Jr., Martin Luther, 21, 224 knowledge economy, 84, 85, 88, 151–2, 217 known knowns, 132, 138 Koch, Charles and David, 154, 164, 174 Korean War (1950–53), 178 Kraepelin, Emil, 139 Kurzweil, Ray, 183–4 Labour Party, 5, 6, 65, 80, 81, 221 Lagarde, Christine, 64 Le Bon, Gustave, 8–12, 13, 15, 16, 20, 24, 25, 38 Le Pen, Marine, 27, 79, 87, 92, 101–2 Leadbeater, Charles, 84 Leeds, West Yorkshire, 85 Leicester, Leicestershire, 85 Leviathan (Hobbes), 34, 39, 45 liberal elites, 20, 58, 88, 89, 161 libertarianism, 15, 151, 154, 158, 164, 173, 196, 209, 226 Liberty Fund, 158 Libya, 143 lie-detection technology, 136 life expectancy, 62, 68–71, 72, 92, 100–101, 115, 224 Lindemann, Frederick Alexander, 1st Viscount Cherwell, 138 Lloyds Bank, 29 London, England bills of mortality, 68–71, 75, 79–80, 81, 89, 127 Blitz (1940–41), 119, 143, 180 EU referendum (2016), 85 Great Fire (1666), 67 Grenfell Tower fire (2017), 10 and gross domestic product (GDP), 77, 78 housing crisis, 84 insurance sector, 59 knowledge economy, 84 life expectancy, 100 newspapers, early, 48 Oxford Circus terror scare (2017), ix–x, xiii, 41 plagues, 67–71, 75, 79–80, 81, 89, 127 Unite for Europe march (2017), 23 London School of Economics (LSE), 160 loss aversion, 145 Louis XIV, King of France, 73, 127 Louisiana, United States, 151, 221 Ludwig von Mises Institute, 154 MacLean, Nancy, 158 Macron, Emmanuel, 33 mainstream media, 197 “Make America Great Again,” 76, 145 Manchester, England, 85 Mann, Geoff, 214 maps, 182 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210, 211 marketing, 14, 139–41, 143, 148, 169 Mars, 175, 226 Marxism, 163 Massachusetts Institute of Technology (MIT), 179 Mayer, Jane, 158 McCarthy, Joseph, 137 McGill Pain Questionnaire, 104 McKibben, William “Bill,” 213 Megaface, 188–9 memes, 15, 194 Menger, Carl, 154 mental illness, 103, 107–17, 139 mercenaries, 126 Mercer, Robert, 174, 175 Mexico, 145 Million-Man March (1995), 4 mind-reading technology, 136 see also telepathy Mirowski, Philip, 158 von Mises, Ludwig, 154–63, 166, 172, 173 Missing Migrants Project, 225 mobilization, 5, 7, 126–31 and Corbyn, 81 and elections, 81, 124 and experts, 27–8 and Internet, 15 and Le Bon’s crowd psychology, 11, 12, 16, 20 and loss, 145 and Napoleonic Wars, xv, 127–30, 141, 144 and Occupy movement, 5 and populism, 16, 22, 60 and violence, opposition to, 21 Moniteur Universel, Le, 142 monopoly on violence, 42 Mont Pelerin Society, 163, 164 moral emotion, 21 morphine, 105 multiculturalism, 84 Murs, Oliver “Olly,” ix Musk, Elon, 175, 176, 178, 183, 226 Nanchang, Jiangxi, 13 Napoleonic Wars (1803–15), 126–30 chappe system, 129, 182 and conscription, 87, 126–7, 129 and disruption, 170–71, 173, 174, 175, 226 and great leader ideal, 146–8 and intelligence, 134 and mobilization, xv, 126–30, 141, 144 and nationalism, 87, 128, 129, 144, 183, 211 and propaganda, 142 Russia, invasion of (1812), 128, 133 Spain, invasion of (1808), 128 National Aeronautics and Space Administration (NASA), 23, 175 National Audit Office (NAO), 29–30 national citizenship, 71 National Defense Research Committee, 180 National Health Service (NHS), 30, 93 National Park Service, 4 National Security Agency (NSA), 152 national sovereignty, 34, 53 nationalism, 87, 141, 210–12 and conservatism, 144 and disempowerment, 118–19 and elites, 22–3, 60–61, 145 ethnic, 15 and health, 92, 211–12, 224 and imagined communities, 87 and inequality, 78 and loss, 145 and markets, 167 and promises, 221 and resentment, 145, 197, 198 and war, 7, 20–21, 118–19, 143–6, 210–11 nativism, 61 natural philosophy, 35–6 nature, 86 see also environment Nazi Germany (1933–45), 137, 138, 154 Netherlands, 48, 56, 129 Neurable, 176 neural networking, 216 Neuralink, 176 neurasthenia, 139 Neurath, Otto, 153–4, 157, 160 neurochemistry, 108, 111, 112 neuroimaging, 176–8, 181 Nevada, United States, 194 new atheism, 209 New Orleans, Louisiana, 151 New Right, 164 New York, United States and climate change, 205 and gross domestic product (GDP), 78 housing crisis, 84 JFK Airport terror scare (2016), x, xiii, 41 knowledge economy, 84 September 11 attacks (2001), 17, 18 New York Times, 3, 27, 85 newspapers, 48, 71 Newton, Isaac, 35 Nietzsche, Friedrich, 217 Nixon, Robert, 206 no-platforming, 22, 208 Nobel Prize, 158–9 non-combatants, 43, 143, 204 non-violence, 224 North Atlantic Treaty Organization (NATO), 123, 145, 214 North Carolina, United States, 84 Northern Ireland, 43, 85 Northern League, 61 Northern Rock, 29 Norwich, Norfolk, 85 nostalgia, xiv, 143, 145, 210, 223 “Not in my name,” 27 nuclear weapons, 132, 135, 137, 180, 183, 192, 196, 204 nudge techniques, 13 Obama, Barack, 3, 24, 76, 77, 79, 158, 172 Obamacare, 172 objectivity, xiv, 13, 75, 136, 223 and crowd-based politics, 5, 7, 24–5 and death, 94 and Descartes, 37 and experts, trust in, 28, 32, 33, 51, 53, 64, 86, 89 and Hayek, 163, 164, 170 and markets, 169, 170 and photography, 8 and Scientific Revolution, 48, 49 and statistics, 72, 74, 75, 82, 88 and telepathic communication, 179 and war, 58, 125, 134, 135, 136, 146 Occupy movement, 5, 10, 24, 61 Oedipus complex, 109 Office for National Statistics, 63, 133 Ohio, United States, 116 oil crisis (1973), 166 “On Computable Numbers” (Turing), 181 On War (Clausewitz), 130 Open Society and Its Enemies, The (Popper), 171 opiates, 105, 116, 172–3 opinion polling, 65, 80–81, 191 Orbán, Viktor, 87, 146 Organisation for Economic Co-operation and Development (OECD), 72 Oxford, Oxfordshire, 85 Oxford Circus terror scare (2017), ix–x, xiii, 41 Oxford University, 56, 151 OxyContin, 105, 116 pacifism, 8, 20, 44, 151 pain, 102–19, 172–3, 224 see also chronic pain painkillers, 104, 105, 116, 172–3 Palantir, 151, 152, 175, 190 parabiosis, 149 Paris climate accord (2015), 205, 207 Paris Commune (1871), 8 Parkland attack (2018), 21 Patriot Act (2001), 137 Paul, Ronald, 154 PayPal, 149 Peace of Westphalia (1648), 34, 53 peer reviewing, 48, 139, 195, 208 penicillin, 94 Pentagon, 130, 132, 135, 136, 214, 216 pesticides, 205 Petty, William, 55–9, 67, 73, 85, 167 pharmacology, 142 Pielke Jr., Roger, 24, 25 Piketty, Thomas, 74 Pinker, Stephen, 207 plagues, 56, 67–71, 75, 79–80, 81, 89, 95 pleasure principle, 70, 109, 110, 224 pneumonia, 37, 67 Podemos, 5, 202 Poland, 20, 34, 60 Polanyi, Michael, 163 political anatomy, 57 Political Arithmetick (Petty), 58, 59 political correctness, 20, 27, 145 Popper, Karl, 163, 171 populism xvii, 211–12, 214, 220, 225–6 and central banks, 33 and crowd-based politics, 12 and democracy, 202 and elites/experts, 26, 33, 50, 152, 197, 210, 215 and empathy, 118 and health, 99, 101–2, 224–5 and immediate action, 216 in Kansas (1880s), 220 and markets, 167 and private companies, 174 and promises, 221 and resentment, 145 and statistics, 90 and unemployment, 88 and war, 148, 212 Porter, Michael, 84 post-traumatic stress disorder (PTSD), 111–14, 117, 209 post-truth, 167, 224 Potsdam Conference (1945), 138 power vs. violence, 19, 219 predictive policing, 151 presidential election, US (2016), xiv and climate change, 214 and data, 190 and education, 85 and free trade, 79 and health, 92, 99 and immigration, 79, 145 and inequality, 76–7 and Internet, 190, 197, 199 “Make America Great Again,” 76, 145 and opinion polling, 65, 80 and promises, 221 and relative deprivation, 88 and Russia, 199 and statistics, 63 and Yellen, 33 prisoners of war, 43 promises, 25, 31, 39–42, 45–7, 51, 52, 217–18, 221–2 Propaganda (Bernays), 14–15 propaganda, 8, 14–16, 83, 124–5, 141, 142, 143 property rights, 158, 167 Protestantism, 34, 35, 45, 215 Prussia (1525–1947), 8, 127–30, 133–4, 135, 142 psychiatry, 107, 139 psychoanalysis, 107, 139 Psychology of Crowds, The (Le Bon), 9–12, 13, 15, 16, 20, 24, 25 psychosomatic, 103 public-spending cuts, 100–101 punishment, 90, 92–3, 94, 95, 108 Purdue, 105 Putin, Vladimir, 145, 183 al-Qaeda, 136 quality of life, 74, 104 quantitative easing, 31–2, 222 quants, 190 radical statistics, 74 RAND Corporation, 183 RBS, 29 Reagan, Ronald, 15, 77, 154, 160, 163, 166 real-time knowledge, xvi, 112, 131, 134, 153, 154, 165–70 Reason Foundation, 158 Red Vienna, 154, 155 Rees-Mogg, Jacob, 33, 61 refugee crisis (2015–), 60, 225 relative deprivation, 88 representative democracy, 7, 12, 14–15, 25–8, 61, 202 Republican Party, 77, 79, 85, 154, 160, 163, 166, 172 research and development (R&D), 133 Research Triangle, North Carolina, 84 resentment, 5, 226 of elites/experts, 32, 52, 61, 86, 88–9, 161, 186, 201 and nationalism/populism, 5, 144–6, 148, 197, 198 and pain, 94 Ridley, Matt, 209 right to remain silent, 44 Road to Serfdom, The (Hayek), 160, 166 Robinson, Tommy, ix Roosevelt, Franklin Delano, 52 Royal Exchange, 67 Royal Society, 48–52, 56, 68, 86, 133, 137, 186, 208, 218 Rumsfeld, Donald, 132 Russian Empire (1721–1917), 128, 133 Russian Federation (1991–) and artificial intelligence, 183 Gerasimov Doctrine, 43, 123, 125, 126 and information war, 196 life expectancy, 100, 115 and national humiliation, 145 Skripal poisoning (2018), 43 and social media, 15, 18, 199 troll farms, 199 Russian Revolution (1917), 155 Russian SFSR (1917–91), 132, 133, 135–8, 155, 177, 180, 182–3 safe spaces, 22, 208 Sands, Robert “Bobby,” 43 Saxony, 90 scarlet fever, 67 Scarry, Elaine, 102–3 scenting, 135, 180 Schneier, Bruce, 185 Schumpeter, Joseph, 156–7, 162 Scientific Revolution, 48–52, 62, 66, 95, 204, 207, 218 scientist, coining of term, 133 SCL, 175 Scotland, 64, 85, 172 search engines, xvi Second World War, see World War II securitization of loans, 218 seismology, 135 self-employment, 82 self-esteem, 88–90, 175, 212 self-harm, 44, 114–15, 117, 146, 225 self-help, 107 self-interest, 26, 41, 44, 61, 114, 141, 146 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 sentiment analysis, xiii, 12–13, 140, 188 September 11 attacks (2001), 17, 18 shell shock, 109–10 Shrecker, Ted, 226 Silicon Fen, Cambridgeshire, 84 Silicon Valley, California, xvi, 219 and data, 55, 151, 185–93, 199–201 and disruption, 149–51, 175, 226 and entrepreneurship, 149–51 and fascism, 203 and immortality, 149, 183–4, 224, 226 and monopolies, 174, 220 and singularity, 183–4 and telepathy, 176–8, 181, 185, 186, 221 and weaponization, 18, 219 singularity, 184 Siri, 187 Skripal poisoning (2018), 43 slavery, 59, 224 smallpox, 67 smart cities, 190, 199 smartphone addiction, 112, 186–7 snowflakes, 22, 113 social indicators, 74 social justice warriors (SJWs), 131 social media and crowd psychology, 6 emotional artificial intelligence, 12–13, 140–41 and engagement, 7 filter bubbles, 66 and propaganda, 15, 18, 81, 124 and PTSD, 113 and sentiment analysis, 12 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 weaponization of, 18, 19, 22, 194–5 socialism, 8, 20, 154–6, 158, 160 calculation debate, 154–6, 158, 160 Socialism (Mises), 160 Society for Freedom in Science, 163 South Africa, 103 sovereignty, 34, 53 Soviet Russia (1917–91), 132, 133, 135–8, 177, 180, 182–3 Spain, 5, 34, 84, 128, 202 speed of knowledge, xvi, 112, 124, 131, 134, 136, 153, 154, 165–70 Spicer, Sean, 3, 5 spy planes, 136, 152 Stalin, Joseph, 138 Stanford University, 179 statactivism, 74 statistics, 62–91, 161, 186 status, 88–90 Stoermer, Eugene, 206 strong man leaders, 16 suicide, 100, 101, 115 suicide bombing, 44, 146 superbugs, 205 surveillance, 185–93, 219 Sweden, 34 Switzerland, 164 Sydenham, Thomas, 96 Syriza, 5 tacit knowledge, 162 talking cure, 107 taxation, 158 Tea Party, 32, 50, 61, 221 technocracy, 53–8, 59, 60, 61, 78, 87, 89, 90, 211 teenage girls, 113, 114 telepathy, 39, 176–9, 181, 185, 186 terrorism, 17–18, 151, 185 Charlottesville attack (2017), 20 emergency powers, 42 JFK Airport terror scare (2016), x, xiii, 41 Oxford Circus terror scare (2017), ix–x, xiii, 41 September 11 attacks (2001), 17, 18 suicide bombing, 44, 146 vehicle-ramming attacks, 17 war on terror, 131, 136, 196 Thames Valley, England, 85 Thatcher, Margaret, 154, 160, 163, 166 Thiel, Peter, 26, 149–51, 153, 156, 174, 190 Thirty Years War (1618–48), 34, 45, 53, 126 Tokyo, Japan, x torture, 92–3 total wars, 129, 142–3 Treaty of Westphalia (1648), 34, 53 trends, xvi, 168 trigger warnings, 22, 113 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 Trump, Donald, xiv and Bannon, 21, 60–61 and climate change, 207 and education, 85 election campaign (2016), see under presidential election, US and free trade, 79 and health, 92, 99 and immigration, 145 inauguration (2017), 3–5, 6, 9, 10 and inequality, 76–7 “Make America Great Again,” 76, 145 and March for Science (2017), 23, 24, 210 and media, 27 and opinion polling, 65, 80 and Paris climate accord, 207 and promises, 221 and relative deprivation, 88 and statistics, 63 and Yellen, 33 Tsipras, Alexis, 5 Turing, Alan, 181, 183 Twitter and Corbyn’s rallies, 6 and JFK Airport terror scare (2016), x and Oxford Circus terror scare (2017), ix–x and Russia, 18 and sentiment analysis, 188 and trends, xvi and trolls, 194, 195 Uber, 49, 185, 186, 187, 188, 191, 192 UK Independence Party, 65, 92, 202 underemployment, 82 unemployment, 61, 62, 72, 78, 81–3, 87, 88, 203 United Kingdom austerity, 100 Bank of England, 32, 33, 64 Blitz (1940–41), 119, 143, 180 Brexit (2016–), see under Brexit Cameron government (2010–16), 33, 73, 100 Center for Policy Studies, 164 Civil Service, 33 climate-gate (2009), 195 Corbyn’s rallies, 5, 6 Dunkirk evacuation (1940), 119 education, 85 financial crisis (2007–9), 29–32, 100 first past the post, 13 general election (2015), 80, 81 general election (2017), 6, 65, 80, 81, 221 Grenfell Tower fire (2017), 10 gross domestic product (GDP), 77, 79 immigration, 63, 65 Irish hunger strike (1981), 43 life expectancy, 100 National Audit Office (NAO), 29 National Health Service (NHS), 30, 93 Office for National Statistics, 63, 133 and opiates, 105 Oxford Circus terror scare (2017), ix–x, xiii, 41 and pain, 102, 105 Palantir, 151 Potsdam Conference (1945), 138 quantitative easing, 31–2 Royal Society, 138 Scottish independence referendum (2014), 64 Skripal poisoning (2018), 43 Society for Freedom in Science, 163 Thatcher government (1979–90), 154, 160, 163, 166 and torture, 92 Treasury, 61, 64 unemployment, 83 Unite for Europe march (2017), 23 World War II (1939–45), 114, 119, 138, 143, 180 see also England United Nations, 72, 222 United States Bayh–Dole Act (1980), 152 Black Lives Matter, 10, 225 BP oil spill (2010), 89 Bush Jr. administration (2001–9), 77, 136 Bush Sr administration (1989–93), 77 Bureau of Labor, 74 Central Intelligence Agency (CIA), 3, 136, 151, 199 Charlottesville attack (2017), 20 Civil War (1861–5), 105, 142 and climate change, 207, 214 Clinton administration (1993–2001), 77 Cold War, see Cold War Defense Advanced Research Projects Agency (DARPA), 176, 178 Defense Intelligence Agency, 177 drug abuse, 43, 100, 105, 115–16, 131, 172–3 education, 85 Federal Bureau of Investigation (FBI), 137 Federal Reserve, 33 Fifth Amendment (1789), 44 financial crisis (2007–9), 31–2, 82, 158 first past the post, 13 Government Accountability Office, 29 gross domestic product (GDP), 75–7, 82 health, 92, 99–100, 101, 103, 105, 107, 115–16, 158, 172–3 Heritage Foundation, 164, 214 Iraq War (2003–11), 74, 132 JFK Airport terror scare (2016), x, xiii, 41 Kansas populists (1880s), 220 libertarianism, 15, 151, 154, 158, 164, 173 life expectancy, 100, 101 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210 McCarthyism (1947–56), 137 Million-Man March (1995), 4 National Aeronautics and Space Administration (NASA), 23, 175 National Defense Research Committee, 180 National Park Service, 4 National Security Agency (NSA), 152 Obama administration (2009–17), 3, 24, 76, 77, 79, 158 Occupy Wall Street (2011), 5, 10, 61 and opiates, 105, 172–3 and pain, 103, 105, 107, 172–3 Palantir, 151, 152, 175, 190 Paris climate accord (2015), 205, 207 Parkland attack (2018), 21 Patriot Act (2001), 137 Pentagon, 130, 132, 135, 136, 214, 216 presidential election (2016), see under presidential election, US psychiatry, 107, 111 quantitative easing, 31–2 Reagan administration (1981–9), 15, 77, 154, 160, 163, 166 Rumsfeld’s “unknown unknowns” speech (2002), 132 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 September 11 attacks (2001), 17, 18 Tea Party, 32, 50, 61, 221 and torture, 93 Trump administration (2017–), see under Trump, Donald unemployment, 83 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 World War I (1914–18), 137 World War II (1939–45), 137, 180 universal basic income, 221 universities, 151–2, 164, 169–70 University of Cambridge, 84, 151 University of Chicago, 160 University of East Anglia, 195 University of Oxford, 56, 151 University of Vienna, 160 University of Washington, 188 unknown knowns, 132, 133, 136, 138, 141, 192, 212 unknown unknowns, 132, 133, 138 “Use of Knowledge in Society, The” (Hayek), 161 V2 flying bomb, 137 vaccines, 23, 95 de Vauban, Sébastien Le Prestre, Marquis de Vauban, 73 vehicle-ramming attacks, 17 Vesalius, Andreas, 96 Vienna, Austria, 153–5, 159 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 violence vs. power, 19, 219 viral marketing, 12 virtual reality, 183 virtue signaling, 194 voice recognition, 187 Vote Leave, 50, 93 Wainright, Joel, 214 Wales, 77, 90 Wall Street, New York, 33, 190 War College, Berlin, 128 “War Economy” (Neurath), 153–4 war on drugs, 43, 131 war on terror, 131, 136, 196 Watts, Jay, 115 weaponization, 18–20, 22, 26, 75, 118, 123, 194, 219, 223 weapons of mass destruction, 132 wearable technology, 173 weather control, 204 “What Is An Emotion?”

Data and the City
by Rob Kitchin,Tracey P. Lauriault,Gavin McArdle
Published 2 Aug 2017

For Statistics Canada and the Office of the Registrar General in Ontario, the mechanics of compiling and processing data take centre-stage as part of the mandate of those government institutions. It is not necessarily the case however that those who compile administrative data are aware of how data generated from vital registrations affect decision-making. For example, in 1991, the Registrar General’s data entry office was relocated from Toronto to Thunder Bay. As a result a lot of tacit knowledge was lost and coding errors were introduced into the data sets. A Toronto-based epidemiologist I spoke with described the effects of this change: [W]e had a problem with birth rate where they were rounding everything to the half-pound and then reporting things out in grams. Again it was like, this is looking strange, this is looking quite weird.

…

The modelled database and its data become an objective reality, and once embedded into a data infrastructure, the model becomes largely invisible except for the rules articulated into algorithms encoded into the system. The machine however knows, and to a lesser extent the model becomes part of the tacit knowledge of its community of data producers and maintainers. The model eventually recedes into the background, becoming distant from its constructed and conceptual roots. Just like a well-functioning infrastructure, it becomes the substrate of other things Polygon Polygon Reference Polygon Polygon Polygon Ireland Polygon Figure 13.2 Basic schematic of the OSi data model. 

Mindware: Tools for Smart Thinking
by Richard E. Nisbett
Published 17 Aug 2015

—Primo Levi, The Drowned and the Saved First baseball umpire: “I call ’em as I see ’em.” Second umpire: “I call ’em as they are.” Third umpire: “They ain’t nothin’ till I call ’em.” When we look at a bird or a chair or a sunset, it feels as if we’re simply registering what is in the world. But in fact our perceptions of the physical world rely heavily on tacit knowledge, and mental processes we’re unaware of, that help us perceive something or accurately categorize it. We know that perception depends on mental doctoring of the evidence because it’s possible to create situations in which the inference processes we apply automatically lead us astray. Have a look at the two tables below.

…

If we live in rural Arizona, with no street sweepers and no fire hydrants, we’re more likely to make the error. INVERSE ERROR 2 If President Obama is Muslim, then he’s not a Christian. President Obama is not Muslim. Therefore, President Obama is a Christian. The conclusion would be valid if we had tacit knowledge operating as an additional premise to the effect that people can only be either Muslim or Christian. We don’t believe that, of course, but we may have gotten into a mood of thinking these are the only alternatives for Obama; for example, if the only alternatives for Obama’s religion ever discussed were Muslim and Christian.

The Evolution of Everything: How New Ideas Emerge
by Matt Ridley

Even if you had been free to copy Google’s search engine in the late 1990s, by the time you had worked through all the hidden obstacles that Google had also worked through, you would have been years behind. Copying is not cheap As this illustrates, the chief reason that copying is not much cheaper than original discovery is ‘tacit knowledge’. Most of the little tricks and short cuts that industrialists follow to achieve their results remain in their heads. Even the most explicit paper or patent application fails to reveal nearly enough to help another to retrace your steps through the maze of possible experiments. One study of lasers found that blueprints and written reports were quite inadequate to help others copy laser design: you had to go and talk to people who had done it.

…

Edwin Mansfield of the University of Pennsylvania studied the development of forty-eight chemical, pharmaceutical, electronic and machine goods in New England in the 1970s, and found that on average it cost 65 per cent as much money, and 70 per cent as much time, to copy as to invent the products. And this was amongst specialists with technical expertise. Copying from scratch would cost even more. Commercial companies do basic research because they know it enables them to acquire the tacit knowledge that leads to innovation. The obvious exception to the rule that copying is expensive is pharmaceuticals, where imitation –‘generics’ – is clearly cheaper than innovation. This is largely a consequence of safety regulation by governments. The state’s not unreasonable demand that new drugs prove in huge clinical trials that they are harmless and effective means that it costs billions to bring them to market.

The Economics of Enough: How to Run the Economy as if the Future Matters
by Diane Coyle
Published 21 Feb 2011

As well as software, the creative industries such as advertising, biotech, and financial services are good examples. People who work in companies of this kind need the intellectual and creative stimulus they get from discussions with other skilled professionals. They need to share information and ideas it might be hard to spell out in writing—economists use the phrase “tacit knowledge” for this. In traditional manufacturing, say auto assembly in the 1970s, it was relatively straightforward to set out a lot of what workers needed to know in a manual or teach it in a brief training course. Experience accumulated over many years would certainly make them better at their job, more productive.

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See also gross domestic product (GDP); measurement Stein, Herbert, 104 Stern, Nicholas, 29, 60–61, 68, 72–74, 82 Stevenson, Betsey, 41 stewardship, 78, 80, 275 Stiglitz, Joseph, 37, 82, 202, 274 stimulus packages, 91, 100–103, 111 Strumpf, Koleman, 197 suicide, 44, 51, 279 superstar effect, 134 sustainability: Brundtlandt Report and, 77; cradle-to-grave social systems and, 104; defining, 24, 77–78, 80; economic, 8, 85–86, 89–90, 98, 100, 102, 104–5, 108, 111, 113, 136, 177, 183–85, 203, 233–34, 240, 244, 248, 261, 293; environmental, 38, 56, 59, 62, 65, 69, 71, 76, 112–13, 233; fairness and, 115; government debt and, 102, 104–12; growth and, 53, 57, 80–86, 89–90, 98, 100; Index of Sustainable Economic Welfare (ISEW) and, 36; kinds of, 25; social, 54, 71, 79, 114–16, 143, 151, 233, 237 Sweden, 141, 143, 172, 251 Switzerland, 125 Tabellini, Guido, 136 tacit knowledge, 166 taxes, 3, 12, 15; business investment and, 295; fairness and, 123, 127–28, 131, 135–36, 144; Golden Rule for, 93; increased future, 286–87; happiness and, 22–25, 40, 43; inequality and, 115–16, 123, 127–28, 131, 135–36; infrastructure spending and, 93; luxury goods and, 23; Medicare and, 93–94; nature and, 62, 71; pension burden and, 92–95; policy recommendations for, 279, 282–86, 289–90, 293–97; posterity and, 85–91, 94, 99, 103–5, 111–13; Social Security and, 93–94; thrift education and, 294–95; trust and, 171–76, 182, 191, 203; values and, 229, 235, 245, 248, 258; wasteful spending and, 23; welfare burden and, 92–95 technology: access to, 36; Boskin Commission and, 37; call centers and, 131, 133, 161; cities and, 165–70; computers and, 156; consumer electronics and, 36–37; cultural suspicion of growth and, 26–29; data explosion and, 205, 291; decreased cost of, 254; electrification and, 155–56; electronic monitoring, 252–53; e-mail, 252; Enlightenment and, 7; fairness and, 116, 131–34, 137; faxes, 252; fractal character of, 134; general purpose, 157; globalization and, 7, 160–65; governance and, 173–77; growth and, 268, 270–77, 287–93, 297; Gutenberg press, 7; happiness and, 24–25, 35–37, 44, 53–54; impact of, 7–8, 24–25, 35, 37, 252–54; Industrial Revolution and, 27, 149, 290, 297; innovation and, 6–8 (see also innovation); institutions and, 244–46, 251–54, 257–63; Internet, 155, 195, 245, 260, 273, 287–89, 291, 296; labor and, 132; measurement and, 181–85, 188–91, 194–201, 204–6; Moore’s Law and, 156; music industry and, 194–98; nature and, 69–72, 76–77, 80, 84; new energy, 6; online empowerment and, 287–88, 296; policy recommendations for, 268, 270, 273–77, 287–93, 297; politics and, 7–8, 16–17, 288–89; posterity and, 107; productivity and, 107–8, 157–59, 268; public domain and, 196; reinvention and, 14; Renaissance and, 7; smart cards, 252–53; software, 253; steam power, 155–57; structural change and, 268; superstar effect and, 134; telephony, 252; trust and, 7–8, 151, 155–61, 165, 170, 173–77; values and, 212–13, 216, 218, 233–34, 237–38; voters and, 288–89 Thatcher, Margaret, 93, 121, 211, 240, 245, 247–48 Theory of Justice (Rawls), 31 Theory of Moral Sentiments, A (Smith), 120 Theory of the Leisure Class, The (Veblen), 22–23 Thomson, William (Lord Kelvin), 187 time: shortage of, 204–7; Slow Movement and, 27–28, 205 tragedy of the commons, 80 transparency, 83, 164, 288, 296 Treatise on Human Nature (Hume), 120 trilemmas, 13–14, 230–36, 275 Trivers, Robert, 118 Trollope, Anthony, 33 trust: bankers and, 88–89, 145–50, 158, 161–64, 174, 176, 257; causality and, 154; challenge of building, 170–73; cities and, 165–70; civic cooperation and, 154; decline in, 5, 139–44; democracy and, 175; diversity and, 170–73; doctors and, 247; economic importance of, 152–57; efficiency and, 158–59; face-to-face contact and, 7, 147, 165–68; fraud and, 146–47, 150, 248; General Social Survey and, 140; globalization and, 149–51, 157, 160–70; goodwill and, 150; governance and, 151, 162–65, 173–77, 255–58; government and, 150, 157, 162, 172, 175–76, 247; gross domestic product (GDP) and, 157, 160; growth and, 152–56, 160, 174; health issues and, 172; innovation and, 157; intangible assets and, 149–52, 157, 161; measurement of, 152–57; morals and, 149, 174; paradox of prosperity and, 174; Pew surveys and, 140; politics and, 154, 162–64, 173–77, 285–87; productivity and, 156–59, 162, 166–67, 170, 174; Putnam on, 140–41, 152–54; reform and, 162–64, 176–77; social capital and, 5, 151–57, 168–74, 177; specialization and, 160–61; statistics and, 154; teachers and, 247; technology and, 7–8, 151, 155–61, 165, 170, 173–77; voter turnout and, 175; weightless activities and, 150 Tullock, Gordon, 242 Turner, Ted, 33 Twitter, 289 Uganda, 147 ultimatum game, 116–17 unemployment, 3, 10, 43, 51, 56, 89, 107, 169, 207, 212–13, 243 unions, 15, 51, 224, 249 United Kingdom, 1, 4, 10, 66; bailouts and, 91; British Social Attitudes and, 140–41; Brown and, 93; debt of, 103–4; diversity and, 172; fairness and, 115–16, 122, 125–26, 130, 139–43; Glastonbury Festival and, 197; inequality in, 122, 125–30; institutions and, 240, 258, 260; measurement and, 198, 203, 206–7; National Health Service and, 285; National Statistics and, 203; negative savings rate in, 105; policy recommendations and, 280–88; posterity and, 93, 95, 103, 105, 111; public deliberation and, 258–59; public sector and, 248; retirement age and, 107; savings rate in, 280–82; Thatcher and, 93, 121, 211, 240, 245, 247–48; time surveys and, 206–8; trust and, 140–41, 146, 163, 168, 172; values and, 211, 223; Victorian Britain and, 28 United Nations, 297, 304n7; Brundtland Report and, 77; climate change and, 59, 62, 66, 77–78, 82–83; happiness and, 38; sustainable development and, 77; TEEB and, 78; trust and, 163–64, 176; values and, 219 United States, 4, 10, 16; additional growth in, 12; bifurcation of social norms and, 231–32; Boskin Commission and, 37; Bush and, 127–28; Cold War and, 93, 112, 147, 209, 213, 239; convergence and, 122; credibility and, 101; debt of, 101; defense budget of, 93; diversity and, 172; Easterlin Paradox and, 39–44; fairness and, 115–16, 121–22, 125–35, 140–43; Founding Fathers of, 31; happiness and, 37, 41–44; inequality in, 122, 125–31, 135, 276; institutions and, 240, 243, 251, 256, 258, 260; Kyoto Protocol and, 62; measurement and, 184, 191, 203, 206; nature and, 55, 62–63, 66; Obama and, 62, 87, 173, 260, 285, 288; policy recommendations and, 276–77, 280–88, 291; posterity and, 91–93, 97, 101, 105, 109; public deliberation and, 258–59; Reagan and, 93, 121, 127, 211, 240, 243, 247–48; savings rate in, 105, 280–82; small public sector of, 243; stimulus packages and, 91; time surveys and, 206–8; trust and, 140, 149, 171–75; values and, 209, 211, 223, 226; voter turnout and, 175; wage penalties and, 133 University of California, Berkeley, 205 University of East Anglia, 67 University of Sheffield, 224 Unto This Last (Ruskin), 27–28 U.S.

Doing Data Science: Straight Talk From the Frontline
by Cathy O'Neil and Rachel Schutt
Published 8 Oct 2013

The campaign was simply insufficiently human, with its war room both “high-tech and bloodless.” Unmentioned went that the contemporaneous Romney ads read similarly. Data science rests on algorithms but does not reduce to those algorithms. The use of those algorithms rests fundamentally on what sociologists of science call “tacit knowledge”—practical knowledge not easily reducible to articulated rules, or perhaps impossible to reduce to rules at all. Using algorithms well is fundamentally a very human endeavor—something not particularly algorithmic. No warning to young data padawans is as central as the many dangers of overfitting, the taking of noise for signal in a given training set; or, alternatively, learning too much from a training set to generalize properly.

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k-Nearest Neighbor algorithms, k-Nearest Neighbors (k-NN)–What are the modeling assumptions? linear regression algorithms, Linear Regression–Exercise supervised learning recipe, Detecting suspicious activity using machine learning Suriowiecki, James, Background: Crowdsourcing Survival Analysis, Example: User Retention T tacit knowledge, Being an Ethical Data Scientist Tarde, Gabriel, Gabriel Tarde, Your Mileage May Vary Idea of Quantification, Gabriel Tarde Taylor Series, In practice teaching data science thought experiment, What Just Happened? test sets, Training and test sets tests, Code readability and reusability text data, Populations and Samples of Big Data text-mining models, Thought Experiment: Meta-Definition TF-IDF vectors, Naive No Longer thought experiments access to medical records, Thought Experiment automated statistician, Thought Experiment: Automated Statistician chaos simulation, Thought Experiment: How Would You Simulate Chaos?

The Code: Silicon Valley and the Remaking of America
by Margaret O'Mara
Published 8 Jul 2019

In wartime and after, rhapsodic press coverage celebrated the mathematical prowess of the mainframe machines—the “electronic brains”—but paid little attention to the mostly female operational labor force that made those feats possible. In the 1950s, despite the mounting evidence that programming was a creative profession that required a great deal of skill and tacit knowledge, it retained its clerical reputation—giving young women an opportunity to get in the door, and learn by doing. If those women had taken a decent amount of college science and math, like Ann Hardy, they were eligible for supervisory roles.25 It wasn’t easy to rise up the ranks, though. Hardy managed to do it in her six years at IBM due to her programming ability, a powerful work ethic, and an unwillingness to acquiesce to the sexist nonsense surrounding her.

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For example, the state’s civil code prohibited enforcement of non-compete clauses in employment contracts, a prohibition that didn’t have a thing to do with the intellectual property or trade secrets of the electronics industry, but instead came into being in 1870, as the state’s early lawmakers attempted to reconcile the chaotic jumble of legal regimes—Spanish, Mexican, Anglo-American—that had ruled the state. But the result of this provision helped facilitate the job-hopping that became a hallmark of the Valley’s tech community. If an engineer left his job and jumped to a direct competitor, his old employer couldn’t do anything about it, even though the employee’s tacit knowledge could be a tech company’s most valuable asset. Massachusetts, in contrast, enforced these clauses. As did Washington, Oregon, Illinois, Texas, New York, New Jersey, and more. Every other place in America that had a tech sector practiced enforcement of non-competes; but California did not. As non-compete clauses grew along with the technology industry, and spread to other sectors as well, the freedom to move kept the Valley filled with funny little companies, and kept knowledge spilling over from one technical generation to another.31 * * * — It would still be two decades more before the Valley decisively pulled out ahead of Boston, but the ingredients were there early.

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It was a collection of different firms sharing resources and expertise, operating symbiotically to create an entire market ecosystem—from the networks and routers to the browsers and portals to the programming languages and software applications. It was how Japan’s electronics consortia had ruled the world in the 1970s and 1980s. But it also fairly characterized the web of personal relationships and specialized expertise and tacit knowledge that made Silicon Valley soar. Other Valley VCs, both veteran and new, had giant Internet wins, of course. But Kleiner Perkins came to symbolize the dot-com generation more than any other. The firm was the MITI of the Internet era, and John Doerr was the wizard behind the curtain.9 FARM TO FACTORY Gordon Moore liked to observe that the most important thing Fred Terman’s university did for Silicon Valley was to graduate 800 masters and PhD students per year, replenishing the region’s intellectual pool.

State-Building: Governance and World Order in the 21st Century
by Francis Fukuyama
Published 7 Apr 2004

The most effective organizations are inevitably those run by highly capable individuals who are granted a large amount of discretion and who face relatively few formal institutional controls. Good judgment is something that cannot be formalized, because it depends on weighing complex contextual factors against a background of experience that provides generalized models of human behavior. Economists refer to tacit knowledge that cannot be learned from a book but arises instead from a worker’s active interaction with a piece of equipment. Such knowledge exists well beyond the factory floor and is part of the repertoire of capable presidents, program managers, CEOs, and administrators. The fact that good judgment on the part of agents cannot be taken for granted is of course the reason that organizations cannot safely delegate large amounts of discretion.

What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence
by John Brockman
Published 5 Oct 2015

Personal imprinting can create frames of beliefs that may lead to disaster—in particular, if people think they own absolute truth. 3.They make mistakes because of the language they use. Thoughts do not map isomorphically onto language, and it is a mistake to believe that explicit knowledge is the only representative of intelligence neglecting implicit or tacit knowledge. 4.And they make mistakes because of the theories they carry around, which often remain implicit and thus represent frozen paradigms or simply prejudices. The question is, Can we help them, with our deeper insight from our robotic world? The answer is yes. We could, but we shouldn’t. There is another deficiency, which would make our offer useless.

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This “semantics problem” is, as John Searle pointed out years ago, why a computer running a translation program converting English into Mandarin speaks neither English nor Mandarin. No computer can learn a human language—only bits and combinatorics for special purposes. Second, there’s the problem of what Searle calls the background and what I refer to as dark matter, or what some philosophers intend by the phrase tacit knowledge. We learn to reason in a cultural context, whereby culture means a system of violable, ranked values, hierarchically structured knowledges, and social roles. We can do this not only because we have an amazing ability to perform what appears to be Bayesian inferencing across our experiences but also because of our emotions, our sensations, our proprioception, and our strong social ties.

Building and Dwelling: Ethics for the City
by Richard Sennett
Published 9 Apr 2018

Most of the actions we perform we don’t think about consciously – we couldn’t do otherwise. Imagine taking a walk and thinking, ‘Now lift the left leg, now lift the right one, now the left again, now…’ Instead, once we have learned to walk as toddlers, we engrain this behaviour into an unthinking habit; it enters the domain of tacit knowledge. In developing a skill like hammering a nail, something similar happens: the craftsman learns how to grip the hammer shank, and the best amount of force to apply, given the weight of his or her own body. Once created, this behaviour enters the tacit realm as something a person knows how to do without self-consciously thinking about what he or she is doing.

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But he is interested in how felt contradictions jolt people into feeling ‘I am here, now’ in a way that familiar recognitions do not. He is the father to Leon Festinger’s belief that ‘we care most about those things we have struggled to understand’. In their separate ways, James and Bergson are philosophers of street-smarts. And both pose the same problem: what jolts our consciousness? That happens when tacit knowledge becomes insufficient to cope with reality. A second phase begins. Something is not quite right: a light is out when usually it is on. The context can no longer be taken for granted. Or there is a sudden, strange sound of bells: should you stop walking? In carpentry, the workman does not think self-consciously about lower-arm weight until an unexpected knot hidden within a piece of wood makes him or her ponder how much lower-arm force to exert.

The Invention of Science: A New History of the Scientific Revolution
by David Wootton
Published 7 Dec 2015

. ———. ‘Introduction: Stages in the Empirical Programme of Relativism’. Social Studies of Science 11 (1981): 3–10. ———. ‘Son of Seven Sexes: The Social Destruction of a Physical Phenomenon’. Social Studies of Science 11 (1981): 33–62. ———. ‘Tacit Knowledge, Trust and the Q of Sapphire’. Social Studies of Science 31 (2001): 71–85. ———. ‘The TEA Set: Tacit Knowledge and Scientific Networks’. Social Studies of Science 4 (1974): 165–85. Collinson, Patrick. ‘The Monarchical Republic of Queen Elizabeth I’. Bulletin of the John Rylands University Library of Manchester 69 (1987): 394–424. Colón, Fernando.

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On the ease with which the Torricellian experiment could be repeated, Glanvill, Plus ultra (1668), 60–1. xvi I discuss below, Chapter 15, Simon Schaffer’s account of Newton’s experimentum crucis; again, the claim that replication was a social artefact turns out to be false. On replication as requiring a transfer of tacit knowledge which ensures that it is (almost) never truly independent: Collins, ‘The TEA Set’ (1974); Collins, ‘Tacit Knowledge, Trust and the Q of Sapphire’ (2001); and Pinch in Labinger & Collins (eds.), The One Culture? (2001), 23. xvii Karl Popper’s approach to the philosophy of science began to be widely known in the English-speaking world with the publication of Popper, The Open Society and Its Enemies (1945); his classic 1935 account of scientific progress as being based on falsification not verification was eventually translated from German as Popper, The Logic of Scientific Discovery (1959).

The Wealth of Networks: How Social Production Transforms Markets and Freedom
by Yochai Benkler
Published 14 May 2006

However, the effect on intrinsic motivation, at least sometimes, operates in the opposite direction. Where intrinsic motivation is an important factor because pricing and contracting are difficult to achieve, or because the payment that can be offered is relatively low, the aggregate effect may be negative. Persuading experienced employees to communicate their tacit knowledge to the teams they work with is a good example of the type of behavior that is very hard to specify for efficient pricing, and therefore occurs more effectively through social motivations for teamwork than through payments. Negative effects of small payments on participation in work that was otherwise volunteer-based are an example of low payments recruiting relatively few people, but making others shift their efforts elsewhere and thereby reducing, rather than increasing, the total level of volunteering for the job. 189 The psychology-based alternative to the "more money for an activity will mean more of the activity" assumption implicit in most of these new economic models is complemented by a sociology-based alternative.

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Bewley, "A Depressed Labor Market as Explained by Participants," American Economic Review (Papers and Proceedings) 85 (1995): 250, provides survey data about managers' beliefs about the effects of incentive contracts; Margit Osterloh and Bruno S. Frey, "Motivation, Knowledge Transfer, and Organizational Form," Organization Science 11 (2000): 538, provides evidence that employees with tacit knowledge communicate it to coworkers more efficiently without extrinsic motivations, with the appropriate social motivations, than when money is offered for "teaching" their knowledge; Bruno S. Frey and Felix Oberholzer-Gee, "The Cost of Price Incentives: An Empirical Analysis of Motivation Crowding-Out," American Economic Review 87 (1997): 746; and Howard Kunreuther and Douslar Easterling, "Are Risk-Benefit Tradeoffs Possible in Siting Hazardous Facilities?"

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Bewley, "A Depressed Labor Market as Explained by Participants," American Economic Review (Papers and Proceedings) 85 (1995): 250, provides survey data about managers' beliefs about the effects of incentive contracts; Margit Osterloh and Bruno S. Frey, "Motivation, Knowledge Transfer, and Organizational Form," Organization Science 11 (2000): 538, provides evidence that employees with tacit knowledge communicate it to coworkers more efficiently without extrinsic motivations, with the appropriate social motivations, than when money is offered for "teaching" their knowledge; Bruno S. Frey and Felix Oberholzer-Gee, "The Cost of Price Incentives: An Empirical Analysis of Motivation Crowding-Out," American Economic Review 87 (1997): 746; and Howard Kunreuther and Douslar Easterling, "Are Risk-Benefit Tradeoffs Possible in Siting Hazardous Facilities?"

Bit by Bit: How P2P Is Freeing the World
by Jeffrey Tucker
Published 7 Jan 2015

I’ve deconstructed the scene in slow motion, but these kinds of micro-dramas occur millions of times in the course of rush hour in every major city in the world. We hardly think about them. Making such judgments, ongoing, instantly, continually, is what it means to be an experienced driver. They are part of the tacit knowledge of how we manage our lives. If you had no confidence in the capacity of humans to manage their own lives, and likewise for order to emerge out of that, you would never allow such a thing to exist in the first place. In fact, given the ethos in government today, there is virtually no chance that government would ever have permitted such a system.

Masters of Management: How the Business Gurus and Their Ideas Have Changed the World—for Better and for Worse
by Adrian Wooldridge
Published 29 Nov 2011

And CEOs are forever waxing lyrical about turning their organizations into innovation machines. This ferment of thinking has produced some of the best books on management in the past few years: witness Prahalad and Hammer’s work on “core competencies” in Competing for the Future, Ikujiro Nonaka’s work on “tacit knowledge” in The Knowledge-Creating Company (1995; revised 2008), and Clay Christensen’s writing about “the innovator’s dilemma” in his classic of the same title. But for all this impressive intellectual effort, the field remains a messy one. We are a long way from producing a “single best system” comparable to Frederick Taylor’s theory of “scientific management” in the early decades of the twentieth century.

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Abbott Laboratories, a large American healthcare company, allows veteran workers to work for four days a week or take up to twenty-five more vacation days a year. Most consultancies have developed pools of retired or semi-retired workers who can be called upon to work on individual projects. They are also trying to capture all the tacit knowledge that is about to walk out of the door. Construction companies such as Sweden’s Elmhults Konstruktions and the Netherlands’ Hazenberg Bouw have introduced mentoring systems that encourage prospective retirees to train their replacements. All these changes mean that the traditional image of careers as ladders is becoming outdated.

Alternatives to Capitalism
by Robin Hahnel and Erik Olin Wright

During the middle third of the twentieth century, social democratic political parties changed their position on this issue, and came out in support of the view that Erik expresses above—a system that combines markets with state regulation and planning through the political system.1 During the last fifth of the twentieth century, many radicals from the generation to which Erik and I both belong reacted to the demise of the planned economies and free market triumphalism by joining social democrats in support of a vision of “socialized markets” while endorsing the “tacit knowledge” critique of comprehensive planning voiced by conservative champions of free market capitalism like Von Mises and Hayek fifty years earlier. I believe the participatory planning procedure that is a key part of the participatory economic model demonstrates that these concessions to the practical necessity of markets were unwarranted, which is fortunate, since the pernicious effects of markets become ever more apparent as the global market system continues to spread its influence destroying community and natural environment alike.

The Social Animal: The Hidden Sources of Love, Character, and Achievement
by David Brooks
Published 8 Mar 2011

Learning is not merely about accumulating facts. It is internalizing the relationships between pieces of information. Every field has its own structure, its own schema of big ideas, organizing principles, and recurring patterns—in short, its own paradigm. The expert has absorbed this structure and has a tacit knowledge of how to operate within it. Economists think like economists. Lawyers think like lawyers. At first, the expert decided to enter a field of study, but soon the field entered her. The skull line, the supposed barrier between her and the object of her analysis, had broken down. The result is that the expert doesn’t think more about a subject, she thinks less.

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The result is that the expert doesn’t think more about a subject, she thinks less. She doesn’t have to compute the effects of a range of possibilities. Because she has domain expertise, she anticipates how things will fit together. Step Three Ms. Taylor’s third step was to help bring Harold’s tacit knowledge of Greek life to the surface. After the weeks of reading, and then more weeks of rereading, she asked him to keep a journal. In it he would describe both his thoughts about Greek life and his own time in high school. She told him to let his mind go free, to let his thoughts bubble up from his unconscious, and to not worry for the time being about what he was writing or how good it might be.

Energy: A Human History
by Richard Rhodes
Published 28 May 2018

Besides working with steam engines from the coal up, as it were, George also, on Saturdays when the engines were idle, took them apart and put them back together, examining each component as he did so to understand its function. Between feeding them, operating them, dismantling and repairing them, he learned their mechanism at a level of tacit knowledge unlikely even for a formally educated professional engineer. Those who worked with him, including professionals, found his ability to diagnose engine troubles uncanny. It was bred in his bones. An opportunity to advance presented itself in 1811, when an atmospheric engine installed the previous year on a new pit at Killingworth Colliery failed to clear the deepening pit of water.

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The following year, the Grand Alliance, the powerful cartel of mine owners, promoted Stephenson to chief enginewright in charge of all the machinery in their collieries at an annual salary of £100 (today £6,300, or $9,000). That salary soon became a retainer, and Stephenson an industrywide consultant. Besides his tacit knowledge of steam engines, Stephenson’s other secret weapon was his son, Robert, the price of whose formal education was teaching his father in turn. Once Robert had completed his training as an engineer, he partnered with his father throughout George’s life. Stephenson built his first steam locomotive in 1814.

On Language: Chomsky's Classic Works Language and Responsibility and Reflections on Language in One Volume
by Noam Chomsky and Mitsou Ronat
Published 26 Jul 2011

For psychology, the important notion will be “cognize,” not “know.” Or, we might make the decision to sharpen and perhaps extend the term “know” so that it has just the properties of “cognize,” thus eliminating the new terminology. Then we will be able to explain explicit knowledge of certain facts by showing how these cases are related to the system of “tacit knowledge.”21 I doubt that this question can be settled by consideration of “ordinary usage,” which seems to me vague and inexplicit at just the crucial points. The philosophical tradition is varied. Leibniz, for one, spoke of unconscious knowledge, though he seems to have regarded all knowledge as accessible to consciousness.

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The Structure of Appearance. Cambridge, Mass.: Harvard University Press. ————. 1969. “The Emperor’s New Ideas.” In Hook, 1969. Gramsci, Antonio. 1957. The Modern Prince & Other Writings. Trans. Louis Marks. New York: International Publishers. Graves, Christina, Jerrold J. Katz, et al. 1973. “Tacit Knowledge.” Journal of Philosophy 70:318–30. Greenfield, Patricia M., Karen Nelson, and Elliot Saltzman. 1972. “The Development of Rulebound Strategies for Manipulating Seriated Cups: A Parallel Between Action and Grammar.” Cognitive Psychology 3:291–310. Gregory, Richard. 1970. “The Grammar of Vision.”

Sorting Things Out: Classification and Its Consequences (Inside Technology)
by Geoffrey C. Bowker
Published 24 Aug 2000

In the case of �IC, the politics move from a politics of certainty to a politics of ambiguity. The essence of this politics is walking a tightrope between increased visibility and increased surveillance; between overspecifying what a nurse should do and taking away discretion from the individual practitioner. When discretion and the tacit knowledge that is part of every occu­ pation meet the medical bureaucracy, which would account for every pill and every moment of health care workers' time, contradictions 30 Introduction ensue. This is especially true m the "softer" areas of care. Social­ psychological care giving is one of the areas where this dilemma is prominent.

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There has been a recent trend in social informatics and science studies to move away from dichotomizing the formal and the infor­ mal. 1 1 In the early 1 980s, the original eclat of discovering the failures of formalisms led to a kind of enthusiastic debunking. People do not really follow formal rules; they make up their own. They tailor rigid computer systems to their everyday working needs. Expert systems do not formally model people's thoughts as they fail to capture tacit knowledge. People do not devise formal, abstract plans and goals and then execute them , as the old cognitive model of Miller, Galanter, and Pribram ( 1 960) would have it. Rather, they use a dynamic and situated improvisation (Suchman 1 987) where plans are resources and are renegotiated as circumstances warrant.

Model Thinker: What You Need to Know to Make Data Work for You
by Scott E. Page
Published 27 Nov 2018

We can estimate the transition probability that an individual (or family) in one category moves to another category within a generation, as shown in the figure below. More equal transition probabilities correspond to greater social mobility. Transition Probabilities Between Income Levels Cause of inequality: Social skills, tacit knowledge, attitudes toward risk and education, and bequests reduce mobility between income classes. If there were no stickiness across generations, then the income of the child of a high-income parent would be equally likely to belong to any of the four income classes—all of the transition probabilities equal .

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See Zahavi 1975. 5 See Bird and Smith 2005. 6 See Smith, Bird, and Bird 2003. Chapter 26: Learning Models 1 The psychological study of learning encompasses a far broader set of contexts than we cover here. A person can learn a fact, such as what the capital of Arkansas is. A person can acquire tacit knowledge, such as how to bake bread, repair an engine, or program a computer. A person can also learn a corpus of knowledge, such as organic chemistry. 2 See Thorndike 1911, 244. 3 See Rescorla and Wagner 1972. 4 The model that I describe builds from the original Rescorla and Wagner (1972) model as well as the models by Herrnstein (1970), Bush and Mosteller (1955), Cyert and March (1963), Bendor, Diermeier, and Ting (2003), and Epstein (2014). 5 The parameter γ must be chosen so that the weight on an alternative remains positive.

Your Computer Is on Fire
by Thomas S. Mullaney , Benjamin Peters , Mar Hicks and Kavita Philip
Published 9 Mar 2021

My argument contradicts the prevalent discourse that all labor is supposedly heading toward automation, a discourse that affords epistemological supremacy to algorithms. In fact, the indexical work of elite content reviewers hinges upon a human memory cache of previously viewed and filed images. These viewers rely on a combination of their tacit knowledge and accumulated expertise as they sift through child abuse image content to identify faces and bodies and draw on instinctual feelings on when to pursue or escalate a case. The database against which NCMEC would match reported photos is the National Child Victim Identification System, established in 2002 along with the Child Victim Identification Program and containing images contributed by local, state, federal, and international law enforcement.

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A problem, in the sense that if the child seems to have aged during the course of the reporting, and various photos at different ages are on file, it is more likely that the child is still being abused and coerced into posing for such photos. Despite the automated matches, Linda still continued to pause and point out her own data points in the images. Her remark that “this is a problem” indicated a gut feeling—her tacit knowledge—that some images represented possible other ages and the need for further investigation. As the anthropologist Charles Goodwin has noted, gestures like Linda’s pointing and verbal cues are embodied communicative modes that structure practice and indicate expertise.24 Her expertise was interactional,25 reflecting the dynamic relationship between software and human at a corporeal level.

The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor
by David S. Landes
Published 14 Sep 1999

Part of his reports was published by his brother, also named Gabriel, as Voyages métallurgiques (1774-81)—Woronoff, L’industrie sidérurgique, p. 16. Also Harris, Essays in Industry, pp. 87-88. * This is what Michael Polanyi called tacit knowledge. Kenneth Arrow speaks of learning-by-doing. See Polanyi, The Tacit Dimension; Arrow, “The Economic Implications of Learning by Doing”; J. Howells, “Tacit Knowledge.” * The classic example is the request made of Richard Roberts, partner in the machine-making firm of Sharp, Roberts, by a group of Lancashire spinners to build a self-acting mule, that is, a machine that would bring the spindle carriage back to begin a new stretch-and-wind cycle.

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Arab Seafaring in the Indian Ocean in Ancient and Early Medieval Times. Rev. and expanded by John Carswell. Princeton: Princeton Univ. Press. Howe, Christopher. 1996. The Origins of Japanese Trade Supremacy: Development and Technology in Asia from 1540 to the Pacific War. London: Hurst. Howells, Jeremy. 1995. “Tacit Knowledge and Technology Transfer.” ESRC Centre for Business Research, Univ. of Cambridge, Paper No. 16. Howells, William W. 1977. “Requiem for a Lost People [the Tasmanians],” Harvard Magazine (January-February): 48-55. Howse, Derek. 1980. Greenwich Time and the Discovery of the longitude. Oxford: Oxford Univ.

The Next Factory of the World: How Chinese Investment Is Reshaping Africa
by Irene Yuan Sun
Published 16 Oct 2017

These are people who are willing to not see their families for a year, people who are willing to get off a plane and go straight to live in a mud-field, people whose entire livelihoods center on building factories in seemingly inhospitable places. These entrepreneurs and managers possess an irreplaceable set of tacit knowledge about development. This is lived experience—no textbook or donors’ conference or development economics program can quite capture its essence—and its relocation to Africa brings a gift beyond investment dollars alone. But perhaps most important, the Chinese showing up in Africa—whether government officials or migrant entrepreneurs—believe that Africa is in the same position China itself was a few short decades ago.

On Nature and Language
by Noam Chomsky
Published 16 Apr 2007

Poverty of stimulus considerations support the view that the initial cognitive state, far from being the tabula rasa of empiricist models, is already a richly structured system. The theory of the initial cognitive state is called Universal Grammar; the theory of a particular stable state is a particular grammar. Acquiring the tacit knowledge of French, Italian, Chinese, etc., is then made possible by the component of the mind–brain that is explicitly modeled by Universal Grammar, in interaction with a specific course of linguistic experience. In the terms of comparative linguistics, Universal 8 Editors’ introduction Grammar is a theory of linguistic invariance, as it expresses the universal properties of natural languages; in terms of the adopted cognitive perspective, Universal Grammar expresses the biologically necessary universals, the properties that are universal because they are determined by our in-born language faculty, a component of the biological endowment of the species.

The End of Traffic and the Future of Transport: Second Edition
by David Levinson and Kevin Krizek
Published 17 Aug 2015

If our car was old enough, maybe—just maybe—we wore lap belts because the three-point seatbelt (the shoulder-belt) had yet to hit the American auto market.90 Today children sit in the back seat because of the rise of so-called 'child safety seats' and air bags.91 Today's back seat kids have a much diminished independent range,92 and are more likely to be driven by a parent or school bus to their school. But we contend there are things, tacit knowledge, one can learn about driving just by riding in the front seat, which today's kids are slower to experience. These include laws of the road, etiquette, and defensive driving. Both of us received our driver's licenses upon turning 16, not a day after. After a few weeks of restricted driving we were on our own.

Work in the Future The Automation Revolution-Palgrave MacMillan (2019)
by Robert Skidelsky Nan Craig
Published 15 Mar 2020

The distinction rested on 13 Work in the Digital Economy 127 the work of Michael Polanyi, the Hungarian philosopher. He drew a distinction between ‘tacit’ and ‘explicit’ knowledge. And the ALM hypothesis argued that ‘routine’ tasks require ‘explicit’ knowledge, the sort of knowledge that human beings find it easy to articulate and, conversely, ‘non-routine’ tasks require ‘tacit’ knowledge, the sort of knowledge that human beings find difficult to articulate. This two-part approach—think in terms of tasks and distinguish between ‘routine’ and ‘non-routine’ ones—fitted neatly with the conception of machine capabilities that many economists held at the time that the ALM hypothesis was being developed.

The Language Instinct: How the Mind Creates Language
by Steven Pinker
Published 1 Jan 1994

The complexity of language, from the scientist’s point of view, is part of our biological birthright; it is not something that parents teach their children or something that must be elaborated in school—as Oscar Wilde said, “Education is an admirable thing, but it is well to remember from time to time that nothing that is worth knowing can be taught.” A preschooler’s tacit knowledge of grammar is more sophisticated than the thickest style manual or the most state-of-the-art computer language system, and the same applies to all healthy human beings, even the notorious syntax-fracturing professional athlete and the, you know, like, inarticulate teenage skateboarder. Finally, since language is the product of a well-engineered biological instinct, we shall see that it is not the nutty barrel of monkeys that entertainer-columnists make it out to be.

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Consider the following words: ptak plaft vlas rtut thale sram flutch toasp hlad mgla dnom nyip All of the phonemes are found in English, but any native speaker recognizes that thale, plaft, and flutch are not English words but could be, whereas the remaining ones are not English words and could not be. Speakers must have tacit knowledge about how phonemes are strung together in their language. Phonemes are not assembled into words as one-dimensional left-to-right strings. Like words and phrases, they are grouped into units, which are then grouped into bigger units, and so on, defining a tree. The group of consonants (C) at the beginning of a syllable is called an onset; the vowel (V) and any consonants coming after it are called the rime: The rules generating syllables define legal and illegal kinds of words in a language.

This Is Service Design Doing: Applying Service Design Thinking in the Real World: A Practitioners' Handbook
by Marc Stickdorn , Markus Edgar Hormess , Adam Lawrence and Jakob Schneider
Published 12 Jan 2018

“Fast iterations in prototyping minimum viable solutions are a key asset for gathering user insights, for reducing the time to product, and for accelerating the innovation process.” — Dr. Markus Durstewitz By having tangible prototypes and the possibility to interact with and alter them, we were able to gain deep insights, tapping into the tacit knowledge of the different stakeholders. We used the prototypes to test early and fail fast and cheap, in order to iterate to a solution that would ultimately be valuable to the end users and approved by all stakeholders. The simple prototypes helped us to perform early user tests and to reach a good level of maturity and alignment before making bigger investments.

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If this phase is bypassed, you run the risk of merely incrementally improving existing solutions instead of innovating. 02 Prototyping is a powerful tool for demonstrating to stakeholders the power of a design team. Designers are fast at making assumptions visible and tangible. This craft helps to make tacit knowledge of stakeholders explicit, and to get buy-in for design thinking as an innovation approach. 03 A combination of external and internal team members is crucial, but the right balance needs to be found. A team of experts is needed to be fast, and it should be complemented by a cross-functional team from the organization to make innovation happen. 04 A new way of working for users leads to a strong commitment to finding solutions.

Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity
by Daron Acemoglu and Simon Johnson
Published 15 May 2023

Or when skilled customer-service representatives, IT specialists, or financial advisers are sidelined by AI algorithms, which then perform badly. Many of the productive tasks performed by humans are a mixture of routine and more complex activities that involve social communication, problem solving, flexibility, and creativity. In such activities, humans draw on tacit knowledge and expertise. Moreover, much of this expertise is highly context dependent and difficult to transfer to AI algorithms, thus likely to get lost once the relevant tasks are automated. To illustrate the importance of accumulated knowledge, take the foraging societies we discussed in Chapter 4.

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The first draws on our overall framework and especially our discussion of so-so automation. Specifically, we argue that artificial intelligence is likely to generate more limited productivity benefits than many of its enthusiasts hope because it is expanding into tasks in which machine capabilities are still quite limited and because human productivity builds on tacit knowledge, accumulated expertise, and social intelligence. This interpretation is inspired by Larson’s (2021) account of human reasoning that is currently out of the reach of AI, Mercier and Sperber’s (2017) discussion of the social nature of human intelligence, and evidence of flexible adaptation by human groups (e.g., Henrich, 2016), as well as Pearl’s (2021) discussion of the limits of machine learning and Chomsky’s views on the shortcomings of AI-based language models (e.g., as shown in this panel discussion: http://languagelog.ldc.upenn.edu/myl/PinkerChomskyMIT.html).

The Global Auction: The Broken Promises of Education, Jobs, and Incomes
by Phillip Brown , Hugh Lauder and David Ashton
Published 3 Nov 2010

It adopted the joint strategy of automating areas of repetitive work and “turning repeatable processes into software” that could be used with different clients.36 Along with many other companies, it attempted to manufacture or industrialize services so that assignments could be carried out using the same software applications in Vietnam and Venezuela in much the same way that identical autos or iPods can be built to the same standard anywhere in the world. As Mike Daniels, head of global technology services at IBM suggests, the real advantage “comes out of doing the work in a codified way.” This required asking the key question of how you do the work using base-level components that do not rely on the tacit knowledge of employees that may lead them to undertake the same assignments in different ways. To help IBM achieve this, it has over 500 efficiency experts “to scrutinize its operations and apply disciplines from ‘lean’ manufacturing.” Likewise, Suresh Gupta from Capco Consulting foresees the arrival of the “financial services factory” because as soon as banks or insurance companies begin to break tasks into a series of procedures or components that can be digitalized, it gives companies more sourcing options such as offshoring.

Kicking Awaythe Ladder
by Ha-Joon Chang
Published 4 Sep 2000

France's attempt under John Law (see section 2.2.4) and Prussia's attempt under Frederick the Great (see section 2.2.3) are just some of the better known examples. Despite all these efforts, legitimate and illegitimate, technological catching-up was not easy. As the recent literature on technology transfer shows, technology contains a lot of tacit knowledge that cannot easily be transferred. This problem could not even be solved by the importation of skilled workers, even in the days when they embodied most of the key technologies. These people faced language and cultural barriers, and more importantly did not have access to the same technological infrastructure as they had at home.

Cogs and Monsters: What Economics Is, and What It Should Be
by Diane Coyle
Published 11 Oct 2021

An additional driver of organisational change has been the long-term structural shift away from manufacturing to an increasingly service-based and knowledge-based economy. Holmstrom and Roberts (1998, 90) noted: ‘Information and knowledge are at the heart of organizational design, because they result in contractual and incentive problems that challenge both markets and firms.’ The role of tacit knowledge (that is, know-how that is hard to write down and convey without experience) in a growing proportion of production, and the asymmetries of information pervading many characteristic modern economic activities, mean it is hard to monitor delegated or contracted activities or write legally-enforceable contracts that will cover all eventualities.

Working in Public: The Making and Maintenance of Open Source Software
by Nadia Eghbal
Published 3 Aug 2020

It matters who uses open source code, but doesn’t it also matter who makes it? In Chapter 3, we looked at how contributors to an open source project are not fungible. A casual contributor doesn’t carry the same value as a maintainer, because it takes time for a new developer to get up to speed. The tacit knowledge required to maintain a project—meaning knowledge that is difficult to externalize and transfer to others—suggests that the perceived value of open source code is also at least partly a function of who’s behind it. Sindre Sorhus is a JavaScript developer who maintains, by his estimate, over 1,100 npm packages,248 which are, in the aggregate, downloaded 2 billion times per month.249 He’s also the creator of a number of other popular projects, including Awesome (curated lists of topics ranging from games to databases, and one of the most-starred repositories on GitHub) and Refined GitHub (a popular browser extension that adds custom improvements to GitHub’s interface).

Reinventing Capitalism in the Age of Big Data
by Viktor Mayer-Schönberger and Thomas Ramge
Published 27 Feb 2018

They also helped mostly very large private or institutional clients to identify the most appropriate targets in which to invest. They were matchmakers, and their success rested on privileged access to information. They had long-term relations with customers, and an investment bank’s success was linked to the tacit knowledge and comprehensive network of its partners. The need to maintain their good reputation kept many of them honest and the valuable information they had access to confidential. They were essentially data-rich information intermediaries in an analog age. Over time, and accelerating with the 1960s, the sector changed, in part because large banks began to compete with traditional investment banks.

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It
by Erica Thompson
Published 6 Dec 2022

Those who make a career facing day-to-day decisions up close to this uncertainty have generally learned strategies for coping with it. Some of that involves humility, remaining sceptical of any optimisation and adding in margins for error. And some of it quite the opposite: it may involve strategically mispricing risk, safe in the tacit knowledge that this is often a good gamble and that a zero in a bank account doesn’t need to mean a permanent exit from the game. It might include using super-fast models to fleece less-informed players with smaller computers rather than making judgements about the fundamentals at all. It might include betting against those quantitatively seduced players who haven’t yet learned not to take their models literally.

Good Profit: How Creating Value for Others Built One of the World's Most Successful Companies
by Charles de Ganahl Koch
Published 14 Sep 2015

They make much faster progress when they focus on how different MBM is from their previous experience. What works best is learning by doing. Yes, training is important, but only to get started. It cannot take the place of continual learning by trial, error, and feedback. We don’t progress if we are afraid of making mistakes. Real-world experience is what creates deep, tacit knowledge regarding the effective application of MBM. MISTAKES TO AVOID WHEN INTRODUCING MBM When applying Market-Based Management in companies we have acquired, we have learned many lessons the hard way. Since other companies typically have a much different business philosophy and management approach, converting a company to MBM is a far bigger challenge than improving an existing Koch business.

Paper Knowledge: Toward a Media History of Documents
by Lisa Gitelman
Published 26 Mar 2014

Chapter 3 seeks to fill in some of the missing details by offering an account not of fans or zines but rather of the xerographic medium so many of them have deployed since the 1960s. What did photocopied documents mean—on their own terms—before the digital media that now frames them as old or analog? It seems clear that tacit knowledge of things digital has worked retrospectively to alter the meanings of xerography, not in the least as a result of technological and corporate convergences and mystifications. Today photocopy machines scan digitally rather than not, while laser printers work xerographically, printing according to INTRODUCTION 15 the electrostatic principles adapted first for making copies on the photocopy machines that were originally marketed in 1959.

The Locavore's Dilemma
by Pierre Desrochers and Hiroko Shimizu
Published 29 May 2012

How our Greatest Invention Makes Us Richer, Smarter, Greener, Healthier, and Happier. Penguin Press, p. 7. See also Mario Polèse. 2010. The Wealth and Poverty of Regions. Why Cities Matter. University of Chicago Press. 14 For a more detailed discussion of the issue, see Pierre Desrochers. 2001. “Geographical Proximity and the Transmission of Tacit Knowledge.” Review of Austrian Economics 14 (1): 25-46. 15 United Nations. 2008. World Urbanization Prospects: The 2007 Revisions. United Nations Department of Economic and Social Affairs, Population Division http://esa.un.org/unup/. For a concise overview of recent global trends, see Anonymous. 2008.

The Eureka Factor
by John Kounios
Published 14 Apr 2015

At present, it isn’t known whether intuition has any underlying similarity to the TOT phenomenon other than the fact that both seem to be tense anticipatory states preceding the sudden emergence of information into awareness. Research on the TOT phenomenon is reviewed in A. S. Brown, “A Review of the Tip-of-the-Tongue Experience,” Psychological Bulletin 109 (1991): 204–23. Intuition in the Laboratory 1 Arthur Reber’s studies of unconscious processing are described in Reber, Implicit Learning and Tacit Knowledge: An Essay on the Cognitive Unconsciousness (New York: Oxford University Press, 1993). Flying Blind 1 Janet Metcalfe’s studies of “feelings of warmth” during problem solving are described in J. Metcalfe and D. Wiebe, “Intuition in Insight and Noninsight Problem Solving,” Memory and Cognition 15 (1987): 238–46.

Social Life of Information
by John Seely Brown and Paul Duguid
Published 2 Feb 2000

New York: Cambridge University Press. Lave, Jean, and Etienne Wenger. 1993. Situated Learning: Legitimate Peripheral Participation. New York: Cambridge University Press. Leonard, Andrew. 1997. Bots: The Origin of New Species. New York: Penguin Books. Leonard, Dorothy, and Silvia Sensiper. 1998. "The Role of Tacit Knowledge in Group Innovation." California Management Review 40 (3): 112 32. Leonard-Barton, Dorothy. 1995. Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation. Boston: Harvard Business School Press. Lessig, Lawrence. Unpublished ms. "The Law of the Horse: What Cyberlaw Might Teach."

The Mind Is Flat: The Illusion of Mental Depth and the Improvised Mind
by Nick Chater
Published 28 Mar 2018

Kosslyn, Image and Mind (Cambridge, MA: Harvard University Press, 1980)). 2 The illusion that the mind is the stage of an inner theatre is explored by philosopher Daniel Dennett in his book Consciousness Explained. My thinking has been heavily influenced by Zenon Pylyshyn’s long-standing critique of pictorial theories of imagery (Z. W. Pylyshyn (1981), ‘The imagery debate: Analogue media versus tacit knowledge’, Psychological Review, 88(1): 16). 3 G. Hinton (1979), ‘Some demonstrations of the effects of structural descriptions in mental imagery’, Cognitive Science, 3(3): 231–50. 4 J. Wolpe and S. Rachman (1960), ‘Psychoanalytic “evidence”: A critique based on Freud’s case of little Hans’, Journal of Nervous and Mental Disease, 131(2): 135–48. 5 Wolpe and Rachman (1960), ‘Psychoanalytic “evidence”: A critique based on Freud’s case of little Hans’. 6 S.

User Story Mapping: Discover the Whole Story, Build the Right Product
by Jeff Patton and Peter Economy
Published 14 Apr 2014

You see, the original idea was also that I could pick up a card and write the title on the front, and then as we had conversations, I could flip it over on the back and write the details of all the things we agreed to that came up. I could sketch the user interface and write a lot of other information on the card. On some projects, it can really work this way. It’s cool when it can, and it’s usually a side effect of small teams working closely together with a lot of tacit knowledge. Those are the teams that don’t have to write much to remember. But I don’t think even Kent and the folks who perfected the concept of stories actually thought that all these conversations between all these different people could be contained on just a single card, and in fact, they usually aren’t.

The Shock of the Old: Technology and Global History Since 1900
by David Edgerton
Published 7 Dec 2006

This is due to increasing confidence in the engine itself and increasing knowledge of what needs maintenance. In other words, the maintenance schemes, programmes and costs are not programmable in advance. In these complex systems a great infrastructure of documentation, control and surveillance is needed, and yet informal, tacit knowledge remains extremely important. People and organisations ‘learn by using’ or ‘learn by doing’. Learning by doing was noticed first not in aircraft maintenance, but in aircraft manufacture, and as long ago as the 1930s. The effect is this: the greater quantity of a good produced, the lower the costs of production.

Inventing the Future: Postcapitalism and a World Without Work
by Nick Srnicek and Alex Williams
Published 1 Oct 2015

For representative critiques of full automation, see Ernest Mandel, Late Capitalism (London: Verso, 1998), p. 205; George Caffentzis, ‘The End of Work or the Renaissance of Slavery? A Critique of Rifkin and Negri’, in In Letters of Blood and Fire (Oakland, CA: PM Press, 2012), p. 78. 46.It should be mentioned that, increasingly, tacit knowledge tasks are being automated through environmental control and machine learning, with more recent innovations eliminating even the need for a controlled environment. Frey and Osborne, Future of Employment, p. 27; Autor, Polanyi’s Paradox; Sarah Yang, ‘New “Deep Learning” Technique Enables Robot Mastery of Skills via Trial and Error’, Phys.org, 21 May 2015, at phys.org. 47.As Marx notes, because of this ‘the field of application for machinery would therefore be entirely different in a communist society from what it is in bourgeois society.’

Frugal Innovation: How to Do Better With Less
by Jaideep Prabhu Navi Radjou
Published 15 Feb 2015

They spent days in the field, sharing agricultural tasks with farmers. Their aim was to find ways to increase mandarin yields. Japan’s agricultural workforce is ageing (currently averaging 65), so Fujitsu decided to investigate how technologies such as mobile phones and wireless sensors could raise productivity and output, and capture farmers’ tacit knowledge of agricultural practices to pass on to future generations.9 Things started badly for the two engineers. They undertook backbreaking manual labour and were unable to understand the technical terms used by the farmers. But after several weeks they began to empathise with the farmers. They saw that the existing technology was too complex and ill-suited to the real-life operating environment.

The Future of the Brain: Essays by the World's Leading Neuroscientists
by Gary Marcus and Jeremy Freeman
Published 1 Nov 2014

For example, psycholinguistic research has documented the existence of a hierarchically organized speech production system in which planning units ranging from articulatory features to words, intonational contours, and even phrases are used. Motor control approaches, on the other hand, have emphasized the role of efference copy signals from motor commands and the role of internal forward models (the tacit “knowledge” an organism has of its action systems and effectors, providing the ability to calculate predicted outcomes of actions) in motor learning and control (see related examples in chapter by Shenoy). Integration of such notions from the two traditions has generated several hierarchical feedback control models of speech production that provide elegant links between the domains.

Straight Talk on Trade: Ideas for a Sane World Economy
by Dani Rodrik
Published 8 Oct 2017

It may facilitate the creation of long-distance relationships that cross national boundaries. On the other hand, the increase in complexity and product differentiation, along with the shift from Fordist mass production to new, distributed modes of learning, increases the relative importance of spatially circumscribed relationships. The new economy runs on tacit knowledge, trust, and cooperation—which still depend on personal contact. As Kevin Morgan put it, spatial reach does not equal “social depth.”29 Hence, market segmentation is a natural feature of economic life, even in the absence of jurisdictional discontinuities. Neither economic convergence nor preference homogenization is the inevitable consequence of globalization.

Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage
by Douglas B. Laney
Published 4 Sep 2017

Knowledge Management (KM) became a more formalized discipline in the early 1990s, but still sufferers from an unwieldy number of differing definitions. Most center on the identification, capture, structuring, value, sharing, and deployment of an organization’s intellectual assets to enhance its performance and competitiveness. Knowledge assets are segregated into explicit and tacit knowledge. As such, KM is quite human-centered compared to asset management disciplines and draws upon a number of diverse fields, from cognitive science to anthropology to web and document management technologies:1415 Information leaders such as CDOs would be well advised to leverage much of what KM offers in the way of: Adapting and dealing with new and exceptional situations in establishing a vision for EIM, including scenario planning, Developing, communicating, and sharing an EIM vision to transmit an “information culture,” Collaborating across other areas of the organization, including IT, business, finance, legal, etc., Identifying, capturing, codifying, and sharing expertise as part of defining the information management organization and associated roles (including other resources spread throughout the enterprise), Developing, implementing, and improving repeatable, experience-based information asset management methods, and Transferring and incorporating knowledge/information assets into business products and services.

Power, for All: How It Really Works and Why It's Everyone's Business
by Julie Battilana and Tiziana Casciaro
Published 30 Aug 2021

But to get executive positions with the highest levels of authority and compensation, women need one more thing: an inner circle of close ties with other women.34 Women who have both many connections and a female-dominated inner circle have an expected job placement level that is 2.5 times greater than women with few connections and a male-dominated inner circle. Because of their strong bond, these fellow women are highly motivated to share tacit knowledge and gender-specific information about employers and opportunities with each other, as well as new connections important for women’s job market success. Without a tight-knit group of women who go out of their way to support one another, women don’t score prestigious leadership positions at nearly the same rate, even when they have the same qualifications as their male counterparts.

The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do
by Erik J. Larson
Published 5 Apr 2021

We make things, but this doesn’t mean we can program everything we make (think of writing a program for writing a novel on the order of, say, James Joyce’s Ulysses. The program would be meaningless. Instead we would write the novel directly—if we were James Joyce). Polanyi wrote at an unfortunate time to suggest contrary views about AI, as the field had kicked off in the 1950s with much fanfare. His defense of tacit knowledge was picked up later in the previously discussed attack on AI by Hubert Dreyfus; perhaps because of his sometimes too tendentious tone, Dreyfus’s remarks became a lightning rod for counterarguments, and at least initially, did not win over mainstream AI thinkers. (Unfortunately, he also declared that an AI system could never beat a grand champion at chess.)8 But the possibility that not all of what we know can be written down is an enduring problem for AI, because it implies that AI programmers are attempting to square a circle.

The Story of Work: A New History of Humankind
by Jan Lucassen
Published 26 Jul 2021

Although these three great civilizations each developed their own writing and counting systems early on, India still stands out in terms of its application of them, particularly in terms of passing on caste-bound professional knowledge from one generation to the next. Not only is formal training important in this regard, but also, in practice, transmitting ‘tacit knowledge’, undocumented professional competence and skill. The general level of education and the organization of vocational training is key to this. India may have had an advantage in terms of vocational training, but probably none or much less in the case of general education. Craftsmanship was monopolized by the castes and, in principle, was fixed.

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A few clever inventor-types are not enough for that. After all, a great many artisans must be suitably motivated to come up with and develop labour-saving technologies, however small, as well as be willing to apply such improvements invented by others.106 This requires formal training through apprenticeship, enabling the passing on of ‘tacit knowledge’ in practice – that is, undocumented professional competence and skills. The general level of education, the nature of education and the organization of vocational education are all crucial in this regard.107 If we consider that so many city dwellers were immigrants, it also means that the guilds operated as an integrating institution that also facilitated social mobility, especially where they maintained a number of rituals that everyone was obliged to participate in, firstly the burial of guild brethren and also (annual) meetings, whether or not followed by a feast.

Reinventing Discovery: The New Era of Networked Science
by Michael Nielsen
Published 2 Oct 2011

It could become a locus for Polymath-style collaboration, with theoreticians gathering to attack the deepest theoretical problems of quantum computation, in a new kind of wiki-science. Or experimentalists could gather to share best practices, all the subtle, hard-to-describe details of experiments that often remain tacit knowledge, making it difficult to reproduce results from one laboratory to the next. Even if this vision was only partially realized, the impact on the field of quantum computing would be extraordinary. The launch of the qwiki was at a workshop I happened to attend, held at Caltech in 2005. ch caused quite a buzz.

Early Retirement Extreme
by Jacob Lund Fisker
Published 30 Sep 2010

If you want to beat the system, try reloading the page or delete the site cookies and try again. (66) Lest I give the impression that the skilled trades are really that easy, let me say that they're easy in principle, but quickly discovering what the problem is requires a large collection of tacit knowledge. Without this knowledge, the apprentice will have to try a lot of possible solutions before hitting on the right one. In other words, the expert will be able to do the same job much faster, but the apprentice will actually be able to do the job about as well--it will just take much longer. (67) Fighting succession requires a lot of resources to prevent the next natural seral stage.

Superforecasting: The Art and Science of Prediction
by Philip Tetlock and Dan Gardner
Published 14 Sep 2015

You obviously cannot adjust the curvature of your bicycle’s path in proportion to the ratio of your unbalance over the square of your speed; and if you could you would fall off the machine, for there are a number of other factors to be taken into account in practice which are left out in the formulation of this rule.”8 The knowledge required to ride a bicycle can’t be fully captured in words and conveyed to others. We need “tacit knowledge,” the sort we only get from bruising experience. To learn to ride a bicycle, we must try to ride one. It goes badly at first. You fall to one side, you fall to the other. But keep at it and with practice it becomes effortless—although if you had to explain how to stay upright, so they can skip the ordeal you just went through, you would succeed no better than Polanyi.

Language and Mind
by Noam Chomsky
Published 1 Jan 1968

I do not know what Harman means by the locution “knows how to understand,” but clearly he is using the term “competence” in a different way from what I proposed in the work he is reviewing. In my sense of “competence,” the ability to speak and understand the language involves not only “competence” (that is, mastery of the generative grammar of the language, tacit knowledge of the language), but also many other factors. In my usage, the grammar is a formal representation of what I have called “competence.” I have no objection to Harman’s using the term in a different way, but when he insists on supposing that his usage is mine, naturally, only confusion will result.

The Sum of Small Things: A Theory of the Aspirational Class
by Elizabeth Currid-Halkett
Published 14 May 2017

I know about the baron in Paris, who went back to his dyke wife rather than marry you…. she has lineage, like a title … and all that stuff. You don’t.” The essence of taste and habitus implies layers of status and acquired knowledge which may be a function of money but is not entirely explained by money alone. Thus, nonpecuniary inconspicuous consumption revolves around tacit knowledge, cultural capital and habitus, and what Michele Lamont calls “symbolic boundaries.”21 Lamont, a sociology professor at Harvard University, believes that Bourdieu’s conception of cultural capital is too rigid and ignores other measures of status, particularly morality, which Lamont believes is highly important (but different) across the upper middle classes.

Lessons-Learned-in-Software-Testing-A-Context-Driven-Approach
by Anson-QA

Test automation is a faint, tinny echo of that rich intellectual process. That's why it's nonsensical to talk about automated tests as if they were automated human testing. Automation does not make the computer do the testing that you do. It performs the testing you explicitly specify, unable to benefit from your tacit knowledge and awareness. The automated test does the same thing each time it runs, at the same speed, in the same order, with exactly the same mouse moves and key clicks. The manual tester, however, can't help but vary a test every time he runs it. These variations can uncover unseen bugs. Automated results verification also has limitations.

Artificial Intelligence: A Guide for Thinking Humans
by Melanie Mitchell
Published 14 Oct 2019

.… If human knowledge, especially knowledge about experience, is largely tacit, i.e., never directly and explicitly expressed, it will not be found in books, and the Kurzweil approach to knowledge acquisition will fail.… It is not in what the computer knows but what the computer does not know and cannot know wherein the problem resides.47 Kurzweil responds that he agrees with Kapor on the role of experiential learning, tacit knowledge, and emotions but believes that before the 2030s virtual reality will be “totally realistic,”48 enough to re-create the physical experiences needed to educate a developing artificial intelligence. (Welcome to the Matrix.) Moreover, this artificial intelligence will have a reverse-engineered artificial brain with emotion as a key component.

Adapt: Why Success Always Starts With Failure
by Tim Harford
Published 1 Jun 2011

Allende’s CyberSyn worked well enough to allow him to coordinate a response when Chile was racked by strikes and industrial sabotage. The opening phases both of the Gulf war and of the Iraq war were astonishing examples of the power of a coordinated, computer-aided attack plan. But such systems always deliver less than they promise, because they remain incapable of capturing the tacit knowledge that really matters. CyberSyn was designed to bring problems to the attention of the President and his economic planners, but it succeeded only in reporting the issues that local factory managers wanted to report. Problems that they wanted to conceal, they had no difficulty in concealing. And when times were good it was hard to persuade them to telex any useful information at all, a state of affairs anticipated by Friedrich Hayek in an article published in 1945.

Coding Freedom: The Ethics and Aesthetics of Hacking
by E. Gabriella Coleman
Published 25 Nov 2012

As Mary Douglas (1975, 96) famously theorized, joking brings together “disparate elements in such a way that one accepted pattern is challenged by the appearance of another,” and can be generally defined as “play upon form.” Before expanding on the role of humor among hackers, it is key to highlight that hackers are able to joke with such facility because of the habituated dispositions (Bourdieu 1977) of thought along with tacit knowledge (Polanyi 1966) acquired through a lifelong and routine practice of logic-oriented problem solving. Hackers liberally enjoy hacking almost anything, and because their cultivated technical practice requires an awareness and rearrangement of form, they are able to easily transfer embodied mental dispositions into other arenas.

New Horizons in the Study of Language and Mind
by Noam Chomsky
Published 4 Dec 2003

Again, as demonstrated in practical experiments, even very young children seem to know such facts, suggesting that the knowledge is in some sense antecedently available to the organism. “Language and interpretation” (Chapter 3) takes these ideas further and, in particular, elaborates his arguments against Willard Quine, Michael Dummett and others on such issues as the indeterminacy of translation, public versus private language, the nature of tacit knowledge xiv Foreword and the status of linguistic “rules”. Chomsky takes simple syntactic examples which have featured widely in the technical literature and uses them to argue for a range of philosophical positions. Consider the interpretation of Mary expects to feed herself (Where Mary and herself are taken to refer to the same individual), as opposed to the partially identical I wonder who Mary expects to feed herself, where this coreferential construal is impossible.

How the Mind Works
by Steven Pinker
Published 1 Jan 1997

When the elders spread religious beliefs, they never bother to spell out these defaults. No one ever says, “If the spirits promise us good weather in exchange for a sacrifice, and they know we want good weather, they predict that we will make the sacrifice.” They don’t have to, because they know that the minds of the pupils will automatically supply these beliefs from their tacit knowledge of psychology. Believers also avoid working out the strange logical consequences of these piecemeal revisions of ordinary things. They don’t pause to wonder why a God who knows our intentions has to listen to our prayers, or how a God can both see into the future and care about how we choose to act.

…

P. 1992. The four elementary forms of sociality: Framework for a unified theory of social relations. Psychological Review, 99, 689–723. Fodor, J. A. 1968a. Psychological explanation: An introduction to the philosophy of psychology. New York: Random House, 1968. Fodor, J. A. 1968b. The appeal to tacit knowledge in psychological explanation. Journal of Philosophy, 65, 627–640. Fodor, J. A. 1975. The language of thought. New York: Crowell. Fodor, J. A. 1981. The present status of the innateness controversy. In J. A. Fodor, Representations. Cambridge, Mass.: MIT Press. Fodor, J. A. 1983. The modularity of mind.

Understanding Sponsored Search: Core Elements of Keyword Advertising
by Jim Jansen
Published 25 Jul 2011

. • Internal information search: The internal information search construct represents the retrieval of knowledge from memory. • External information search: The external information search construct represents the motivated acquisition of information from the environment. Certainly, there is interplay between these two, as internal information (a.k.a., tacit knowledge) interacts with information gathered from external searching. However, for our focus on sponsored search, we are interested in the external information searching, specifically on the Internet. External search precedes many consumer decisions [6]. Understanding Consumer Behavior Goal Achieved Yes, else go to search Begin internet search Navigate to URL Guess URL Browsing Search Goal Not Achieved; Try Search Yes, else go to search Repeat based on feedback Browsing and search unsuccessful Goal Not Achieved; Try Browsing Repeat based on feedback Select Search Engine Search Options Exhausted End internet search Know URL 89 View SERP Click Result Goal Achieved Figure 5.1.╇ Flow diagram of consumer information search on the Internet.

How Will Capitalism End?
by Wolfgang Streeck
Published 8 Nov 2016

What this must amount to is, in essence, an extended efficiency theory with strong prescriptive implications: to make markets really work, you need to factor in networks and trust and the like as indispensable devices for reducing transaction costs, and generally to recognize the hidden efficiencies of particularistic as distinguished from universalistic social relations even in presumably impersonal and in this sense ‘rational’ markets and organizations. In a more ethnographic mode, this sort of economic sociology undertakes to produce thick descriptions of how the economy is ‘being done on the ground’: with intuition and tacit knowledge, following half-conscious rules of thumb, and of course deviating widely from the rationalistic homo economicus model of standard economic theory. The ironic point the theory makes is that it is only because of such deviation that ‘the economy’ can function as efficiently as economists assume it functions only if actors behave according to their ideal rather than empirical model of rational individualism.

The Computer Boys Take Over: Computers, Programmers, and the Politics of Technical Expertise
by Nathan L. Ensmenger
Published 31 Jul 2010

What did matter is that whatever its deficiencies, this study and others seemed to confirm plentiful anecdotal evidence that good programmers appeared to have been “born, not made.”42 It should be noted that computer programming is not by any means the only technical occupation in which elements of both art and science are seen as being inextricably intertwined. There is a large literature in the history of science and technology that describes the role of intuition, tacit knowledge, and craft technique in many technical industries.43 Computer work is different in the degree to which this blurry boundary is perceived to be a central contributing factor to an ongoing crisis. The administrative and managerial problems associated with finding and keeping the “right” programmers was complicated by both the newness of the discipline and the extent and duration of the early computer revolution.

The Power of Habit: Why We Do What We Do in Life and Business
by Charles Duhigg
Published 1 Jan 2011

Zeggelink, “Evolving Friendship Networks: An Individual-Oriented Approach Implementing Similarity,” Social Networks 17 (1996): 83–110; Judith Blau, “When Weak Ties Are Structured,” unpublished manuscript, Department of Sociology, State University of New York, Albany, 1980; Peter Blau, “Parameters of Social Structure,” American Sociological Review 39, no. 5 (1974): 615–35; Scott Boorman, “A Combinatorial Optimization Model for Transmission of Job Information Through Contact Networks,” Bell Journal of Economics 6, no. 1 (1975): 216–49; Ronald Breiger and Philippa Pattison, “The Joint Role Structure of Two Communities’ Elites,” Sociological Methods and Research 7, no. 2 (1978): 213–26; Daryl Chubin, “The Conceptualization of Scientific Specialties,” Sociological Quarterly 17, no. 4 (1976): 448–76; Harry Collins, “The TEA Set: Tacit Knowledge and Scientific Networks,” Science Studies 4, no. 2 (1974): 165–86; Rose Coser, “The Complexity of Roles as Seedbed of Individual Autonomy,” in The Idea of Social Structure: Essays in Honor of Robert Merton, ed. L. Coser (New York: Harcourt, 1975); John Delany, “Aspects of Donative Resource Allocation and the Efficiency of Social Networks: Simulation Models of Job Vacancy Information Transfers Through Personal Contacts,” PhD diss., Yale University, 1980; E.

Designing Social Interfaces
by Christian Crumlish and Erin Malone
Published 30 Sep 2009

The very nature of knowledge makes it difficult to manage like other organizational assets. Knowledge assets can be explicit, easy to articulate and precise; or tacit, understood in context of an experience or a situation, and difficult to codify or articulate. An organization has to leverage both explicit and tacit knowledge inherent in its social networks, both within and outside organizational boundaries, to get jobs done. Organizations use this everyday knowledge to empower decision making, improve performance, reduce risk, and encourage innovation. The popularity of social networks and user-generated content in organizations is gradually changing the way knowledge is created, shared, and utilized.

Why We Drive: Toward a Philosophy of the Open Road
by Matthew B. Crawford
Published 8 Jun 2020

There is no set of rules that could guide one adequately. Further, there isn’t some separate faculty of moral reasoning that we call on, to be applied in discreet episodes of moral choice. Rather, we become a certain kind of person; our ethical dispositions develop continuously in concert with the way we perceive the world, and with tacit knowledge that we acquire but are unable to articulate. We know more than we can say, and “doing the right thing” (or not) becomes habitual, rather than something one has to deliberate about in each instance (or outsource to an expert). Often our response to a situation is already latent in the way we perceive the situation.

Exponential: How Accelerating Technology Is Leaving Us Behind and What to Do About It
by Azeem Azhar
Published 6 Sep 2021

As Graeber put it, ‘It has more in common with a nurse’s work than a bricklayer’s.’27 This dynamic means that, in practice, much of the labour economists consider ‘unskilled’ might prove difficult to automate. A workplace manual is usually barely even a rough guide to what a job is – it doesn’t cover half of the things you need to be successful. And when such tacit knowledge exists in a workplace, it makes artificial intelligence that can do the job very hard to build. An AI system needs a clear and unambiguous goal, and modern systems need to be trained on that data. If the know-how about a job is largely hidden, an AI system will be trained on only half the picture.

New Laws of Robotics: Defending Human Expertise in the Age of AI
by Frank Pasquale
Published 14 May 2020

If so, then ask when the fever started. If not, ask if the patient has a cough.” There was enormous enthusiasm for such systems, but they remained cumbersome and inconvenient. Professional judgment turned out to be much harder to systematize than AI researchers expected. The philosopher Hubert L. Dreyfus developed theories of tacit knowledge to explain why expert systems performed so poorly.72 We know more than we can explain. Think of how difficult it would be to boil down your job into a series of “if, then” statements. Could the situations you encounter daily be recognized by a computer? Would possible responses to those situations also be readily articulated, evaluated, and ranked?

Green Philosophy: How to Think Seriously About the Planet
by Roger Scruton
Published 30 Apr 2014

Nor have downtown developments fared any better. The glass and steel-frame blocks, built without façades and indifferent to alignment with their neighbours, have proved to be entirely unable to adapt. Traditional architecture concentrates on the generality of form, on details that embody the tacit knowledge of how to live with a building and adapt to it. Hence traditional architecture in turn adapts to us. It fits to our uses, and shelters whatever we do. Hence it survives – in the way that Rome, Paris and Helsinki have survived, or in the way that Georgetown, Greenwich Village and Old Town Alexandria have survived, despite zoning laws that reduce their ability to adjust to modern needs.

The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
by Mustafa Suleyman
Published 4 Sep 2023

In this book we go with a commonsense, everyday definition: the application of scientific knowledge (in the broadest possible sense) to produce tools or practical outcomes. However, the full, multifaceted complexity of the term is also acknowledged. Technology extends back into cultures and practices. It is not just transistors, screens, and keyboards. It is the explicit and tacit knowledge of coders, the social lives and societies that support them. GO TO NOTE REFERENCE IN TEXT Technology has a clear Scholars of technology make distinctions between diffusion and proliferation that are for the most part elided here. We mean them more in their colloquial rather than formal senses.

Warnings
by Richard A. Clarke
Published 10 Apr 2017

Ever-improving weak AI married with large bodies of data will obviate the need for stockbrokers, medical diagnosticians, information technology support staff, and travel agents. It suggests that even lawyers, doctors, and investment managers will soon find themselves competing and losing to weak-AI software that can more rapidly assess the relevant data and make decisions with “deep, specialized, and often tacit knowledge.”25 A 2013 McKinsey Global Institute study predicts that weak AI will depose 140 million full-time knowledge workers worldwide.26 The idea is certainly not new. In 1933, John Maynard Keynes predicted widespread unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.”27 Technological evolution is part and parcel of the history of humanity; the introduction of the wheel, gunpowder, the steam engine, the car, the adding machine, have all led to systemic societal transformation.

Machine, Platform, Crowd: Harnessing Our Digital Future
by Andrew McAfee and Erik Brynjolfsson
Published 26 Jun 2017

I just see it.” It’s not that Go players are an unusually tongue-tied lot. It turns out the rest of us can’t access all of our own knowledge either. When we recognize a face or ride a bike, on reflection we can’t fully explain how or why we’re doing what we’re doing. It is hard to make such tacit knowledge explicit—a state of affairs beautifully summarized by the twentieth-century Hungarian-British polymath Michael Polanyi’s observation “We know more than we can tell.” “Polanyi’s Paradox,” as it came to be called, presented serious obstacles to anyone attempting to build a Go-playing computer.

Innovation and Its Enemies
by Calestous Juma
Published 20 Mar 2017

Margaret Sharp, “The Science of Nations: European Multinationals and American Biotechnology,” International Journal of Biotechnology 1, no. 1 (1999): 146. 19. Sharp, “Science of Nations,” 146. 20. Sharp, “Science of Nations,” 146. 21. “Failure to keep in touch can result in a cumulative loss of capabilities. Unless there are effective means of actively transferring the tacit knowledge from the American subsidiaries/partners back to the home laboratories of the European multinationals, it is the European science base that loses and suffers a cumulative falling behind the frontiers of scientific practice. This in turn could affect Europe’s ability to create the high value-added jobs in this sector over the longer run.”

The Most Powerful Idea in the World: A Story of Steam, Industry, and Invention
by William Rosen
Published 31 May 2010

In the words of the study’s authors, “The more inventive an independent inventor is,12 the more disposed he will be—and this indeed to a marked degree—to try anything that might work.” WATT’S FLASH OF INSIGHT, like those of Newcomen and Savery before him (and thousands more after), was the result of complicated neural activity, operating on a fund of tacit knowledge, in response to both a love of inventing and a love of financial gain. But what gave him the ability to recognize and test that insight was a trained aptitude for mathematics. The history of mechanical invention in Britain began in a distinctively British manner: with a first generation of craftsmen whose knowledge of machinery was exclusively practical and who were seldom if ever trained in the theory or science behind the levers, escapements, gears, and wheels that they manipulated.

Overdosed America: The Broken Promise of American Medicine
by John Abramson
Published 20 Sep 2004

See Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) Study Group, op. cit. 202 Nurses Health Study: M. J. Stampfer, F. B. Hu, J. E. Manson, et al., “Primary Prevention of Coronary Heart Disease in Women through Diet and Lifestyle,” New England Journal of Medicine 343:16–22, 2000. 202 unspoken professional values, beliefs, and techniques: Kuhn used the phrase “tacit knowledge” to describe the unspoken presuppositions that are shared by scientists that define what they do. Michael Polyani developed the idea: “When we accept a certain set of presuppositions and use them as our interpretative framework, we may be said to dwell in them as we do in our own body.. . . As they are themselves our ultimate framework, they are essentially inarticulable.”

The Village Effect: How Face-To-Face Contact Can Make Us Healthier, Happier, and Smarter
by Susan Pinker
Published 30 Sep 2013

The rich signaling within the team meant that actual conversations propelled the work forward. But the opposite was true in email networks.52 These work best when a larger, more diverse and loosely knit network shares information that can be “written into succinct rules,” as the researchers put it. In other words, if everyone shares the same tacit knowledge and the problem is not that complex, there’s not much advantage to getting together in person to brainstorm solutions. What’s needed in those instances is what Mark Granovetter calls the power of weak bonds: the Internet’s unique capacity to assemble diverse groups of people so they can fill in one another’s gaps in knowledge.53 The Value of a Coffee Break The face-to-face advantage wasn’t seen only among techies.

World Cities and Nation States
by Greg Clark and Tim Moonen
Published 19 Dec 2016

There is good evidence that global companies that are integrated into the local economy play an important role in vertical knowledge transfer to smaller local partners and suppliers of intermediate inputs, both in established and emerging countries. Local industry competition to serve multinational companies is a major driver of technological improvements. The evidence of horizontal spillovers between multinational and local firms within the same industry is understandably more mixed, but there are many important examples of tacit knowledge transfer taking place hosted by globally oriented cities (Rand, 2015). • Spending by the large affluent and high‐net‐worth populations in world cities increases demand for certain kinds of national goods and services. Demand for medical care, retail, children’s education and construction have all increased considerably and the resources and talent in these sectors are often drawn from around the region and the country. • They are visitor and tourist gateways to the rest of the country for customers who otherwise would not visit.

User Friendly: How the Hidden Rules of Design Are Changing the Way We Live, Work & Play
by Cliff Kuang and Robert Fabricant
Published 7 Nov 2019

She’d find herself tasked with designing something that looked “succulent,” and to do so, she’d gather dozens of images that might evoke the word: aloe leaves, maple syrup flowing from a spout. And then she’d try to evoke those shapes in what she was designing. This is almost a universal practice in design, creating mood boards to summon how something should look and feel, and then trying to translate those into form-giving metaphors and words. “Designers have this tacit knowledge of abstract emotive experiences like trust and curiosity,” she explained. “Somehow they translate that into a qualitative attribute like the radius of an object, which is what CAD tools require from us.” She carried that question through her studies at MIT, using as a starting point the striking ability of animators to imbue anything with human character, merely with a few strokes—for example, Beauty and the Beast, whose characters include a rotund, motherly teapot and a haughty mantel clock with a puffed-out chest.

Building Habitats on the Moon: Engineering Approaches to Lunar Settlements
by Haym Benaroya
Published 12 Jan 2018

The two Space Shuttle accidents are examples where we believed that our systems were safe, but the reality proved otherwise. 12.4 Regulation and Certification Downer examined the FAA’s type certification process. ( 4 ) This is the way that it evaluates civil aircraft and certifies that they are sufficiently reliable for public use. The essential thesis is that “regulators of high technologies face an inevitable epistemic barrier when making technological assessments, which forces them to delegate technical questions to people with more tacit knowledge, and hence to ‘regulate’ at a distance by evaluating ‘trust’ rather than ‘technology’.” Because the regulators do not and cannot have the same level of technical knowledge as those who manufacture and repair the airplanes, the regulators make judgments based on their assessments of the people who build and repair airplanes, in lieu of assessing the actual airplanes.

Bourgeois Dignity: Why Economics Can't Explain the Modern World
by Deirdre N. McCloskey
Published 15 Nov 2011

In the Mahabharata, the Achilles character Karna declares, “I see it now: this world is swiftly passing.”3 “Lay up not for yourself treasures upon earth,” said Jesus of Nazareth, “where moth and rust do corrupt.” St. Augustine was eloquent on the point: “All things pass away, fly away, and vanish like smoke; and woe to those who love such things!”4 What does not vanish like entropic smoke, aside from God, is knowledge, or the tacit knowledge in design or sport or art transmitted in practice, or the bookable knowledge of the formula for aspirin or the procedure for habeas corpus, and most particularly, with the greatest consequence, the information-plus-judgment embodied in the Bourgeois Deal. To be sure, knowledge does not always persist.

…

Merely act, following your DNA, the traditions of the Spartanate, the Baconian method, the volonté générale, the Party line (Partiinost’), the views of Thabo Mbeki about AIDS, or whatever else your lord or your utility function says. The rule is: Don’t reflect. Don’t discuss. Heh, just do it. No rhetoric. For many purposes it is not a crazy rule. Indeed an innovative society depends on tacit knowledge scattered over the economy, and the economy depends on allowing such tacit and habitual knowledge to be combined by invisible hands. As Hayek put it, “Civilization enables us constantly to profit from knowledge we individually do not possess. . . . These ‘tools’ which man has evolved . . . consist in a large measure of forms of conduct which we habitually follow without knowing why.”21 You type on your computer without understanding machine language or what a “registry” is.

Digital Apollo: Human and Machine in Spaceflight
by David A. Mindell
Published 3 Apr 2008

Most of his time had been spent following well-established procedures to deploy and operate other scientists’ automated experiments. Under such conditions, what is the necessity for scientific training? Or for human presence at all? Still, that same astronaut acknowledged that being able to ‘‘speak the same language’’ as the scientists on the ground proved an important part of his job. Clearly, tacit knowledge, social interaction, and shared vocabulary play an important role in space operations. Scholars who can deeply analyze scientific practice can explore these issues further, across a broad range of spaceflight. Like this study, an anthropology of space operations would examine skill, training, professional identity, automation, risk, organizations, divisions of power, and other aspects of human-machine relationships.

The Future of the Professions: How Technology Will Transform the Work of Human Experts
by Richard Susskind and Daniel Susskind
Published 24 Aug 2015

See Lieberman, The Tyranny of the Experts, 275. 79 Anthony Kenny, What I Believe (2006), 123. 80 <http://www.kpmg.com>. 81 Our thinking on asymmetry of knowledge aligns to some extent with that of Durkheim, Parsons, and Abbott. 82 Herbert Hart, The Concept of Law (1994), 197. Original emphasis. 83 On the distinction between ‘knowing that’ and ‘knowing how’, see Gilbert Ryle, The Concept of Mind (1949), 28–32. 84 On tacit knowledge, see Michael Polanyi, ‘The Logic of Tacit Inference’, Philosophy, 41: 155 (1966), 1–18. 85 See e.g. Amos Tversky and Daniel Kahneman, ‘Judgment under Uncertainty: Heuristics and Biases’, Science, 185: 4157 (1974), 1124–31. They explore the problems with some of these rules of thumb. 86 Note the correspondence here with philosophical and psychological concepts of practical reason and practical reasoning.

Pedigree: How Elite Students Get Elite Jobs
by Lauren A. Rivera
Published 3 May 2015

Harrison, an attorney, described a typically unacceptable expression of interest: “They gave me the same BS answer as everybody else, ‘I really like international law firms and international arbitration sounds really cool.’ So those kinds of things I don’t want to hear about…. I am looking for something a little bit different.” Strong answers conveyed difficult-to-acquire, tacit knowledge about the industry, the firm, and its employees—the kind of information that signaled it had been obtained from industry insiders. A banker named Gayatri told me that she looked for signs that job candidates “really know what they’re in for, and if [banking is] really what they want to do. And then if that is [true], then what have they done to prove that?”

Between Human and Machine: Feedback, Control, and Computing Before Cybernetics
by David A. Mindell
Published 10 Oct 2002

If the Arab were to convert from his “godless” ways, he too would see how the ship drives itself. 6 The ad makes the point that although ships may have been “beasts of burden,” the gyropilot made them seem intelligent and domesticated (and Christian). Because the gyropilot did not require a person to operate it, questions arose about its relationship to human operators. Some believed it could never replace the tacit knowledge embedded in an expert helmsman. Elmer Sperry countered by arguing that the helmsman’s skill inhered in the ability to “anticipate” the ship’s motions and that he had incorporated such a feature into the gyropilot. 7 Sperry Gyroscope offered as an add-on product a paper recorder to plot minute changes in course over time.

Open: The Story of Human Progress
by Johan Norberg
Published 14 Sep 2020

The conclusion is that over a five-hundred-year period, ‘opposition to innovation was not just an incidental aspect of guild’s activities, but central to their incentives as privileged interest groups’.15 It happened everywhere and in all sectors, as soon as an innovation was thought to threaten business interests. Before the Industrial Revolution, all the great episodes of progress and open inquiry were ended. Those with social status, formal skills, tacit knowledge, special equipment, natural resources or any kind of privileged position tied to a specific way of doing and producing things, always sensed a lethal danger whenever someone introduced new technologies or organizational forms that threatened it. Therefore, they had an incentive to take control of the political process and stop it, or at least slow it down.

Convergence Culture: Where Old and New Media Collide
by Henry Jenkins
Published 31 Jul 2006

Supercession: According to P a u l D u g u i d , the idea that each new med i u m displaces what came before. Synergy: The economic opportunities that emerge i n a context of hori- Skenovâno pro studijni ucely Glossary zontal integration where one media conglomerate holds interests i n multiple channels of distribution. Tacit knowledge: According to James Gee, knowledge that is not explicitly expressed but rather gets embodied through the everyday activities of an affinity space or knowledge community. Talking points: Arguments constructed by campaigns to be deployed b y their supporters. Technological convergence: The combination of functions w i t h i n the same technological device.

Why We Can't Afford the Rich
by Andrew Sayer
Published 6 Nov 2014

An important objection from the Right The Right often challenge any questioning of capitalist property rights by saying that to remove them would deny people the freedom to produce, or even to do what they want with their property. Since no one would be responsible for the upkeep and use of means of production it would be neglected or misused. Alternatively, if central state planners try to organise it, they will inevitably lack the detailed and often tacit knowledge that the producers have on the ground, and in trying to conduct it from above will make a mess of it, as happened in the former Soviet Bloc. As the neoliberal guru Friedrich Hayek argued, in a society with a complex division of labour such as our own, only those actually involved in particular specialisms within that economy can know what their specific needs are – how many and what kind of widgets are needed for producing other widgets and so on.

The Precipice: Existential Risk and the Future of Humanity
by Toby Ord
Published 24 Mar 2020

The good news is that for all our flirtation with biowarfare, there appear to have been relatively few deaths from either accidents or use (assuming the Black Death to have been a natural pandemic).42 The confirmed historical death toll from biowarfare is dwarfed by that of natural pandemics over the same time frame.43 Exactly why this is so is unclear. One reason may be that bioweapons are unreliable and prone to backfiring, leading states to use other weapons in preference. Another suggestion is that tacit knowledge and operational barriers make it much harder to deploy bioweapons than it may first appear.44 But the answer may also just be that we have too little data. The patterns of disease outbreaks, war deaths and terrorist attacks all appear to follow power law distributions. Unlike the familiar “normal” distribution where sizes are clustered around a central value, power law distributions have a “heavy tail” of increasingly large events, where there can often be events at entirely different scales, with some being thousands, or millions, of times bigger than others.

Globalists: The End of Empire and the Birth of Neoliberalism
by Quinn Slobodian
Published 16 Mar 2018

Hayek’s “neuro-­sensory conjecture” has been explored deeply by scholars both sympathetic to and critical of his thinking.76 What Philip Mirowski 232 GLOBALISTS calls Hayek’s “agnotology” is echoed in the presumption of “radical ignorance” of economic actors in the work of t­ hose who seek to explain why Hayek’s model is incompatible with the “rational search” implied in con­temporary forms of neoclassical economics.77 As the above meta­phors make clear, the idea of agency is diffuse in Hayek’s work. One scholar speaks of Hayek’s “instrumental justification of liberty, [by which] freedom is essential for the utilization of dispersed, fragmented, and habitual or tacit knowledge.” 78 Freedom, in this reading, exists to discover new and better rules. The vanishing of the subject is consistent with system theory in general, where the system itself becomes the protagonist. As one scholar puts it, “the seat of causality” in Hayek’s framework is not the individual but “appears to be the entire web or network.”79 Another goes even farther, saying that “the only subject is at the level of the w ­ hole system of humanity and his80 tory.”

As Gods: A Moral History of the Genetic Age
by Matthew Cobb
Published 15 Nov 2022

As a number of scholars such as Katherine Vogel, Sonia Ben Ouagrham-Gormley and Claire Marris have emphasised, one major explanation of this apparent paradox is that it is one thing to understand a piece of research but quite another to be able to replicate or apply it.117 This is perhaps particularly the case in molecular biology, where experiments are difficult to do and often fail (anyone who has tried to do a supposedly straightforward PCR experiment will know this). As well as an academic understanding of the subject, actually doing the experiment requires tacit knowledge, often built up in a laboratory team over years, which enables scientists to know which techniques work best and how to perform them. Vogel has described this as ‘the unarticulated, personally held knowledge that one acquires through a practical, hands-on process, through either “learning by doing” or “learning by example”’.118 Even when you have acquired such expert skills, experiments that have worked regularly can stop giving the expected result for a number of reasons, including seasonal variations in the reagents being used.119 A scientific article presents a set of selected facts in a constructed narrative and does not describe the underlying social connections that were required for the whole thing to happen, nor will it mention the myriad occasions when experiments failed for unknown or tedious reasons.

The Rise and Fall of Modern Medicine
by M. D. James le Fanu M. D.
Published 1 Jan 1999

This intellectual hubris of not recognising what is not known opens the door to false explanations where, as with The Social Theory, people are blamed for their illnesses and are deceived into believing their everyday lives are full of hazards. Nor is that the end of it. For medical science now recognises only one source of knowledge, that which has ‘been proven’ by statistics, and this too is a potent source of error. There are many ways of knowing, and among the most powerful is the tacit knowledge that comes from experience and is best described as ‘judgement’.5 Sir Austin Bradford Hill’s legacy, albeit unintentional on his part, has been to marginalise this tacit form of knowledge, so it is deemed less reliable and inferior to that which can be objectively and explicitly demonstrated with statistical techniques and clinical trials.

The Rise and Fall of Nations: Forces of Change in the Post-Crisis World
by Ruchir Sharma
Published 5 Jun 2016

Gupta, Shekhar. “Modi and the Art of the Sell.” Indian Express, December 18, 2012. Haberman, Clyde. “The Unrealized Horrors of Population Explosion.” New York Times, May 31, 2015. Harari, Yuval Noah, and Daniel Kahneman. “Death Is Optional.” Edge, November 25, 2015. Hausmann, Ricardo. “The Tacit-Knowledge Economy.” Project Syndicate, October 30, 2013. Hessler, Peter. “Learning to Speak Lingerie.” New Yorker, August 10, 2015. Hokenson, Richard F. “Retiring the Current Model of Retirement.” Hokenson Research, March 2004. ——. “Rethinking Old Age Economic Security.” Evercore ISI Research, July 30, 2015. ——.

The Technology Trap: Capital, Labor, and Power in the Age of Automation
by Carl Benedikt Frey
Published 17 Jun 2019

One reason is because of what the economist David Autor has called “Polanyi’s paradox.”17 A key bottleneck to automation that engineers have found hard to overcome is well summarized by Michael Polanyi’s famous phrase: “We know more than we can tell.”18 (We shall take a closer look at the AI-enabled inroads on Polanyi’s paradox in chapter 12.) Humans constantly draw upon large reservoirs of tacit knowledge that we struggle to articulate and define even to ourselves, making it exceedingly hard to specify it in computer code. To illustrate Polanyi’s point, it is helpful to contrast the task of repetitive assembly with that of designing a new car, writing a piece of music, or giving a galvanizing speech.

Antifragile: Things That Gain From Disorder
by Nassim Nicholas Taleb
Published 27 Nov 2012

Anti-Enlightenment: For a review, Sternhell (2010), McMahon (2001), Delon (1997). Horkheimer and Adorno provide a powerful critique of the cosmeticism and sucker-traps in the ideas of modernity. And of course the works of John Gray, particularly Gray (1998) and Straw Dogs, Gray (2002). Wittgenstein and tacit knowledge: Pears (2006). On Joseph de Maistre: Companion (2005). Ecological, non-soccer-mom economics: Smith (2008), also Nobel lecture given along with Kahneman’s. Gigerenzer further down. Wisdom of the ages: Oakeshott (1962, 1975, 1991). Note that Oakeshott conservatism means accepting the necessity of a certain rate of change.

The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous
by Joseph Henrich
Published 7 Sep 2020

In fact, in some cases, cultural products operate more effectively when people don’t understand how or why they work, as will become clear when I discuss rituals and religions.9 What’s amazing about the products of cumulative cultural evolution is that they are often smarter than we are—much smarter. These practices, which range from poison recipes to incest taboos, have evolved culturally to embody a tacit knowledge of the world that we—the practitioners—often lack. To see this, let’s begin with a case in which there’s a well-understood goal: making a deadly arrow poison used by Congo Basin hunter-gatherers. This is perhaps the deadliest hunting poison known, dropping prey in their tracks before they can vanish into the bush.

The Blank Slate: The Modern Denial of Human Nature
by Steven Pinker
Published 1 Jan 2002

That is why every language, far from being an immutable penitentiary, is constantly under renovation. Despite the lamentations of language lovers and the coercion of tongue troopers, languages change unstoppably as people need to talk about new things or convey new attitudes.37 Finally, language itself could not function if it did not sit atop a vast infrastructure of tacit knowledge about the world and about the intentions of other people. When we understand language, we have to listen between the lines to winnow out the unintended readings of an ambiguous sentence, piece together fractured utterances, glide over slips of the tongue, and fill in the countless unsaid steps in a complete train of thought.

Public Places, Urban Spaces: The Dimensions of Urban Design
by Matthew Carmona , Tim Heath , Steve Tiesdell and Taner Oc
Published 15 Feb 2010

Arguing that IT applications were largely metropolitan phenomena, Graham & Marvin (1999: 90) note how the value-added in IT industries has shifted to places able to sustain innovation in software and content – and crucially where the employees of such industries want to live and hang out. They cite a study of Manhattan’s SoHo and TriBeCa, which found the raw material for such industries was:‘… the sort of informal networks, high levels of creativity and skills, tacit knowledge, and intense and continuous innovation processes that become possible in an intensely-localised culture, based on on-going, face-to-face contacts supported by rich, dense and interdependent combinations of meeting places and public spaces.’ (Graham & Marvin 1999: 97) They also note how, despite the growth of some e-tailers, a wide range of consumer services both remain crucially embedded in urban locations – tourism, shopping, visiting museums and leisure attractions, eating and drinking, sport, theatre, cinema and so on – and seem likely to resist any simple, substantial substitution by ‘online’ equivalents (Graham & Marvin 1999: 95).

Command and Control: Nuclear Weapons, the Damascus Accident, and the Illusion ofSafety
by Eric Schlosser
Published 16 Sep 2013

His views on the process of scientific and technological change resonate strongly with one of my own long-standing beliefs: if things aren’t inevitable, then things don’t have to be the way they are. Without being utopian or overly optimistic, MacKenzie and Graham Spinardi applied that sort of thinking to weapons of mass destruction, after interviewing dozens of scientists at Los Alamos and Lawrence Livermore, in their essay “Tacit Knowledge and the Uninvention of Nuclear Weapons.” It can be found in MacKenzie’s book Knowing Machines: Essays on Technical Change (Cambridge, MA: MIT Press, 1998). Many of the declassified documents cited in this book were found online. Two of the best sites for historical material are the Pentagon’s Defense Technical Information Center, “Provider of DoD Technical Information to Support the WarFighter,” and the U.S.

The Empire Project: The Rise and Fall of the British World-System, 1830–1970
by John Darwin
Published 23 Sep 2009

(He remained Prime Minister until 1902 but gave up the Foreign Office in 1900). Salisbury was greatly helped by the ruthless skill with which Evelyn Baring (later Lord Cromer) created a ‘veiled protectorate’ in Egypt to minimise open dissent. Baring's ‘system’ preserved the fiction of Egyptian autonomy. But it rested on the tacit knowledge of the Egyptian ruler that defiance would mean deposition; on the studied manipulation of Egypt's internal stresses; and on the systematic infiltration of the government by British ‘advisers’ who were Baring's eyes and ears. With unrivalled political intelligence, a British garrison (of 6,000 men), a reorganised local army under British officers, and an extraordinary hold over his political masters in London (a measure of their trust), Baring was able to restore Egypt's solvency (by 1890) and ride out the crises of his eccentric regime.39 Salisbury's other advantage lay in the chronic mistrust between France and Germany and the gradual emergence of two rival diplomatic groupings: Germany, Austria-Hungary and Italy on one side; France and Russia (after 1892) on the other.