crowdsourcing

Blank Space: A Cultural History of the Twenty-First Century

by W. David Marx  · 18 Nov 2025  · 642pp  · 142,332 words

without direct governmental interference or having to change voters’ minds. Surowiecki’s “wisdom of the crowd” thesis found its most immediate validation in Wikipedia, a crowdsourced website that became the largest and most accessible repository of knowledge in human history. By offering free, multilingual information to anyone with an internet connection

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from empowering dissidents, cracked down on activists’ accounts while regimes like Saudi Arabia deployed “troll armies” to suppress dissent. Even grassroots online activism faced setbacks. Crowdsourcing, once heralded as a democratic tool, became a cautionary tale. Reddit users wrongly identified a missing Brown student as the Boston Marathon bomber in 2013

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-media. GO TO NOTE REFERENCE IN TEXT missing Brown student: James Surowiecki, “The Wise Way to Crowdsource a Manhunt,” New Yorker, April 23, 2013, https://www.newyorker.com/news/daily-comment/the-wise-way-to-crowdsource-a-manhunt. GO TO NOTE REFERENCE IN TEXT wrong police officers: David Kushner, “What Anonymous Got

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Culture, The (Roy), 273 critical race theory (CRT), 153–54 Cross Colours, 29 Cross, David, 22 Crouch, Ian, 106 Crouching Tiger, Hidden Dragon (film), 245 crowdsourcing, 162 “Cruel Summer” (song), 211 Crumbs Bake Shop, 212 cryptocurrencies, 235–36, 240–42, 271 CryptoPunks, 236 cultural appropriation, 157–58 cultural canon, 279–80

Extremely Hardcore: Inside Elon Musk's Twitter

by Zoë Schiffer  · 13 Feb 2024  · 343pp  · 92,693 words

difficult by the fact that Musk had cut off free API access and recently eliminated headlines from news articles. Musk had promoted Community Notes, a crowdsourced fact-checking tool, as his preferred news-vetting methodology. Two days after the attacks began, however, I searched for footage of the fireworks in Algeria

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/02/heres-the-guy-who-unwittingly-live-tweeted-the-raid-on-bin-laden-2. GO TO NOTE REFERENCE IN TEXT Amnesty International found: Press release, “Crowdsourced Twitter Study Reveals Shocking Scale of Online Abuse Against Women,” Amnesty International, December 18, 2018, amnesty.org/en/latest/press-release/2018/12

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/crowdsourced-twitter-study-reveals-shocking-scale-of-online-abuse-against-women. GO TO NOTE REFERENCE IN TEXT CEO Bob Iger said: Peter Kafka, “Why Disney Didn’

Doing Data Science: Straight Talk From the Frontline

by Cathy O'Neil and Rachel Schutt  · 8 Oct 2013  · 523pp  · 112,185 words

a bit), finishing very near the top in multiple competitions, and now works for Kaggle. After giving us some background in data science competitions and crowdsourcing, Will will explain how his company works for the participants in the platform as well as for the larger community. Will will then focus on

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figuring out what questions to ask, so the question is: while they’re doing data science, are the contestants? Background: Crowdsourcing There are two kinds of crowdsourcing models. First, we have the distributive crowdsourcing model, like Wikipedia, which is for relatively simplistic but large-scale contributions. On Wikipedia, the online encyclopedia, anyone in

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set of people with highly specialized skills compete. There is usually a cash prize, and glory or the respect of your community, associated with winning. Crowdsourcing projects have historically had a number of issues that can impact their usefulness. A couple aspects impact the likelihood that people will participate. First off

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is given, and the metric of success is given. Moreover, the prizes are established up front. Let’s get a bit of historical context for crowdsourcing, since it is not a new idea. Here are a few examples: In 1714, the British Royal Navy couldn’t measure longitude, and put out

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efficient process overall—but on the other hand, it could very well be efficient for the people offering the prize if it gets solved. Terminology: Crowdsourcing and Mechanical Turks These are a couple of terms that have started creeping into the vernacular over the past few years. Although

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crowdsourcing—the concept of using many people to solve a problem independently—is not new, the term was only fairly recently coined in 2006. The basic

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groups of people can arrive at the correct solution. And only certain problems are well-suited to this approach. Amazon Mechanical Turk is an online crowdsourcing service where humans are given tasks. For example, there might be a set of images that need to be labeled as “happy” or “sad.” These

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can use Amazon Mechanical Turk as long as they provide compensation for the humans. And any human can sign up and be part of the crowdsourcing service, although there are some quality control issues—if the researcher realizes the human is just labeling every other image as “happy” and not actually

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data science a sport.” Kaggle forms relationships with companies and with data scientists. For a fee, Kaggle hosts competitions for businesses that essentially want to crowdsource (or leverage the wider data science community) to solve their data problems. Kaggle provides the infrastructure and attracts the data science talent. They also have

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top-notch data scientists, including Will himself. The companies are their paying customers, and they provide datasets and data problems that they want solved. Kaggle crowdsources these problems with data scientists around the world. Anyone can enter. Let’s first describe the Kaggle experience for a data scientist and then discuss

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’s innovation is that it convinces businesses to share proprietary data with the benefit that their large data problems will be solved for them by crowdsourcing Kaggle’s tens of thousands of data scientists around the world. Kaggle’s contests have produced some good results so far. Allstate, the auto insurance

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Amazon, Why Now?, Amazon Case Study: Big Spenders recommendation engines and, Recommendation Engines: Building a User-Facing Data Product at Scale Amazon Mechanical Turk, Background: Crowdsourcing ambient analytics, Data Visualization at Square Amstat News, The Current Landscape (with a Little History) analytical applications Hadoop, So How to Get Started with Hadoop

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curve, Evaluation area under the curve (AUC), How to Be a Good Modeler goodness of, Research Experiment (Observational Medical Outcomes Partnership) Artificial Artificial Intelligence, Background: Crowdsourcing Artificial Intelligence (AI), Machine Learning Algorithms ASA, The Current Landscape (with a Little History) association algorithms, Being an Ethical Data Scientist associations, Linear Regression assumptions

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cross-validation, Adding in modeling assumptions about the errors, Last Thoughts on These Algorithms crowdsourcing DARPA and, Background: Crowdsourcing distributive, Background: Crowdsourcing InnoCentive and, Background: Crowdsourcing issues with, Background: Crowdsourcing Kaggle and, Background: Crowdsourcing Mechanical Turks vs., Background: Crowdsourcing organization, Background: Crowdsourcing Wikipedia and, Background: Crowdsourcing Cukier, Kenneth Neil, Datafication Cukierski, William, William Cukierski curves, goodness of, Research Experiment

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(Observational Medical Outcomes Partnership) D Dalessandro, Brian, Logistic Regression DARPA, Background: Crowdsourcing data abundance vs. scarcity, Data Abundance Versus Data Scarcity clustering, k-means extracting meaning from, Extracting Meaning from Data–Thought Experiment: What Is the Best

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Neighbors distant reading, Franco Moretti distribution, Populations and Samples conditional, Probability distributions Gaussian, Probability distributions joint, Probability distributions named, Probability distributions normal, Probability distributions distributive crowdsourcing, Background: Crowdsourcing domain expertise vs. machine learning algorithms, Thought Experiment: What Are the Ethical Implications of a Robo-Grader? Dorsey, Jack, About Square Driscoll, Mike, The

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ERGMs inferential degeneracy, Inference for ERGMs information gain, Entropy maximize, The Decision Tree Algorithm inherent chaos, Thought Experiment: How Would You Simulate Chaos? InnoCentive, Background: Crowdsourcing inspecting elements, Scraping the Web: APIs and Other Tools interpretability as constraint, Interpretability of logistic regression, Interpretability predictive power vs., User Retention: Interpretability Versus Predictive

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Neighbors? sparseness, Some Problems with Nearest Neighbors test sets, Training and test sets training sets, Training and test sets Kaggle, Background: Crowdsourcing, The Kaggle Model–Their Customers crowdsourcing and, Background: Crowdsourcing customer base of, Their Customers Facebook and, Their Customers leapfrogging and, A Single Contestant Katz, Elihu, Case-Attribute Data versus Social Network

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the errors, Evaluation, How to Be a Good Modeler meaning of features, Causality measurement errors, Some Problems with Nearest Neighbors Mechanical Turks, Background: Crowdsourcing Amazon, Background: Crowdsourcing crowdsourcing vs., Background: Crowdsourcing Mechanize, Scraping the Web: APIs and Other Tools Media 6 Degrees (M6D), Your Mileage May Vary Media 6 Degrees (M6D) case study, M6D

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(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

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Wabbit, Stochastic Gradient Descent W web, scraping data from, Scraping the Web: APIs and Other Tools–Scraping the Web: APIs and Other Tools Wikipedia, Background: Crowdsourcing Wills, Josh, Machine Learning Algorithms, About Josh Wills Wong, Ian, Data Science and Risk–Ian’s Thought Experiment word frequency problems, Word Frequency Problem–Enter

Reality Is Broken: Why Games Make Us Better and How They Can Change the World

by Jane McGonigal  · 20 Jan 2011  · 470pp  · 128,328 words

decided to enlist the public’s direct help in uncovering whatever it was the authorities didn’t want uncovered. In other words, they “crowdsourced” the investigation. The term crowdsourcing, coined by technology journalist Jeff Howe in 2006, is shorthand for outsourcing a job to the crowd.3 It means inviting a large

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, the collaboratively authored online encyclopedia created by a crowd of more than 10 million unpaid (and often anonymous) writers and editors, is a prime example. Crowdsourcing is a way to do collectively, faster, better, and more cheaply what might otherwise be impossible for a single organization to do alone. With a

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the MPs’ records are on there now—so let us know what you find. Just three days into the game, it was clear that the crowdsourcing effort was an unprecedented success. More than 20,000 players had already analyzed more than 170,000 electronic documents. Michael Andersen, a member of the

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Nieman Journalism Lab at Harvard University and an expert on Internet journalism, reported at the time: “Journalism has been crowdsourced before, but it’s the scale of the Guardian’s project—170,000 documents reviewed in the first 80 hours, thanks to a visitor participation

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visitor participation rate measures the percentage of visitors who sign up and make a contribution to a network. A rate of 56 percent for any crowdsourced project was unheard of previously. (By comparison, roughly 4.6 percent of visitors to Wikipedia make a contribution to the online encyclopedia.)5 It’s

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free—lowering the costs of investigative journalism and speeding up the democratic reform process. Not all crowdsourcing projects are so successful. Working together on extreme scales is easier said than done. You can’t crowdsource without a crowd—and it turns out that actively engaged crowds can be hard to come by

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-size projects every single day—if we could convince all 1.7 billion Internet users to spend most of their free time voluntarily contributing to crowdsourced projects. Maybe that’s unrealistic. More reasonably, if we could convince every Internet user to volunteer just one single hour a week, we could accomplish

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factors in, for example, more than 1 million public social networks created on Ning, more than 100,000 wikis on Wikia, more than 100,000 crowdsourcing projects on Amazon’s Mechanical Turk, at least 20,000 videos awaiting transcription and translation on DotSUB, as well as myriad smaller clusters of open

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how to capture the mental energy and the active effort it takes to make individual contributions to a larger whole. For this reason, the overall crowdsourcing culture likely will not be immune from “the tragedy of the commons”—the crisis that occurs when individuals selfishly exhaust a collective resource. Collaboration projects

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keep it participating over the long haul. But it’s not hopeless. As both Wikipedia and Investigate Your MP’s Expenses show, there are significant crowdsourcing projects succeeding. And they all have one important thing in common: they’re structured like a good multiplayer game. The most active contributors to Wikipedia

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, the world’s most successful crowdsourced project, already know this. In fact, they’ve created a special project to detail all the ways in which Wikipedia is like a game. As

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you managed to successfully engage only that group, it would still take them only two months of channeling their usual WoW playing time to a crowdsourcing project to collectively create a resource on the scale of Wikipedia. By comparison, Wikipedia took eight years to collect 100 million hours of cognitive effort

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to reap enormous benefits. (And clearly, the Guardian’s Investigate Your MP’s Expenses represents one of the first organizations to do just that.) Second, crowdsourcing projects—if they have any hope of capturing enough participation bandwidth to achieve truly ambitious goals—must be intentionally designed to offer the same kinds

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Use of Gamers’ Participation Bandwidth My experience and research suggests that gamers are more likely than anyone on the planet to contribute to an online crowdsourcing project. They already have the time and the desire to tackle voluntary obstacles. They’re playing games precisely because they hunger for more and better

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of rice and counting—enough to provide more than 10 million meals worldwide. Free Rice in one respect seems like a perfect embodiment of the crowdsourcing philosophy: lots of people come together to make a small contribution, all of it adding up to something bigger. But Free Rice actually falls short

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of real crowdsourcing. That’s because the grains of rice aren’t coming from the players—they’re coming from a small number of advertisers who agree to

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when he discovered Folding@home for the PlayStation 3, the world’s first distributed computing initiative just for gamers. A distributed computing system is like crowdsourcing for computers. It connects individual computers via the Internet into a giant virtual supercomputer in order to tackle complex computational tasks that no individual computer

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The Folding@home project for the PlayStation 3 is a perfect example of matching ability with opportunity, which is the fundamental dynamic of any good crowdsourcing project. It’s not enough to draw a crowd—you have to ask the crowd to do something they have a real chance of doing

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of world-changing collective work to be done—so we can’t allow ourselves to be limited by a shortage of incentive or compensation. Many crowdsourcing projects today are experimenting with micropayments, or small amounts of monetary reward, in return for contributions. The Amazon Mechanical Turk marketplace, which gives businesses access

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rewards, and not more lucrative compensation. So if not money or prizes, then what will most likely emerge as the most powerful currency in the crowdsourcing economy? I believe that emotions will drive this new economy. Positive emotions are the ultimate reward for participation. And we are already hardwired to produce

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mass collaboration for years. Games inspire extreme effort. Games create communities that stick together over time, long enough to get amazing things done together. If crowdsourcing is the theory, then games are the platform. Which brings us to our next fix for reality: FIX # 11 : A SUSTAINABLE ENGAGEMENT ECONOMY Compared with

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kinds of citizen journalism, collective intelligence, humanitarian, and citizen science projects that we will increasingly seek to undertake. As the examples in this chapter demonstrate, crowdsourcing games have an important role to play in how we achieve our democratic, scientific, and humanitarian goals over the next decade and beyond. And more

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and more, these crowdsourcing games won’t be just about online work or computational tasks. Increasingly, they will take us out into physical environments and face-to-face social

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to design social participation tasks (SPTs) to stand alongside the growing number of human intelligence tasks (HITs) that currently make up the majority of online crowdsourcing projects: transcribing and subtitling videos on DotSUB, for example, analyzing an MP’s receipts in Investigate Your MP’s Expenses, or even simply evaluating an

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child is, it’s a lot of pressure, and they spend their whole life preparing for it. What we’re trying to do is basically crowdsource the pat on the back.4 I chose to write my good-luck message to a student in India. I shared my favorite trick: “Before

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the rise around the world among nongamers as well. From widespread basic Internet literacy and mobile technology smarts to rapidly expanding Web 2.0 and crowdsourcing know-how, people everywhere are becoming increasingly connected and improving their ability to cooperate, coordinate, and create together in many important ways. In this sense

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and lower-cost boating. • Spark Library, a venture developed by a U.S. graduate student in architecture, to design and pilot a new kind of crowdsourced library across sub-Saharan Africa. In order to check out a book from a Spark Library, you must first contribute a piece of local or

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. What specifically would making a move in the game entail? We envisioned a combination of events. Social rituals and circle games to build common ground. Crowdsourced challenges and collective feats—in the style of a traditional barn raising—to focus the world’s energy and attention on a single problem and

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big games can help save the real world—by helping to generate more participation bandwidth for our most important collective efforts. We’ve looked at crowdsourcing games that successfully engage tens of thousands of players in tackling real-world problems for free—from curing cancer to investigating political scandals (Fix #11

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games being invented and publicly playtested in the United Kingdom at www.hideandseekfest.co.uk. INVESTIGATE YOUR MP’S EXPENSES (Chapter 11) Play with the crowdsourcing tool and read updates about the Guardian’s political investigation of UK parliament members at http://mps-expenses.guardian.co.uk. JETSET (Chapter 8) See

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Redactions Black Out Documents.” Guardian, June 19, 2009. http://www.guardian.co.uk/politics/2009/jun/18/mps-expenses-censorship-black-out. 3 Jeff Howe. Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business (New York: Crown Business, 2008), 4-17. 4 Andersen, Michael. “Four

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from the Guardian’s (Spectacular) Expenses-Scandal Experiment.” Nieman Journalism Lab, June 23, 2009. http://www.niemanlab.org/2009/06/four-crowdsourcing-lessons-from-the-guardians-spectacular-expenses-scandal-experiment/. 5 “Participation on Web 2.0 Websites Remains Weak.” Reuters, April 18, 2007. http://www.reuters.com/

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digital games concept ARGs Cookman, Daniel co-op mode Crawford, Matthew Crecente, Brian crowd games dancing in social connections in see also crowdsourcing projects; massive multiplayer collaboration projects crowdsourcing projects citizen science research in clear goals in collaboration in distributed computing initiatives in empowerment in epic meaning in feedback in for fighting

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(positive stress) Evans, Simon Evokation Station EVOKE experience sampling method (ESM) Extraordinaries, The extrinsic rewards Facebook Fahey, Rob famine FarmVille feedback systems ambient avatar in crowdsourcing projects intensity of leveling up in in massive collaboration projects phasing as form of positive failure in potential downfalls of in real-life activities three

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see also world-changing games Foursquare Free Rice Friedman, Thomas Friend, Tad fun failure game communities collaborative culture in collective intelligence in creating of in crowdsourcing and massive collaboration projects discussion forums in user profiles in game consoles Game Developers Conference game industry and design addiction dilemma and collaboration innovations in

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Television Service (ITVS) India in-flight games injury and illness recovery games Institute for the Future (IFTF) Ten-Year Forecast of International Olympic Committee Internet crowdsourcing projects on discussion forums on game-learning resources on see also online games; social networks intrinsic rewards extrinsic vs. four categories of of wholehearted participation

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Sameshima, Pauline satisfying work actionable next steps in ARGs as turning real world tasks into blissful productivity of in casual games clear goals in in crowdsourcing and massive collaboration projects “endgame” payoff in as fix for reality in games vs. work in reality guarantee of productivity in intrinsic rewards of leveling

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American Art Museum social connections ambient sociability and ARGs and closing generation gap in combating loneliness with community-building games and in crowd games in crowdsourcing and massive collaboration projects eye contact and touch in strengthening of as fix for reality forging new relationships vs. strengthening of existing intrinsic rewards of

Bold: How to Go Big, Create Wealth and Impact the World

by Peter H. Diamandis and Steven Kotler  · 3 Feb 2015  · 368pp  · 96,825 words

Four: Climbing Mount Bold Chapter Five: The Secrets of Going Big Chapter Six: Billionaire Wisdom: Thinking at Scale PART THREE: THE BOLD CROWD Chapter Seven: Crowdsourcing: Marketplace of the Rising Billion Chapter Eight: Crowdfunding: No Bucks, No Buck Rogers Chapter Nine: Building Communities Chapter Ten: Incentive Competitions: Getting the Best and

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incredible power and essential best practices that allow anyone to leverage today’s hyperconnected crowd like never before. Here you’ll learn how to harness crowdsourcing solutions to massively increase the speed of your business, to design and use incentive competitions to find breakthrough solutions, to launch million-dollar crowdfunding campaigns

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, it’s to teach you to harness exponential platforms like Quirky, or to encourage you to create similar platforms yourself. Consider Candace Klein, a crowdsourcing expert and the very busy CEO of Bad Girl Ventures, a company that helps women start businesses. Every Saturday night, Klein gets together with a

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include exponential technologies like infinite computing, sensors and networks, 3-D printing, artificial intelligence, robotics, and synthetic biology and exponential organizational tools such as crowdfunding, crowdsourcing, incentive competitions, and the potency of a properly built community. These exponential advantages empower entrepreneurs like never before. Welcome to the age of exponentials. CHAPTER

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when Google paid $1 billion to acquire Waze, an Israeli-based company that generates maps and traffic information, not via electronic sensors, but instead via crowdsourced user reports—i.e., human sensors, generating maps by using GPS to track the movements of some 50 million users, then generating traffic-flow data

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backed by Watson is Modernizing Medicine. Back in 2011, Modernizing Medicine launched as an iPad-based, specialty-specific electronic medical records platform with a cool crowdsourced twist.38 For example, all dermatologists who sign up with Modernizing Medicine have their outcome data—that is, what was wrong with a patient and

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Usually, capital comes in stages as entrepreneurs find new ways to mitigate risk. Instead of one lump sum, money arrives in discrete waves: seed capital, crowdsourced capital, angel capital, super-angel capital, strategic partners, series A venture, series B venture, and sometimes even a public offering. More and more investment comes

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Wright Brothers, the Apollo 11 Mission, the Manhattan Project, and our Founding Fathers look limited in scope.”46 PART THREE THE BOLD CROWD * * * CHAPTER SEVEN Crowdsourcing Marketplace of the Rising Billion * * * It’s the fall of 2000. There are now more than 20 million websites on the Internet.1 The browser

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often undertaken by sole individuals. The crucial prerequisite is the use of the open call format and the large network of potential laborers.”5 As crowdsourcing gained steam, crowdfunding (covered in detail in the next chapter) was developing. While the idea dates back to the 1980s, it became a mainstream

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crowdfunding platforms have materialized, giving entrepreneurs access to what will soon exceed tens of billions of dollars in annual funding. As movements, both crowdfunding and crowdsourcing diversified quickly, with all sorts of commercial applications beginning to emerge. The graphic design hub 99designs, for example, allows users to submit a design need

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and an associated budget—say, a new logo for $299—and the crowd competes for the business. Gengo.com offers crowdsourced human translators, CastingWords does audio transcription, and Maven Research—aka the global knowledge marketplace—provides expertise in hundreds of thousands of disciplines. Big business has

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them for protein folding, and Zooniverse allows anyone to categorize galaxies, discover new planets and even hunt for alien life. So why does this whole crowdsourcing arena matter so much for exponential entrepreneurs? Consider what Larry Page’s dream of artificial intelligence might look like when it finally arrives. This would

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before. Global fixed-broadband and mobile Internet penetration (%) 2008–2017 Internet Penetration: The Rising Billions Source: http://www.pwc.com Before we launch into crowdsourcing in greater detail, it’s helpful to pull back a bit and see how these ideas work within the greater context of part three of

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reading the thriller, DeJulio decided there had to be a better way. That was about the time he bumped into Jack Hughes, founder of the crowdsourcing software-solutions company TopCoder, who helped him realize that the same distributed, crowd-powered approach that TopCoder employs in helping companies fulfill their software needs

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with many other microtasks (for example, reCAPTCHA), collectively solve much larger problems. This means that one of the most important questions to answer when approaching crowdsourcing is whether the work can be broken down into smaller, simpler units. If so, what is the simplest microtask that can be defined and distributed

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myriad of macrotask sites. For a detailed list of the latest sites with examples of how to use them, please see www.AbundanceHub.com. 2. Crowdsourced Creative/Operational Assets An asset is anything that provides value to you and your business—that is to say, applications, websites, videos, software, designs,

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algorithms, marketing materials, physical goods, machinery, and technical plans. To understand how to crowdsource assets, I’ve broken things into two different categories: creative and operational assets. Creative assets include a wide variety of design-based assets such as

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in weeks instead of months and at a cost that is usually about a tenth the industry average, and 99Designs (www.99designs.com), which provides crowdsourced graphic design (logos, apps, web pages, infographics, blogs, and more). I’ve used 99designs repeatedly and have found that contests usually yield between 25

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server implementation, technical designs, models, and frameworks that organize deal flow and customer acquisition strategies, and so on. A number of companies allow you to crowdsource the creation of operational assets. In fact, doing so is one of the keys to becoming a data-driven, exponential organization. A great example of

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small denomination to incentivize the crowd (i.e., anyone who has the Gigwalk app) to perform a simple task at a particular place and time. “Crowdsourced platforms are being quickly adopted in the retail and consumer products industry,” says Marcus Shingles, a principal with Deloitte Consulting. Retailers and consumer products manufacturers

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Data will create an insights ‘arms race,’ where competitive advantage will be dominated by individuals and organizations that capitalize on these emerging technologies.”20 3. Crowdsourced Testing and Discovery Insights Insights are invaluable to your business. They can shape the goals and operations of the entire company, dramatically improve and optimize

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performance, and provide you with counterintuitive ideas or hidden data for a strategic advantage over competitors. When it comes to crowdsourcing insights, there are two main variants: testing and discovery. Testing-based insights often come from examining existing assumptions and current best practices. These include surveys

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functionality, and quicker time to market. Creatives are also getting in on the insight game. Take ReverbNation (www.reverbnation.com), a music distribution, publishing, and crowdsourced testing platform. Say you’re an aspiring musician. You’ve produced a few songs, but before spending money on paid advertising or management, you want

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releases, video animations, project updates, cartoons, emails, T-shirt designs, giveaways, flyers, stickers, and pamphlets. Again, these are all elements that can (and should) be crowdsourced from the sites discussed in the previous chapter, but your design lead will coordinate the content. As I reflect on the ARKYD campaign, two things

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Harvard. It was there he heard a presentation on Threadless, the previously mentioned open-source T-shirt company. He was stunned by the power of crowdsourcing. Certainly, building cars was far more difficult than designing T-shirts, but Rogers also knew that the talent he needed was readily available. In

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outdoor cafés and pop-up shops—all without governmental approval. Not only does this help them build their community, the point they make with these crowdsourced, temporary urban improvements usually leads to changes in legislature and long-term urban renewal.27 6. Host Events. This has been discussed before, but

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As we shall see, this mechanism pulls together most of the knowledge from the previous nine chapters: the use of exponential technologies, thinking at scale, crowdsourcing genius, providing opportunities for crowdfunding, and stimulating the creation of DIY communities. Moreover, incentive competitions are brutally objective. They don’t care where you went

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only now that these competitions are beginning to reach their prime. In our hyperconnected world, with the maturation of social media and the explosion of crowdsourcing capabilities, our ability to design and utilize these prizes to drive breakthroughs has never been stronger.”4 The success of these competitions stems from a

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Fool” by the press, won the competition. Had Orteig been investing in teams, Lindbergh would have been the least likely to get an endorsement. 3. Crowdsourcing genius. Prizes attract new players—outsiders, mavericks, and other innovators unlikely to work within a traditional research setting. A properly structured incentive prize will draw

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of leaders is extremely rare and often underappreciated at first glance. Perhaps such leadership will materialize from experimentation in virtual worlds, or emerge from some crowdsourced competition, or be yielded over to a benevolent artificial intelligence. Each is, for the first time ever, a real possibility. Perhaps such leadership will

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goes to Peter’s team at PHD Ventures (Marissa Brassfield, Cody Rapp, Maxx Bricklin, and Kelley Lujan) for their incredible support in doing research, crowdsourcing content, and providing twenty-four by seven input. And recognition to Connie Fox for the herculean task of coordinating Peter’s schedule and life. On

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Jason Calacanis, “#googlewinseverything (part 1),” Launch, October 30, 2013, http://blog.launch.co/blog/googlewinseverything-part-1.html. PART THREE: THE BOLD CROWD Chapter Seven: Crowdsourcing: Marketplace of the Rising Billion 1 Netcraft Web Server Survey, Netcraft, Accessed June 2014, http://news.netcraft.com/archives/category/web-server-survey/. 2 AI

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Businessweek, November 26, 2006, http://www.businessweek.com/the_thread/techbeat/archives/2006/11/second_lifes_fi.html. 5 Jeff Howe, “Crowdsourcing: A Definition,” Crowdsourcing, http://crowdsourcing.typepad.com/cs/2006/06/crowdsourcing_a.html. 6 “Statistics,” Kiva, http://www.kiva.org/about/stats. 7 Rob Walker, “The Trivialities and Transcendence of Kickstarter,”

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of the TopCoder rating system, see http://community.topcoder.com/longcontest/?module=Static&d1=support&d2=ratings. 20 Carolyn Johnson, “Thorny research problems, solved by crowdsourcing,” Boston Globe, February 11, 2013, http://www.bostonglobe.com/business/2013/02/11crowdsourcing-innovation-harvard-study-suggests-prizes-can-spur-scientific-problem-solving/JxDkOkuIKboRjWAoJpM0OK/story

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additive manufacturing, 30, 31, 33, 41 AdhereTech, 47 AdSense, 139 Advanced Research Projects Agency Network (ARPANET), 27 advertising, 241, 242 in crowdfunding campaigns, 212–13 crowdsourcing platforms for, 151, 152–54, 158 advocates, in crowdfunding campaigns, 200–201, 205 AdWords, 241 aerospace industry, 112, 117, 133 skunk methodology used in, 71

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, 232, 236–37 reputation economics in building of, 217–19, 230, 232, 236–37 self-organizing structures of, 217, 237 see also crowdfunding, crowdfunding campaigns; crowdsourcing Compaq, 117 computers, x, 7, 26, 72, 76, 135 see also artificial intelligence (AI); supercomputers Comsat, 102 constraints, power of, 248–49, 259 contract

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(CRAMS), 65 Coolest Cooler campaign, 210–13 corporate sponsorship, 246, 246 Cotichini, Christian, 257 Cotteleer, Mark, 33 Coulson, Simon, 150 Craigslist, 11, 257 creative assets, crowdsourcing of, 158 Creative Commons license, 224 Credit Suisse, 56 Cretaceous Period, ix CrossFit, 229 Crowdfunder, 172, 173, 175 crowdfunding, crowdfunding campaigns, xiii, 22, 103, 144

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–21, 227, 228–29 in software development, 144, 159, 161, 226–27, 236 of testing and discovery insights, 160–62 traffic data garnered by, 47 Crowdsourcing.org, 162 Csikszentmihalyi, Mihaly, 89, 92 Cube, 32 CubeSats, 36–37 Culver, Irv, 72 Cummins Engine, 222 Curiosity rover, 99 customer-centric business, 84,

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203, 266, 272 building online communities for, see communities, online choosing technology for development by, see technology, exponential crowd tools of, see crowdfunding, crowdfunding campaigns; crowdsourcing; incentive competitions incentive prizes as tools of, see incentive competitions infinite computing and, 50–52 networks and sensors trend and, 43, 47–48 passion as

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vs., 7, 9 Six Ds of, see Six Ds of Exponentials exponential organizations, 15–17, 18–21, 22 crowd tools of, see crowdfunding, crowdfunding campaigns; crowdsourcing; incentive competitions definition of, 15 linear vs., 15, 17, 18, 19, 20, 21 structure of, 21 see also entrepreneurs, exponential; specific exponential entrepreneurs and

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data mining Inman, Matthew, 178, 192, 193, 200 innovation, 8, 30, 56, 137, 256 companies resistant to, xi, 9–10, 12, 15, 23, 76 crowdsourcing and, see crowdsourcing as disruptive technology, 9–10 feedback loops in fostering of, 28, 77, 83, 84, 86, 87, 90–91, 92, 120, 176 Google’s eight

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144, 153, 154, 163, 177, 207, 208, 209, 212, 216, 217, 228 building communities on, see communities, online crowd tools on, see crowdfunding, crowdfunding campaigns; crowdsourcing development of, 27 explosion of connectivity to, 42, 46, 46, 146, 147, 245 mainstreaming of, 27, 32, 33 reputation economics and, 217–19, 230, 232

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, 58, 66, 85, 137, 167, 216 see also artificial intelligence (AI) Macintosh computer, 72 McKinsey & Company, 245 McLucas, John, 102 Macondo Prospect, 250 macrotasks, crowdsourcing of, 156, 157–58 Made in Space, 36–37 Made to Stick: Why Some Ideas Survive and Others Die (Heath and Heath), 248 MakerBot printers

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–58 Michigan, University of, 135, 136 microfactories, 224, 225 microlending, 172 microprocessors, 49, 49 Microsoft, 47, 50, 99 Microsoft Windows, 27 Microsoft Word, 11 microtasks, crowdsourcing of, 156–57, 166 Mightybell, 217, 233 Migicovsky, Eric, 175–78, 186, 191, 193, 198, 199, 200, 206, 209 Millington, Richard, 233 Mims, Christopher,

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room

by David Weinberger  · 14 Jul 2011  · 369pp  · 80,355 words

out, or to be a knowledge resource about a topic far too big for any individual expert. The simplest forms are what Jeff Howe called “crowdsourcing” in a 2006 article in Wired.13 He intended it as a play on “outsourcing,” and his examples mainly were of “plugged-in enthusiasts” who

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which the mass of the Net lets us do things for little or no cost that otherwise would have been prohibitively expensive. The examples of crowdsourcing are familiar at this point. When Members of Parliament were found to be routinely taking frivolous deductions, the British newspaper The Guardian set up a

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you need only a tiny fraction of people to volunteer. Sometimes the fact that the Internet covers so much physical ground is enough to create crowdsourced expertise. For example, in 2009, the Defense Advanced Research Projects Agency (DARPA)—the R&D branch of the US Department of Defense—decided to celebrate

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.16 That objection misses the point: Without the network, the offer of money would have gone nowhere. Indeed, some of the most powerful ways to crowdsource expertise involve paying people. Amazon’s Mechanical Turk, launched in 2005, enables vast numbers of people to work on small, distributed tasks for a small

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the Internet not only made it feasible to assemble experts from around the world but also made it possible for those experts to collaborate. While crowdsourcing can aggregate information—people in every neighborhood of New York City can report on what their local groceries are charging for diapers—networked experts who

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oil up from the Exxon Valdez—via contests. But amateurs are contributing in yet more structured ways. For example: • Volunteers at Galaxy Zoo, a science crowdsourcing Web site, have created what it claims is “the world’s largest database of galaxy shapes.”24 Beginning in July 2007 it posted images of

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objects from space, these are important discoveries. Wired.com pronounced, “The age of armchair crater hunting has arrived.”28 Not all amateur science projects are crowdsourced. Rather than handing data out to humans to scan, Einstein@Home parcels data out to personal computers volunteered from all across the Net; the computers

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human brain.30 A study of Foldit players found that humans outperformed the best of the computer algorithms in several types of problem. Amateurs can crowdsource the processing of large volumes of data, they can donate computer time, they can use peculiar capabilities of the human brain, but they can also

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as they could, recording the results in an open notebook that contained no heroic narrative, just daily results. He then started another open notebook that crowdsources the nearly endless question of which chemicals are soluble in which other chemicals. The result is a mammoth spreadsheet of interactions, most of which are

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, Smart Mobs: The Next Social Revolution (Basic Books, 2003). 12 James Surowiecki, The Wisdom of Crowds (Random House, 2004). 13 Jeff Howe, “The Rise of Crowdsourcing,” Wired 14, no. 6 (June 2006), http://www.wired.com/wired/archive/14.06/crowds.html. See also Howe’s

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Crowdsourcing (Crown Business, 2008). 14 “Darpa Network Challenge: We Have a Winner,” https://network-challenge.darpa.mil/Default.aspx. 15 “How It Works” (MIT), 2009, http://

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_id(entry_subtopic_type)=8&type_id(entry_subtopic_type)=4. (The ORR is part of the National Oceanic and Atmospheric Administration.) 21 Kermit Pattison, “Crowdsourcing Innovation: Q&A with Dwayne Spradlin of InnoCentive,” FastCompany, December 15, 2008, http://www.fastcompany.com/blog/kermit-pattison/fast-talk/millions-eyes-prize-qa

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figure) Ackoff, Russell African Americans, homophily and Aggressor-prey simulation AIDS Albert, Jacob Algorithmic tools: information overload ALS (amyotrophic lateral sclerosis) Alzheimer’s disease Amazon crowdsourcing information filtering American Association for the Advancement of Science (AAAS) American Association for the Promotion of Social Science The American Magazine AmericaSpeakingOut.com Analogies Ancient

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persons (BLPs) Biotechnology and Bioprocess Engineering journal Birkerts, Sven Birthers Blanchard, Heather Blane, Gilbert Blind shear ram Blogs information overload linking within PressThink.org scientific crowdsourcing Bonabeau, Eric Books and book publishing book-shaped thought information filtering information overload limitations of linked knowledge long-form thinking making the past present narrow

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Boston Globe Boundary-free information boyd, danah Boyle, Alan Bradley, Jean-Claude Brahe, Tycho Brand, Stewart Brilliant, Larry Bringsjord, Selmer Britain child labor laws contests crowdsourcing open government statistical support for Bentham’s ideas British Petroleum (BP) oil spill Brookings Institution Brown, Michael Burgess, Anthony Business sector consulting firms Primary Insight

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Complexity Contests Cooley, Michael Cooper, Ashley Corruption of knowledge Creationism Creative Commons. See Science at Creative Commons Crick, Francis Crisis of knowledge CrisisCommons.org Crowds Crowdsourcing information amateur scientists British Parliamentarians’ use of expertise and leadership effectiveness Netflix contest open-notebook science Culture, information overload and Cybercascades Cyberchiefs: Autonomy and Authority

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, Charles amateur scientists’ contributions barnacle studies Hunch.com and insight and leap of thought long-form thinking science and publishing Data accuracy of published data crowdsourcing scientific and medical information data commons evaluating metadata information and overaccumulation of scientific data scientific knowledge Data.gov Data-information-knowledge-wisdom (DIKW) hierarchy Davis

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Waldo Enders, John Engadget Environmental niche modeling Environmental Protection Agency (EPA) Eureqa computer program Evolutionary science Experiments, scientific method and Expert Labs Expertise Challenger investigation crowdsourcing diversity in networking knowledge networks outperforming individuals professionalization of scaling knowledge and networking sub-networks Extremism: group polarization Exxon Valdez oil disaster Facebook Fact-based

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) Rogers, William Rorty, Richard Rosen, Jay Roskam, Peter Rushkoff, Douglas Russia: Dogger Bank Incident Salk, Jonas Sanger, Larry Schmidt, Michael School shootings Science amateurs in crowdsourcing expertise failures in goals of hyperlinked inflation of scientific studies interdisciplinary approaches media relations Net-based inquiry open filtering journal articles open-notebook overgeneration of

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thought Simulation of physical interactions Slashdot.com Sloan Digital Sky Survey Smart mobs “Smarter planet” initiative Smith, Arfon Smith, Richard Soccer Social conformity Social networks crowdsourcing expertise Middle East revolutions pooling expertise scaling social filtering Social policy: social role of facts Social reform Dickens’s antipathy to fact-based knowledge global

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It)

by Salim Ismail and Yuri van Geest  · 17 Oct 2014  · 292pp  · 85,151 words

Organization. Salim’s vision of the Exponential Organization is a powerful one. Potent forces are emerging in the world—exponential technologies, the DIY innovator, crowdfunding, crowdsourcing, and the rising billion—that will give us the power to solve many of the world’s grandest challenges and the potential to meet the

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was founded around the same time. Instead of making a massive capital investment in in-road sensor hardware, the founders of Waze chose instead to crowdsource location information by leveraging the GPS sensors on its users’ phones—the new world of smartphones just announced at Apple by Steve Jobs—to capture

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ecosystems are clear testaments to this trend, with the Apple and Android platforms each hosting more than 1.2 million applications programs, most of them crowdsourced from customers. Nowhere is this staggering pace of change more apparent than with the consumer Internet. Many products are now launched early—unfinished and in

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high NPS, then your sales function is free. If you are using peer-to-peer models, your service costs can also essentially be free. Using crowdsourcing and community ideation (such as Quirky or Gustin), your R&D and product development costs can also approach zero. And it doesn’t stop there

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answer creates its own set of questions, the most germane of which right now is: How can ExOs leverage the benefits of SCALE elements like crowdsourcing, community management, gamification, incentive competitions, data science, leveraged assets and staff on demand to become platforms? We believe the answer is that they will wire

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was concerned, which resulted in almost no contribution to the platform [Experimentation]. Undaunted, Jones and Rogers took another shot at attracting community, this time via crowdsourcing. They were successful this time around, and in March 2008, Local Motors debuted as the first community to completely

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crowdsource a car. (The company currently has eighty-three employees and three micro-factories for manufacturing.) The Local Motors staff then turned its attention to evangelizing,

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(incentive competitions), but for cars and other vehicles. Once the initial community was established, Rogers moved on to his next goal: to build the first crowdsourced automobile. In 2009, Local Motors achieved that goal with the production of the Rally Fighter, a car whose ultimate design was a culmination of 35

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the best time in the history of business to build a new enterprise. The confluence of breakthrough technologies, acceptance (and even celebration) of entrepreneurship, different crowdsourcing options, crowdfunding opportunities and legacy markets ripe for disruption—all create a compelling (and unprecedented) scenario for new company creation. Furthermore, traditional risk areas have

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possible; keep FTEs to a minimum. Community & Crowd: Validate idea in MTP communities. Get product feedback. Find co-founders, contractors and experts. Use crowdfunding and crowdsourcing to validate market demand and as a marketing technique. Algorithms: Identify data streams that can be automated and help with product development. Implement cloud-based

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, the studio’s focus is primarily on ideation and scaling with a much smaller core team, more staff on demand and a great deal of crowdsourcing. Revenues in 2014 will top three million euros—a sixtyfold increase over 2007. For an art studio, with physical products that are less scalable and

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, has two billion consumers worldwide consume one or more of its four hundred brands daily. In June 2013, Unilever announced a partnership with eYeka—a crowdsourcing platform that connects brands with 288,907 creative problem solvers from 164 countries. In total there have been 683 contests awarding 4.4 million in

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paper’s website so they could leverage content on the site [Algorithms]. Investigative reporting for the millions of WikiLeaks cables fully crowdsourced [Community & Crowd]. The Guardian has institutionalized the crowdsourcing of investigative reporting and has successfully used that approach on several occasions, including after obtaining public documents from Sarah Palin’s tenure

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this book and will now focus on its MTP, which is “Make Invention Accessible.” General Electric early on saw the huge potential of the new crowdsourced model of product development. It subsequently partnered with Quirky in 2012 on incentive competition [Engagement], whereby the Quirky community was tasked with dreaming up innovative

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spoil or run low, as the top product. Each subsequent phase of the Milkmaid’s production, including product design, name, tagline and even price, was crowdsourced as well [Crowd], resulting in a total of 2,530 contributions from the Quirky community for a single product. Although the Milkmaid was just a

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pricing to maximize pricing based on real-time demand (e.g., airline tickets). AIs will prove extremely valuable in this transition. Crowdsourced online marketplaces for marketing materials Using online marketplaces to crowdsource TV commercials (Tongal), logos and banners (99 designs), or any marketing expertise (Freelancer). PR & marketing will have to aim a

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an age in which HR will be critical in effectively managing not only core FTEs, but also the larger Staff on Demand (as well as crowdsourced inputs), which will now operate on a global scale. Managing the ExO attributes Interfaces and Staff on Demand will be key new requirements for the

Whiplash: How to Survive Our Faster Future

by Joi Ito and Jeff Howe  · 6 Dec 2016  · 254pp  · 76,064 words

aren’t the only areas of human endeavor undergoing a transition to new ways of generating discoveries or promoting innovation. Call it citizen science or crowdsourcing or open innovation, but what the rise of synthetic biology shows is that soon we’ll simply call it standard operating procedure. The triumph of

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reach.20 Capital in hand, our innovators-slash-entrepreneurs can easily extend their resources, and discover some they didn’t know they were missing, through crowdsourcing. Rather than hiring large teams of engineers, designers, and programmers, start-ups and individuals can tap into a global community of freelancers and volunteers who

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with dubious ideas for new products, but Experiment.com shows that the same system can be used to fund serious scientific research.17 Beyond crowdfunding, crowdsourcing also provides independent creators with affordable options for extending their resources. Rather than hiring large teams of engineers, designers, and programmers, start-ups and individuals

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underestimated. Indeed, before the Internet, it often seemed difficult to achieve. In June 2006, Jeff wrote an article for Wired magazine entitled “The Rise of Crowdsourcing.” 6 Drawing evidence from industries like stock photography and customer support, the article proposed that a radical new form of economic production had sprung from

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crowd,” Jeff wrote. “The labor isn’t always free, but it costs a lot less than paying traditional employees. It’s not outsourcing; it’s crowdsourcing.” The term, originally coined in a joking conversation between Jeff and his Wired editor Mark Robinson, was quickly adopted, initially by people in vocations like

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advertising and journalism in which crowdsourcing had taken root, and then by the public at large. (The word first appeared in the Oxford English Dictionary in 2013.)7 As a business

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practice crowdsourcing has become standard operating procedure in fields ranging from technology and media to urban planning, academia, and beyond. When it works—and contrary to the

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initial hype, it’s hardly a digital age panacea—crowdsourcing exhibits an almost magical efficacy. Institutions and companies like NASA, the LEGO Group, and Samsung have integrated public contributions into the core of how they

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are a collaborative effort. The theoretical underpinnings for this approach lie in the nascent discipline of complex systems; the potency of the pixie dust in crowdsourcing is largely a function of the diversity that naturally occurs in any large group of people. The sciences have long utilized various distributed knowledge networks

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and more of. A bigger circle benefits us all. PS: The Difference Difference Makes I spent much of 2007 and 2008 writing a book about crowdsourcing. I had no trouble identifying fascinating case studies; a burst of ambitious, if often ill-conceived, start-ups had sprung up in the years since

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Wired published my original article on the subject. But there were very few serious researchers studying the kinds of group behaviors that either made crowdsourcing click, or insured that it didn’t. Discovering Scott E. Page’s work on the mechanics of diversity represented a turning point—diversity was more

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is an assistant professor at Northeastern University and the coordinator of its Media Innovation program. A longtime contributing editor at Wired, he coined the term “crowdsourcing” in a 2006 article for that magazine. In 2008 he published a book with Random House that looked more deeply at the phenomenon of massive

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online collaboration. Called Crowdsourcing: How the Power of the Crowd Is Driving the Future of Business, it has been translated into ten languages. He was a Nieman Fellow at

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/sites/ryanmac/2014/08/06/backed-with-millions-startups-turn-to-crowdfunding-for-marketing/#6cfda89c56a3. 21 For a more extensive discussion of crowdsourcing, Jeff modestly recommends his first book, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business, (New York: Crown Business, 2009). 22 See, for example, Christina

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?page=me_tab. 5 An earlier version of this section, including the quotes from Zoran Popović and Adrien Treuille, appeared in Slate. Jeff Howe, “The Crowdsourcing of Talent,” Slate, February 27, 2012, http://www.slate.com/articles/technology/future_tense/2012/02/foldit

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, June 1, 2006, http://www.wired.com/2006/06/crowds/. 7 Todd Wasserman, “Oxford English Dictionary Adds ‘Crowdsourcing,’ ‘Big Data,’” Mashable, June 13, 2013, http://mashable.com/2013/06/13/dictionary-new-words-2013/. 8 “Longitude Found: John Harrison,” Royal Museums Greenwich, October

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

by Eric Siegel  · 19 Feb 2013  · 502pp  · 107,657 words

Recession—Why Microscopes Can’t Detect Asteroid Collisions After Math Chapter 5: The Ensemble Effect (ensembles) Casual Rocket Scientists Dark Horses Mindsourced: Wealth in Diversity Crowdsourcing Gone Wild Your Adversary Is Your Amigo United Nations Meta-Learning A Big Fish at the Big Finish Collective Intelligence The Wisdom of Crowds . . . of

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of innovation—I mean, this crouching, uncomfortable imposter. In the modern-day equivalent, human workers perform low-level tasks for the Amazon Mechanical Turk, a crowdsourcing website by Amazon.com that coordinates hundreds of thousands of workers to do “things that human beings can [still] do much more effectively than computers

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case study, mortgage prepayments. But predicting delinquent accounts with PA is also subject to these same limitations. Chapter 5 The Ensemble Effect Netflix, Crowdsourcing, and Supercharging Prediction To crowdsource predictive analytics—outsource it to the public at large—a company launches its strategy, data, and research discoveries into the public spotlight. How

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can this possibly help the company compete? What key innovation in predictive analytics has crowdsourcing helped develop? Must supercharging predictive precision involve overwhelming complexity, or is there an elegant solution? Is there wisdom in nonhuman crowds? Casual Rocket Scientists A

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by doing more for so much less. PA competitions do for data science what the X Prize did for rocket science. Mindsourced: Wealth in Diversity [Crowdsourcing is] a perfect meritocracy, where age, gender, race, education, and job history no longer matter; the quality of the work is all that counts. —Jeff

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Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business When pursuing a grand challenge, from where will key discoveries appear? If we

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that one cannot know, there’s only one place to look: everywhere. Contests tap the greatest resource, the general public. A common way to enact crowdsourcing, an open competition brings together scientists from far and wide to compete for the win and cooperate for the joy. With

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company outsources to the world. The $1 million Netflix Prize attracted a white-hot spotlight and built a new appreciation for the influence crowdsourcing has to rally an international wealth of bright minds. In total, 5,169 teams formed to compete in this contest, submitting 44,014 entries by

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the end of the event. PA crowdsourcing reaps the rewards brought by a diverse brainshare. Chris Volinsky, a member of a leading Netflix Prize team named BellKor from AT&T Research, put

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eventual winner). As he explains it, aspects of his work mapping the edges of glaciers from satellite photos could extend to mapping galaxies as well. Crowdsourcing Gone Wild Given the right set of conditions, the crowd will almost always outperform any number of employees. —Jeff Howe

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, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business The organizations I’ve worked with have mostly viewed the competition in business

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as a race that benefits from sharing, rather than a fight, where one’s gain can come only from another’s loss. The openness of crowdsourcing aligns with this philosophy. —Stein Kretsinger, Founding Executive of Advertising.com One small groundbreaking firm, Kaggle, has taken charge and leads the production of PA

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crowdsourcing. Kaggle has launched 53 PA competitions, including the essay-grading and dark matter ones mentioned above. Over 50,000 registered competitors are incentivized by prizes

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, have submitted over 144,000 attempts for the win.2 An enterprise turns research and development completely on its head in order to leverage PA crowdsourcing. Instead of protecting strategy, plans, data, and research discoveries as carefully guarded secrets, a company must launch them fully into the public spotlight. And, instead

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take part in the contest and join in on the fun (for fully public contests, as is the norm). Crowdsourcing must be the most ironic, fantastical way for a business to compete. Crowdsourcing forms a match made in heaven. Kaggle’s founder and CEO, Anthony Goldbloom (a Forbes “30 Under 30: Technology

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, the two über-teams madly submitted new entries, tweaking, retweaking, and submitting again, even into the final hours and minutes of this multiple-year contest. Crowdsourcing competitions cultivate a heated push for scientific innovation, engendering focus and drive sometimes compared to that attained during wartime. Time ran out. The countdown was

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the PA industry by storm. It’s often considered the most important predictive modeling advancement of this century’s first decade. While its success in crowdsourcing competitions has helped bolster its credibility, the craft of ensembling pervades beyond that arena, both in commercial application and in research advancement. But increasing complexity

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the prior chapter. 2Moving beyond PA to a broader range of science and business problems, InnoCentive is the analogue to Kaggle, with over 1,300 crowdsourcing challenges posted to date. The cover illustration of this book was developed by the winner of a “crystal ball” design contest the author hosted on

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game puzzle that anyone can learn to play, Foldit broke ground in protein folding to produce three discoveries that have been published in Nature. Noncompetitive crowdsourcing includes the advent of Wikipedia and open source software such as the Linux operating system and R, the most popular free software for analytics, which

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really hard does not necessarily mean you’re pushing in the right direction. From where will scientific epiphany emerge? Recall the key innovation that the crowdsourcing approach to grand challenges helped bring to light, ensemble models, introduced in the prior chapter. It’s just what the doctor ordered for IBM’s

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Customer Behaviour,” Predictive Analytics World London Conference, December 1, 2011, London, UK. www.predictiveanalyticsworld.com/london/2011/agenda.php#day1–16a. Crowdsourcing in general, beyond analytics projects: Jeff Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business (Three Rivers Press, 2008). Quote from Anthony Goldbloom about Kaggle

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’s crowdsourcing: Tanya Ha, “Lucrative Algorithms,” Catalyst Online, August 18, 2011. www.abc.net.au/catalyst/stories/3296837.htm. Regarding the shortage of analytics experts: James Manyika,

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.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation. More on Kaggle and crowdsourcing predictive analytics: Kaggle, “About Us: Our Team,” www.kaggle.com/about. Karthik Sethuraman, Kaggle, “Crowdsourcing Predictive Analytics: Why 25,000 Heads Are Better Than One,” Predictive Analytics World Chicago Conference, June 25, 2012

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/2012/03/28/bizarre-insights-from-big-data/. For other data mining competitions, see: KDnuggets: Analytics, Data Mining Competitions. www.kdnuggets.com/competitions/index.html. Crowdsourcing for Search and Data Mining (CSDM 2011): A workshop of the Fourth ACM International Conference on Web Search and Data Mining (WSDM 2011), Hong Kong

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, China, February 9, 2011. http://ir.ischool.utexas.edu/csdm2011/. CSDM 2011 Crowdsourcing for Search and Data Mining, Hong Kong, China. http://ir.ischool.utexas.edu/csdm2011/. CrowdANALYTIX. www.crowdanalytix.com/welcome. Netflix Prize, September 21, 2009. www

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About!” YouTube, May 8, 2008, uploaded by UWfoldit. www.youtube.com/watch?v=lGYJyur4FUA. For more crowdsourcing projects, see Wikipedia’s list of dozens: Wikipedia, “List of Crowdsourcing Projects.” http://en.wikipedia.org/wiki/List_of_crowdsourcing_projects. Ensemble modeling is often considered the most important predictive modeling advancement of this century’s

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an editor will make five months from the end date of the training dataset,” Competition, June 28, 2011. www.kaggle.com/c/wikichallenge. Karthik Sethuraman, “Crowdsourcing Predictive Analytics: Why 25,000 Heads Are Better Than One,” Predictive Analytics World Chicago Conference, June 25, 2012, Chicago, IL. www.predictiveanalyticsworld.com/chicago/2012

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for judicial decisions and murder, predicting PA application PA examples and insights prediction models for, pros and cons of recidivism CrowdANALYTIX crowdsourcing collective intelligence and Kaggle PA crowdsourcing contests noncompetitive crowdsourcing PA and Cruise, Tom customer need, predicting fault in customer retention cancellations and predicting with churn modeling with churn uplift modeling contacting

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quitting, predicting Energex (Australia) energy consumption, predicting Ensemble Effect, The Ensemble Experts ensemble models about CART decision trees and bagging collective intelligence in complexity in crowdsourcing and generalization paradox and IBM Watson question answering computer and IRS (tax fraud) meta-learning and Nature Conservancy (donations) Netflix (movie recommendations) Nokia-Siemens Networks

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Transportation Safety Board natural language processing (NLP) Nature Conservancy Nazarko, Edward Nerds on Wall Street (Leinweber) Netflix movie recommendations Netflix Prize about competition and winning crowdsourcing and PA for meta-learning and ensemble models in Netflix Prize PragmaticTheory team net lift modeling. See uplift modeling net response modeling. See uplift modeling

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Tables insert PA (predictive analytics) competitions and contests in astronomy and science for design and games for educational applications Facebook/IBM student performance contest Kaggle crowdsourcing contests Netflix Prize PA (predictive analytics) insights consumer behavior crime and law enforcement finance and insurance miscellaneous PA (predictive analytics) about choosing what to predict

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crime fighting and fraud detection crowdsourcing and defined for employees and staff in family and personal life fault detection for safety and efficiency in finance and accounting fraud detection in financial

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Webster, Eric Wei, L. J. Whiting, Rick Who Wants to Be a Millionaire? (TV show) Wiener, Norbert Wikipedia editor attrition predicting entries as data noncompetitive crowdsourcing in Wilde, Oscar Wilson, Earl Windows vs. Mac users Winn-Dixie Wired magazine Wisdom of Crowds, The (Surowiecki) WolframAlpha WordPress workplace injuries, predicting Wright, Andy

The Dictionary People: The Unsung Heroes Who Created the Oxford English Dictionary

by Sarah Ogilvie  · 17 Oct 2023

never be done alone by a small group of men in London or Oxford. The OED was the Wikipedia of the nineteenth century – a huge crowdsourcing project in which, over seventy years between 1858 and 1928, members of the public were invited to read the books that they had to hand

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of Bath, who sent in 13,259 slips. The underlinings and markings were made by Dr Murray. In the first twenty years, this system of crowdsourcing enlisted the help of several hundred helpers. It expanded considerably under James Murray, who sent out a global appeal for people to read their local

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Surgeon of Crowthorne (1998). Through these sources, historians have thought that there were hundreds of contributors, but have not known who they all were. Today, crowdsourcing happens at extraordinary speed, scale, and scope thanks to the internet. In the mid-nineteenth century, the launch of ‘uniform penny post’ and the birth

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-average number of ‘lunatics’ contributing detailed and rigorous work from mental hospitals; and of families reading together by gaslight and sending in quotations. This extraordinary crowdsourced project was powered by faithful and loyal volunteers who took up the invitation to read their favourite books and describe their local words not just

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? The OED editors were able to learn from the lexicographic successes and mistakes of their European counterparts, not least the Germans who had already pioneered crowdsourcing and experienced the difficulties of coordinating volunteers of unreliable ability and indifferent adherence to deadlines. By the time the OED project commenced, Europe already had

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practised the application of historical principles; they pioneered the descriptive method of defining and tracing a word’s meaning across time; and they forged the crowdsourcing techniques and lexicographic policies and practices adopted by the OED editors. Given how advanced Europe was in the philological world, it probably comes as no

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Of Law Terms, and was twice thanked in the prefaces for help with legal terminology in 1899 and 1903. It is a hazard of all crowdsourced projects, including the OED, that a small proportion of contributors will do the bulk of the work, and a large proportion will comprise a ‘long

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to the Dictionary project all these wrongs were exactly right. Their hunger to be part of a big prestigious project meant that this was a crowdsourced project that worked. There were two volunteers among the Dictionary People who personified the range and value of the outsider. First among them was Joseph

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icicle, and zwodder, a Somerset term for feeling drowsy. Wright’s dialect dictionary followed the same structure as the OED and it was also a crowdsourced project with many of the same volunteers, especially women who lived in rural areas of England and sent in their local words – Miss Eleanor Lloyd

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’s Mrs Mary Pringle. It was so popular, he gave up his day job and devoted himself entirely to coordinating the British Rainfall Organisation, a crowdsourced project which, like the OED, was definitely a full-time job. Mary was not the only person who collected both rain and words. Other Dictionary

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of mouth. Even though Murray and Symons had distributed leaflets and had advertised their projects in newspapers and journals, most people who joined in the crowdsourced projects did so through the recommendation of another volunteer. In Mary’s case, others in her village also volunteered in one or other of the

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can’t have been too shut off from the world because, during the years that Leslie Stephen contributed to the OED, he started his own crowdsourced project, the Dictionary of National Biography (DNB). Just as Murray’s Dictionary traced the lives of thousands of words, Stephen’s dictionary traced the lives

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words, though he was that, with a grand total of 4,690 slips for the Dictionary; he was also a collector of plants for another crowdsourced project, run by the Botanical Society of London, to catalogue and map the indigenous wild flowers of Britain. The Botanical Society had been founded in

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1836 and from its beginnings ‘welcomed professionals and amateurs’. Like the Dictionary, the Society had a system of cards or slips for its crowdsourced project. The botanist noted on the card the name of the plant, its location, their own name and the date of the plant sighting. Over

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Data Action: Using Data for Public Good

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Exponential: How Accelerating Technology Is Leaving Us Behind and What to Do About It

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Breaking News: The Remaking of Journalism and Why It Matters Now

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The Internet of Us: Knowing More and Understanding Less in the Age of Big Data

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Free Speech: Ten Principles for a Connected World

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Super Thinking: The Big Book of Mental Models

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The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future

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Groundswell: Winning in a World Transformed by Social Technologies

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Designing Social Interfaces

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The Content Trap: A Strategist's Guide to Digital Change

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The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine

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WTF?: What's the Future and Why It's Up to Us

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The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives

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The Open Organization: Igniting Passion and Performance

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Just Keep Buying: Proven Ways to Save Money and Build Your Wealth

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Terms of Service: Social Media and the Price of Constant Connection

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The End of Absence: Reclaiming What We've Lost in a World of Constant Connection

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Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity

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Spies, Lies, and Algorithms: The History and Future of American Intelligence

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The End of Big: How the Internet Makes David the New Goliath

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Gigged: The End of the Job and the Future of Work

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Going Dark: The Secret Social Lives of Extremists

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Bulletproof Problem Solving

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Tomorrowland: Our Journey From Science Fiction to Science Fact

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Beautiful Data: The Stories Behind Elegant Data Solutions

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Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You

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Data Wrangling With Python: Tips and Tools to Make Your Life Easier

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Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance

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Future Perfect: The Case for Progress in a Networked Age

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Speaking Code: Coding as Aesthetic and Political Expression

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The Launch Pad: Inside Y Combinator, Silicon Valley's Most Exclusive School for Startups

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Present Shock: When Everything Happens Now

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Artificial Intelligence: A Modern Approach

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New Power: How Power Works in Our Hyperconnected World--And How to Make It Work for You

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The People's Platform: Taking Back Power and Culture in the Digital Age

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Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy

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Shadow Work: The Unpaid, Unseen Jobs That Fill Your Day

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Uberland: How Algorithms Are Rewriting the Rules of Work

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Cataloging the World: Paul Otlet and the Birth of the Information Age

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Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations

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The Purpose Economy: How Your Desire for Impact, Personal Growth and Community Is Changing the World

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Drugs 2.0: The Web Revolution That's Changing How the World Gets High

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Blockchain: Blueprint for a New Economy

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Radical Markets: Uprooting Capitalism and Democracy for a Just Society

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The Ethical Algorithm: The Science of Socially Aware Algorithm Design

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Artificial Unintelligence: How Computers Misunderstand the World

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Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots

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Masters of Management: How the Business Gurus and Their Ideas Have Changed the World—for Better and for Worse

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The History and Uncertain Future of Handwriting

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Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire

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China's Disruptors: How Alibaba, Xiaomi, Tencent, and Other Companies Are Changing the Rules of Business

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Indelible City: Dispossession and Defiance in Hong Kong

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What Algorithms Want: Imagination in the Age of Computing

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Found in Translation: How Language Shapes Our Lives and Transforms the World

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The Gig Economy: A Critical Introduction

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Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy

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Makers and Takers: The Rise of Finance and the Fall of American Business

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The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity

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Give People Money

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Human Compatible: Artificial Intelligence and the Problem of Control

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Investing Amid Low Expected Returns: Making the Most When Markets Offer the Least

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The Soil Will Save Us

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Rationality: What It Is, Why It Seems Scarce, Why It Matters

by Steven Pinker  · 14 Oct 2021  · 533pp  · 125,495 words

The Authoritarian Moment: How the Left Weaponized America's Institutions Against Dissent

by Ben Shapiro  · 26 Jul 2021  · 309pp  · 81,243 words

Long Game: How Long-Term Thinker Shorthb

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System Error: Where Big Tech Went Wrong and How We Can Reboot

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Cooking for Geeks

by Jeff Potter  · 2 Aug 2010  · 728pp  · 182,850 words

Delivering Happiness: A Path to Profits, Passion, and Purpose

by Tony Hsieh  · 6 Jun 2010  · 222pp  · 75,778 words

The Thank You Economy

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Android Cookbook

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Liars and Outliers: How Security Holds Society Together

by Bruce Schneier  · 14 Feb 2012  · 503pp  · 131,064 words

Kindle Fire: The Missing Manual

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97 Things Every Programmer Should Know

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The Idealist: Aaron Swartz and the Rise of Free Culture on the Internet

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New York 2140

by Kim Stanley Robinson  · 14 Mar 2017  · 693pp  · 204,042 words

The End of Ownership: Personal Property in the Digital Economy

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Nomadland: Surviving America in the Twenty-First Century

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The Future of War

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World Without Mind: The Existential Threat of Big Tech

by Franklin Foer  · 31 Aug 2017  · 281pp  · 71,242 words

Confessions of a Crypto Millionaire: My Unlikely Escape From Corporate America

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The Enlightened Capitalists

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Rules for Revolutionaries: How Big Organizing Can Change Everything

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The Power of Moments: Why Certain Experiences Have Extraordinary Impact

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This Is Service Design Doing: Applying Service Design Thinking in the Real World: A Practitioners' Handbook

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The Ones We've Been Waiting For: How a New Generation of Leaders Will Transform America

by Charlotte Alter  · 18 Feb 2020  · 504pp  · 129,087 words

Hustle and Gig: Struggling and Surviving in the Sharing Economy

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A Bit of a Stretch: The Diaries of a Prisoner

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Demystifying Smart Cities

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Snowden's Box: Trust in the Age of Surveillance

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Dawn of the New Everything: Encounters With Reality and Virtual Reality

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Enlightenment Now: The Case for Reason, Science, Humanism, and Progress

by Steven Pinker  · 13 Feb 2018  · 1,034pp  · 241,773 words

Surveillance Valley: The Rise of the Military-Digital Complex

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Raw Data Is an Oxymoron

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Editing Humanity: The CRISPR Revolution and the New Era of Genome Editing

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Heads I Win, Tails I Win

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The Revolution That Wasn't: GameStop, Reddit, and the Fleecing of Small Investors

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NeuroTribes: The Legacy of Autism and the Future of Neurodiversity

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Beyond: Our Future in Space

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Growth Hacking Techniques, Disruptive Technology - How 40 Companies Made It BIG – Online Growth Hacker Marketing Strategy

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How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy

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The Information: A History, a Theory, a Flood

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Invisible Women

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Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies

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Humble Pi: A Comedy of Maths Errors

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Sustainable Minimalism: Embrace Zero Waste, Build Sustainability Habits That Last, and Become a Minimalist Without Sacrificing the Planet (Green Housecleaning, Zero Waste Living)

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Calling Bullshit: The Art of Scepticism in a Data-Driven World

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Catch and Kill: Lies, Spies, and a Conspiracy to Protect Predators

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Capital Allocators: How the World’s Elite Money Managers Lead and Invest

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The Smart Wife: Why Siri, Alexa, and Other Smart Home Devices Need a Feminist Reboot

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Private Equity: A Memoir

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The Passenger

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Filterworld: How Algorithms Flattened Culture

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The Bad-Ass Librarians of Timbuktu: And Their Race to Save the World's Most Precious Manuscripts

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Quiet: The Power of Introverts in a World That Can't Stop Talking

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Dual Transformation: How to Reposition Today's Business While Creating the Future

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Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World

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Hello World: Being Human in the Age of Algorithms

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Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage

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The Glorious Heresies

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Machine Translation

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The Buddha and the Badass: The Secret Spiritual Art of Succeeding at Work

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Zero to Sold: How to Start, Run, and Sell a Bootstrapped Business

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Blood, Sweat, and Pixels: The Triumphant, Turbulent Stories Behind How Video Games Are Made

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Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth

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The Stolen Year

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Freezing Order: A True Story of Money Laundering, Murder, and Surviving Vladimir Putin's Wrath

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Raising Lazarus: Hope, Justice, and the Future of America’s Overdose Crisis

by Beth Macy  · 15 Aug 2022  · 389pp  · 111,372 words

The Awoken: A Novel

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Drunk on All Your Strange New Words

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Spike: The Virus vs The People - The Inside Story

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Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency

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The Future Is Analog: How to Create a More Human World

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Limitless: The Federal Reserve Takes on a New Age of Crisis

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The Chaos Machine: The Inside Story of How Social Media Rewired Our Minds and Our World

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Like, Comment, Subscribe: Inside YouTube's Chaotic Rise to World Domination

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The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma

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Working in Public: The Making and Maintenance of Open Source Software

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Reaganland: America's Right Turn 1976-1980

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The Infinite Machine: How an Army of Crypto-Hackers Is Building the Next Internet With Ethereum

by Camila Russo  · 13 Jul 2020  · 349pp  · 102,827 words

Architects of Intelligence

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The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity

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The Deep Learning Revolution (The MIT Press)

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Reset: How to Restart Your Life and Get F.U. Money: The Unconventional Early Retirement Plan for Midlife Careerists Who Want to Be Happy

by David Sawyer  · 17 Aug 2018  · 572pp  · 94,002 words

Building the Cycling City: The Dutch Blueprint for Urban Vitality

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Driverless: Intelligent Cars and the Road Ahead

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I'm Judging You: The Do-Better Manual

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Mindwise: Why We Misunderstand What Others Think, Believe, Feel, and Want

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Messy: The Power of Disorder to Transform Our Lives

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The Bitcoin Guidebook: How to Obtain, Invest, and Spend the World's First Decentralized Cryptocurrency

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Who Needs the Fed?: What Taylor Swift, Uber, and Robots Tell Us About Money, Credit, and Why We Should Abolish America's Central Bank

by John Tamny  · 30 Apr 2016  · 268pp  · 74,724 words

Wonderland: How Play Made the Modern World

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Dragnet Nation: A Quest for Privacy, Security, and Freedom in a World of Relentless Surveillance

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Fabricated: The New World of 3D Printing

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Digital Gold: Bitcoin and the Inside Story of the Misfits and Millionaires Trying to Reinvent Money

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Digital Wars: Apple, Google, Microsoft and the Battle for the Internet

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Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else

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Stuffocation

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Reamde

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Work Optional: Retire Early the Non-Penny-Pinching Way

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Trick Mirror: Reflections on Self-Delusion

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That Will Never Work: The Birth of Netflix and the Amazing Life of an Idea

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The Twittering Machine

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Reinventing Organizations: A Guide to Creating Organizations Inspired by the Next Stage of Human Consciousness

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Pax Technica: How the Internet of Things May Set Us Free or Lock Us Up

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Peak Car: The Future of Travel

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The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

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The Pentagon's Brain: An Uncensored History of DARPA, America's Top-Secret Military Research Agency

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Inventing the Future: Postcapitalism and a World Without Work

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How We Got to Now: Six Innovations That Made the Modern World

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The Dark Net

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Nexus

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The Despot's Accomplice: How the West Is Aiding and Abetting the Decline of Democracy

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Alpha Trader

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Rebel Ideas: The Power of Diverse Thinking

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Wordslut: A Feminist Guide to Taking Back the English Language

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Reset

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Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy

by Jonathan Taplin  · 17 Apr 2017  · 222pp  · 70,132 words

Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success

by Sean Ellis and Morgan Brown  · 24 Apr 2017  · 344pp  · 96,020 words

PostGIS in Action, 2nd Edition

by Regina O. Obe and Leo S. Hsu  · 2 May 2015

Where Good Ideas Come from: The Natural History of Innovation

by Steven Johnson  · 5 Oct 2010  · 298pp  · 81,200 words

Mining the Social Web: Finding Needles in the Social Haystack

by Matthew A. Russell  · 15 Jan 2011  · 541pp  · 109,698 words

The Art of Community: Building the New Age of Participation

by Jono Bacon  · 1 Aug 2009  · 394pp  · 110,352 words

Countdown to Zero Day: Stuxnet and the Launch of the World's First Digital Weapon

by Kim Zetter  · 11 Nov 2014  · 492pp  · 153,565 words

The End of Traffic and the Future of Transport: Second Edition

by David Levinson and Kevin Krizek  · 17 Aug 2015  · 257pp  · 64,285 words

City 2.0: The Habitat of the Future and How to Get There

by Ted Books  · 20 Feb 2013  · 83pp  · 23,805 words

Leading From the Emerging Future: From Ego-System to Eco-System Economies

by Otto Scharmer and Katrin Kaufer  · 14 Apr 2013  · 351pp  · 93,982 words

Protest and Power: The Battle for the Labour Party

by David Kogan  · 17 Apr 2019  · 458pp  · 136,405 words

Whiteshift: Populism, Immigration and the Future of White Majorities

by Eric Kaufmann  · 24 Oct 2018  · 691pp  · 203,236 words

The Creativity Code: How AI Is Learning to Write, Paint and Think

by Marcus Du Sautoy  · 7 Mar 2019  · 337pp  · 103,522 words

Hands-On Machine Learning With Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

by Aurelien Geron  · 14 Aug 2019

The Art of Invisibility: The World's Most Famous Hacker Teaches You How to Be Safe in the Age of Big Brother and Big Data

by Kevin Mitnick, Mikko Hypponen and Robert Vamosi  · 14 Feb 2017  · 305pp  · 93,091 words

Brave New Work: Are You Ready to Reinvent Your Organization?

by Aaron Dignan  · 1 Feb 2019  · 309pp  · 81,975 words

The Metric Society: On the Quantification of the Social

by Steffen Mau  · 12 Jun 2017  · 254pp  · 69,276 words

Blueprint: The Evolutionary Origins of a Good Society

by Nicholas A. Christakis  · 26 Mar 2019

Radicalized

by Cory Doctorow  · 19 Mar 2019  · 444pp  · 84,486 words

Rockonomics: A Backstage Tour of What the Music Industry Can Teach Us About Economics and Life

by Alan B. Krueger  · 3 Jun 2019