crowdsourcing

Data Action: Using Data for Public Good

by Sarah Williams  · 14 Sep 2020

innovations in digital technology are turning everything from mobile phones to dog collars into data collection devices. Often referred to as participatory sensing projects, or crowdsourcing,1 these citizen-based efforts in data collection fill gaps in knowledge by equipping people with the ability to collect raw data that was previously

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doing and where they are doing it, and if we can tap into that community we can use it to understand new social-spatial phenomenon. Crowdsourcing a Global Data Set A well-known example of VGI (or community mapping) is Open-StreetMap. By allowing participants anywhere to upload GPS traces, OpenStreetMap

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: S. Ahmed et al. 2015. Cooking Up a Storm: Community-Led Mapping and Advocacy with Food Vendors in Nairobi's Informal Settlements. IIED Working Paper. Crowdsourced Data: Why Governments Need It We expect governments to have the data they need to make informed decisions—whether or not they steward it well

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—but that's not always the case. Crowdsourcing techniques can help governments to generate that data. An exemplary project of this sort is Safecast. It grew out of a desire to map radiation

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DIY kit from the KitHub website.44 Rather than going to test the sites themselves, the Safecast team decided to employ crowdsourcing techniques to collect data from all over Japan. Crowdsourcing is a term that describes a spectrum of initiatives involving (sometimes) massive numbers of people participating in task-based problem solving

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. Jeff Howe codified the term's more contemporary meaning in a 2006 article in Wired titled “The Rise of Crowdsourcing,” using the term to describe the strategic appropriation of specialized labor markets to “create content, solve problems, even do corporate R&D.” 45 Howe tied

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crowdsourcing to Amazon's Mechanical Turk program, a “Web-based marketplace that helps companies find people to perform tasks computers are generally lousy at,” such as

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identifying images, sifting through interpretive information in documents, creating annotations, and more.46 This is where historical and contemporary treatments of the term “crowdsourcing” diverge: modern crowdsourcing privileges human intervention over computational algorithms, and relies on the dialectic relationship between humans and technology. Although the term

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“crowdsourcing” was coined for application to corporations, many public participation science research projects have employed elements of crowdsourcing methodologies in order to annotate or collect large amounts of data that could not otherwise be annotated

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with a smaller number of researchers addressing the problem. Crowdsourcing is controversial. One of the criticisms levelled at the crowdsourcing method of data collection involves the same criticism of participatory methods: data inaccuracy. Some methods of

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crowdsourcing are extremely exploitative: at sites such as Amazon's Mechanical Turk, CrowdFlower, Clickworker, or Toluna, for example, workers are often paid well below minimum wage—

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exploiting labor pools at home and abroad.47 Data Action does not support using exploitative crowdsourcing. In many ways the popularity of crowdsourcing was driven by technology that allowed easy access to vast groups of people. The increased availability of smartphones beginning in 2007 with

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not the point of data collection projects, getting enough data to provide evidence for a claim is, and crowdsourcing can therefore be an effective technique for collecting data meant to generate civic change. Crowdsourcing projects appear to work best when the groups involved have a stake in collecting the data. Whether it

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can help the government take action should there be an environmental threat in the community. Having a completely crowdsourced database for radiation levels in Japan is itself an accomplishment. Gathering complete data in a crowdsourcing project is often difficult, because it is challenging to obtain participants across all geographies or socioeconomic groups

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” citizens actively participate in data collection in the wake of a natural or civic emergency. One of the first tools to address disaster relief through crowdsourcing was Ushahidi, a web and mobile platform designed to provide a way for people to report on what is happening during a crisis. Once installed

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on Border and Smith” would appear, which would help focus responders’ relief efforts.58 After twenty-five days, the site had received almost 2,500 crowdsourced complaints, which helped save many lives. The work done as part of the Haiti earthquake response helped popularize Ushahidi, which was not well known before

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it—or did not have cell service—unrecorded. It is important to interrogate who is missing from your crowdsourced data, as that, too, can provide insights. One of the biggest problems encountered in crowdsourced data projects is finding enough participants to create a significant amount of meaningful data. When Hurricane Sandy hit

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view satellite imagery to evaluate damage.60 Enlisting an established volunteer group from the crisis mapper network to verify the data, the results of this crowdsourcing project were systematic and, therefore, more accurate than what was seen in previous Ushahidi projects. While the hurricane was happening and during subsequent relief efforts

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professionals from all over the country who volunteer during disaster events, helped ground these observations in a more “expert” perspective by evaluating the accuracy of crowdsourced annotations of the aerial images. The application pulled up an aerial image and asked the volunteers to assess whether structures in the image were okay

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, not okay, or bad (see figures 2.16 and 2.17). The results of the combination of crowdsourcing and expertise determined a map of areas to target for recovery (figure 2.18). 2.16 The interface for Humanitarian OpenStreetMap was site developed to

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how to make the sensors that would measure radiation. OpenStreetMap generated a community of open-source mappers dedicated to making data free and devoted to crowdsourcing to perform that work. Community building through data collection can even happen when governments implement the project. This was true of New York City's

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, nature, human, mechanical, indoor, and music. These same noise-related Flickr photos extracted from the API were then analyzed for their emotion, using EmoLex (a crowdsourced word-emotion lexicon used for semantic analysis that can estimate the emotion of tags) to analyze user tags, and the resulting analysis showed where noise

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appeared in neighborhoods with high numbers of Latin American and Asian immigrants. Source: Image created by Sarah Williams, Spatial Information Design Lab Cities also share crowdsourced data they collect through APIs and open data sites. The call records that come from 311 hotlines, which now exist in most major cities, are

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Participatory GIS: Deconstructions, Reconstructions, and New Research Directions,” Transactions in GIS 10, no. 5 (2006): 693–708; and Daniel Sui, Sarah Elwood, and Michael Goodchild, Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice (New York: Springer Science & Business Media, 2012). 9 Jeffrey A. Burke, Deborah Estrin, Mark Hansen

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.org/2011/04/first-safecast/. 44 “Hands-On Projects for Curious Minds,” n.d., KitHub homepage, https://kithub.cc/. 45 Jeff Howe, “The Rise of Crowdsourcing,” Wired, June 1, 2006, https://www.wired.com/2006/06/crowds/. 46 Ibid. 47 Alek Felstiner, “Working the Crowd: Employment and Labor Law in the

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Crowdsourcing Industry,” Berkeley Journal of Employment and Labor Law 32 (2011): 143–204; Alana Semuels, “The Internet Is Enabling a New Kind of Poorly Paid Hell,”

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.openstreetmap.org/wiki/2014_West_Africa_Ebola_Response. 56 “Ushahidi,” accessed January 25, 2019, https://www.ushahidi.com/. 57 Ida Norheim-Hagtun and Patrick Meier, “Crowdsourcing for Crisis Mapping in Haiti,” Innovations: Technology, Governance, Globalization 5, no. 4 (2010): 81–89. 58 Jessica Ramirez, “‘Ushahidi’ Technology Saves Lives in Haiti and

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,” Newsweek, March 3, 2010, https://www.newsweek.com/ushahidi-technology-saves-lives-haiti-and-chile-210262. 59 Norheim-Hagtun and Meier, “Crowdsourcing for Crisis Mapping in Haiti.” 60 Patrick Meier, “Crowdsourcing the Evaluation of Post-Sandy Building Damage Using Aerial Imagery,” IRevolutions (blog), November 1, 2012, https://irevolutions.org/2012/11/01

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/crowdsourcing-sandy-building-damage/. 61 Introduction to Data Science (IDA), “About,” IDS webpage, https://www.idsucla.org/about. 62 Ron Eglash, Juan E. Gilbert, and Ellen

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Washington, DC, 2013). 34 Anselin and Williams, “Digital Neighborhoods.” 35 Francis Harvey, “To Volunteer or to Contribute Locational Information? Towards Truth in Labeling for Crowdsourced Geographic Information,” in Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice, ed. Daniel Sui, Sarah Elwood, and Michael Goodchild (Dordrecht: Springer Netherlands, 2013), 31

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Social Media Reacted to Mumbai,” CNN.com, 2008, https://www.cnn.com/2008/WORLD/asiapcf/11/27/mumbai.twitter/. 70 J. Rogstadius et al., “CrisisTracker: Crowdsourced Social Media Curation for Disaster Awareness,” IBM Journal of Research and Development 57, no. 5 (September 2013): 4:1–4:13, https://doi.org/10

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-way/2017/03/11/519839892/federal-court-rules-three-texas-congressional-districts-illegally-drawn. Felstiner, Alek. “Working the Crowd: Employment and Labor Law in the Crowdsourcing Industry.” Berkeley Journal of Employment and Labor Law 32 (2011): 143–204. Fessenden, Ford, and Josh Keller. “How Minorities Have Fared in States With Affirmative

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://doi.org/10.1111/j.0033-0124.1984.00001.x. Harvey, Francis. “To Volunteer or to Contribute Locational Information? Towards Truth in Labeling for Crowdsourced Geographic Information.” In Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice, edited by Daniel Sui, Sarah Elwood, and Michael Goodchild, 31–42. Dordrecht: Springer

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Geographer 56, no. 2 (May 1, 2004): 160–173. https://doi.org/10.1111/j.0033-0124.2004.05602002.x. Howe, Jeff. “The Rise of Crowdsourcing.” Wired, June 1, 2006. https://www.wired.com/2006/06/crowds/. Huang, Daisy J., Charles K. Leung, and Baozhi Qu. “Do Bank Loans and Local

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: Understanding the Constitutionality of Stop and Frisk as a Program, Not an Incident,” 2014. https://doi.org/10.13140/2.1.4252.6404. Meier, Patrick. “Crowdsourcing the Evaluation of Post-Sandy Building Damage Using Aerial Imagery.” IRevolutions (blog), November 1, 2012. https://irevolutions.org/2012/11/01

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/crowdsourcing-sandy-building-damage/. Meier, Patrick. “Human Computation for Disaster Response.” In Handbook of Human Computation, 95–104. New York: Springer, 2013. https://doi.org/10.

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. January 7, 2019. https://dailycaller.com/2014/04/23/new-york-times-excludes-asian-americans-from-affirmative-action-study/. Norheim-Hagtun, Ida, and Patrick Meier. “Crowdsourcing for Crisis Mapping in Haiti.” Innovations: Technology, Governance, Globalization 5, no. 4 (2010): 81–89. NYCLU. “NYPD STOP-AND-FRISK ACTIVITY IN 2011 (2012),” 2012

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–127. https://doi.org/10.17645/up.v1i2.617. Rogstadius, J., M. Vukovic, C. A. Teixeira, V. Kostakos, E. Karapanos, and J. A. Laredo. “CrisisTracker: Crowdsourced Social Media Curation for Disaster Awareness.” IBM Journal of Research and Development 57, no. 5 (September 2013): 4:1–4:13. https://doi.org/10

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Regulated Slave Trade, Act of 1788.’” The Abolition Seminar. Accessed July 19, 2019. https://www.abolitionseminar.org/brooks/. Sui, Daniel, Sarah Elwood, and Michael Goodchild. Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice. New York: Springer Science & Business Media, 2012. Sultana, Selima. “Job/Housing Imbalance and Commuting Time

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Cities 32, 156. See also Urban planners; Urban planning; autonomous vehicles (AVs) and 195–196 big data and xiii–xiv creation of buzz 114–120 crowdsourced data and 77–78, 127 Getty Images data and 114–120 social media and 120–129 Citizens, data from 78–79 Citizen Sense project 68

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, data and 89–136, 217–218 Crime maps 158 Criminal Justice Reinvestment Act of 2009, 162 “Crisis mapping,” 80 Critical cartographers 166, 219 CrowdFlower 74 Crowdsourced data 73–75, 77–78, 82 Android HTC device and 74 cities and 127 government need for 73–75, 77–78 iPhone and 74 Currid

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, 113–114, 193–196, 217–218 change and 14, 140–143 from citizens 78–79 communities and 216–217 creativity and 89–136, 217–218 crowdsourced 73–75, 77–78, 82, 127 cybernetics and 43–45 data access 206–208 data sharing xvii–xviii, 137–186, 200–203 do no harm

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) 92 Interstate 95 highway plan (Miami, Florida) 38, 39 Introduction to Readings in Planning Theory (Feinstein and Campbell) 48 IoT (Internet of Things) 207 iPhone, crowdsourcing and 74 Jacobs, Jane 39–41, 40 Jakarta, Indonesia 202 Japan, radiation detection in 75, 76 Japanese Atomic Energy Agency 73 Japan International Cooperation Agency

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Data (organization) 199 Responsive City, The (Goldsmith and Crawford) 47 The Revolution Will Not Be Funded 58 Rio de Janeiro, Brazil 47 “The Rise of Crowdsourcing” (Howe) 73 Roads, data on 66, 144, 146 Rockefeller Foundation 147 Rogstadius, Jakob 132 Romans 1 Roter, Rebecca, sensors of 68 Royal Housing Commission 17

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,

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It

by Marc Goodman  · 24 Feb 2015  · 677pp  · 206,548 words

The Lean (Criminal) Start-Up A Sophisticated Matrix of Crime Honor Among Thieves: The Criminal Code of Ethics Crime U Innovation from the Underworld From Crowdsourcing to Crime Sourcing CHAPTER 11: INSIDE THE DIGITAL UNDERGROUND Passport to the Dark Web A Journey into the Abyss Dark Coins Crime as a Service

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Technology in Israel hacked the incredibly popular Waze GPS navigational app (purchased by Google in 2013 for a cool $1 billion). The app, which offers crowdsourced real-time traffic management, relies on users to report accidents, police checkpoints, and road hazards as a means of improving vehicle flow. Once the app

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adapt, either by mimicking legitimate Internet start-ups or by abusing their services. Borrowing a page from Uber, the ride-sharing phone app that connects crowdsourced drivers to passengers, a woman in the U.K. created her own SMS vehicle-on-demand service—for getaway cars. Sensing a market need by

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boss’s gamification strategy paid off and received widespread attention among his workers, with the Ferrari reserved for the chosen “employee of the month.” From Crowdsourcing to Crime Sourcing Of all the business innovation techniques utilized by Crime, Inc., perhaps none has been as widely adopted as

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crowdsourcing. Crowdsourcing began as a legitimate tool to leverage the wisdom of crowds to solve complex business and scientific challenges. The concept of crowdsourcing first gained widespread attention in an article written in 2006 by Jeff Howe for Wired

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. Howe defined crowdsourcing as the act of “outsourcing a task to a large, undefined group of people through an

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open call.” While hundreds of examples of crowdsourcing have been documented with great results, these very same techniques can be harnessed for criminal purposes as well. YouTube is replete with great examples of

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, whom they met for the first time at the scene of the crime. Similar incidents have taken place in Chicago, Philadelphia, and Los Angeles. Some crowdsourcing techniques are meant to give potential lawbreakers a leg up on the police. In the United States, mobile apps such as DUI Dodger, Buzzed, and

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Checkpoint Wingman allow those who have had too much to drink to crowdsource the location of DUI checkpoints, view them on an interactive map on the iPhone or Android device, and receive alerts when checkpoints are moved or

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government spending cuts turned violent, protesters created an app called Sukey, which allowed them to photograph police and upload their geo-tagged images to a crowdsourced interactive map. When other protest participants launched Sukey on their mobiles, they knew which areas contained riot police and were shown interactive compasses advising them

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how to avoid the cops (green pointed to safe areas, red to police danger zones). Hacktivists too have taken good advantage of crowdsourcing techniques. At the height of its dispute with Sony and News Corp, LulzSec brazenly established a crime-request telephone hotline asking whom the hacktivists should

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as taking the whole or part of a criminal act and outsourcing it to a crowd of either witting or unwitting individuals. By aggressively adopting crowdsourcing techniques, Crime, Inc. is able to build largely anonymous distributed criminal networks that can self-organize and assemble with amazing rapidity. To put these capabilities

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coopted by organized crime, believing they were “working from home” as “regional accounts receivable representatives.” Technology makes it easier than ever for Crime, Inc. to crowdsource its work to unwitting co-conspirators who have no idea they are taking part in an illicit plot. For example, criminals need a constant stream

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and provided it to random strangers to solve for them. But why would any stranger do this? Simple. They were properly incentivized, with pornography. To crowdsource its problem, Crime, Inc. just created dozens of free porn sites and told visitors they would have to solve a CAPTCHA to prove they were

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create their spam e-mail accounts, cut, pasted, and switched in real time. A win-win situation, free high-quality porn in exchange for unwitting crowdsourced participation in a phishing scam. Though the CAPTCHA scheme was clever, it pales in comparison with a criminal casting call posted in an online ad

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at the scene matching the description provided by the armored car guard. What authorities did not realize is that the actual bank robber had carefully crowdsourced his escape well in advance. A few days prior to the robbery, the true bandit placed an ad on Craigslist in the help wanted section

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, and a respiratory mask. Dozens looking for work showed up at the appointed place and time, having no idea they were unwittingly suckered into a crowdsourced bank robbery. In the world of “in screen we trust,” the public is easy to deceive. Only when all the construction workers were rounded up

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, could be held over the Touch ID sensor to unlock the phone. Mission accomplished. As if crowdfunding hackers weren’t serious enough, recently yet another crowdsourced enterprise surfaced in the digital underground: the Assassination Market. Regrettably, the service is not some sort of deeply disturbing joke. Rather, it is the work

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of a dedicated anarchist who goes by the pseudonym Kuwabatake Sanjuro. As of late 2014, eight U.S. government officials have been selected via crowdsourced voting for assassination, with the former Federal Reserve chairman Ben Bernanke receiving the greatest number of votes. Donations have been made via encrypted and untraceable

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the crowd funded the activity willingly. In what was perhaps the most masterful single heist ever carried out by Crime, Inc., thieves around the world crowdsourced a robbery in twenty-seven separate countries, carried out simultaneously. The massive larceny occurred in early 2013 when coders, engineers, and the R&D team

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the card numbers on the magnetic strips on the reverse. What happened next is perhaps one of the greatest feats in crime sourcing, or even crowdsourcing, history. The cards were distributed to hundreds of teams of worker-bee criminals around the world. When Crime, Inc. gave the signal, the race was

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of outlaws went on a synchronized withdrawal spree, hitting as many ATMs as humanly possible. In the ten-hour time span that Crime, Inc.’s crowdsourced operation ran, thieves carried out thirty-six thousand ATM transactions in twenty-seven countries and walked away with over $45 million in cash. Because Crime

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of low-level thugs were caught by police, the Crime, Inc. masterminds behind the plot remain unidentified and at large, probably organizing their next massive crowdsourced caper. Ten hours, thirty-six thousand transactions, twenty-seven countries: an amazing logistical feat that few corporations or governments could actually execute. Welcome to the

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moral considerations, it is free to profit without limit and use the very latest business practices to do so. Crime, Inc. uses freemium pricing, gamification, crowdsourcing, crowdfunding, reputation engines, just-in-time manufacturing, online training, swarms for distributed project management in pursuit of the long tail of crime victims around the

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when it comes to political assassinations. No worries, though, there are just as many services that are dedicated to killing government officials, such as the crowdsourced Assassination Market mentioned previously. Prices range from a low of $20,000 to more than $100,000 to kill a police officer. The sites request

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, investment fraud, computer hacking, child pornography, and narcotics trafficking.” It is also thought to have played a central role in the previously noted $45 million crowdsourced ATM heist that took place over a ten-hour time frame in 2013. Though Liberty Reserve, like Silk Road, was ultimately taken down by the

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be unwittingly participating in an ongoing cyber attack against others, and you have no idea it’s happening. Thank you for your service. Hackers have crowdsourced and off-loaded their attack to you and your computers, involuntarily embroiling you and them in their international criminal conspiracy. Crime, Inc. can even draft

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hardware systems. These illicit knowledge workers of the twenty-first century are deeply innovative, adaptive, and ever learning and employ the latest business practices, from crowdsourcing to affiliate marketing, to subvert the technologies around us. Advances in computing and artificial intelligence mean that crime has now become scripted, run algorithmically, to

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the bad. That is a huge advantage but one that we have not yet fully leveraged to our benefit. Crime, Inc. is well versed in crowdsourcing, capable of mobilizing mobs of thousands, as we saw with the massive 2013 ATM cyber attack in which thieves carried out thirty-six thousand in

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trained agents on hand to protect all of us, we are far better off enabling ordinary citizens to combat the problem as a group through crowdsourcing. To beat Crime, Inc. at its game, we must get good to scale, but bigger and better. The idea of

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crowdsourcing law enforcement is hardly new. In 1865, when John Wilkes Booth assassinated President Lincoln, he became the first fleeing felon to have his photograph appear

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on a wanted poster. Today, 150 years after the murder of our nation’s sixteenth president, government’s implementation of crowdsourced law enforcement has changed nary a bit. Cops distribute photographs to local news channels, and broadcasters warn that the wanted party is “armed and dangerous

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we the people began using our available cognitive surplus to help protect and defend our own future. Open-source warfare and crowdsourced crime must be met with open-source security and crowdsourced public safety. Fortunately, there are a few bright spots where this new paradigm of public safety is beginning to shine

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Nairobi. Citizens in Mexico, a country racked by fifty thousand narcotics-related murders from 2006 to 2012, are using tools such as Google Maps to crowdsource reporting on the cartels, their activities, and their whereabouts. In eastern Europe, the Organized Crime and Corruption Reporting Project, comprising journalists and citizens

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, crowdsources sophisticated multinational investigations to reveal which dictators, crooked officials, terrorists, and organized crime groups are moving and laundering their massive ill-gotten gains around the

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to marshal evidence by channeling time and energy to decipher data to produce results faster than any policing or governmental organization could have done alone. Crowdsourcing public safety delivers clear results and must become an integral component of our global security strategy in an exponentially changing world, especially one so short

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who were all eventually arrested by the FBI as a result of the students’ work. In order to have lasting and meaningful success, however, such crowdsourcing efforts cannot be merely ad hoc but rather have to be formalized systemically in order to scale for growth. In 2011, police in the U

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extensive training and background investigations, and operate under clearly defined operational and legal frameworks. Timing is of the essence to establish and build such a crowdsourced force for good—now before the cyber crisis occurs. There are many private sector professional organizations that could prove immensely helpful in jump-starting such

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of crisis. Remarkably, a team from MIT found all ten balloons hidden in the farthest reaches of our country in a mere nine hours, by crowdsourcing the task over social media to forty-four hundred volunteers. As it turns out, playing games needn’t be a waste of time and can

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days, a discovery that had eluded AIDS researchers around the world who had been actively trying to solve the problem for more than a decade. Crowdsourced games such as MalariaSpot and Foldit should provide far-reaching inspiration and important take-away lessons we can apply to the conundrum we face with

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: Paul Peachey, “Cybercrime Boss Offers a Ferrari for Hacker Who Dreams Up the Biggest Scam,” Independent, May 11, 2014. 32 The concept of crowdsourcing: Jeff Howe, “The Rise of Crowdsourcing,” Wired, June 2006. 33 While hundreds of examples: Marc Goodman, “The Rise of Crime-Sourcing,” Forbes, Oct. 3, 2011. 34 YouTube is

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documents: George Arnett and James Ball, “Are UK MPs Really Claiming More Expenses Now Than Before the Scandal?,” Guardian, Sept. 12, 2014; Michael Anderson, “Four Crowdsourcing Lessons from the Guardian’s (Spectacular) Expenses-Scandal Experiment,” Nieman Lab, June 23, 2009. 7 The Rand Corporation has noted: “Shortage of Cybersecurity Professionals Poses

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It Be MORE Worth It?,” TED Conversations, http://​www.​ted.​com/. 13 Because the same image: Miguel Angel Luengo-Oroz, Asier Arran, and John Frean, “Crowdsourcing Malaria Parasite Quantification,” Journal of Medical Internet Research, Nov. 29, 2012. 14 In one remarkable case: Katia Moskvitch, “Online Game Foldit Helps Anti-AIDS Drug

The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence

by Sebastian Mallaby;  · 30 Mar 2026  · 607pp  · 161,998 words

. BACK TO NOTE REFERENCE 25 Buchanan, author interview. BACK TO NOTE REFERENCE 26 Later, the rival post-training efforts were submitted to LMSYS, a popular crowdsourced tool for evaluating chatbots. The results, published on January 26, 2024, showed that the Bard team’s “Elo score” was almost 100 points higher. BACK

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got our payoff in the end. All this innovation did eventually get appreciated.” Rae, author interview. BACK TO NOTE REFERENCE 20 On Chatbot Arena, a crowdsourced ranking system, Gemini 2.5 Pro was ranked equal first as of October 15, 2025, sharing that position with two models from Anthropic. Four OpenAI

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

The Deepest Map

by Laura Trethewey  · 15 May 2023

: Marie Tharp and the Map That Changed the World Chapter 5: The Loneliest Ocean on Earth Chapter 6: Naming and Claiming the Seafloor Chapter 7: Crowdsourcing a Map of the Arctic Chapter 8: The Robot Revolution at Sea Chapter 9: Buried History Chapter 10: Mining the Deep Chapter 11: To the

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of scrappy ocean mappers from all over the world, Seabed 2030 planned to recruit vessels already at sea, from cruise ships to luxury yachts, to crowdsource the map. Its participants wanted to harness new autonomous technology to survey the seafloor with drones. At this pivotal moment in history, when the planet

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still achievable target based on the number of dedicated survey ships available at the time. But there was always another idea simmering in the background: crowdsourcing. Almost every vessel at sea, from aircraft carriers to fishing dinghies, has sonar equipment installed for sounding the seafloor. “By utilising assets already at sea

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of Palau, the Republic of Kiribati, and the Republic of the Marshall Islands, are all grappling with a dire need for new and improved charts. Crowdsourcing offers a way into the mapping world without the bigger budget of a developed country. A smaller local survey boat can reach shallow, hard-to

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-reach coastlines regularly where a larger survey vessel might get snagged or return only occasionally. Jennifer Jencks felt excited by the potential to crowdsource the seafloor. Jencks, who oversees the NOAA data center in Boulder, Colorado, where all of Seabed 2030’s maps are held, also chairs the

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Crowdsourced Bathymetry Working Group at the International Hydrographic Organization (IHO). Over the years, she’s attended countless ocean-mapping talks and workshops, and she tends to

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about charting the seafloor. But it was clear that their numbers weren’t growing, and neither was the map. To Jencks, those problems seemed interconnected. “Crowdsourced bathymetry came about a few years ago, when IHO was saying, ‘At this rate we’re never going to map the whole darn ocean. We

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really need to start looking outside the box,’” she remembered. As her working group started to spearhead crowdsourcing projects, she began to notice new faces at ocean-mapping events. When we spoke, she had just wrapped up a Caribbean mapping workshop during which

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Costa Rica had agreed to allow crowdsourcing in its waters under national jurisdiction. “The folks who are coming to the table is so much broader now,” she said. Jencks mentioned a few

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crowdsourcing projects getting off the ground in Palau, South Africa, and Greenland. One effort was already under way in Australia, where a marine geologist, Robin Beaman,

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couldn’t wait any longer for government or industry to come map the water for them. They set out to do it themselves. Chapter 7 Crowdsourcing a Map of the Arctic Civilization is like a thin layer of ice upon a deep ocean of chaos. —Werner Herzog 1. I caught my

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edge, the pale green tundra slipped into the ocean gradually and, without any fanfare, land became sea. I had come to see the vanguard in crowdsourcing ocean maps, and this had led me to uncharted waters overlooked by government and industry alike. The Arctic Ocean is the smallest and shallowest of

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take longer to map,” explained Jamie McMichael-Phillips, the director of Seabed 2030 and a big champion of crowdsourcing. Basic single-beam soundings are still a vast improvement on satellite predictions. “The magic of crowdsourcing is that [the soundings might be] lesser quality but still hugely valuable as far as the [Seabed

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,” said Brian Calder, the associate director of CCOM. Calder has written extensively about the uncertainties contained in professionally made maps, and he’s experimenting with crowdsourcing himself. Yes, trained hydrographers make good maps, he said, but so can a “superobserver,” his term for an untrained

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crowdsourcer committed to the cause. Both Calder and Desrochers dislike the crowdsourcing label. It naturally draws comparisons with the world’s best-known and most successful crowdsourcing effort: Wikipedia. The online encyclopedia’s legion of unpaid writers and editors validate

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vaguely aware that it isn’t the most authoritative take available, but for settling a disagreement with a family member, it’s often good enough. Crowdsourcing a seafloor map follows roughly the same principle: a critical mass of volunteers surveys the same seafloor and eventually arrives at a reasonably accurate measurement

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a key tenet of Inuit identity. Information has no value unless it is shared, the elders say.38 Over the last decade, the prejudice against crowdsourcing ocean maps has started to wane, said Mathieu Rondeau, a colleague of Julien Desrochers who helped develop the HydroBlock. Back in 2010, Rondeau was just

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starting out in crowdsourcing maps when he gave a talk on the topic at a hydrography conference. Very few people attended, and no one asked him any questions when

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the Canadian Hydrographic Service (CHS), where he says he’s seen a sea change within the community. Although some government surveyors are still resistant to crowdsourcing, Seabed 2030 and other major mapping groups have thrown their weight behind the effort. Perhaps there’s also a grudging acceptance that trained hydrographers cannot

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Arctic Circle, the highest total over three years.42 Back at the CHS, Mathieu Rondeau is trying to convince his superiors of the benefits of crowdsourcing: the rising number of accidents, the staggering amount of territory left to survey, the sheer cost of sending a ship to the north. The typical

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counterargument is that crowdsourcing could lead to a major shipping accident. A nautical chart is technically a legal document; it is constantly updated to support the international maritime industry

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days in 2021, it halted nearly $10 billion in trade, and the insurance and legal costs ran into the hundreds of millions of dollars. A crowdsourced map didn’t lead to the Ever Given blockage, but this is the type of headline accident that hydrographers raise when they warn against nonexperts

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contributing to maps: Who will be responsible when something goes very, very wrong? Perhaps the most compelling argument for crowdsourcing maps is not cost or efficiency but the danger of repeating the colonial history of surveying in the Arctic. In the past, governments in the

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progress Seabed 2030 had made in the early years, leapfrogging from 6 percent completed in 2017 to more than 20 percent in 2021.53 Major crowdsourcing partnerships were announced, with the offshore survey company Fugro pledging to donate all the maps collected on transits between work sites. An Israeli mapper at

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the University of New Hampshire set to work recruiting the superwealthy and their superyachts to crowdsource maps on their jaunts around the world. As the 2020s dawned—along with the COVID-19 pandemic, disrupted supply chains, and the largest land war

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in Europe since World War II—Seabed 2030’s prospects dimmed. When I checked in with Jennifer Jencks about the crowdsourcing projects in Palau and South Africa in 2021, both countries were still waiting on equipment shipments, delayed indefinitely by supply-chain issues. Seabed 2030 wasn

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that are never going to get touched by any of those methods.” Robin Beaman, the marine geologist leading the crowdsourcing project on Australia’s Great Barrier Reef, told me much the same. Crowdsourcing worked well in shallow areas along the continental shelf, but Seabed 2030 needed to enlist deepwater multibeam sonars to

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. Hudson Bay made the magnitude of the uncharted ocean crystal clear. It also made Seabed 2030’s deadline look pretty much impossible to me, too. Crowdsourcing, it seemed, would not be a major force in finishing Seabed 2030 after all, but perhaps that had never been the point. “The community aspect

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as I moved around the world. Falling off the map had raised another question for me: If crowdsourcing wasn’t the magic bullet for Seabed 2030, what was? At the launch of Seabed 2030, crowdsourcing was often mentioned in tandem with autonomous mapping, that is, mapping the seafloor using drones or some

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other remotely operated hardware. As the 2020s wore on, I heard less about people-powered solutions, such as crowdsourcing, and more about big technological breakthroughs. When a big, ambitious goal, such as limiting global warming to no more than 1.5 degrees Celsius—2

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Review 2021,” Allianz Global Corporate & Specialty, August 2021, 9, https://www.agcs.allianz.com/news-and-insights/reports/shipping-safety/shipping-report.html. CHAPTER 7: CROWDSOURCING A MAP OF THE ARCTIC 1.Heather A. Stewart and Alan J. Jamieson, “The Five Deeps: The Location and Depth of the Deepest Place in

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, 27–28, 76, 224 seafloor mapping and, 78, 87 Seabed 2030 Project challenges of, 104, 148–49, 163, 165–67 cost of mission, 5, 116 crowdsourcing and, 127–29, 140–41, 144, 148, 149–50 drones and, 152, 166 errata and, 117–18 formation of, 3–4, 148 funding of, 59

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2030 Project autonomous mapping, 150 beauty of seafloor maps, 38–39, 86 confidentiality of, 56, 70–71, 83, 88, 103–4, 119, 123–27, 153 crowdsourcing and, 4, 127–29, 140–46, 149–50 difficulties of, 26–27, 39, 94 drones used for, 5, 150, 151–52, 159–62 history of

The Future of the Professions: How Technology Will Transform the Work of Human Experts

by Richard Susskind and Daniel Susskind  · 24 Aug 2015  · 742pp  · 137,937 words

than half of the doctors in the United States are members of Doximity, another doctor-specific networking tool.41 Medicine is also making use of crowdsourcing, where large numbers of individuals are drawn upon for their collective ideas and support. At CrowdMed, people post their symptoms and

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crowdsource diagnoses from an online community of 2,000 doctors—so-called ‘Medical Detectives’.42 At InnoCentive, medical institutions crowdsource ideas by offering large online rewards for those who solve their medical ‘challenges’.43 At Watsi

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to translate some of their news stories). The platform acts, then, as both a free online language-learning tool and as a fee-based translation crowdsourcing service.92 In all of these illustrations the historical monopoly of traditional teachers, tutors, and lecturers is challenged. There is less need for the ‘sage

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Corporate Executive Board, a membership-only consulting business, uses its online member network of 16,000 executives to identify and spread best practice.238 Recently, crowdsourcing platforms for consulting services have been built. Open IDEO is an online platform built by the design consultancy IDEO. Problems, predominantly social, are posted online

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greatest insight.240 In the Cabinet Office of the British Government, the Open Policy Making Team uses a range of online platforms (blogs, social media, crowdsourcing) to try to break the ‘monopoly’ that traditional civil servants have on policymaking. There are systems that require less human input. Platforms like Ayasdi and

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-management) services. Their selling proposition is that the assurance given is by trustworthy and expert specialists, in whom clients have confidence. In less complex audits, crowdsourcing has been used. For example, in 2009 the British Government published, online, 700,000 individual documents that related to the expenses of British MPs. In

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> (accessed 27 March 2015). 40 <https://secure.quantiamd.com> (accessed 27 March 2015). 41 <https://www.doximity.com> (accessed 27 March 2015). 42 Daniel Gaitan, ‘Crowdsourcing the answers to medical mysteries’, Reuters, 1 Aug. 2014 <http://www.reuters.com> (accessed 27 March 2015). 43 <http://www.innocentive.com>. 44 <https://watsi

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Data, 32. 278 Mayer-Schönberger and Cukier, Big Data, and James Surowiekcki, ‘A Billion Prices Now’, New Yorker, 30 May 2011. 279 Michael Andersen, ‘Four crowdsourcing lessons from the Guardian’s (spectacular) expenses-scandal experiment’, NiemanLab, 23 June 2009 <http://www.niemanlab.org> (accessed 8 March 2015). 280 <https://www.xbrl

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people collaborate with each other, with the former, for example, reviewing, editing, or supplementing the user-generated content. A third type of online collaboration is crowdsourcing. Here large numbers of people—experts or non-specialists—are invited to contribute to a well-defined project or problem that is so large that

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be found if the net of inquiry is spread widely enough. WikiHouse and Arcbazar in architecture, and Open Ideo and WikiStrat in consulting, have run crowdsourcing projects in this manner. Realization of latent demand One of the attractions of the new approaches to professional work and, in particular, of various online

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of ‘affective data’ are being assembled. Some of this data is being taken from existing data sets. And some of it is being gathered using crowdsourcing methods.72 The data themselves are of various types. Some of them are plain text, but many of them are audio-visual. Importantly, the data

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of what happens online, and not present a watertight taxonomy. Box 4.2. What connected humans do Communicate Research Socialize Share Build communities Co-operate Crowdsource Compete Trade In the first instance, human beings who are online are able to communicate with one another in new ways and on a larger

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is easy jointly to co-author complex documents, even if the contributors are in different countries. A related form of production occurs when online humans crowdsource (as is discussed briefly in section 3.7). Ordinarily, this involves large numbers of people being called upon to co-operate on discrete projects whose

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to break some large task down into a manageable number of sub-tasks and invite a community of users each to undertake some of them. Crowdsourcing draws on networks of human beings to solve particular problems, to carry out pieces of work, or even to raise finance for given initiatives. Again

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work, or a sum of money is subdivided and the burden is distributed across a community. There is an overlap here with mass collaboration, but ‘crowdsourcing’ tends to be the term used when a given project is well bounded in scope and likely time-scale, and there is a clear commission

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or invitation from an individual or institution for the contributions of others.96 There are many businesses that specialize in crowdsourcing. At CrowdFlower, for example, it is said that an online workforce of millions of people can be drawn from to put together teams to clean

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data is supplied to a network of statisticians who vie with one another to provide the best analysis. At InnoCentive, in the spirit also of crowdsourcing, people are invited to compete in the solving of a wide range of difficult problems. Finally, connected human beings now trade extensively online. We are

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research very differently than in a pre-Internet world; but much more than this, they are also able to socialize, share, build communities, co-operate, crowdsource, compete, and trade in ways and on a scale that has no analogues in the analogue world. Systems and services such as Twitter, Facebook, eBay

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, and Who is Sponsoring it’, Sept. 2013 <http://www.linuxfoundation.org/publication/linux-foundation/who-writes-linux-2013> (accessed 24 March 2015). 96 Daren Brabham, Crowdsourcing (2013). 97 Yochai Benkler, The Penguin and the Leviathan (2011), 23. 98 Benkler, The Penguin and the Leviathan, 182. 99 See <http://www.retailresearch.org

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of communities, often in large numbers, are called upon each to contribute, often modestly, to the resolution of some issue. This is an example of crowdsourcing (see sections 3.7 and 4.8). The content or know-how that is assembled in this way will be less structured and generalized than

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. 2008. Andersen, Erika, ‘Why Writing a Book is Good Business’, Forbes, 12 Oct. 2012 <http://www.forbes.com> (accessed 8 March 2015). Andersen, Michael, ‘Four crowdsourcing lessons from the Guardian’s (spectacular) expenses-scandal experiment’, NiemanLab, 23 June 2009 <http://www.niemanlab.org> (accessed 8 March 2015). Anderson, Chris, Makers: The

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of the Private Domain’, Law and Contemporary Problems, 66 (2003), 33–74. Boyle, James, The Public Domain (New Haven: Yale University Press, 2010). Brabham, Daren, Crowdsourcing (Cambridge, Mass.: MIT Press, 2013). Bradshaw, Tim, ‘Scientists and Investors Warn on AI’, Financial Times, 12 Jan. 2015. Bray, David, Karen Croxson, William Dutton, and

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Work’, published online, 2014 <http://www.lod.co.uk/media/pdfs/The_New_World_Of_Legal_Digital_Download.pdf> (accessed 28 March 2015). Gaitan, Daniel, ‘Crowdsourcing the answers to medical mysteries’, Reuters, 1 Aug. 2014 <http://www.reuters.com> (accessed 27 March 2015). Gant, Scott, We’re All Journalists Now (New

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, 206, 215, 244, 246 craftsmanship 2, 142, 208, 215, 262 craftspeople 106, 198–9, 201–2, 205, 264 creative commons 224 credentials 15–16, 128 crowdsourcing 53, 82, 93, 133, 179–81, 223 Cukier, Kenneth 59, 92, 162, 191 culture 30, 147, 180, 188, 262 customization 103, 222 individual 130 mass

The Data Journalism Handbook

by Jonathan Gray, Lucy Chambers and Liliana Bounegru  · 9 May 2012

century indicates a new phase wherein the sheer volume of data that is freely available online—combined with sophisticated user-centric tools, self-publishing, and crowdsourcing tools—enables more people to work with more data more easily than ever before. Data Journalism Is About Mass Data Literacy Digital technologies and the

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2-5. The Guardian Datablog production process visualized (the Guardian) Gradually, the Datablog’s work has reflected and added to the stories we faced. We crowdsourced 458,000 documents relating to MPs’ expenses and we analyzed the detailed data of which MPs had claimed what. We helped our users explore detailed

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. With this data, I made an interactive map in Fusion Tables. We asked our readers to play around with the data and crowdsourced results at http://bit.ly/scratchbook-crowdsourcing, for example. After a lot of questions on how we made a map in Fusion Tables, I also recorded a video tutorial

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the “big board” a great piece of visual journalism that maps almost perfectly to the tried-and-true inverted pyramid. — Aron Pilhofer, New York Times Crowdsourcing the Price of Water Since March 2011, information about the price of tap water throughout France is gathered through a

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crowdsourcing experiment. In just 4 months, over 5,000 people fed up with corporate control of the water market took the time to look for their

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% of the data has been collected. To go faster, France Libertés wanted to get citizens directly involved. Together with the OWNI team, I designed a crowdsourcing interface where users would scan their water utility bill and enter the price they paid for tap water on http://www.prixdeleau.fr/. In the

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to design policy papers. They will be more willing to pay for a data collection operation than a newspaper executive. Users can provide raw data Crowdsourcing works best when users do a data collection or data-refining task. Ask for the source We pondered whether to ask users for a scan

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get relative percentages, which can be hard to interpret. Figure 4-11. Google Insights (Google) — Pete Warden, independent data analyst and developer Crowdsourcing Data at the Guardian Datablog Crowdsourcing, according to Wikipedia, is “a distributed problem-solving and production process that involves outsourcing tasks to a network of people, also known as

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the crowd.” The following is from an interview with Simon Rogers on how the Datablog used crowdsourcing to cover the MPs’ expenses scandal, drug use, and the Sarah Palin papers: Sometimes you will get a ton of files, statistics, or reports which

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get hold of material that is inaccessible or in a bad format and you aren’t able to do much with it. This is where crowdsourcing can help. One thing the Guardian has got is lots of readers, lots of pairs of eyes. If there is an interesting project where we

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common is that they are about issues that people really care about, so they are willing to spend time on them. A lot of the crowdsourcing we have done relies on help from obsessives. With the MPs’ expenses, we had a massive amount of traffic at the beginning and it really

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going through every page looking for anomalies and stories. One person has done 30,000 pages. They know a lot of stuff. We also used crowdsourcing with the Sarah Palin papers. Again this was a great help in scouring the raw information for stories. In terms of generating stories

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us. People really liked it and it made the Guardian look good. But in terms of generating data, we haven’t used crowdsourcing so much. Some of the crowdsourcing projects that we’ve done that have worked really well have been more like old-fashioned surveys. When you are asking people about

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, it wasn’t producing raw numbers that we could confidently use. If I were to give advice to aspiring data journalists who want to use crowdsourcing to collect data, I would encourage them do this on something that people really care about, and will continue to care about when it stops

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think making it fun is really important. — Marianne Bouchart, Data Journalism Blog, interviewing Simon Rogers, the Guardian How the Datablog Used Crowdsourcing to Cover Olympic Ticketing I think the crowdsourcing project that got the biggest response was a piece on the Olympic ticket ballot. Thousands of people in the UK tried to

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think “What do people want to tell me right now?” And it’s only when you tap into what people want to talk about that crowdsourcing is going to be successful. The volume of responses for this project, which is one of our first attempts at

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crowdsourcing, was huge. We had a thousand responses in less than an hour and seven thousand by the end of that day. So obviously, we took

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invisible to the user that we are using one. So it is very convenient. In terms of advice for data journalists who want to use crowdsourcing, you have to have very specific things you want to know. Ask things that get multiple choice responses as much as possible. Try to get

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, we’re fulfilling our mission. One of my favorite news apps is the Los Angeles Times’s Mapping L.A., which started out as a crowdsourced map of Los Angeles’s many neighborhoods, which up until Mapping L.A. launched, had no independent, widely-accepted set of boundaries. After the initial

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crowdsourcing project, the Times has been able to use neighborhoods as a framing device for great data reporting—things like crime rate by neighborhood, school quality

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 Slow Fix: Solve Problems, Work Smarter, and Live Better in a World Addicted to Speed

by Carl Honore  · 29 Jan 2013  · 266pp  · 87,411 words

LONG: Tackling Tomorrow Today 6. THINK SMALL: Devil in the Details 7. PREPARE: Ready for Anything 8. COLLABORATE: Two Heads Are Better Than One 9. CROWDSOURCE: The Wisdom of the Masses 10. CATALYZE: First among Equals 11. DEVOLVE: Self-Help (in a Good Way) 12. FEEL: Twiddling the Emotional Thermostat 13

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there that is hard to marshal into an organized team. Sometimes, to find the right fix, you have to turn to the crowd. CHAPTER NINE CROWDSOURCE: The Wisdom of the Masses Two heads are better than one. Proverb “Thetta reddast” is an expression you hear in Iceland a lot these days

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dots merge to produce a vivid scene of people lounging on the banks of the Seine. To understand what has come to be known as “crowdsourcing,” you have to make a similar mental leap. When you aggregate the decisions of the many, even if some of those decisions are bone-headed

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. Only a select few are invited to work on projects at Le Laboratoire or conduct research in those open-format labs at Columbia and Princeton. Crowdsourcing means taking a problem normally tackled by the few and putting it to the many. In the wrong hands it might only deliver a quick

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financial markets. But sometimes the crowd does its best work when its members communicate and collaborate. One of the drivers behind Iceland’s experiment in crowdsourcing is Gudjon Mar Gudjonsson, a boyish, fortysomething entrepreneur with a string of high-tech companies and patents on his CV. Surveying the wreckage of the

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of crowds to capture the heartbeat of a nation’s creativity.” Working with like-minded reformers, Gudjonsson convened a “National Assembly” in 2009 based on crowdsourcing and open-innovation techniques from the private sector. It consisted of 1,500 members, nearly 5 per cent of Iceland’s population – a cross-section

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Icelandic Parliament set one up to gather input for the new national constitution. It also canvassed opinions on Twitter, YouTube and Facebook. To see how crowdsourcing politics works in the wild, I join an Assembly held in a school gymnasium on the outskirts of Reykjavik. Its mandate is to identify the

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competencies” upon which Iceland should be building its future. Some 150 people turn up on a grey, wet Saturday morning. True to the spirit of crowdsourcing, they represent a cross-section of Icelandic society plus a smattering of parliamentarians, a former mayor and the city’s chief of police. Most people

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, geo-thermal power and agriculture seem to have emerged as the leading USPs. So has the Assembly done its job? Has Iceland’s experiment in crowdsourcing unleashed a torrent of creative solutions to the nation’s problems? Sitting at Table K, brainstorming with the locals, I did not feel like I

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am trying to assess a pointilliste painting from too close up. When you step back and look at the big picture, Iceland’s experiment with crowdsourcing does seem to be churning up useful ideas that might one day make their way into government policy. “A part of every National Assembly is

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it is?’ ” says Jakobsdottir. “I am already looking at how to integrate this idea into the national curriculum.” Many people leave my Assembly optimistic that crowdsourcing can help reboot Iceland. Some talk of laying the groundwork for a new form of politics. “What you’re seeing here is super-democracy,” says

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and computer engineers spread across the US, Canada, Austria and Israel claimed the prize. That same year Fiat started building the world’s first fully crowdsourced car at its flagship factory in Betim, Brazil. The company set up a web portal where anyone in the world could post ideas on how

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, which is entirely hidden and secretive,” said Peter Fassbender, manager of Centro Estilo, the firm’s design centre. Fiat went a step further than other crowdsourcers by moving from the virtual to the real world, inviting the smartest members of the crowd, which included a civil servant, an IT specialist and

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where crowds offer advice on everything from relationships to health to home repairs. Now is the time to sound a note of caution: collaboration and crowdsourcing both have their limits. Working together is not the only answer to every problem. Even teams with a fine track record can, over time, grow

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make mistakes or be sabotaged by rogue members. With around 100,000 contributors constantly editing its content, Wikipedia is an example of the perils of crowdsourcing. Though a goldmine of information, the online encyclopedia is prone to inaccuracies and biases. The bubbles and crashes of recent years are a reminder that

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Iceland. Even if not one single suggestion from the National Assemblies makes its way into the new constitution, or into government policy, the investment in crowdsourcing may yet pay off. Voters will feel they have been consulted, that their ideas count for something, and that they have a real stake in

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government.” That is sweet vindication to Gudjon Gudjonsson, the main man behind the Assemblies. He thinks crowdsourcing is the perfect tonic to reinvigorate electoral politics around the world. “In this new model of democracy, you crowdsource vision and values to give you a guiding light from the population,” he says. “And that

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Molecular Biology, the scientists behind the game hailed the breakthrough as a landmark moment: “Although much attention has recently been given to the potential of crowdsourcing and game playing, this is the first instance we are aware of in which online gamers solved a longstanding scientific problem.” A few months later

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presence in our homes.” This underlines perhaps the most vexing truth about the search for the Slow Fix: no matter how much planning, thinking, collaborating, crowdsourcing and testing you do, no matter how strenuously you empower, inspire and connect emotionally with the people around you, no matter how humbly you learn

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on the small stuff. How David Edwards pulled together a multidisciplinary team to invent a new drinking vessel at Le Laboratoire. How Iceland is using crowdsourcing to reboot democracy. How Enrique Peñalosa played a catalytic role in the transformation of Bogotá. How Ricardo Pérez became a better coffee farmer by taking

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Library of Science ONE, Volume 5, Number 12 (2010). Isaac Kohane quote: Jonah Lehrer, “Groupthink: The Brainstorming Myth,” New Yorker, 30 January 2012. Chapter 9 – Crowdsource: The Wisdom of the Masses Wutbürger as German word of the year: Full list available from German Language Society at http://www.gfds.de/aktionen

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$1 million prize: “Innovation Prizes – And the Winner Is,” Economist, 5 August 2010. Fiat builds first crowdsourced car: “The Case for Letting Customers Design Your Products,” Inc. Magazine, 20 September 2011. Prototype military vehicle crowdsourced: Based on interview with Ariel Ferreira of Local Motors. Steve Jobs on designing without focus groups: From

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York: Random House, 2007. Hewitt, Ben. The Town That Food Saved: How One Community Found Vitality in Local Food. New York: Rodale, 2009. Howe, Jeff. Crowdsourcing: How the Power of the Crowd Is Driving the Future of Business. London: Random House, 2008. Johnson, Steven. Where Good Ideas Come From: The Natural

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Rules for Revolutionaries: How Big Organizing Can Change Everything

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

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The Lucky Years: How to Thrive in the Brave New World of Health

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Wonderland: How Play Made the Modern World

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The Information: A History, a Theory, a Flood

by James Gleick  · 1 Mar 2011  · 855pp  · 178,507 words

The Glass Universe: How the Ladies of the Harvard Observatory Took the Measure of the Stars

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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)

by Stephanie Marie Seferian  · 19 Jan 2021

Beginners: The Joy and Transformative Power of Lifelong Learning

by Tom Vanderbilt  · 5 Jan 2021  · 312pp  · 92,131 words

Stuffocation

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Architects of Intelligence

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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

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Building the Cycling City: The Dutch Blueprint for Urban Vitality

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Humble Pi: A Comedy of Maths Errors

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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

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

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Filterworld: How Algorithms Flattened Culture

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The Passenger

by The Passenger  · 27 Dec 2021  · 202pp  · 62,397 words

Badvertising

by Andrew Simms  · 314pp  · 81,529 words

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by Wendy Liu  · 22 Mar 2020  · 223pp  · 71,414 words

Private Equity: A Memoir

by Carrie Sun  · 13 Feb 2024  · 267pp  · 90,353 words

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

by Rana Foroohar  · 16 May 2016  · 515pp  · 132,295 words

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

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

What's Yours Is Mine: Against the Sharing Economy

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

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Undoing the Demos: Neoliberalism's Stealth Revolution

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Surveillance Valley: The Rise of the Military-Digital Complex

by Yasha Levine  · 6 Feb 2018  · 474pp  · 130,575 words

Engineering Security

by Peter Gutmann

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

by Erik Brynjolfsson  · 23 Jan 2012  · 72pp  · 21,361 words

That Used to Be Us

by Thomas L. Friedman and Michael Mandelbaum  · 1 Sep 2011  · 441pp  · 136,954 words

Advertisers at Work

by Tracy Tuten  · 28 May 2012  · 411pp  · 127,755 words

NeuroTribes: The Legacy of Autism and the Future of Neurodiversity

by Steve Silberman  · 24 Aug 2015  · 786pp  · 195,810 words

Measure What Matters: How Google, Bono, and the Gates Foundation Rock the World With OKRs

by John Doerr  · 23 Apr 2018  · 280pp  · 71,268 words

Leonardo Da Vinci

by Walter Isaacson  · 16 Oct 2017  · 799pp  · 187,221 words

Give People Money

by Annie Lowrey  · 10 Jul 2018  · 242pp  · 73,728 words

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

by Pedro Domingos  · 21 Sep 2015  · 396pp  · 117,149 words

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

by Byron Reese  · 23 Apr 2018  · 294pp  · 96,661 words

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

by Frederic Laloux and Ken Wilber  · 9 Feb 2014  · 436pp  · 141,321 words

Lurking: How a Person Became a User

by Joanne McNeil  · 25 Feb 2020  · 239pp  · 80,319 words

How to Make a Spaceship: A Band of Renegades, an Epic Race, and the Birth of Private Spaceflight

by Julian Guthrie  · 19 Sep 2016

Raw Data Is an Oxymoron

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

by Joshua Hammer  · 18 Apr 2016  · 297pp  · 83,563 words

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

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

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

by Arvid Kahl  · 24 Jun 2020  · 461pp  · 106,027 words

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

by Jason Schreier  · 4 Sep 2017  · 297pp  · 90,806 words

Blueprint: The Evolutionary Origins of a Good Society

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

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

by Stuart Ritchie  · 20 Jul 2020

Whiteshift: Populism, Immigration and the Future of White Majorities

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

Protest and Power: The Battle for the Labour Party

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

Spineless: The Science of Jellyfish and the Art of Growing a Backbone

by Juli Berwald  · 14 May 2017  · 397pp  · 113,304 words

San Francisco Like a Local

by DK Eyewitness  · 4 Oct 2021  · 268pp  · 35,416 words

Heads I Win, Tails I Win

by Spencer Jakab  · 21 Jun 2016  · 303pp  · 84,023 words

Together

by Vivek H. Murthy, M.D.  · 5 Mar 2020  · 405pp  · 112,470 words

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

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A Bit of a Stretch: The Diaries of a Prisoner

by Chris Atkins  · 6 Feb 2020  · 335pp  · 98,847 words

Owning the Sun

by Alexander Zaitchik  · 7 Jan 2022  · 341pp  · 98,954 words

Butler to the World: How Britain Became the Servant of Tycoons, Tax Dodgers, Kleptocrats and Criminals

by Oliver Bullough  · 10 Mar 2022  · 257pp  · 80,698 words

The Soil Will Save Us

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Your Face Belongs to Us: A Secretive Startup's Quest to End Privacy as We Know It

by Kashmir Hill  · 19 Sep 2023  · 487pp  · 124,008 words

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

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The Stolen Year

by Anya Kamenetz  · 23 Aug 2022  · 347pp  · 103,518 words

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

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Merchants of the Right: Gun Sellers and the Crisis of American Democracy

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

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

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

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

by Bill Browder  · 11 Apr 2022  · 335pp  · 100,154 words

Before Babylon, Beyond Bitcoin: From Money That We Understand to Money That Understands Us (Perspectives)

by David Birch  · 14 Jun 2017  · 275pp  · 84,980 words

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

by Steven Johnson  · 28 Sep 2014  · 243pp  · 65,374 words

The Fourth Industrial Revolution

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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

by Thierry Poibeau  · 14 Sep 2017  · 174pp  · 56,405 words

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

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Winners Take All: The Elite Charade of Changing the World

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

by Bruce Schneier  · 3 Sep 2018  · 448pp  · 117,325 words

The Metric Society: On the Quantification of the Social

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

Radicalized

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

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

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

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

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

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

by Tanja Hester  · 12 Feb 2019  · 231pp  · 76,283 words

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

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DeFi and the Future of Finance

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Stake Hodler Capitalism: Blockchain and DeFi

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Androids: The Team That Built the Android Operating System

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The Loop: How Technology Is Creating a World Without Choices and How to Fight Back

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

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Limitarianism: The Case Against Extreme Wealth

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What If We Get It Right?: Visions of Climate Futures

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There Is No Place for Us: Working and Homeless in America

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Where Good Ideas Come from: The Natural History of Innovation

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

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Cooking for Geeks

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The Art of Community: Building the New Age of Participation

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Indelible City: Dispossession and Defiance in Hong Kong

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The Dark Net

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

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The Crash Detectives: Investigating the World's Most Mysterious Air Disasters

by Christine Negroni  · 26 Sep 2016  · 269pp  · 74,955 words

Site Reliability Engineering: How Google Runs Production Systems

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The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory

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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

What Went Wrong: How the 1% Hijacked the American Middle Class . . . And What Other Countries Got Right

by George R. Tyler  · 15 Jul 2013  · 772pp  · 203,182 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

Streetfight: Handbook for an Urban Revolution

by Janette Sadik-Khan  · 8 Mar 2016  · 441pp  · 96,534 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

The City Always Wins: A Novel

by Omar Robert Hamilton  · 12 Jun 2017  · 276pp  · 74,074 words

World Without Mind: The Existential Threat of Big Tech

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

The Future of War

by Lawrence Freedman  · 9 Oct 2017  · 592pp  · 161,798 words

New York 2140

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

Trick Mirror: Reflections on Self-Delusion

by Jia Tolentino  · 5 Aug 2019  · 305pp  · 101,743 words

The Twittering Machine

by Richard Seymour  · 20 Aug 2019  · 297pp  · 83,651 words

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

by Marc Randolph  · 16 Sep 2019  · 334pp  · 102,899 words

This Chair Rocks: A Manifiesto Against Ageism

by Ashton Applewhite  · 10 Feb 2016  · 312pp  · 84,421 words

Impact: Reshaping Capitalism to Drive Real Change

by Ronald Cohen  · 1 Jul 2020  · 276pp  · 59,165 words

Framers: Human Advantage in an Age of Technology and Turmoil

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Alpha Trader

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Reset

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The Awoken: A Novel

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Drunk on All Your Strange New Words

by Eddie Robson  · 27 Jun 2022  · 294pp  · 81,850 words

Win Every Argument: The Art of Debating, Persuading, and Public Speaking

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Everything Is Predictable: How Bayesian Statistics Explain Our World

by Tom Chivers  · 6 May 2024  · 283pp  · 102,484 words

The New Tourist: Waking Up to the Power and Perils of Travel

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Shocks, Crises, and False Alarms: How to Assess True Macroeconomic Risk

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The Future Was Now: Madmen, Mavericks, and the Epic Sci-Fi Summer Of 1982

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The Price of Life: In Search of What We're Worth and Who Decides

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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

by Ted Seides  · 23 Mar 2021  · 199pp  · 48,162 words

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

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

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

by Steve Lohr  · 10 Mar 2015  · 239pp  · 70,206 words

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

by Nathaniel Popper  · 18 May 2015  · 387pp  · 112,868 words

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

by Charles Arthur  · 3 Mar 2012  · 390pp  · 114,538 words

97 Things Every Programmer Should Know

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European Founders at Work

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Liars and Outliers: How Security Holds Society Together

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Kindle Fire: The Missing Manual

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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

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

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

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The End of Alchemy: Money, Banking and the Future of the Global Economy

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PostGIS in Action, 2nd Edition

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Nexus

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Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence

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

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Hello World: Being Human in the Age of Algorithms

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I'm Judging You: The Do-Better Manual

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Invisible Women

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

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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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Driverless: Intelligent Cars and the Road Ahead

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

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Spike: The Virus vs The People - The Inside Story

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These Strange New Minds: How AI Learned to Talk and What It Means

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