Tim Harford in the Financial Times:”Kickended is important. It reminds us that the world is biased in systematic ways…I’m sure I’m not the only person to ponder launching an exciting project on Kickstarter before settling back to count the money. Dean Augustin may have had the same idea back in 2011; he sought $12,000 to produce a documentary about John F Kennedy. Jonathan Reiter’s “BizzFit” looked to raise $35,000 to create an algorithmic matching service for employers and employees. This October, two brothers in Syracuse, New York, launched a Kickstarter campaign in the hope of being paid $400 to film themselves terrifying their neighbours at Halloween. These disparate campaigns have one thing in common: they received not a single penny of support. Not one of these people was able to persuade friends, colleagues or even their parents to kick in so much as a cent.
My inspiration for these tales of Kickstarter failure is Silvio Lorusso, an artist and designer based in Venice. Lorusso’s website, Kickended, searches Kickstarter for all the projects that have received absolutely no funding. (There are plenty: about 10 per cent of Kickstarter projects go nowhere at all, and only 40 per cent raise enough money to hit their funding targets.)
Kickended performs an important service. It reminds us that what we see around us is not representative of the world; it is biased in systematic ways. Normally, when we talk of bias we think of a conscious ideological slant. But many biases are simple and unconscious. I have never read a media report or blog post about a typical, representative Kickstarter campaign – but I heard a lot about the Pebble watch, the Coolest cooler and potato salad. If I didn’t know better, I might form unrealistic expectations about what running a Kickstarter campaign might achieve.
This isn’t just about Kickstarter. Such bias is everywhere. Most of the books people read are bestsellers – but most books are not bestsellers. And most book projects do not become books at all. There’s a similar story to tell about music, films and business ventures in general.
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In 1943, the American statistician Abraham Wald was asked to advise the US air force on how to reinforce their planes. Only a limited weight of armour plating was feasible, and the proposal on the table was to reinforce the wings, the centre of the fuselage, and the tail. Why? Because bombers were returning from missions riddled with bullet holes in those areas.
Wald explained that this would be a mistake. What the air force had discovered was that when planes were hit in the wings, tail or central fuselage, they made it home. Where, asked Wald, were the planes that had been hit in other areas? They never returned. Wald suggested reinforcing the planes wherever the surviving planes had been unscathed instead.
It’s natural to look at life’s winners – often they become winners in the first place because they’re interesting to look at. That’s why Kickended gives us an important lesson. If we don’t look at life’s losers too, we may end up putting our time, money, attention or even armour plating in entirely the wrong place.”
Macon Money: A serious game for civic engagement
Wilson Center Commons Lab: “In 2011, residents of Macon, Georgia received over $65,000 in free local currency—with a catch.
This money was locked in bonds redeemable for an unknown value between $10 and $100. Prior to circulation, each bond was cut in half. Residents of Macon wishing to “cash” their bonds were required to first find the missing half, held by an unknown community member.
These were the rules for Macon Money, a real-world game created by Area/Code Inc. in collaboration with several community partners. Benjamin Stokes was brought on board by the Knight Foundation as an advisor and researcher for the game. Stokes describes real-world games as activities where “playing the game is congruent with making impact in the world; making progress in the game, also does something in the real world.” Macon Money was designed to foster civic engagement through a number of means.
First, the two halves of each bond were intentionally distributed in neighborhoods on opposite ends of Macon, or in neighborhoods characterized by different socio-economic status. This “game mechanic” forced residents who would not normally interact to collaborate towards a common goal. Bond holders found each other through a designated website, social media platforms including Facebook and Twitter, and even serendipitous face-to-face interaction.
Bonds were redeemable for Macon Money, a currency that could only be spent at local businesses (which were reimbursed with U.S. currency). This ensured continuing engagement with the Macon community, and in some cases continuing engagement between players. Macon Money was also designed to foster community identity through the visual design of the currency itself. Macon dollars depicted symbols of communal value, such a picture of Otis Redding, a native of the town.
While the game Macon Money is over, researchers continue to analyze the how the game helped foster civic engagement within a local community. Most recently, Stokes described these impacts during a talk at American University co-sponsored by The American University Game Lab, the Series Games Initiative at the Woodrow Wilson International Center for Scholars, the AU Library, and the American University Center for Media and Social Impact. A video for the talk was recently posted here:…”
Wiser: Getting Beyond Groupthink to Make Groups Smarter
New publication by Reid Hastie and Cass Sunstein: “Why are group decisions so hard? Since the beginning of human history, people have made decisions in groups–first in families and villages, and now as part of companies, governments, school boards, religious organizations, or any one of countless other groups. And having more than one person to help decide is good because the group benefits from the collective knowledge of all of its members, and this results in better decisions. Right? Back to reality. We’ve all been involved in group decisions–and they’re hard. And they often turn out badly. Why? Many blame bad decisions on “groupthink” without a clear idea of what that term really means. Now, “Nudge” coauthor Cass Sunstein and leading decision-making scholar Reid Hastie shed light on the specifics of why and how group decisions go wrong–and offer tactics and lessons to help leaders avoid the pitfalls and reach better outcomes. In the first part of the book, they explain in clear and fascinating detail the distinct problems groups run into: They often amplify, rather than correct, individual errors in judgment; They fall victim to cascade effects, as members follow what others say or do; They become polarized, adopting more extreme positions than the ones they began with; They emphasize what everybody knows instead of focusing on critical information that only a few people know. In the second part of the book, the authors turn to straightforward methods and advice for making groups smarter. These approaches include silencing the leader so that the views of other group members can surface, rethinking rewards and incentives to encourage people to reveal their own knowledge, thoughtfully assigning roles that are aligned with people’s unique strengths, and more. With examples from a range of organizations–from Google to the CIA–and written in an engaging and witty style, “Wiser” will not only enlighten you; it will help your team and your organization make better decisions–decisions that lead to greater success.”
World Development Report 2015: Mind, Society, and Behavior
World Development Report (WorldBank): “Every policy relies on explicit or implicit assumptions about how people make choices. Those assumptions typically rest on an idealized model of how people think, rather than an understanding of how everyday thinking actually works. This year’s World Development Report argues that a more realistic account of decision-making and behavior will make development policy more effective. The Report emphasizes what it calls “the three marks of everyday thinking.” In everyday thinking, people use intuition much more than careful analysis. They employ concepts and tools that prior experience in their cultural world has made familiar. And social emotions and social norms motivate much of what they do. These insights together explain the extraordinary persistence of some social practices, and rapid change in others. They also offer new targets for development policy. A richer understanding of why people save, use preventive health care, work hard, learn, and conserve energy provides a basis for innovative and inexpensive interventions. The insights reveal that poverty not only deprives people of resources but is an environment that shapes decision making, a fact that development projects across the board need to recognize. The insights show that the psychological foundations of decision making emerge at a young age and require social support. The Report applies insights from modern behavioral and social sciences to development policies for addressing poverty, finance, productivity, health, children, and climate change. It demonstrates that new policy ideas based on a richer view of decision-making can yield high economic returns. These new policy targets include: • the choice architecture (for example, the default option) • the scope for social rewards • frames that influence whether or not a norm is activated • information in the form of rules of thumb • opportunities for experiences that change mental models or social norms Finally, the Report shows that small changes in context have large effects on behavior. As a result, discovering which interventions are most effective, and with which contexts and populations, inherently requires an experimental approach. Rigor is needed for testing the processes for delivering interventions, not just the products that are delivered…”
Big video data could change how we do everything — from catching bad guys to tracking shoppers
Sean Varah at VentureBeat: “Everyone takes pictures and video with their devices. Parents record their kids’ soccer games, companies record employee training, police surveillance cameras at busy intersections run 24/7, and drones monitor pipelines in the desert.
With vast amounts of video growing vaster at a rate faster than the day before, and the hottest devices like drones decreasing in price and size until everyone has one (OK, not in their pocket quite yet) it’s time to start talking about mining this mass of valuable video data for useful purposes.
Julian Mann, the cofounder of Skybox Imaging — a company in the business of commercial satellite imagery and the developer advocate for Google Earth outreach — says that the new “Skybox for Good” program will provide “a constantly updated model of change of the entire planet” with the potential to “save lives, protect the environment, promote education, and positively impact humanity.”…
Mining video data through “man + machine” artificial intelligence is new technology in search of unsolved problems. Could this be the next chapter in the ever-evolving technology revolution?
For the past 50 years, satellite imagery has only been available to the U.S. intelligence community and those countries with technology to launch their own. Digital Globe was one of the first companies to make satellite imagery available commercially, and now Skybox and a few others have joined them. Drones are even newer, having been used by the U.S. military since the ‘90s for surveillance over battlefields or, in this age of counter-terrorism, playing the role of aerial detectives finding bad guys in the middle of nowhere. Before drones, the same tasks required thousands of troops on the ground, putting many young men and women in harm’s way. Today, hundreds of trained “eyes” safely located here in the U.S. watch hours of video from a single drone to assess current situations in countries far away….”
Bringing the data revolution to education, and education to the data revolution
Pauline Rose at Post2015.org: “Calls for a data revolution are putting the spotlight on the importance of more and better data as a means to hold policymakers to account for post-2015 goals. In many ways, education has been at the forefront of approaches to measuring progress over the past 15 years. The influence of the Education for All Global Monitoring Report (GMR) and the efforts of the UNESCO Institute for Statistics (UIS) in improving the availability of education data provide important lessons for tracking progress post-2015. This experience should play an important contribution to informing the practical next steps for the data revolution.
Building on this experience, a roundtable held at the Overseas Development Institute on 17 November brought together over 40 technical experts, who debated approaches to measuring progress towards post-2015 education targets, with a focus on learning and equity. The meeting coincided with the launch of consultation on post-2015 education indicators by the Technical Advisory Group (TAG) to the EFA Steering Committee. As noted in the opening remarks on the data revolution by Neil Jackson, Chief Statistician at DFID, in many ways the education sector is leading the way in thinking about how to monitor post-2015 progress in concrete ways.
One of the problems that the GMR and UIS faced in tracking progress over the past 15 years was that indicators were not set at the time of deciding on education for all goals in 2000, hence the importance of the current consultation process. Another was that data have not been available a sufficiently disaggregated form to track progress on the most disadvantaged subgroups within each country, that is those most likely to be left behind. The GMR’s World Inequality Database on Education (WIDE), drawing on internationally-comparable household survey data, has been one step forward in presenting data in an accessible format to show that the poorest children living in rural areas, and often girls, are still far from completing primary school in many countries, and that many are also not learning the basics in reading and mathematics even if they have spent time in school….”
Using twitter to get ground truth on floods
Interview with Floodtags founder Jurjen Wagemaker at Global Pulse: “…Twtitter has proved to be a fantastic flood monitor tool and we encourage people to share even more of their flood experiences on Twitter. Now the difficult part is, to create the right flood filters and enrichments, so that disaster managers only need to look at a fraction of the hundreds of thousands of observations coming in.
So we enrich and analyse all flood data in real-time, and present them in an understandable format through our web service. A good example is the water depth of a flood. It turns out that a large number of people both mention the flood depth as well as the location where they monitored it. Take for instance January 29th, 2014: out of the 360.000 tweets we collected on floods, 15.000 included water depth observations (see picture). Together with the Dutch water management institute Deltares (@arnejanvl) we are working to develop a sound interpretation framework for these observations to create real-time floodmaps. For reference, to make a reliable floodmap of the January 2013 flood took a total of nine days. This was thanks to the hard work of the disaster management office and the HOT team (Humanitarian OpenStreetMap Team)….
We will launch the site at the upcoming Data Innovation for Policy Makers conference in Bali. And from that date onwards you can use Floodtags to get realtime flood information in Indonesia. Just go to Floodtags.com and sign-up. Especially when it rains it can become quite interesting: you can search for different neighbourhoods and see what people tweeted and how deep the water is. There is also a realtime tweet density map and you can request tweet statistics (e.g. figure 5, where we compare flood tweets with flood response tweets) – and we have got so much more to come. “
The Year of Data-Driven Government Accountability
in Pacific Standard: “Indeed, 2014 could be called the Year of Government Accountability, as voters on just about every continent have demanded that public officials govern with relentless efficiency, fiscal responsibility, and transparency….
The bottom line, in my view, is that facts must be the fundamental basis for critical and strategic decision-making at every level of government around the world today.
This belief—the foundation of massive technology and social movements, such as open data, big data, and data-driven government—is currently shared by a number of global government leaders. Just recently, for example, President Obama declared that “We must respond based on facts, not fear” when confronting the global Ebola crisis.
To be sure, presenting facts to decision-makers where and when they are needed is one of the most urgent technology priorities of our time. The good news is that we’re seeing progress on this front each and every day as civic organizations around the world rush to open their vast troves of data on the Internet and usher in a new era in data-driven government that will produce facts at the speed of light, and deliver them in context to political leaders, everyday citizens, professional academicians, scientists, journalists, and software developers wherever they are connected to the Web.
Data-driven government, which capitalizes on data, one of the most valuable natural resources of the 21st century, is a breakthrough opportunity of truly significant proportions. And it will be absolutely critical if governments everywhere are to achieve their ultimate mission. Without it, I worry that we just won’t be able to provide citizens with a higher quality of life and with greater opportunities to achieve their full potential.
The Paradox of Openness
New Book on Transparency and Participation in Nordic Cultures of Consensus, edited by Norbert Götz, Södertörn University, and Carl Marklund, Södertörn University: “The ‘open society’ has become a watchword of liberal democracy and the market system in the modern globalized world. Openness stands for individual opportunity and collective reason, as well as bottom-up empowerment and top-down transparency. It has become a cherished value, despite its vagueness and the connotation of vulnerability that surrounds it. Scandinavia has long considered itself a model of openness, citing traditions of freedom of information and inclusive policy making. This collection of essays traces the conceptual origins, development, and diverse challenges of openness in the Nordic countries and Austria. It examines some of the many paradoxes that openness encounters and the tensions it arouses when it addresses such divergent ends as democratic deliberation and market transactions, freedom of speech and sensitive information, compliant decision making and political and administrative transparency, and consensual procedures and the toleration of dissent.”
Big Data: The Key Vocabulary Everyone Should Understand
Bernard Marr at LinkedIn Pulse: “The field of Big Data requires more clarity and I am a big fan of simple explanations. This is why I have attempted to provide simple explanations for some of the most important technologies and terms you will come across if you’re looking at getting into big data.
Here they are:
Algorithm: A mathematical formula or statistical process run by software to perform an analysis of data. It usually consists of multiple calculations steps and can be used to automatically process data or solve problems.
Amazon Web Services: A collection of cloud computing services offered by Amazon to help businesses carry out large scale computing operations (such as big data projects) without having to invest in their own server farms and data storage warehouses. Essentially, Storage space, processing power and software operations are rented rather than having to be bought and installed from scratch.
Analytics: The process of collecting, processing and analyzing data to generate insights that inform fact-based decision-making. In many cases it involves software-based analysis using algorithms. For more, have a look at my post: What the Heck is… Analytics
Big Table: Google’s proprietary data storage system, which it uses to host, among other things its Gmail, Google Earth and Youtube services. It is also made available for public use through the Google App Engine.
Biometrics: Using technology and analytics to identify people by one or more of their physical traits, such as face recognition, iris recognition, fingerprint recognition, etc. For more, see my post: Big Data and Biometrics
Cassandra: A popular open source database management system managed by The Apache Software Foundation that has been designed to handle large volumes of data across distributed servers.
Cloud: Cloud computing, or computing “in the cloud”, simply means software or data running on remote servers, rather than locally. Data stored “in the cloud” is typically accessible over the internet, wherever in the world the owner of that data might be. For more, check out my post: What The Heck is… The Cloud?
Distributed File System: Data storage system designed to store large volumes of data across multiple storage devices (often cloud based commodity servers), to decrease the cost and complexity of storing large amounts of data.
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See also: Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance