Big Data’s Dangerous New Era of Discrimination

Curated on Posted on by Stefaan Verhulst

Michael Schrage in HBR blog: “Congratulations. You bought into Big Data and it’s paying off Big Time. You slice, dice, parse and process every screen-stroke, clickstream, Like, tweet and touch point that matters to your enterprise. You now know exactly who your best — and worst — customers, clients, employees and partners are.  Knowledge is power.  But what kind of power does all that knowledge buy?
Big Data creates Big Dilemmas. Greater knowledge of customers creates new potential and power to discriminate. Big Data — and its associated analytics — dramatically increase both the dimensionality and degrees of freedom for detailed discrimination. So where, in your corporate culture and strategy, does value-added personalization and segmentation end and harmful discrimination begin?
Let’s say, for example, that your segmentation data tells you the following:
Your most profitable customers by far are single women between the ages of 34 and 55 closely followed by “happily married” women with at least one child. Divorced women are slightly more profitable than “never marrieds.” Gay males — single and in relationships — are also disproportionately profitable. The “sweet spot” is urban and 28 to 50. These segments collectively account for roughly two-thirds of your profitability.  (Unexpected factoid: Your most profitable customers are overwhelmingly Amazon Prime subscriber. What might that mean?)
Going more granular, as Big Data does, offers even sharper ethno-geographic insight into customer behavior and influence:

  • Single Asian, Hispanic, and African-American women with urban post codes are most likely to complain about product and service quality to the company. Asian and Hispanic complainers happy with resolution/refund tend to be in the top quintile of profitability. African-American women do not.
  • Suburban Caucasian mothers are most likely to use social media to share their complaints, followed closely by Asian and Hispanic mothers. But if resolved early, they’ll promote the firm’s responsiveness online.
  • Gay urban males receiving special discounts and promotions are the most effective at driving traffic to your sites.

My point here is that these data are explicit, compelling and undeniable. But how should sophisticated marketers and merchandisers use them?
Campaigns, promotions and loyalty programs targeting women and gay males seem obvious. But should Asian, Hispanic and white females enjoy preferential treatment over African-American women when resolving complaints? After all, they tend to be both more profitable and measurably more willing to effectively use social media. Does it make more marketing sense encouraging African-American female customers to become more social media savvy? Or are resources better invested in getting more from one’s best customers? Similarly, how much effort and ingenuity flow should go into making more gay male customers better social media evangelists? What kinds of offers and promotions could go viral on their networks?…
Of course, the difference between price discrimination and discrimination positively correlated with gender, ethnicity, geography, class, personality and/or technological fluency is vanishingly small. Indeed, the entire epistemological underpinning of Big Data for business is that it cost-effectively makes informed segmentation and personalization possible…..
But the main source of concern won’t be privacy, per se — it will be whether and how companies and organizations like your own use Big Data analytics to justify their segmentation/personalization/discrimination strategies. The more effective Big Data analytics are in profitably segmenting and serving customers, the more likely those algorithms will be audited by regulators or litigators.
Tomorrow’s Big Data challenge isn’t technical; it’s whether managements have algorithms and analytics that are both fairly transparent and transparently fair. Big Data champions and practitioners had better be discriminating about how discriminating they want to be.”

The Age of ‘Infopolitics’

Curated on Posted on by Stefaan Verhulst

Colin Koopman in the New York Times: “We are in the midst of a flood of alarming revelations about information sweeps conducted by government agencies and private corporations concerning the activities and habits of ordinary Americans. After the initial alarm that accompanies every leak and news report, many of us retreat to the status quo, quieting ourselves with the thought that these new surveillance strategies are not all that sinister, especially if, as we like to say, we have nothing to hide.
One reason for our complacency is that we lack the intellectual framework to grasp the new kinds of political injustices characteristic of today’s information society. Everyone understands what is wrong with a government’s depriving its citizens of freedom of assembly or liberty of conscience. Everyone (or most everyone) understands the injustice of government-sanctioned racial profiling or policies that produce economic inequality along color lines. But though nearly all of us have a vague sense that something is wrong with the new regimes of data surveillance, it is difficult for us to specify exactly what is happening and why it raises serious concern, let alone what we might do about it.
Our confusion is a sign that we need a new way of thinking about our informational milieu. What we need is a concept of infopolitics that would help us understand the increasingly dense ties between politics and information. Infopolitics encompasses not only traditional state surveillance and data surveillance, but also “data analytics” (the techniques that enable marketers at companies like Target to detect, for instance, if you are pregnant), digital rights movements (promoted by organizations like the Electronic Frontier Foundation), online-only crypto-currencies (like Bitcoin or Litecoin), algorithmic finance (like automated micro-trading) and digital property disputes (from peer-to-peer file sharing to property claims in the virtual world of Second Life). These are only the tip of an enormous iceberg that is drifting we know not where.
Surveying this iceberg is crucial because atop it sits a new kind of person: the informational person. Politically and culturally, we are increasingly defined through an array of information architectures: highly designed environments of data, like our social media profiles, into which we often have to squeeze ourselves. The same is true of identity documents like your passport and individualizing dossiers like your college transcripts. Such architectures capture, code, sort, fasten and analyze a dizzying number of details about us. Our minds are represented by psychological evaluations, education records, credit scores. Our bodies are characterized via medical dossiers, fitness and nutrition tracking regimens, airport security apparatuses. We have become what the privacy theorist Daniel Solove calls “digital persons.” As such we are subject to infopolitics (or what the philosopher Grégoire Chamayou calls “datapower,” the political theorist Davide Panagia “datapolitik” and the pioneering thinker Donna Haraway “informatics of domination”).
Today’s informational person is the culmination of developments stretching back to the late 19th century. It was in those decades that a number of early technologies of informational identity were first assembled. Fingerprinting was implemented in colonial India, then imported to Britain, then exported worldwide. Anthropometry — the measurement of persons to produce identifying records — was developed in France in order to identify recidivists. The registration of births, which has since become profoundly important for initiating identification claims, became standardized in many countries, with Massachusetts pioneering the way in the United States before a census initiative in 1900 led to national standardization. In the same era, bureaucrats visiting rural districts complained that they could not identify individuals whose names changed from context to context, which led to initiatives to universalize standard names. Once fingerprints, biometrics, birth certificates and standardized names were operational, it became possible to implement an international passport system, a social security number and all other manner of paperwork that tells us who someone is. When all that paper ultimately went digital, the reams of data about us became radically more assessable and subject to manipulation, which has made us even more informational.
We like to think of ourselves as somehow apart from all this information. We are real — the information is merely about us. But what is it that is real? What would be left of you if someone took away all your numbers, cards, accounts, dossiers and other informational prostheses? Information is not just about you — it also constitutes who you are….”

The Moneyball Effect: How smart data is transforming criminal justice, healthcare, music, and even government spending

Curated on Posted on by Stefaan Verhulst

TED: “When Anne Milgram became the Attorney General of New Jersey in 2007, she was stunned to find out just how little data was available on who was being arrested, who was being charged, who was serving time in jails and prisons, and who was being released. It turns out that most big criminal justice agencies like my own didn’t track the things that matter,” she says in today’s talk, filmed at TED@BCG. “We didn’t share data, or use analytics, to make better decisions and reduce crime.”
Milgram’s idea for how to change this: “I wanted to moneyball criminal justice.”
Moneyball, of course, is the name of a 2011 movie starring Brad Pitt and the book it’s based on, written by Michael Lewis in 2003. The term refers to a practice adopted by the Oakland A’s general manager Billy Beane in 2002 — the organization began basing decisions not on star power or scout instinct, but on statistical analysis of measurable factors like on-base and slugging percentages. This worked exceptionally well. On a tiny budget, the Oakland A’s made it to the playoffs in 2002 and 2003, and — since then — nine other major league teams have hired sabermetric analysts to crunch these types of numbers.
Milgram is working hard to bring smart statistics to criminal justice. To hear the results she’s seen so far, watch this talk. And below, take a look at a few surprising sectors that are getting the moneyball treatment as well.

Moneyballing music. Last year, Forbes magazine profiled the firm Next Big Sound, a company using statistical analysis to predict how musicians will perform in the market. The idea is that — rather than relying on the instincts of A&R reps — past performance on Pandora, Spotify, Facebook, etc can be used to predict future potential. The article reads, “For example, the company has found that musicians who gain 20,000 to 50,000 Facebook fans in one month are four times more likely to eventually reach 1 million. With data like that, Next Big Sound promises to predict album sales within 20% accuracy for 85% of artists, giving labels a clearer idea of return on investment.”
Moneyballing human resources. In November, The Atlantic took a look at the practice of “people analytics” and how it’s affecting employers. (Billy Beane had something to do with this idea — in 2012, he gave a presentation at the TLNT Transform Conference called “The Moneyball Approach to Talent Management.”) The article describes how Bloomberg reportedly logs its employees’ keystrokes and the casino, Harrah’s, tracks employee smiles. It also describes where this trend could be going — for example, how a video game called Wasabi Waiter could be used by employers to judge potential employees’ ability to take action, solve problems and follow through on projects. The article looks at the ways these types of practices are disconcerting, but also how they could level an inherently unequal playing field. After all, the article points out that gender, race, age and even height biases have been demonstrated again and again in our current hiring landscape.
Moneyballing healthcare. Many have wondered: what about a moneyball approach to medicine? (See this call out via Common Health, this piece in Wharton Magazine or this op-ed on The Huffington Post from the President of the New York State Health Foundation.) In his TED Talk, “What doctors can learn from each other,” Stefan Larsson proposed an idea that feels like something of an answer to this question. In the talk, Larsson gives a taste of what can happen when doctors and hospitals measure their outcomes and share this data with each other: they are able to see which techniques are proving the most effective for patients and make adjustments. (Watch the talk for a simple way surgeons can make hip surgery more effective.) He imagines a continuous learning process for doctors — that could transform the healthcare industry to give better outcomes while also reducing cost.
Moneyballing government. This summer, John Bridgeland (the director of the White House Domestic Policy Council under President George W. Bush) and Peter Orszag (the director of the Office of Management and Budget in Barack Obama’s first term) teamed up to pen a provocative piece for The Atlantic called, “Can government play moneyball?” In it, the two write, “Based on our rough calculations, less than $1 out of every $100 of government spending is backed by even the most basic evidence that the money is being spent wisely.” The two explain how, for example, there are 339 federally-funded programs for at-risk youth, the grand majority of which haven’t been evaluated for effectiveness. And while many of these programs might show great results, some that have been evaluated show troubling results. (For example, Scared Straight has been shown to increase criminal behavior.) Yet, some of these ineffective programs continue because a powerful politician champions them. While Bridgeland and Orszag show why Washington is so averse to making data-based appropriation decisions, the two also see the ship beginning to turn around. They applaud the Obama administration for a 2014 budget with an “unprecendented focus on evidence and results.” The pair also gave a nod to the nonprofit Results for America, which advocates that for every $99 spent on a program, $1 be spent on evaluating it. The pair even suggest a “Moneyball Index” to encourage politicians not to support programs that don’t show results.
In any industry, figuring out what to measure, how to measure it and how to apply the information gleaned from those measurements is a challenge. Which of the applications of statistical analysis has you the most excited? And which has you the most terrified?”

Innovation in the Government Industry

Curated on Posted on by Stefaan Verhulst

in Huffington Post: “Government may be susceptible to the same forces that are currently changing many major industries. Software is eating government, too. Therefore government must use customer development to better serve customers else it risks becoming the next Blockbuster, Borders, or what the large publishing and financial services companies are at risk of becoming…
Government is currently one size fits all. In a free market, there is unblunding and multiple offerings for different segments of a market. For example there’s Natural Light, Budweiser, and Guinness. Competition forces companies to serve customers because if customers don’t like one offering they will simply choose a different one. If you don’t like your laundromat, restaurant, or job, you can simply go somewhere else. In contrast, switching governments is really hard.
Why Now
Government has been able to go a very long time without significant innovation. However now is the time for government to begin adapting because the forces changing nearly every industry may do the same to government. I will reiterate a few themes that Fred Wilson cited in a talk at LeWeb while talking about several different industries and add some more thoughts.
1. Organization: Technology driven networks replacing bureaucratic hierarchies
Bureaucratic hierarchies involve chains of command with lower levels of management making more detailed decisions and reporting back to higher levels of management. These systems often entail long communication lags, high costs, and principal/agent problems.
Technology driven networks are providing more efficient systems for organization and communication. For example, Amazon has changed the publishing industry by enabling anyone to publish content and enabling customers to decide what they want. Twitter has created a network around communication and news, enabling anyone who people want to hear to be heard.
2. Competition: Unbundling of product and service offerings
Technology advancements have made it cheaper and easier than ever before to produce a product and bring it to market. One result is that it’s become easier for an entrepreneur to provide one offering of a larger offering as a standalone offering. It provides customers with the option to buy what they want without having to pay more for stuff they don’t want. In addition, the offerings can be improved because producers are completely focused on that specific offering. For example, we used to buy one newspaper and get world, local, sports, etc. Now it’s all from different sources.
Bundling exists because it was more efficient than attempting to contract in the market for every tiny service. However some of the technology driven networks (as described above) are helping markets become more efficient and giving customers more customizable buying options. For example, you can buy a half hour of education, or borrow money from a peer.
We’re starting to see some of the governments offerings begin to be unbundled. For example, Uber and Hyperloop are providing transportation. A neighborhood in Oakland crowdfunded private security.
3. Finance: Lower payment transaction fees and crowdfunding
Innovation in payments, including Bitcoin, has made it cheaper and easier than ever to transfer money. It’s as easy as sending an email, clicking a hyperlink, or scanning a QR code. In addition, Bitcoin is not controlled by any regulators or intermediaries like the government, credit card companies, or even PayPal.
Crowdfunding enables the collective efforts of individuals to connect and pool their money to back initiatives, make purchases, or fund new projects. A school in Houston crowdfunded some exercise equipment instead of using government funding.
4. Communication: We are all connected and graphed
Mobile devices have become nearly as powerful as desktops or laptops. There are many things we can do with our phone that we can’t do on our desktop/laptop. For example, smartphones have sensors, are location aware, can be carried with us at all times, and are cheaper than desktops or laptops. These factors have lead to mass adoption of mobile devices across the world, including in countries with high poverty where people could not previously afford a desktop or laptop. Mobile is making innovative offerings like Uber and mobile payments possible.
Platforms like Facebook and Twitter provide everyone with access to millions of people. In addition, companies like Klout and Quora are measuring our reputation and social graph improving our ability to transact with each other. For example, when market participants trust one another (through the vehicle of a reputation system) many transactions that wouldn’t otherwise happen can now happen.This illustrated in the rise in popularity of collaborative consumption platforms and peer to peer marketplaces.
Serving Customers
The current government duopoly inhibits us from selecting the government that we want as well as from receiving the best possible service because of lack of incentive. However the technologies described above are making it possible to get services previously provided by the government through more efficient and effective means. They’re enabling a more free market for government services….
If government were to take the customer development route, it could try things like unbundling (see above) so that people could opt for the specific solutions they desire. Given the US government’s current balance sheet, it may actually need to start relying on other providers.
It could also rely more on “economic feedback” to inform its actions. Currently economic feedback is given through voting. Most people vote once every two or four years and then hope they get what they “paid” for. Can you imagine paying for a college without knowing which one you would be going to, know what they would be providing, or being able to request a refund or switch colleges? With more economic incentive, services would need to improve. For example, if there was a free market for roads, people would pay for and use the roads that were most safe.”

Google Hangouts vs Twitter Q&As: how the US and Europe are hacking traditional diplomacy

Curated on Posted on by Stefaan Verhulst

Wired (UK): “We’re not yet sure if diplomacy is going digital or just the conversations we’re having,” Moira Whelan, Deputy Assistant Secretary for Digital Strategy, US Department of State, admitted on stage at TedxStockholm. “Sometimes you just have to dive in, and we’re going to, but we’re not really sure where we’re going.”
The US has been at the forefront of digital diplomacy for many years now. President Obama was the first leader to sign up to Twitter, and has amassed the greatest number of followers among his peers at nearly 41 million. The account is, however, mainly run by his staff. It’s understandable, but demonstrates that there still remains a diplomatic disconnect in a country Whelan says knows it’s “ready, leading the conversation and on cutting edge”.
In Europe  Swedish Minister for Foreign Affairs Carl Bildt, on the other hand, carries out regular Q&As on the social network and is regarded as one of the most conversational leaders on Twitter and the best connected, according to annual survey Twiplomacy. Our own William Hague is chasing Bildt with close to 200,000 followers, and is the world’s second most connected Foreign Minister, while David Cameron is active on a daily basis with more than 570,000 followers. London was in fact the first place to host a “Diplohack”, an event where ambassadors are brought together with developers and others to hack traditional diplomacy, and Whelan travelled to Sweden to take place in the third European event, the Stockholm Initiative for Digital Diplomacy held 16-17 January in conjunction with TedxStockholm.
Nevertheless, Whelan, who has worked for the state for a decade, says the US is in the game and ready to try new things. Case in point being its digital diplomacy reaction to the crisis in Syria last year.
“In August 2013 we witnessed tragic events in Syria, and obviously the President of the United States and his security team jumped into action,” said Whelan. “We needed to bear witness and… very clearly saw the need for one thing — a Google+ Hangout.” With her tongue-in-cheek comment, Whelan was pointing out social media’s incredibly relevant role in communicating to the public what’s going on when crises hit, and in answering concerns and questions through it.
“We saw speeches and very disturbing images coming at us,” continued Whelan. “We heard leaders making impassioned speeches, and we ourselves had conversations about what we were seeing and how we needed to engage and inform; to give people the chance to engage and ask questions of us.
“We thought, clearly let’s have a Google+ Hangout. Three people joined us and Secretary John Kerry — Nicholas Kirstof of the New York Times, executive editor of Syria Deeply, Lara Setrakian and Andrew Beiter, a teacher affiliated with the Holocaust Memorial Museum who specialises in how we talk about these topics with our children.”
In the run up to the Hangout, news of the event trickled out and soon Google was calling, asking if it could advertise the session at the bottom of other Hangouts, then on YouTube ads. “Suddenly 15,000 people were watching the Secretary live — that’s by far largest number we’d seen. We felt we’d tapped into something, we knew we’d hit success at what was a challenging time. We were engaging the public and could join with them to communicate a set of questions. People want to ask questions and get very direct answers, and we know it’s a success. We’ve talked to Google about how we can replicate that. We want to transform what we’re doing to make that the norm.”
Secretary of State John Kerry is, Whelan told Wired.co.uk later, “game for anything” when it comes to social media — and having the department leader enthused at the prospect of taking digital diplomacy forward is obviously key to its success.
“He wanted us to get on Instagram and the unselfie meme during the Philippines crisis was his idea — an assistant had seen it and he held a paper in front of him with the URL to donate funds to Typhoon Haiyan victims,” Whelan told Wired.co.uk at the Stockholm diplohack.  “President Obama came in with a mandate that social media would be present and pronounced in all our departments.”
“[As] government changes and is more influenced away from old paper models and newspapers, suspenders and bow ties, and more into young innovators wanting to come in and change things,” Whelan continued, “I think it will change the way we work and help us get smarter.”

Use big data and crowdsourcing to detect nuclear proliferation, says DSB

Curated on Posted on by Stefaan Verhulst

FierceGovernmentIT: “A changing set of counter-nuclear proliferation problems requires a paradigm shift in monitoring that should include big data analytics and crowdsourcing, says a report from the Defense Science Board.
Much has changed since the Cold War when it comes to ensuring that nuclear weapons are subject to international controls, meaning that monitoring in support of treaties covering declared capabilities should be only one part of overall U.S. monitoring efforts, says the board in a January report (.pdf).
There are challenges related to covert operations, such as testing calibrated to fall below detection thresholds, and non-traditional technologies that present ambiguous threat signatures. Knowledge about how to make nuclear weapons is widespread and in the hands of actors who will give the United States or its allies limited or no access….
The report recommends using a slew of technologies including radiation sensors, but also exploitation of digital sources of information.
“Data gathered from the cyber domain establishes a rich and exploitable source for determining activities of individuals, groups and organizations needed to participate in either the procurement or development of a nuclear device,” it says.
Big data analytics could be used to take advantage of the proliferation of potential data sources including commercial satellite imaging, social media and other online sources.
The report notes that the proliferation of readily available commercial satellite imagery has created concerns about the introduction of more noise than genuine signal. “On balance, however, it is the judgment from the task force that more information from remote sensing systems, both commercial and dedicated national assets, is better than less information,” it says.
In fact, the ready availability of commercial imagery should be an impetus of governmental ability to find weak signals “even within the most cluttered and noisy environments.”
Crowdsourcing also holds potential, although the report again notes that nuclear proliferation analysis by non-governmental entities “will constrain the ability of the United States to keep its options open in dealing with potential violations.” The distinction between gathering information and making political judgments “will erode.”
An effort by Georgetown University students (reported in the Washington Post in 2011) to use open source data analyzing the network of tunnels used in China to hide its missile and nuclear arsenal provides a proof-of-concept on how crowdsourcing can be used to augment limited analytical capacity, the report says – despite debate on the students’ work, which concluded that China’s arsenal could be many times larger than conventionally accepted…
For more:
– download the DSB report, “Assessment of Nuclear Monitoring and Verification Technologies” (.pdf)
– read the WaPo article on the Georgetown University crowdsourcing effort”

The Power to Decide

Curated on Posted on by Stefaan Verhulst

Special Report by Antonio Regalado in MIT Technology Review: “Back in 1956, an engineer and a mathematician, William Fair and Earl Isaac, pooled $800 to start a company. Their idea: a score to handicap whether a borrower would repay a loan.
It was all done with pen and paper. Income, gender, and occupation produced numbers that amounted to a prediction about a person’s behavior. By the 1980s the three-digit scores were calculated on computers and instead took account of a person’s actual credit history. Today, Fair Isaac Corp., or FICO, generates about 10 billion credit scores annually, calculating 50 times a year for many Americans.
This machinery hums in the background of our financial lives, so it’s easy to forget that the choice of whether to lend used to be made by a bank manager who knew a man by his handshake. Fair and Isaac understood that all this could change, and that their company didn’t merely sell numbers. “We sell a radically different way of making decisions that flies in the face of tradition,” Fair once said.
This anecdote suggests a way of understanding the era of “big data”—terabytes of information from sensors or social networks, new computer architectures, and clever software. But even supercharged data needs a job to do, and that job is always about a decision.
In this business report, MIT Technology Review explores a big question: how are data and the analytical tools to manipulate it changing decision making today? On Nasdaq, trading bots exchange a billion shares a day. Online, advertisers bid on hundreds of thousands of keywords a minute, in deals greased by heuristic solutions and optimization models rather than two-martini lunches. The number of variables and the speed and volume of transactions are just too much for human decision makers.
When there’s a person in the loop, technology takes a softer approach (see “Software That Augments Human Thinking”). Think of recommendation engines on the Web that suggest products to buy or friends to catch up with. This works because Internet companies maintain statistical models of each of us, our likes and habits, and use them to decide what we see. In this report, we check in with LinkedIn, which maintains the world’s largest database of résumés—more than 200 million of them. One of its newest offerings is University Pages, which crunches résumé data to offer students predictions about where they’ll end up working depending on what college they go to (see “LinkedIn Offers College Choices by the Numbers”).
These smart systems, and their impact, are prosaic next to what’s planned. Take IBM. The company is pouring $1 billion into its Watson computer system, the one that answered questions correctly on the game show Jeopardy! IBM now imagines computers that can carry on intelligent phone calls with customers, or provide expert recommendations after digesting doctors’ notes. IBM wants to provide “cognitive services”—computers that think, or seem to (see “Facing Doubters, IBM Expands Plans for Watson”).
Andrew Jennings, chief analytics officer for FICO, says automating human decisions is only half the story. Credit scores had another major impact. They gave lenders a new way to measure the state of their portfolios—and to adjust them by balancing riskier loan recipients with safer ones. Now, as other industries get exposed to predictive data, their approach to business strategy is changing, too. In this report, we look at one technique that’s spreading on the Web, called A/B testing. It’s a simple tactic—put up two versions of a Web page and see which one performs better (see “Seeking Edge, Websites Turn to Experiments” and “Startups Embrace a Way to Fail Fast”).
Until recently, such optimization was practiced only by the largest Internet companies. Now, nearly any website can do it. Jennings calls this phenomenon “systematic experimentation” and says it will be a feature of the smartest companies. They will have teams constantly probing the world, trying to learn its shifting rules and deciding on strategies to adapt. “Winners and losers in analytic battles will not be determined simply by which organization has access to more data or which organization has more money,” Jennings has said.

Of course, there’s danger in letting the data decide too much. In this report, Duncan Watts, a Microsoft researcher specializing in social networks, outlines an approach to decision making that avoids the dangers of gut instinct as well as the pitfalls of slavishly obeying data. In short, Watts argues, businesses need to adopt the scientific method (see “Scientific Thinking in Business”).
To do that, they have been hiring a highly trained breed of business skeptics called data scientists. These are the people who create the databases, build the models, reveal the trends, and, increasingly, author the products. And their influence is growing in business. This could be why data science has been called “the sexiest job of the 21st century.” It’s not because mathematics or spreadsheets are particularly attractive. It’s because making decisions is powerful…”

Citizen roles in civic problem-solving and innovation

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Satish Nambisan: “Can citizens be fruitfully engaged in solving civic problems? Recent initiatives in cities such as Boston (Citizens Connect), Chicago (Smart Chicago Collaborative), San Francisco (ImproveSF) and New York (NYC BigApps) indicate that citizens can be involved in not just identifying and reporting civic problems but in conceptualizing, designing and developing, and implementing solutions as well.
The availability of new technologies (e.g. social media) has radically lowered the cost of collaboration and the “distance” between government agencies and the citizens they serve. Further involving citizens — who are often closest to and possess unique knowledge about the problems they face — makes a lot of sense given the increasing complexity of the problems that need to be addressed.
A recent research report that I wrote highlights four distinct roles that citizens can play in civic innovation and problem-solving.
As explorer, citizens can identify and report emerging and existing civic problems. For example, Boston’s Citizen Connect initiative enables citizens to use specially built smartphone apps to report minor and major civic problems (from potholes and graffiti to water/air pollution). Closer to home, both Wisconsin and Minnesota have engaged thousands of citizen volunteers in collecting data on the quality of water in their neighborhood streams, lakes and rivers (the data thus gathered are analyzed by the state pollution control agency). Citizens also can be engaged in data analysis. The N.Y.-based Datakind initiative involves citizen volunteers using their data analysis skills to mine public data in health, education, environment, etc., to identify important civic issues and problems.
As “ideator,”citizens can conceptualize novel solutions to well-defined problems in public services. For example, the federal government’s Challenge.gov initiative employs online contests and competitions to solicit innovative ideas from citizens to solve important civic problems. Such “crowdsourcing” initiatives also have been launched at the county, city and state levels (e.g. Prize2theFuture competition in Birmingham, Ala.; ImproveSF in San Francisco).
As designer, citizens can design and/or develop implementable solutions to well-defined civic problems. For example, as part of initiatives such as NYC Big Apps and Apps for California, citizens have designed mobile apps to address specific issues such as public parking availability, public transport delays, etc. Similarly, the City Repair project in Portland, Ore., focuses on engaging citizens in co-designing and creatively transforming public places into sustainable community-oriented urban spaces.
As diffuser,citizens can play the role of a change agent and directly support the widespread adoption of civic innovations and solutions. For example, in recent years, physicians interacting with peer physicians in dedicated online communities have assisted federal and state government agencies in diffusing health technology innovations such as electronic medical record systems (EMRs).
In the private sector, companies across industries have benefited much from engaging with their customers in innovation. Evidence so far suggests that the benefits from citizen engagement in civic problem-solving are equally tangible, valuable and varied. However, the challenges associated with organizing such citizen co-creation initiatives are also many and imply the need for government agencies to adopt an intentional, well-thought-out approach….”

Social Media: A Critical Introduction

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New book: “Now more than ever, we need to understand social media – the good as well as the bad. We need critical knowledge that helps us to navigate the controversies and contradictions of this complex digital media landscape. Only then can we make informed judgements about what’s
happening in our media world, and why.
Showing the reader how to ask the right kinds of questions about social media, Christian Fuchs takes us on a journey across social media,
delving deep into case studies on Google, Facebook, Twitter, WikiLeaks and Wikipedia. The result lays bare the structures and power relations
at the heart of our media landscape.
This book is the essential, critical guide for understanding social media and for all students of media studies and sociology. Readers will
never look at social media the same way again.
Sample chapter:
Twitter and Democracy: A New Public Sphere?
Introduction: What is a Critical Introduction to Social Media?“

How Internet surveillance predicts disease outbreak before WHO

Curated on Posted on by Stefaan Verhulst

Kurzweil News: “Have you ever Googled for an online diagnosis before visiting a doctor? If so, you may have helped provide early warning of an infectious disease epidemic.
In a new study published in Lancet Infectious Diseases, Internet-based surveillance has been found to detect infectious diseases such as Dengue Fever and Influenza up to two weeks earlier than traditional surveillance methods, according to Queensland University of Technology (QUT) research fellow and senior author of the paper Wenbiao Hu.
Hu, based at the Institute for Health and Biomedical Innovation, said there was often a lag time of two weeks before traditional surveillance methods could detect an emerging infectious disease.
“This is because traditional surveillance relies on the patient recognizing the symptoms and seeking treatment before diagnosis, along with the time taken for health professionals to alert authorities through their health networks. In contrast, digital surveillance can provide real-time detection of epidemics.”
Hu said the study used search engine algorithms such as Google Trends and Google Insights. It found that detecting the 2005–06 avian influenza outbreak “Bird Flu” would have been possible between one and two weeks earlier than official surveillance reports.
“In another example, a digital data collection network was found to be able to detect the SARS outbreak more than two months before the first publications by the World Health Organization (WHO),” Hu said.
According to this week’s CDC FluView report published Jan. 17, 2014, influenza activity in the United States remains high overall, with 3,745 laboratory-confirmed influenza-associated hospitalizations reported since October 1, 2013 (credit: CDC)
“Early detection means early warning and that can help reduce or contain an epidemic, as well alert public health authorities to ensure risk management strategies such as the provision of adequate medication are implemented.”
Hu said the study found that social media including Twitter and Facebook and microblogs could also be effective in detecting disease outbreaks. “The next step would be to combine the approaches currently available such as social media, aggregator websites, and search engines, along with other factors such as climate and temperature, and develop a real-time infectious disease predictor.”
“The international nature of emerging infectious diseases combined with the globalization of travel and trade, have increased the interconnectedness of all countries and that means detecting, monitoring and controlling these diseases is a global concern.”
The other authors of the paper were Gabriel Milinovich (first author), Gail Williams and Archie Clements from the University of Queensland School of Population, Health and State.
Supramap 
Another powerful tool is Supramap, a web application that synthesizes large, diverse datasets so that researchers can better understand the spread of infectious diseases across hosts and geography by integrating genetic, evolutionary, geospatial, and temporal data. It is now open-source — create your own maps here.
Associate Professor Daniel Janies, Ph.D., an expert in computational genomics at the Wexner Medical Center at The Ohio State University (OSU), worked with software engineers at the Ohio Supercomputer Center (OSC) to allow researchers and public safety officials to develop other front-end applications that draw on the logic and computing resources of Supramap.
It was originally developed in 2007 to track the spread and evolution of pandemic (H1N1) and avian influenza (H5N1).
“Using SUPRAMAP, we initially developed maps that illustrated the spread of drug-resistant influenza and host shifts in H1N1 and H5N1 influenza and in coronaviruses, such as SARS,” said Janies. “SUPRAMAP allows the user to track strains carrying key mutations in a geospatial browser such as Google Earth. Our software allows public health scientists to update and view maps on the evolution and spread of pathogens.”
Grant funding through the U.S. Army Research Laboratory and Office supports this Innovation Group on Global Infectious Disease Research project. Support for the computational requirements of the project comes from  the American Museum of Natural History (AMNH) and OSC. Ohio State’s Wexner Medical Center, Department of Biomedical Informatics and offices of Academic Affairs and Research provide additional support.”
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