DATA – Page 583 – The Living Library

Are We Puppets in a Wired World?

Curated on October 27, 2013May 29, 2019 by Stefaan Verhulst

Sue Halpern in The New York Review of Books: “Also not obvious was how the Web would evolve, though its open architecture virtually assured that it would. The original Web, the Web of static homepages, documents laden with “hot links,” and electronic storefronts, segued into Web 2.0, which, by providing the means for people without technical knowledge to easily share information, recast the Internet as a global social forum with sites like Facebook, Twitter, FourSquare, and Instagram.
Once that happened, people began to make aspects of their private lives public, letting others know, for example, when they were shopping at H+M and dining at Olive Garden, letting others know what they thought of the selection at that particular branch of H+M and the waitstaff at that Olive Garden, then modeling their new jeans for all to see and sharing pictures of their antipasti and lobster ravioli—to say nothing of sharing pictures of their girlfriends, babies, and drunken classmates, or chronicling life as a high-paid escort, or worrying about skin lesions or seeking a cure for insomnia or rating professors, and on and on.
The social Web celebrated, rewarded, routinized, and normalized this kind of living out loud, all the while anesthetizing many of its participants. Although they likely knew that these disclosures were funding the new information economy, they didn’t especially care…
The assumption that decisions made by machines that have assessed reams of real-world information are more accurate than those made by people, with their foibles and prejudices, may be correct generally and wrong in the particular; and for those unfortunate souls who might never commit another crime even if the algorithm says they will, there is little recourse. In any case, computers are not “neutral”; algorithms reflect the biases of their creators, which is to say that prediction cedes an awful lot of power to the algorithm creators, who are human after all. Some of the time, too, proprietary algorithms, like the ones used by Google and Twitter and Facebook, are intentionally biased to produce results that benefit the company, not the user, and some of the time algorithms can be gamed. (There is an entire industry devoted to “optimizing” Google searches, for example.)
But the real bias inherent in algorithms is that they are, by nature, reductive. They are intended to sift through complicated, seemingly discrete information and make some sort of sense of it, which is the definition of reductive.”
Books reviewed:

To Save Everything, Click Here: The Folly of Technological Solutionism

by Evgeny Morozov

PublicAffairs, 413 pp., $28.99

Hacking the Future: Privacy, Identity and Anonymity on the Web

by Cole Stryker

Overlook, 255 pp., $25.95

From Gutenberg to Zuckerberg: What You Really Need to Know About the Internet

by John Naughton

Quercus, 302 pp., $24.95

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

by Eric Siegel

Wiley, 302 pp., $28.00

Big Data: A Revolution That Will Transform How We Live, Work, and Think

by Viktor Mayer-Schönberger and Kenneth Cukier

Eamon Dolan/Houghton Mifflin Harcourt, 242 pp., $27.00

Status Update: Celebrity, Publicity, and Branding in the Social Media Age

by Alice E. Marwick

Yale University Press, 368 pp., $27.50

Privacy and Big Data: The Players, Regulators and Stakeholders

by Terence Craig and Mary E. Ludloff

O’Reilly Media, 108 pp., $19.99 (paper)

The "crowd computing" revolution

Curated on October 23, 2013December 6, 2018 by Stefaan Verhulst

Michael Copeland in the Atlantic: “Software might be eating the world, but Rob Miller, a professor of computer science at MIT, foresees a “crowd computing” revolution that makes workers and machines colleagues rather than competitors….
Miller studies human-computer interaction, specifically a field called crowd computing. A play on the more common term “cloud computing,” crowd computing is software that employs a group of people to do small tasks and solve a problem better than an algorithm or a single expert. Examples of crowd computing include Wikipedia, Amazon’s Mechanical Turk (where workers outsource projects that computers can’t do to an online community) a Facebook’s photo tagging feature.
But just as humans are better than computers at some things, Miller concedes that algorithms have surpassed human capability in several fields. Take a look at libraries, which now have advanced digital databases, eliminating the need for most human reference librarians. There’s also flight search, where algorithms are much better than people at finding the cheapest fare.
That said, more complicated tasks even in those fields can get tricky for a computer.
“For complex flight search, people are still better,” Miller says. A site called Flightfox lets travelers input a complex trip while a group of experts help find the cheapest or most convenient combination of flights. “There are travel agents and frequent flyers in that crowd, people with expertise at working angles of the airfare system that are not covered by the flight searches and may never be covered because they involve so many complex intersecting rules that are very hard to code.”
Social and cultural understanding is another area in which humans will always exceed computers, Miller says. People are constantly inventing new slang, watching the latest viral videos and movies, or partaking in some other cultural phenomena together. That’s something that an algorithm won’t ever be able to catch up to. “There’s always going to be a frontier of human understanding that leads the machines,” he says.
A post-employee economy where every task is automated by a computer is something Miller does not see happening, nor does he want it to happen. Instead, he considers the relationship between human and machine symbiotic. Both machines and humans benefit in crowd computing, “the machine wants to acquire data so it can train and get better. The crowd is improved in many ways, like through pay or education,” Miller says. And finally, the end users “get the benefit of a more accurate and fast answer.”
Miller’s User Interface Design Group at MIT has made several programs illustrating how this symbiosis between user, crowd and machine works. Most recently, the MIT group created Cobi, a tool that taps into an academic community to plan a large-scale conference. The software allows members to identify papers they want presented and what authors are experts in specific fields. A scheduling tool combines the community’s input with an algorithm that finds the best times to meet.
Programs more practical for everyday users include Adrenaline, a camera driven by a crowd, and Soylent, a word processing tool that allows people to do interactive document shortening and proofreading. The Adrenaline camera took a video and then had a crowd on call to very quickly identify the best still in that video, whether it was the best group portrait, mid-air jump, or angle of somebody’s face. Soylent also used users on Mechanical Turk to proofread and shorten text in Microsoft Word. In the process, Miller and his students found that the crowd found errors that neither a single expert proofreader nor the program—with spell and grammar check turned on—could find.
“It shows this is the essential thing that human beings bring that algorithms do not,” Miller said.
That said, you can’t just use any crowd for any task. “It does depend on having appropriate expertise in the crowd. If [the text] had been about computational biology, they might not have caught [the error]. The crowd does have to have skills.” Going forward, Miller thinks that software will increasingly use the power of the crowd. “In the next 10 or 20 years it will be more likely we already have a crowd,” he says. “There will already be these communities and they will have needs, some of which will be satisfied by software and some which will require human help and human attention. I think a lot of these algorithms and system techniques that are being developed by all these startups, who are experimenting with it in their own spaces, are going to be things that we’ll just naturally pick up and use as tools.”

A Data Revolution for Poverty Eradication

Curated on October 23, 2013August 3, 2018 by Stefaan Verhulst

Report from devint.org: “The High Level Panel on the Post–2015 Development Agenda called for a data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens. It recommended actively taking advantage of new technology, crowd sourcing, and improved connectivity to empower people with information on the progress towards the targets. Development Initiatives believes there a number of steps that should be put in place in order to deliver the ambition set out by the Panel.
The data revolution should be seen as a basis on which greater openness and a wider transparency revolution can be built. The openness movement – one of the most exciting and promising developments of the last decade – is starting to transform the citizen-state compact. Rich and developing country governments are adapting the way they do business, recognising that greater transparency and participation leads to more effective, efficient, and equitable management of scarce public resources. Increased openness of data has potential to democratise access to information, empowering individuals with the knowledge they need to tackle the problems that they face. To realise this bold ambition, the revolution will need to reach beyond the niche data and statistical communities, sell the importance of the revolution to a wide range of actors (governments, donors, CSOs and the media) and leverage the potential of open data to deliver more usable information”

7 Tactics for 21st-Century Cities

Curated on October 23, 2013August 3, 2018 by Stefaan Verhulst

Abhi Nemani, co-director of Code for America: “Be it the burden placed on them by shrinking federal support, or the opportunity presented by modern technology, 21st-century cities are finding new ways to do things. For four years, Code for America has worked with dozens of cities, each finding creative ways to solve neighborhood problems, build local capacity and steward a national network. These aren’t one-offs. Cities are championing fundamental, institutional reforms to commit to an ongoing innovation agenda.
Here are a few of the ways how:

…Create an office of new urban mechanics or appoint a chief innovation officer…
…Appoint a chief data officer or create an office of performance management/enhancement…
…Adopt the Gov.UK Design Principles, and require plain, human language on every interface….
…Share open source technology with a sister city or change procurement rules to make it easier to redeploy civic tech….
…Work with the local civic tech community and engage citizens for their feedback on city policy through events, tech and existing forums…
…Create an open data policy and adopt open data specifications…
…Attract tech talent into city leadership, and create training opportunities citywide to level up the tech literacy for city staff…”

From open data to open democracy

Curated on October 23, 2013August 15, 2018 by Stefaan Verhulst

Article by Jeffrey Roy: “Such debates further underscore the complexities of open data and where it might lead. While open data may be viewed by some inside and outside government as a technically-focused and largely incremental project based upon information formatting and accessibility (with the degree of openness subject to a myriad of security and confidentiality provisions), such an approach greatly limits its potential. Indeed, the growing ubiquity of mobile and smart devices, the advent of open source operating systems and social media platforms, and the growing commitment by governments themselves to expansive public engagement objectives, all suggest a widening scope.
Yet, what will incentivize the typical citizen to access open data and to partake in collective efforts to create public value? It is here where our digital culture may well fall short, emphasizing individualized service and convenience at the expense of civic responsibility and community-mindedness. For one American academic, this “citizenship deficit” erodes democratic legitimacy and renders our politics more polarized and less discursive. For other observers in Europe, notions of the digital divide are giving rise to new “data divides.”
The politics and practicalities of data privacy often bring further confusion. While privacy advocates call for greater protection and a culture of data activism among Internet users themselves, the networked ethos of online communities and commercialization fuels speed and sharing, often with little understanding of the ramifications of doing so. Differences between consumerism and citizenship are subtle yet profoundly important, while increasingly blurred and overlooked.
A key conundrum provincially and federally, within the Westminster confines of parliamentary democracy, is that open data is being hatched mainly from within the executive branch, whereas the legislative branch watches and withers. In devising genuine democratic openness, politicians and their parties must do more than post expenses online: they must become partners and advocates for renewal. A lesson of open source technology, however, is that systemic change demands an informed and engaged civil society, disgruntled with the status quo but also determined to act anew.
Most often, such actions are highly localized, even in a virtual world, giving rise to the purpose and meaning of smarter and more intelligent communities. And in Canada it bears noting that we see communities both large and small embracing open data and other forms of online experimentation such as participatory budgeting. It is often within small but connected communities where a virtuous cycle of online and in-person identities and actions can deepen and impact decision-making most directly.
How, then, do we reconcile traditional notions of top-down political federalism and national leadership with this bottom-up approach to community engagement and democratic renewal? Shifting from open data to open democracy is likely to be an uneven, diverse, and at times messy affair. Better this way than attempting to ordain top-down change in a centralized and standardized manner.”

Our Privacy Problem is a Democracy Problem in Disguise

Curated on October 23, 2013August 3, 2018 by Stefaan Verhulst

Evgeny Morozov in MIT Technology Review: “Intellectually, at least, it’s clear what needs to be done: we must confront the question not only in the economic and legal dimensions but also in a political one, linking the future of privacy with the future of democracy in a way that refuses to reduce privacy either to markets or to laws. What does this philosophical insight mean in practice?

First, we must politicize the debate about privacy and information sharing. Articulating the existence—and the profound political consequences—of the invisible barbed wire would be a good start. We must scrutinize data-intensive problem solving and expose its occasionally antidemocratic character. At times we should accept more risk, imperfection, improvisation, and inefficiency in the name of keeping the democratic spirit alive.
Second, we must learn how to sabotage the system—perhaps by refusing to self-track at all. If refusing to record our calorie intake or our whereabouts is the only way to get policy makers to address the structural causes of problems like obesity or climate change—and not just tinker with their symptoms through nudging—information boycotts might be justifiable. Refusing to make money off your own data might be as political an act as refusing to drive a car or eat meat. Privacy can then reëmerge as a political instrument for keeping the spirit of democracy alive: we want private spaces because we still believe in our ability to reflect on what ails the world and find a way to fix it, and we’d rather not surrender this capacity to algorithms and feedback loops.
Third, we need more provocative digital services. It’s not enough for a website to prompt us to decide who should see our data. Instead it should reawaken our own imaginations. Designed right, sites would not nudge citizens to either guard or share their private information but would reveal the hidden political dimensions to various acts of information sharing. We don’t want an electronic butler—we want an electronic provocateur. Instead of yet another app that could tell us how much money we can save by monitoring our exercise routine, we need an app that can tell us how many people are likely to lose health insurance if the insurance industry has as much data as the NSA, most of it contributed by consumers like us. Eventually we might discern such dimensions on our own, without any technological prompts.
Finally, we have to abandon fixed preconceptions about how our digital services work and interconnect. Otherwise, we’ll fall victim to the same logic that has constrained the imagination of so many well-meaning privacy advocates who think that defending the “right to privacy”—not fighting to preserve democracy—is what should drive public policy. While many Internet activists would surely argue otherwise, what happens to the Internet is of only secondary importance. Just as with privacy, it’s the fate of democracy itself that should be our primary goal.

Open Data and Open Government: Rethinking Telecommunications Policy and Regulation

Curated on October 23, 2013August 3, 2018 by Stefaan Verhulst

New paper by Ewan Sutherland: “While attention has been given to the uses of big data by network operators and to the provision of open data by governments, there has been no systematic attempt to re-examine the regulatory systems for telecommunications. The power of public authorities to access the big data held by operators could transform regulation by simplifying proof of bias or discrimination, making operators more susceptible to behavioural remedies, while it could also be used to deliver much finer granularity of decision making. By opening up data held by government and its agencies to enterprises, think tanks and research groups it should be possible to transform market regulation.“

The small-world effect is a modern phenomenon

Curated on October 21, 2013November 1, 2018 by Stefaan Verhulst

New paper by Seth A. Marvel, Travis Martin, Charles R. Doering, David Lusseau, M. E. J. Newman: “The “small-world effect” is the observation that one can find a short chain of acquaintances, often of no more than a handful of individuals, connecting almost any two people on the planet. It is often expressed in the language of networks, where it is equivalent to the statement that most pairs of individuals are connected by a short path through the acquaintance network. Although the small-world effect is well-established empirically for contemporary social networks, we argue here that it is a relatively recent phenomenon, arising only in the last few hundred years: for most of mankind’s tenure on Earth the social world was large, with most pairs of individuals connected by relatively long chains of acquaintances, if at all. Our conclusions are based on observations about the spread of diseases, which travel over contact networks between individuals and whose dynamics can give us clues to the structure of those networks even when direct network measurements are not available. As an example we consider the spread of the Black Death in 14th-century Europe, which is known to have traveled across the continent in well-defined waves of infection over the course of several years. Using established epidemiological models, we show that such wave-like behavior can occur only if contacts between individuals living far apart are exponentially rare. We further show that if long-distance contacts are exponentially rare, then the shortest chain of contacts between distant individuals is on average a long one. The observation of the wave-like spread of a disease like the Black Death thus implies a network without the small-world effect.”

Chicago: Increase and improve City data

Curated on October 21, 2013May 29, 2019 by Stefaan Verhulst

Initiative 14 of the Chicago Tech Plan: “The City will continue to increase and improve the quality of City data available internally and externally, and facilitate methods for analyzing that data to help create a smarter and more efficient city.”
Releasing data is a crucial component of creating an open and transparent government. Chicago is currently a leader in open data, capturing and publishing more than 400 machine-readable datasets to date. In 2012, Mayor Emanuel issued an executive order ensuring that the City continues to release new data, and empowering the Chief Data Officer to work with other City departments and agencies to develop new datasets. The City is following an aggressive schedule for releasing new datasets to the public and updating existing sets. It is also working to facilitate ways the City and others can use data to help improve City operations.
Chicago Shovels Plow Tracker
Source: https://web.archive.org/web/2000/https://www.chicago.gov/city/en/depts/mayor/iframe/plow_tracker.html

Open Data Success Story: ChicagoWorks
A collaboration between Alderman Ameya Pawar and local graphic design company 2pensmedia, ChicagoWorks is a free app that is changing the way Chicagoans interact with government. Using the app, residents can submit service requests directly to 311
and track the progress of reported issues. So far, more than 3,000 residents have downloaded the app.¹⁸

Open Data Success Story: SpotHero and Techstars Chicago
The app SpotHero makes residents’ lives easier by helping them find and reserve parking spots online. Developed in Chicago, the app had its start at Excelerate Labs, a Chicago start-up accelerator, now Techstars Chicago, that provides mentorship, training, and networking opportunities to 10 selected start-ups each year. After graduating from the program, ranked as one of the top 3 accelerators nationally, SpotHero attracted $2.5 million in VC funding. With this funding, the company is hiring new staff working to expand to other cities.¹⁹

Open Data Success Story: OpenGov Hack Night
Chicago boasts a community of “civic hackers” who are passionate about using technology to improve the city. An example of this passion in action is the OpenGov Hack Night. Organized by Open City, an organization that builds web apps and other tools using open government data, the Hack Night attracts civic hackers and curious residents eager to explore the intersection of open government data, smart cities, and technology. Every week, the Hack Night provides a collaborative environment for residents to learn about open data, working on cutting-edge projects and networking with passionate civic technologists.²⁰