Erika G. Martin, Natalie Helbig, and Nirav R. Shah on New York’s Open Data Experience in JAMA: “The health community relies on governmental survey, surveillance, and administrative data to track epidemiologic trends, identify risk factors, and study the health care delivery system. Since 2009, a quiet “open data” revolution has occurred. Catalyzed by President Obama’s open government directive, federal, state, and local governments are releasing deidentified data meeting 4 “open” criteria: public accessibility, availability in multiple formats, free of charge, and unlimited use and distribution rights.1 As of February 2014, HealthData.gov, the federal health data repository, has more than 1000 data sets, and Health Data NY, New York’s health data site, has 48 data sets with supporting charts and maps. Data range from health interview surveys to administrative transactions. The implicit logic is that making governmental data readily available will improve government transparency; increase opportunities for research, mobile health application development, and data-driven quality improvement; and make health-related information more accessible. Together, these activities have the potential to improve health care quality, reduce costs, facilitate population health planning and monitoring, and empower health care consumers to make better choices and live healthier lives.”
Is Crowdsourcing the Future for Legislation?
Brian Heaton in GovTech: “…While drafting legislation is traditionally the job of elected officials, an increasing number of lawmakers are using digital platforms such as Wikispaces and GitHub to give constituents a bigger hand in molding the laws they’ll be governed by. The practice has been used this year in both California and New York City, and shows no signs of slowing down anytime soon, experts say.
Trond Undheim, crowdsourcing expert and founder of Yegii Inc., a startup company that provides and ranks advanced knowledge assets in the areas of health care, technology, energy and finance, said crowdsourcing was “certainly viable” as a tool to help legislators understand what constituents are most passionate about.
“I’m a big believer in asking a wide variety of people the same question and crowdsourcing has become known as the long-tail of answers,” Undheim said. “People you wouldn’t necessarily think of have something useful to say.”
California Assemblyman Mike Gatto, D-Los Angeles, agreed. He’s spearheaded an effort this year to let residents craft legislation regarding probate law — a measure designed to allow a court to assign a guardian to a deceased person’s pet. Gatto used the online Wikispaces platform — which allows for Wikipedia-style editing and content contribution — to let anyone with an Internet connection collaborate on the legislation over a period of several months.
The topic of the bill may not have been headline news, but Gatto was encouraged by the media attention his experiment received. As a result, he’s committed to running another crowdsourced bill next year — just on a bigger, more mainstream public issue.
New York City Council Member Ben Kallos has a plethora of technology-related legislation being considered in the Big Apple. Many of the bills are open for public comment and editing on GitHub. In an interview with Government Technology last month, Kallos said he believes using crowdsourcing to comment on and edit legislation is empowering and creates a different sense of democracy where people can put forward their ideas.
County governments also are joining the crowdsourcing trend. The Catawba Regional Council of Governments in South Carolina and the Centralia Council of Governments in North Carolina are gathering opinions on how county leaders should plan for future growth in the region.
At a public forum earlier this year, attendees were given iPads to go online and review four growth options and record their views on which they preferred. The priorities outlined by citizens will be taken back to decision-makers in each of the counties to see how well existing plans match up with what the public wants.
Gatto said he’s encouraged by how quickly the crowdsourcing of policy has spread throughout the U.S. He said there’s a disconnect between governments and their constituencies who believe elected officials don’t listen. But that could change as crowdsourcing continues to make its impact on lawmakers.
“When you put out a call like I did and others have done and say ‘I’m going to let the public draft a law and whatever you draft, I’m committed to introducing it … I think that’s a powerful message,” Gatto said. “I think the public appreciates it because it makes them understand that the government still belongs to them.”
Protecting the Process
Despite the benefits crowdsourcing brings to the legislative process, there remain some question marks about whether it truly provides insight into the public’s feelings on an issue. For example, because many political issues are driven by the influence of special interest groups, what’s preventing those groups from manipulating the bill-drafting process?
Not much, according to Undheim. He cautioned policymakers to be aware of the motivations from people taking part in crowdsourcing efforts to write and edit laws. Gatto shared Undheim’s concerns, but noted that the platform he used for developing his probate law – Wikispaces – has safeguards in place so that a member of his staff can revert language of a crowdsourced bill back to a previous version if it’s determined that someone was trying to unduly influence the drafting process….”
Participant Index Seeks to Determine Why One Film Spurs Activism, While Others Falter
in the New York Times: “You watched the wrenching documentary. You posted your outrage on Twitter. But are you good for more than a few easy keystrokes of hashtag activism?
Participant Media and some powerful partners need to know.
For the last year Participant, an activist entertainment company that delivers movies with a message, has been quietly working with the Bill & Melinda Gates Foundation, the Knight Foundation and the University of Southern California’s Annenberg School for Communication and Journalism to answer a question vexing those who would use media to change the world.
That is, what actually gets people moving? Do grant-supported media projects incite change, or are they simply an expensive way of preaching to the choir?…
To get the answers it wants, Participant is developing a measuring tool that it calls the Participant Index, assisted in the effort by the Annenberg school’s Media Impact Project. In rough parallel to the Nielsen television ratings, the still-evolving index compiles raw audience numbers for issue-driven narrative films, documentaries, television programs and online short videos, along with measures of conventional and social media activity, including Twitter and Facebook presence.
The two measures are then matched with the results of an online survey, about 25 minutes long, that asks as many as 350 viewers of each project an escalating set of questions about their emotional response and level of engagement.
Did it affect you emotionally? Did you share information about it? Did you boycott a product or company? Did it change your life?
“If this existed, we would not be doing it,” said James G. Berk, chief executive of Participant. “We desperately need more and more information, to figure out if what we were doing is actually working.”
The answers result in a score that combines separate emotional and behavioral measures. On a scale of 100, for instance, “The Square,” a documentary about Egyptian political upheaval that was included in Participant’s first echelon of 35 indexed titles this year, scored extremely high for emotional involvement, with a 97, but lower in terms of provoking action, with an 87, for a combined average of 92.
By contrast, “Farmed and Dangerous,” a comic web series about industrial agriculture, hit 99 on the action scale, as respondents said, for instance, that they had bought or shunned a product, and 94 for emotion, for an average of 97. That marked it as having potentially higher impact than “The Square” among those who saw it….”
EU: Communication on data-driven economy
Related Documents:
What is democracy? A reconceptualization of the quality of democracy
Paper by Gerardo L. Munck: “Works on the quality of democracy propose standards for evaluating politics beyond those encompassed by a minimal definition of democracy. Yet, what is the quality of democracy? This article first reconstructs and assesses current conceptualizations of the quality of democracy. Thereafter, it reconceptualizes the quality of democracy by equating it with democracy pure and simple, positing that democracy is a synthesis of political freedom and political equality, and spelling out the implications of this substantive assumption. The proposal is to broaden the concept of democracy to address two additional spheres: government decision-making – political institutions are democratic inasmuch as a majority of citizens can change the status quo – and the social environment of politics – the social context cannot turn the principles of political freedom and equality into mere formalities. Alternative specifications of democratic standards are considered and reasons for discarding them are provided.”
Diffusers of Useful Knowledge
Book review of Visions of Science: Books and Readers at the Dawn of the Victorian Age (By James A Secord): “For a moment in time, just before Victoria became queen, popular science seemed to offer answers to everything. Around 1830, revolutionary information technology – steam-powered presses and paper-making machines – made possible the dissemination of ‘useful knowledge’ to a mass public. At that point professional scientists scarcely existed as a class, but there were genteel amateur researchers who, with literary panache, wrote for a fascinated lay audience.
The term ‘scientist’ was invented only in 1833, by the polymath William Whewell, who gave it a faintly pejorative odour, drawing analogies to ‘journalist’, ‘sciolist’, ‘atheist’, and ‘tobacconist’. ‘Better die … than bestialise our tongue by such barbarisms,’ scowled the geologist Adam Sedgwick. ‘To anyone who respects the English language,’ said T H Huxley, ‘I think “Scientist” must be about as pleasing a word as “Electrocution”.’ These men preferred to call themselves ‘natural philosophers’ and there was a real distinction. Scientists were narrowly focused utilitarian data-grubbers; natural philosophers thought deeply and wrote elegantly about the moral, cosmological and metaphysical implications of their work….
Visions of Science offers vignettes of other pre-Darwin scientific writers who generated considerable buzz in their day. Consolations in Travel, a collection of meta-scientific musings by the chemist Humphry Davy, published in 1830, played a salient role in the plot of The Tenant of Wildfell Hall (1848), with Anne Brontë being reasonably confident that her readers would get the reference. The general tone of such works was exemplified by the astronomer John Herschel in Preliminary Discourse on the Study of Natural Philosophy (1831) – clear, empirical, accessible, supremely rational and even-tempered. These authors communicated a democratic faith that science could be mastered by anyone, perhaps even a woman.
Mary Somerville’s On the Connexion of the Physical Sciences (1834) pulled together mathematics, astronomy, electricity, light, sound, chemistry and meteorology in a grand middlebrow synthesis. She even promised her readers that the sciences were converging on some kind of unified field theory, though that particular Godot has never arrived. For several decades the book sold hugely and was pirated widely, but as scientists became more specialised and professional, it began to look like a hodgepodge. Writing in Nature in 1874, James Clerk Maxwell could find no theme in her pudding, calling it a miscellany unified only by the bookbinder.
The same scientific populism made possible the brief supernova of phrenology. Anyone could learn the fairly simple art of reading bumps on the head once the basics had been broadcast by new media. The first edition of George Combe’s phrenological treatise The Constitution of Man, priced at six shillings, sold barely a hundred copies a year. But when the state-of-the-art steam presses of Chambers’s Edinburgh Journal (the first mass-market periodical) produced a much cheaper version, 43,000 copies were snapped up in a matter of months. What the phrenologists could not produce were research papers backing up their claims, and a decade later the movement was moribund.
Charles Babbage, in designing his ‘difference engine’, anticipated all the basic principles of the modern computer – including ‘garbage in, garbage out’. In Reflections on the Decline of Science in England (1830) he accused his fellow scientists of routinely suppressing, concocting or cooking data. Such corruption (he confidently insisted) could be cleaned up if the government generously subsidised scientific research. That may seem naive today, when we are all too aware that scientists often fudge results to keep the research money flowing. Yet in the era of the First Reform Act, everything appeared to be reformable. Babbage even stood for parliament in Finsbury, on a platform of freedom of information for all. But he split the scientific radical vote with Thomas Wakley, founder of The Lancet, and the Tory swept home.
After his sketches of these forgotten bestsellers, Secord concludes with the literary bomb that blew them all up. In Sartor Resartus Thomas Carlyle fiercely deconstructed everything the popular scientists stood for. Where they were cool, rational, optimistic and supremely organised, he was frenzied, mystical, apocalyptic and deliberately nonsensical. They assumed that big data represented reality; he saw that it might be all pretence, fabrication, image – in a word, ‘clothes’. A century and a half before Microsoft’s emergence, Carlyle grasped the horror of universal digitisation: ‘Shall your Science proceed in the small chink-lighted, or even oil-lighted, underground workshop of Logic alone; and man’s mind become an Arithmetical Mill?’ That was a dig at the clockwork utilitarianism of both John Stuart Mill and Babbage: the latter called his central processing unit a ‘mill’.
The scientific populists sincerely aimed to democratise information. But when the movement was institutionalised in the form of mechanics’ institutes and the Society for the Diffusion of Useful Knowledge, did it aim at anything more than making workers more productive? Babbage never completed his difference engine, in part because he treated human beings – including the artisans who were supposed to execute his designs – as programmable machines. And he was certain that Homo sapiens was not the highest form of intelligence in the universe. On another planet somewhere, he suggested, the Divine Programmer must have created Humanity 2.0….”
Eigenmorality
Blog from Scott Aaronson: “This post is about an idea I had around 1997, when I was 16 years old and a freshman computer-science major at Cornell. Back then, I was extremely impressed by a research project called CLEVER, which one of my professors, Jon Kleinberg, had led while working at IBM Almaden. The idea was to use the link structure of the web itself to rank which web pages were most important, and therefore which ones should be returned first in a search query. Specifically, Kleinberg defined “hubs” as pages that linked to lots of “authorities,” and “authorities” as pages that were linked to by lots of “hubs.” At first glance, this definition seems hopelessly circular, but Kleinberg observed that one can break the circularity by just treating the World Wide Web as a giant directed graph, and doing some linear algebra on its adjacency matrix. Equivalently, you can imagine an iterative process where each web page starts out with the same hub/authority “starting credits,” but then in each round, the pages distribute their credits among their neighbors, so that the most popular pages get more credits, which they can then, in turn, distribute to their neighbors by linking to them.
I was also impressed by a similar research project called PageRank, which was proposed later by two guys at Stanford named Sergey Brin and Larry Page. Brin and Page dispensed with Kleinberg’s bipartite hubs-and-authorities structure in favor of a more uniform structure, and made some other changes, but otherwise their idea was very similar. At the time, of course, I didn’t know that CLEVER was going to languish at IBM, while PageRank (renamed Google) was going to expand to roughly the size of the entire world’s economy.
In any case, the question I asked myself about CLEVER/PageRank was not the one that, maybe in retrospect, I should have asked: namely, “how can I leverage the fact that I know the importance of this idea before most people do, in order to make millions of dollars?”
Instead I asked myself: “what other ‘vicious circles’ in science and philosophy could one unravel using the same linear-algebra trick that CLEVER and PageRank exploit?” After all, CLEVER and PageRank were both founded on what looked like a hopelessly circular intuition: “a web page is important if other important web pages link to it.” Yet they both managed to use math to defeat the circularity. All you had to do was find an “importance equilibrium,” in which your assignment of “importance” to each web page was stable under a certain linear map. And such an equilibrium could be shown to exist—indeed, to exist uniquely.
Searching for other circular notions to elucidate using linear algebra, I hit on morality. Philosophers from Socrates on, I was vaguely aware, had struggled to define what makes a person “moral” or “virtuous,” without tacitly presupposing the answer. Well, it seemed to me that, as a first attempt, one could do a lot worse than the following:
A moral person is someone who cooperates with other moral people, and who refuses to cooperate with immoral people.
Obviously one can quibble with this definition on numerous grounds: for example, what exactly does it mean to “cooperate,” and which other people are relevant here? If you don’t donate money to starving children in Africa, have you implicitly “refused to cooperate” with them? What’s the relative importance of cooperating with good people and withholding cooperation with bad people, of kindness and justice? Is there a duty not to cooperate with bad people, or merely the lack of a duty to cooperate with them? Should we consider intent, or only outcomes? Surely we shouldn’t hold someone accountable for sheltering a burglar, if they didn’t know about the burgling? Also, should we compute your “total morality” by simply summing over your interactions with everyone else in your community? If so, then can a career’s worth of lifesaving surgeries numerically overwhelm the badness of murdering a single child?
For now, I want you to set all of these important questions aside, and just focus on the fact that the definition doesn’t even seem to work on its own terms, because of circularity. How can we possibly know which people are moral (and hence worthy of our cooperation), and which ones immoral (and hence unworthy), without presupposing the very thing that we seek to define?
Ah, I thought—this is precisely where linear algebra can come to the rescue! Just like in CLEVER or PageRank, we can begin by giving everyone in the community an equal number of “morality starting credits.” Then we can apply an iterative update rule, where each person A can gain morality credits by cooperating with each other person B, and A gains more credits the more credits B has already. We apply the rule over and over, until the number of morality credits per person converges to an equilibrium. (Or, of course, we can shortcut the process by simply finding the principal eigenvector of the “cooperation matrix,” using whatever algorithm we like.) We then have our objective measure of morality for each individual, solving a 2400-year-old open problem in philosophy….”
Smart cities from scratch? a socio-technical perspective
Paper by Luís Carvalho in Cambridge Journal of Regions, Economy and Society: “This paper argues that contemporary smart city visions based on ITs (information and tele- communication technologies) configure complex socio-technical challenges that can benefit from strategic niche management to foster two key processes: technological learning and societal embedding. Moreover, it studies the extent to which those processes started to unfold in two paradigmatic cases of smart city pilots ‘from scratch’: Songdo (South Korea) and PlanIT Valley (Portugal). The rationale and potentials of the two pilots as arenas for socio-technical experimentation and global niche formation are analysed, as well as the tensions and bottlenecks involved in nurturing socially rich innovation ecosystems and in maintaining social and political support over time.”
Want to Brainstorm New Ideas? Then Limit Your Online Connections
Steve Lohr in the New York Times: “The digitally connected life is both invaluable and inevitable.
Anyone who has the slightest doubt need only walk down the sidewalk of any city street filled with people checking their smartphones for text messages, tweets, news alerts or weather reports or any number of things. So glued to their screens, they run into people or create pedestrian traffic jams.
Just when all the connectedness is useful and when it’s not is often difficult to say. But a recent research paper, published on the Social Science Research Network, titled “Facts and Figuring,” sheds some light on that question.
The research involved customizing a Pentagon lab program for measuring collaboration and information-sharing — a whodunit game, in which the subjects sitting at computers search for clues and solutions to figure out the who, what, when and where of a hypothetical terrorist attack.
The 417 subjects, played more than 1,100 rounds of the 25-minute web-based game, and they were mostly students from the Boston area, selected from the pool of volunteers in the Harvard Decision Science Laboratory and Harvard Business School’s Computer Lab for Experimental Research.
They could share clues and solutions. But the study was designed to measure the results from different network structures — densely clustered networks and unclustered networks of communication. Problem solving, the researchers write, involves “both search for information and search for solutions.” They found that “clustering promotes exploration in information space, but decreases exploration in solution space.”
In looking for unique facts or clues, clustering helped since members of the dense communications networks effectively split up the work and redundant facts were quickly weeded out, making them five percent more efficient. But the number of unique theories or solutions was 17.5 percent higher among subjects who were not densely connected. Clustering reduced the diversity of ideas.
The research paper, said Jesse Shore, a co-author and assistant professor at the Boston University School of Management, contributes to “the growing awareness that being connected all the time has costs. And we put a number to it, in an experimental setting.”
The research, of course, also showed where the connection paid off — finding information, the vital first step in decision making. “There are huge, huge benefits to information sharing,” said Ethan Bernstein, a co-author and assistant professor at the Harvard Business School. “But the costs are harder to measure.”…
Big Data from the bottom up
Paper by Nick Couldry and Alison Powell in the Journal Big Data and Society: “This short article argues that an adequate response to the implications for governance raised by ‘Big Data’ requires much more attention to agency and reflexivity than theories of ‘algorithmic power’ have so far allowed. It develops this through two contrasting examples: the sociological study of social actors used of analytics to meet their own social ends (for example, by community organisations) and the study of actors’ attempts to build an economy of information more open to civic intervention than the existing one (for example, in the environmental sphere). The article concludes with a consideration of the broader norms that might contextualise these empirical studies, and proposes that they can be understood in terms of the notion of voice, although the practical implementation of voice as a norm means that voice must sometimes be considered via the notion of transparency”