New book by Stephen Jeffares: “Why do policy actors create branded terms like Big Society and does launching such policy ideas on Twitter extend or curtail their life? This book argues that the practice of hashtag politics has evolved in response to an increasingly congested and mediatised environment, with the recent and rapid growth of high speed internet connections, smart phones and social media. It examines how policy analysis can adapt to offer interpretive insights into the life and death of policy ideas in an era of hashtag politics.
This text reveals that policy ideas can at the same time be ideas, instruments, visions, containers and brands, and advises readers on how to tell if a policy idea is dead or dying, how to map the diversity of viewpoints, how to capture the debate, when to engage and when to walk away. Each chapter showcases innovative analytic techniques, illustrated by application to contemporary policy ideas.”
OkCupid reveals it’s been lying to some of its users. Just to see what’ll happen.
Brian Fung in the Washington Post: “It turns out that OkCupid has been performing some of the same psychological experiments on its users that landed Facebook in hot water recently.
In a lengthy blog post, OkCupid cofounder Christian Rudder explains that OkCupid has on occasion played around with removing text from people’s profiles, removing photos, and even telling some users they were an excellent match when in fact they were only a 30 percent match according to the company’s systems. Just to see what would happen.
OkCupid defends this behavior as something that any self-respecting Web site would do.
“OkCupid doesn’t really know what it’s doing. Neither does any other Web site,” Rudder wrote. “But guess what, everybody: if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.”…
we have a bigger problem on our hands: A problem about how to reconcile the sometimes valuable lessons of data science with the creep factor — particularly when you aren’t notified about being studied. But as I’ve written before, these kinds of studies happen all the time; it’s just rare that the public is presented with the results.
Short of banning the practice altogether, which seems totally unrealistic, corporate data science seems like an opportunity on a number of levels, particularly if it’s disclosed to the public. First, it helps us understand how human beings tend to behave at Internet scale. Second, it tells us more about how Internet companies work. And third, it helps consumers make better decisions about which services they’re comfortable using.
I suspect that what bothers us most of all is not that the research took place, but that we’re slowly coming to grips with how easily we ceded control over our own information — and how the machines that collect all this data may all know more about us than we do ourselves. We had no idea we were even in a rabbit hole, and now we’ve discovered we’re 10 feet deep. As many as 62.5 percent of Facebook users don’t know the news feed is generated by a company algorithm, according to a recent study conducted by Christian Sandvig, an associate professor at the University of Michigan, and Karrie Karahalios, an associate professor at the University of Illinois.
OkCupid’s blog post is distinct in several ways from Facebook’s psychological experiment. OkCupid didn’t try to publish its findings in a scientific journal. It isn’t even claiming that what it did was science. Moreover, OkCupid’s research is legitimately useful to users of the service — in ways that Facebook’s research is arguably not….
But in any case, there’s no such motivating factor when it comes to Facebook. Unless you’re a page administrator or news organization, understanding how the newsfeed works doesn’t really help the average user in the way that understanding how OkCupid works does. That’s because people use Facebook for all kinds of reasons that have nothing to do with Facebook’s commercial motives. But people would stop using OkCupid if they discovered it didn’t “work.”
If you’re lying to your users in an attempt to improve your service, what’s the line between A/B testing and fraud?”
The Social Laboratory
Shane Harris in Foreign Policy: “…, Singapore has become a laboratory not only for testing how mass surveillance and big-data analysis might prevent terrorism, but for determining whether technology can be used to engineer a more harmonious society….Months after the virus abated, Ho and his colleagues ran a simulation using Poindexter’s TIA ideas to see whether they could have detected the outbreak. Ho will not reveal what forms of information he and his colleagues used — by U.S. standards, Singapore’s privacy laws are virtually nonexistent, and it’s possible that the government collected private communications, financial data, public transportation records, and medical information without any court approval or private consent — but Ho claims that the experiment was very encouraging. It showed that if Singapore had previously installed a big-data analysis system, it could have spotted the signs of a potential outbreak two months before the virus hit the country’s shores. Prior to the SARS outbreak, for example, there were reports of strange, unexplained lung infections in China. Threads of information like that, if woven together, could in theory warn analysts of pending crises.
The RAHS system was operational a year later, and it immediately began “canvassing a range of sources for weak signals of potential future shocks,” one senior Singaporean security official involved in the launch later recalled.
The system uses a mixture of proprietary and commercial technology and is based on a “cognitive model” designed to mimic the human thought process — a key design feature influenced by Poindexter’s TIA system. RAHS, itself, doesn’t think. It’s a tool that helps human beings sift huge stores of data for clues on just about everything. It is designed to analyze information from practically any source — the input is almost incidental — and to create models that can be used to forecast potential events. Those scenarios can then be shared across the Singaporean government and be picked up by whatever ministry or department might find them useful. Using a repository of information called an ideas database, RAHS and its teams of analysts create “narratives” about how various threats or strategic opportunities might play out. The point is not so much to predict the future as to envision a number of potential futures that can tell the government what to watch and when to dig further.
The officials running RAHS today are tight-lipped about exactly what data they monitor, though they acknowledge that a significant portion of “articles” in their databases come from publicly available information, including news reports, blog posts, Facebook updates, and Twitter messages. (“These articles have been trawled in by robots or uploaded manually” by analysts, says one program document.) But RAHS doesn’t need to rely only on open-source material or even the sorts of intelligence that most governments routinely collect: In Singapore, electronic surveillance of residents and visitors is pervasive and widely accepted…”
App offers a comprehensive guide to local and real-time parking restrictions
Springwise: “Finding a parking space in big cities can be a nightmare, which recently prompted on-demand valet service Caarbon to do the job for drivers. But even when a space is discovered, it’s easy to fall foul of rules and regulations that aren’t clearly marked or are just plain confusing. AppyParking is an app that details paid and non-paid parking spaces in real time, as well as factors such as congestion charges and special restrictions.
The main interface of the app is a map of the local area. Users first select the type of parking space they’re looking for, whether it’s a paid meter bay, car park, disabled parking space or even a vacant resident’s driveway through a partnership with ParkatmyHouse. AppyParking shows the nearest locations, along with details about any rules in place. A green thumbs up means it’s free to park at the current time, but a red thumbs down means that there’s a charge or the space has resident priority at the time, suggesting the driver may want to look elsewhere. The app features up-to-date information on parking restrictions for each individual space, including changes on public holidays. It also alerts users if large events such as soccer games are scheduled to take place that might affect their ability to park.
Watch the video to learn more about the app.
Website: www.appyparking.com“
Crowdsourcing Ideas to Accelerate Economic Growth and Prosperity through a Strategy for American Innovation
at the White House Blog: “America’s future economic growth and international competitiveness depend crucially on our capacity to innovate. Creating the jobs and industries of the future will require making the right investments to unleash the unmatched creativity and imagination of the American people.
We want to gather bold ideas for how we as a nation can build on and extend into the future our historic strengths in innovation and discovery. Today we are calling on thinkers, doers, and entrepreneurs across the country to submit their proposals for promising new initiatives or pressing needs for renewed investment to be included in next year’s updated Strategy for American Innovation.
What will the next Strategy for American Innovation accomplish? In part, it’s up to you. Your input will help guide the Administration’s efforts to catalyze the transformative innovation in products, processes, and services that is the hallmark of American ingenuity.
Today, we released a set of questions for your comment, which you can access here and on Quora – an online platform that allows us to crowdsource ideas from the American people.
Calling on America’s Inventors and Innovators for Great Ideas
Among the questions we are posing today to innovators across the country are:
Among the questions we are posing today to innovators across the country are:
- What specific policies or initiatives should the Administration consider prioritizing in the next version of the Strategy for American Innovation?
- What are the biggest challenges to, and opportunities for, innovation in the United States that will generate long-term economic growth and rising standards of living for more Americans?
- What additional opportunities exist to develop high-impact platform technologies that reduce the time and cost associated with the “design, build, test” cycle for important classes of materials, products, and systems?
- What investments, strategies, or technological advancements, across both the public and private sectors, are needed to rebuild the U.S. “industrial commons” (i.e., regional manufacturing capabilities) and ensure the latest technologies can be produced here?
- What partnerships or novel models for collaboration between the Federal Government and regions should the Administration consider in order to promote innovation and the development of regional innovation ecosystems?
In today’s world of rapidly evolving technology, the Administration is adapting its approach to innovation-driven economic growth to reflect the emergence of new and exciting possibilities. Now is the time to gather input from the American people in order to envision and shape the innovations of the future. The full Request for Information can be found here and the 2011 Strategy for American Innovation can be found here. Comments are due by September 23, 2014, and can be sent to [email protected]. We look forward to hearing your ideas!”
Unleashing Climate Data to Empower America’s Agricultural Sector
at the White House Blog: “Today, in a major step to advance the President’s Climate Data Initiative, the Obama administration is inviting leaders of the technology and agricultural sectors to the White House to discuss new collaborative steps to unleash data that will help ensure our food system is resilient to the effects of climate change.
More intense heat waves, heavier downpours, and severe droughts and wildfires out west are already affecting the nation’s ability to produce and transport safe food. The recently released National Climate Assessment makes clear that these kinds of impacts are projected to become more severe over this century.
Food distributors, agricultural businesses, farmers, and retailers need accessible, useable data, tools, and information to ensure the effectiveness and sustainability of their operations – from water availability, to timing of planting and harvest, to storage practices, and more.
Today’s convening at the White House will include formal commitments by a host of private-sector companies and nongovernmental organizations to support the President’s Climate Data Initiative by harnessing climate data in ways that will increase the resilience of America’s food system and help reduce the contribution of the nation’s agricultural sector to climate change.
Microsoft Research, for instance, will grant 12 months of free cloud-computing resources to winners of a national challenge to create a smartphone app that helps farmers increase the resilience of their food production systems in the face of weather variability and climate change; the Michigan Agri-Business Association will soon launch a publicly available web-based mapping tool for use by the state’s agriculture sector; and the U.S. dairy industry will test and pilot four new modules – energy, feed, nutrient, and herd management – on the data-driven Farm Smart environmental-footprint calculation tool by the end of 2014. These are just a few among dozens of exciting commitments.
And the federal government is also stepping up. Today, anyone can log onto climate.data.gov and find new features that make data accessible and usable about the risks of climate change to food production, delivery, and nutrition – including current and historical data from the Census of Agriculture on production, supply, and distribution of agricultural products, and data on climate-change-related risks such as storms, heat waves, and drought.
These steps are a direct response to the President’s call for all hands on deck to generate further innovation to help prepare America’s communities and business for the impacts of climate change.
We are delighted about the steps being announced by dozens of collaborators today, and we can’t wait to see what further tools, apps, and services are developed as the Administration and its partners continue to unleash data to make America’s agriculture enterprise stronger and more resilient than ever before.
Read a fact sheet about all of today’s Climate Data Initiative commitments here.“
Request for Proposals: Exploring the Implications of Government Release of Large Datasets
“The Berkeley Center for Law & Technology and Microsoft are issuing this request for proposals (RFP) to fund scholarly inquiry to examine the civil rights, human rights, security and privacy issues that arise from recent initiatives to release large datasets of government information to the public for analysis and reuse. This research may help ground public policy discussions and drive the development of a framework to avoid potential abuses of this data while encouraging greater engagement and innovation.
This RFP seeks to:
- Gain knowledge of the impact of the online release of large amounts of data generated by citizens’ interactions with government
- Imagine new possibilities for technical, legal, and regulatory interventions that avoid abuse
- Begin building a body of research that addresses these issues
– BACKGROUND –
Governments at all levels are releasing large datasets for analysis by anyone for any purpose—“Open Data.” Using Open Data, entrepreneurs may create new products and services, and citizens may use it to gain insight into the government. A plethora of time saving and other useful applications have emerged from Open Data feeds, including more accurate traffic information, real-time arrival of public transportation, and information about crimes in neighborhoods. Sometimes governments release large datasets in order to encourage the development of unimagined new applications. For instance, New York City has made over 1,100 databases available, some of which contain information that can be linked to individuals, such as a parking violation database containing license plate numbers and car descriptions.
Data held by the government is often implicitly or explicitly about individuals—acting in roles that have recognized constitutional protection, such as lobbyist, signatory to a petition, or donor to a political cause; in roles that require special protection, such as victim of, witness to, or suspect in a crime; in the role as businessperson submitting proprietary information to a regulator or obtaining a business license; and in the role of ordinary citizen. While open government is often presented as an unqualified good, sometimes Open Data can identify individuals or groups, leading to a more transparent citizenry. The citizen who foresees this growing transparency may be less willing to engage in government, as these transactions may be documented and released in a dataset to anyone to use for any imaginable purpose—including to deanonymize the database—forever. Moreover, some groups of citizens may have few options or no choice as to whether to engage in governmental activities. Hence, open data sets may have a disparate impact on certain groups. The potential impact of large-scale data and analysis on civil rights is an area of growing concern. A number of civil rights and media justice groups banded together in February 2014 to endorse the “Civil Rights Principles for the Era of Big Data” and the potential of new data systems to undermine longstanding civil rights protections was flagged as a “central finding” of a recent policy review by White House adviser John Podesta.
The Berkeley Center for Law & Technology (BCLT) and Microsoft are issuing this request for proposals in an effort to better understand the implications and potential impact of the release of data related to U.S. citizens’ interactions with their local, state and federal governments. BCLT and Microsoft will fund up to six grants, with a combined total of $300,000. Grantees will be required to participate in a workshop to present and discuss their research at the Berkeley Technology Law Journal (BTLJ) Spring Symposium. All grantees’ papers will be published in a dedicated monograph. Grantees’ papers that approach the issues from a legal perspective may also be published in the BTLJ. We may also hold a followup workshop in New York City or Washington, DC.
While we are primarily interested in funding proposals that address issues related to the policy impacts of Open Data, many of these issues are intertwined with general societal implications of “big data.” As a result, proposals that explore Open Data from a big data perspective are welcome; however, proposals solely focused on big data are not. We are open to proposals that address the following difficult question. We are also open to methods and disciplines, and are particularly interested in proposals from cross-disciplinary teams.
- To what extent does existing Open Data made available by city and state governments affect individual profiling? Do the effects change depending on the level of aggregation (neighborhood vs. cities)? What releases of information could foreseeably cause discrimination in the future? Will different groups in society be disproportionately impacted by Open Data?
- Should the use of Open Data be governed by a code of conduct or subject to a review process before being released? In order to enhance citizen privacy, should governments develop guidelines to release sampled or perturbed data, instead of entire datasets? When datasets contain potentially identifiable information, should there be a notice-and-comment proceeding that includes proposed technological solutions to anonymize, de-identify or otherwise perturb the data?
- Is there something fundamentally different about government services and the government’s collection of citizen’s data for basic needs in modern society such as power and water that requires governments to exercise greater due care than commercial entities?
- Companies have legal and practical mechanisms to shield data submitted to government from public release. What mechanisms do individuals have or should have to address misuse of Open Data? Could developments in the constitutional right to information policy as articulated in Whalen and Westinghouse Electric Co address Open Data privacy issues?
- Collecting data costs money, and its release could affect civil liberties. Yet it is being given away freely, sometimes to immensely profitable firms. Should governments license data for a fee and/or impose limits on its use, given its value?
- The privacy principle of “collection limitation” is under siege, with many arguing that use restrictions will be more efficacious for protecting privacy and more workable for big data analysis. Does the potential of Open Data justify eroding state and federal privacy act collection limitation principles? What are the ethical dimensions of a government system that deprives the data subject of the ability to obscure or prevent the collection of data about a sensitive issue? A move from collection restrictions to use regulation raises a number of related issues, detailed below.
- Are use restrictions efficacious in creating accountability? Consumer reporting agencies are regulated by use restrictions, yet they are not known for their accountability. How could use regulations be implemented in the context of Open Data efficaciously? Can a self-learning algorithm honor data use restrictions?
- If an Open Dataset were regulated by a use restriction, how could individuals police wrongful uses? How would plaintiffs overcome the likely defenses or proof of facts in a use regulation system, such as a burden to prove that data were analyzed and the product of that analysis was used in a certain way to harm the plaintiff? Will plaintiffs ever be able to beat first amendment defenses?
- The President’s Council of Advisors on Science and Technology big data report emphasizes that analysis is not a “use” of data. Such an interpretation suggests that NSA metadata analysis and large-scale scanning of communications do not raise privacy issues. What are the ethical and legal implications of the “analysis is not use” argument in the context of Open Data?
- Open Data celebrates the idea that information collected by the government can be used by another person for various kinds of analysis. When analysts are not involved in the collection of data, they are less likely to understand its context and limitations. How do we ensure that this knowledge is maintained in a use regulation system?
- Former President William Clinton was admitted under a pseudonym for a procedure at a New York Hospital in 2004. The hospital detected 1,500 attempts by its own employees to access the President’s records. With snooping such a tempting activity, how could incentives be crafted to cause self-policing of government data and the self-disclosure of inappropriate uses of Open Data?
- It is clear that data privacy regulation could hamper some big data efforts. However, many examples of big data successes hail from highly regulated environments, such as health care and financial services—areas with statutory, common law, and IRB protections. What are the contours of privacy law that are compatible with big data and Open Data success and which are inherently inimical to it?
- In recent years, the problem of “too much money in politics” has been addressed with increasing disclosure requirements. Yet, distrust in government remains high, and individuals identified in donor databases have been subjected to harassment. Is the answer to problems of distrust in government even more Open Data?
- What are the ethical and epistemological implications of encouraging government decision-making based upon correlation analysis, without a rigorous understanding of cause and effect? Are there decisions that should not be left to just correlational proof? While enthusiasm for data science has increased, scientific journals are elevating their standards, with special scrutiny focused on hypothesis-free, multiple comparison analysis. What could legal and policy experts learn from experts in statistics about the nature and limits of open data?…
To submit a proposal, visit the Conference Management Toolkit (CMT) here.
Once you have created a profile, the site will allow you to submit your proposal.
If you have questions, please contact Chris Hoofnagle, principal investigator on this project.”
Designing an Online Civic Engagement Platform: Balancing “More” vs. “Better” Participation in Complex Public Policymaking
Paper by Cynthia R. Farina et al in E-Politics: “A new form of online citizen participation in government decisionmaking has arisen in the United States (U.S.) under the Obama Administration. “Civic Participation 2.0” attempts to use Web 2.0 information and communication technologies to enable wider civic participation in government policymaking, based on three pillars of open government: transparency, participation, and collaboration. Thus far, the Administration has modeled Civic Participation 2.0 almost exclusively on a universalist/populist Web 2.0 philosophy of participation. In this model, content is created by users, who are enabled to shape the discussion and assess the value of contributions with little information or guidance from government decisionmakers. The authors suggest that this model often produces “participation” unsatisfactory to both government and citizens. The authors propose instead a model of Civic Participation 2.0 rooted in the theory and practice of democratic deliberation. In this model, the goal of civic participation is to reveal the conclusions people reach when they are informed about the issues and have the opportunity and motivation seriously to discuss them. Accordingly, the task of civic participation design is to provide the factual and policy information and the kinds of participation mechanisms that support and encourage this sort of participatory output. Based on the authors’ experience with Regulation Room, an experimental online platform for broadening effective civic participation in rulemaking (the process federal agencies use to make new regulations), the authors offer specific suggestions for how designers can strike the balance between ease of engagement and quality of engagement – and so bring new voices into public policymaking processes through participatory outputs that government decisionmakers will value.”
Towards Timely Public Health Decisions to Tackle Seasonal Diseases With Open Government Data
Paper by Vandana Srivastava and Biplav Srivastava for the Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence : “Improving public health is a major responsibility of any government, and is of major interest to citizens and scientific communities around the world. Here, one sees two extremes. On one hand, tremendous progress has been made in recent years in the understanding of causes, spread and remedies of common and regularly occurring diseases like Dengue, Malaria and Japanese Encephalistis (JE). On the other hand, public agencies treat these diseases in an ad hoc manner without learning from the experiences of previous years. Specifically, they would get alerted once reported cases have already arisen substantially in the known disease season, reactively initiate a few actions and then document the disease impact (cases, deaths) for that period, only to forget this learning in the next season. However, they miss the opportunity to reduce preventable deaths and sickness, and their corresponding economic impact, which scientific progress could have enabled. The gap is universal but very prominent in developing countries like India.
In this paper, we show that if public agencies provide historical disease impact information openly, it can be analyzed with statistical and machine learning techniques, correlated with best emerging practices in disease control, and simulated in a setting to optimize social benefits to provide timely guidance for new disease seasons and regions. We illustrate using open data for mosquito-borne communicable diseases; published results in public health on efficacy of Dengue control methods and apply it on a simulated typical city for maximal benefits with available resources. The exercise helps us further suggest strategies for new regions that may be anywhere in the world, how data could be better recorded by city agencies and what prevention methods should medical community focus on for wider impact.
In this paper, we show that if public agencies provide historical disease impact information openly, it can be analyzed with statistical and machine learning techniques, correlated with best emerging practices in disease control, and simulated in a setting to optimize social benefits to provide timely guidance for new disease seasons and regions. We illustrate using open data for mosquito-borne communicable diseases; published results in public health on efficacy of Dengue control methods and apply it on a simulated typical city for maximal benefits with available resources. The exercise helps us further suggest strategies for new regions that may be anywhere in the world, how data could be better recorded by city agencies and what prevention methods should medical community focus on for wider impact.
Full Text: PDF“
The Innovators
Kirkus Review of “The innovators. How a Group of Inventors, Hackers, Geniuses, and Geeks Created the Digital Revolution” by Walter Isaacson: “Innovation occurs when ripe seeds fall on fertile ground,” Aspen Institute CEO Isaacson (Steve Jobs, 2011, etc.) writes in this sweeping, thrilling tale of three radical innovations that gave rise to the digital age. First was the evolution of the computer, which Isaacson traces from its 19th-century beginnings in Ada Lovelace’s “poetical” mathematics and Charles Babbage’s dream of an “Analytical Engine” to the creation of silicon chips with circuits printed on them. The second was “the invention of a corporate culture and management style that was the antithesis of the hierarchical organization of East Coast companies.” In the rarefied neighborhood dubbed Silicon Valley, new businesses aimed for a cooperative, nonauthoritarian model that nurtured cross-fertilization of ideas. The third innovation was the creation of demand for personal devices: the pocket radio; the calculator, marketing brainchild of Texas Instruments; video games; and finally, the holy grail of inventions: the personal computer. Throughout his action-packed story, Isaacson reiterates one theme: Innovation results from both “creative inventors” and “an evolutionary process that occurs when ideas, concepts, technologies, and engineering methods ripen together.” Who invented the microchip? Or the Internet? Mostly, Isaacson writes, these emerged from “a loosely knit cohort of academics and hackers who worked as peers and freely shared their creative ideas….Innovation is not a loner’s endeavor.” Isaacson offers vivid portraits—many based on firsthand interviews—of mathematicians, scientists, technicians and hackers (a term that used to mean anyone who fooled around with computers), including the elegant, “intellectually intimidating,” Hungarian-born John von Neumann; impatient, egotistical William Shockley; Grace Hopper, who joined the Army to pursue a career in mathematics; “laconic yet oddly charming” J.C.R. Licklider, one father of the Internet; Bill Gates, Steve Jobs, and scores of others.
Isaacson weaves prodigious research and deftly crafted anecdotes into a vigorous, gripping narrative about the visionaries whose imaginations and zeal continue to transform our lives.”