The DeepMind debacle demands dialogue on data

Curated on Posted on by Stefaan Verhulst

Hetan Shah in Nature: “Without public approval, advances in how we use data will stall. That is why a regulator’s ruling against the operator of three London hospitals is about more than mishandling records from 1.6 million patients. It is a missed opportunity to have a conversation with the public about appropriate uses for their data….

What can be done to address this deficit? Beyond meeting legal standards, all relevant institutions must take care to show themselves trustworthy in the eyes of the public. The lapses of the Royal Free hospitals and DeepMind provide, by omission, valuable lessons.

The first is to be open about what data are transferred. The extent of data transfer between the Royal Free and DeepMind came to light through investigative journalism. In my opinion, had the project proceeded under open contracting, it would have been subject to public scrutiny, and to questions about whether a company owned by Google — often accused of data monopoly — was best suited to create a relatively simple app.

The second lesson is that data transfer should be proportionate to the task. Information-sharing agreements should specify clear limits. It is unclear why an app for kidney injury requires the identifiable records of every patient seen by three hospitals over a five-year period.

Finally, governance mechanisms must be strengthened. It is shocking to me that the Royal Free did not assess the privacy impact of its actions before handing over access to records. DeepMind does deserve credit for (belatedly) setting up an independent review panel for health-care projects, especially because the panel has a designated budget and has not required members to sign non-disclosure agreements. (The two groups also agreed a new contract late last year, after criticism.)

More is needed. The Information Commissioner asked the Royal Free to improve its processes but did not fine it or require it to rescind data. This rap on the knuckles is unlikely to deter future, potentially worse, misuses of data. People are aware of the potential for over-reach, from the US government’s demands for state voter records to the Chinese government’s alleged plans to create a ‘social credit’ system that would monitor private behaviour.

Innovations such as artificial intelligence, machine learning and the Internet of Things offer great opportunities, but will falter without a public consensus around the role of data. To develop this, all data collectors and crunchers must be open and transparent. Consider how public confidence in genetic modification was lost in Europe, and how that has set back progress.

Public dialogue can build trust through collaborative efforts. A 14-member Citizen’s Reference Panel on health technologies was convened in Ontario, Canada in 2009. The Engage2020 programme incorporates societal input in the Horizon2020 stream of European Union science funding….(More)”

Some Countries Like ‘Nudges’ More Than Others

Curated on Posted on by Stefaan Verhulst

Cass Sunstein at Bloomberg: “All over the world, private and public institutions have been adopting “nudges” — interventions that preserve freedom of choice, but that steer people in a particular direction.

A GPS device nudges you. So does a reminder from your doctor, informing you that you have an appointment next Wednesday; an automatic enrollment policy from your employer, defaulting you into a 401(k) plan; and a calorie label at fast-food restaurants, telling you that a cheeseburger won’t be great for your waistline.

Recent evidence demonstrates that nudges can be amazingly effective — far more so, per dollar spent, than other tools, such as economic incentives. But a big question remains: Across different nations, do nudges have the same impact? Here’s a cautionary note.

One of the most famous success stories in the annals of nudging comes from the U.K. To encourage delinquent taxpayers to pay up, British officials simply informed them, by letter, that the overwhelming majority of British taxpayers pay their taxes on time.

It worked. Within just a few weeks, the letters produced millions of dollars in additional revenue. Consistent with standard findings in behavioral science, recipients of the letters didn’t like learning that they were deviating from the social norm. Like most of us, they didn’t want to be creeps or shirkers, and so they paid up.

For other nations, including the U.S., that was an intriguing finding. So our Department of Treasury tried the same approach. It sent letters to delinquent taxpayers, informing them (accurately) that 91 percent of American taxpayers pay on time. On the basis of the British data, the expectation was that a lot of people would be ashamed, and pay their taxes.

Except they didn’t. The U.S. Treasury didn’t get any more money.

How come? It’s reasonable to speculate that in the U.S., delinquent taxpayers just don’t care about the social norm. If they learn about it, they still aren’t motivated to pay.

This finding demonstrates that different groups can react very differently to nudges. It’s well known that when people are told that they are using more energy than their neighbors, they scale back — so that information is an effective nudge. But a study in California suggests that things are a bit more complicated….

In general, we don’t yet have a lot of evidence of international differences on the impact of nudges. But it would be surprising if such evidence doesn’t start to accumulate. Wherever people begin with strong preferences, and don’t like the direction in which they are being nudged, nudges are going to have a weaker effect.

For many nudges, that’s just fine. Actually, it’s part of the point….(More)”.

Democracy Promotion: An Objective of U.S. Foreign Assistance

Curated on Posted on by Stefaan Verhulst

New Report by Congressional Research Service: “Promoting democratic institutions, processes, and values has long been a U.S. foreign policy objective, though the priority given to this objective has been inconsistent. World events, competing priorities, and political change within the United States all shape the attention and resources provided to democracy promotion efforts and influence whether such efforts focus on supporting fair elections abroad, strengthening civil society, promoting rule of law and human rights, or other aspects of democracy promotion.

Proponents of democracy promotion often assert that such efforts are essential to global development and U.S. security because stable democracies tend to have better economic growth and stronger protection of human rights, and are less likely to go to war with one another. Critics contend that U.S. relations with foreign countries should focus exclusively on U.S. interests and stability in the world order. U.S. interest in global stability, regardless of the democratic nature of national political systems, could discourage U.S. support for democratic transitions—the implementation of which is uncertain and may lead to more, rather than less, instability.

Funding for democracy promotion assistance is deeply integrated into U.S. foreign policy institutions. More than $2 billion annually has been allocated from foreign assistance funds over the past decade for democracy promotion activities managed by the State Department, the U.S. Agency for International Development, the National Endowment for Democracy, and other entities. Programs promoting good governance (characterized by participation, transparency, accountability, effectiveness, and equity), rule of law, and promotion of human rights have typically received the largest share of this funding in contrast to lower funding to promote electoral processes and political competition. In recent years, increasing restrictions imposed by some foreign governments on civil society organizations have resulted in an increased emphasis in democracy promotion assistance for strengthening civil society.

Despite bipartisan support for the general concept of democracy promotion, policy debates in the 115th Congress continue to question the consistency, effectiveness, and appropriateness of such foreign assistance. With the Trump Administration indicating that democracy and human rights might not be a top foreign policy priority, advocates in Congress may be challenged to find common ground with the Administration on this issue.

As part of its budget and oversight responsibilities, the 115th Congress may consider the impact of the Trump Administration’s requested FY2018 foreign assistance spending cuts on U.S. democracy promotion assistance, review the effectiveness of democracy promotion activities, evaluate the various channels available for democracy promotion, and consider where democracy promotion ranks among a wide range of foreign policy and budget priorities….(More)”.

Uber Releases Open Source Project for Differential Privacy

Curated on Posted on by Stefaan Verhulst

Katie Tezapsidis at Uber Security: “Data analysis helps Uber continuously improve the user experience by preventing fraud, increasing efficiency, and providing important safety features for riders and drivers. Data gives our teams timely feedback about what we’re doing right and what needs improvement.

Uber is committed to protecting user privacy and we apply this principle throughout our business, including our internal data analytics. While Uber already has technical and administrative controls in place to limit who can access specific databases, we are adding additional protections governing how that data is used — even in authorized cases.

We are excited to give a first glimpse of our recent work on these additional protections with the release of a new open source tool, which we’ll introduce below.

Background: Differential Privacy

Differential privacy is a formal definition of privacy and is widely recognized by industry experts as providing strong and robust privacy assurances for individuals. In short, differential privacy allows general statistical analysis without revealing information about a particular individual in the data. Results do not even reveal whether any individual appears in the data. For this reason, differential privacy provides an extra layer of protection against re-identification attacks as well as attacks using auxiliary data.

Differential privacy can provide high accuracy results for the class of queries Uber commonly uses to identify statistical trends. Consequently, differential privacy allows us to calculate aggregations (averages, sums, counts, etc.) of elements like groups of users or trips on the platform without exposing information that could be used to infer details about a specific user or trip.

Differential privacy is enforced by adding noise to a query’s result, but some queries are more sensitive to the data of a single individual than others. To account for this, the amount of noise added must be tuned to the sensitivity of the query, which is defined as the maximum change in the query’s output when an individual’s data is added to or removed from the database.

As part of their job, a data analyst at Uber might need to know the average trip distance in a particular city. A large city, like San Francisco, might have hundreds of thousands of trips with an average distance of 3.5 miles. If any individual trip is removed from the data, the average remains close to 3.5 miles. This query therefore has low sensitivity, and thus requires less noise to enable each individual to remain anonymous within the crowd.

Conversely, the average trip distance in a smaller city with far fewer trips is more influenced by a single trip and may require more noise to provide the same degree of privacy. Differential privacy defines the precise amount of noise required given the sensitivity.

A major challenge for practical differential privacy is how to efficiently compute the sensitivity of a query. Existing methods lack sufficient support for the features used in Uber’s queries and many approaches require replacing the database with a custom runtime engine. Uber uses many different database engines and replacing these databases is infeasible. Moreover, custom runtimes cannot meet Uber’s demanding scalability and performance requirements.

Introducing Elastic Sensitivity

To address these challenges we adopted Elastic Sensitivity, a technique developed by security researchers at the University of California, Berkeley for efficiently calculating the sensitivity of a query without requiring changes to the database. The full technical details of Elastic Sensitivity are described here.

Today, we are excited to share a tool developed in collaboration with these researchers to calculate Elastic Sensitivity for SQL queries. The tool is available now on GitHub. It is designed to integrate easily with existing data environments and support additional state-of-the-art differential privacy mechanisms, which we plan to share in the coming months….(More)”.

Political Inequality in Affluent Democracies

Curated on Posted on by Stefaan Verhulst

 for the SSRC: “A key characteristic of a democracy,” according to Robert Dahl, is “the continuing responsiveness of the government to the preferences of its citizens, considered as political equals.” Much empirical research over the past half century, most of it focusing on the United States, has examined the relationship between citizens’ policy preferences and the policy choices of elected officials. According to Robert Shapiro, this research has generated “evidence for strong effects of public opinion on government policies,” providing “a sanguine picture of democracy at work.”

In recent years, however, scholars of American politics have produced striking evidence that the apparent “strong effects” of aggregate public opinion in these studies mask severe inequalities in responsiveness. As Martin Gilens put it, “The American government does respond to the public’s preferences, but that responsiveness is strongly tilted toward the most affluent citizens. Indeed, under most circumstances, the preferences of the vast majority of Americans appear to have essentially no impact on which policies the government does or doesn’t adopt.”

One possible interpretation of these findings is that the American political system is anomalous in its apparent disregard for the preferences of middle-class and poor people. In that case, the severe political inequality documented there would presumably be accounted for by distinctive features of the United States, such as its system of private campaign finance, its weak labor unions, or its individualistic political culture. But, what if severe political inequality is endemic in affluent democracies? That would suggest that fiddling with the political institutions of the United States to make them more like Denmark’s (or vice versa) would be unlikely to bring us significantly closer to satisfying Dahl’s standard of democratic equality. We would be forced to conclude either that Dahl’s standard is fundamentally misguided or that none of the political systems commonly identified as democratic comes anywhere close to meriting that designation.

Analyzing policy responsiveness

“I have attempted to test the extent to which policymakers in a variety of affluent democracies respond to the preferences of their citizens considered as political equals.”

To address this question, I have attempted to test the extent to which policymakers in a variety of affluent democracies respond to the preferences of their citizens considered as political equals. My analyses focus on the relationship between public opinion and government spending on social welfare programs, including pensions, health, education, and unemployment benefits. These programs represent a major share of government spending in every affluent democracy and, arguably, an important source of public well-being. Moreover, social spending figures prominently in the comparative literature on the political impact of public opinion in affluent democracies, with major scholarly works suggesting that it is significantly influenced by citizens’ preferences.

My analyses employ data on citizens’ views about social spending and the welfare state from three major cross-national survey projects—the International Social Survey Programme (ISSP), the World Values Survey (WVS), and the European Values Survey (EVS). In combination, these three sources provide relevant opinion data from 160 surveys conducted between 1985 and 2012 in 30 countries, including most of the established democracies of Western Europe and the English-speaking world and some newer democracies in Eastern Europe, Latin America, and Asia. I examine shifts in (real per capita) social spending in the two years following each survey. Does greater public enthusiasm for the welfare state lead to increases in social spending, other things being equal? And, more importantly here, do the views of low-income people have the same apparent influence on policy as the views of affluent people?…(More)”.

Open Data Blueprint

Curated on Posted on by Stefaan Verhulst

ODX Canada: “In Canada, the open data environment should be viewed as a supply chain. The movement of open data from producers to consumers involves many different organizations, people, activities, projects and initiatives, all of which work together to push out a final product. Naturally, if there is a break or hurdle in this supply chain, it doesn’t work efficiently. A fundamental hurdle highlighted by companies across the country was the inability to scale their business at the provincial, national and international levels.

This blueprint aims to address the challenges Canadian entrepreneurs are facing by encouraging municipalities to launch open data initiatives. By sharing best practices, we hope to encourage the accessibility of datasets within existing jurisdictions. The structured recommendations in this Open Data Blueprint are based on feedback and best practices seen in major cities across Canada collected through ODX’s primary research….(More)”

(Read more about the OD150 initiative here)

NIH-funded team uses smartphone data in global study of physical activity

Curated on Posted on by Stefaan Verhulst

National Institutes of Health: “Using a larger dataset than for any previous human movement study, National Institutes of Health-funded researchers at Stanford University in Palo Alto, California, have tracked physical activity by population for more than 100 countries. Their research follows on a recent estimate that more than 5 million people die each year from causes associated with inactivity.

The large-scale study of daily step data from anonymous smartphone users dials in on how countries, genders, and community types fare in terms of physical activity and what results may mean for intervention efforts around physical activity and obesity. The study was published July 10, 2017, in the advance online edition of Nature.

“Big data is not just about big numbers, but also the patterns that can explain important health trends,” said Grace Peng, Ph.D., director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis.

“Data science and modeling can be immensely powerful tools. They can aid in harnessing and analyzing all the personalized data that we get from our phones and wearable devices.”

Almost three quarters of adults in developed countries and half of adults in developing economies carry a smartphone. The devices are equipped with tiny accelerometers, computer chip that maintains the orientation of the screen, and can also automatically record stepping motions. The users whose data contributed to this study subscribed to the Azumio Argus app, a free application for tracking physical activity and other health behaviors….

In addition to the step records, the researchers accessed age, gender, and height and weight status of users who registered the smartphone app. They used the same calculation that economists use for income inequality — called the Gini index — to calculate activity inequality by country.

“These results reveal how much of a population is activity-rich, and how much of a population is activity-poor,” Delp said. “In regions with high activity inequality there are many people who are activity poor, and activity inequality is a strong predictor of health outcomes.”…

The researchers investigated the idea that making improvements in a city’s walkability — creating an environment that is safe and enjoyable to walk — could reduce activity inequality and the activity gender gap.

“If you must cross major highways to get from point A to point B in a city, the walkability is low; people rely on cars,” Delp said. “In cities like New York and San Francisco, where you can get across town on foot safely, the city has high walkability.”

Data from 69 U.S. cities showed that higher walkability scores are associated with lower activity inequality. Higher walkability is associated with significantly more daily steps across all age, gender, and body-mass-index categories.  However, the researchers found that women recorded comparatively less activity than men in places that are less walkable.

The study exemplifies how smartphones can deliver new insights about key health behaviors, including what the authors categorize as the global pandemic of physical inactivity….(More)”.

Principles and Practices for a Federal Statistical Agency

Curated on Posted on by Stefaan Verhulst

National Academies of Sciences Report: “Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens.

In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit.

Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence.� Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they’ve been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years….(More)”.

Lessons from Airbnb and Uber to Open Government as a Platform

Curated on Posted on by Stefaan Verhulst

Interview by Marquis Cabrera with Sangeet Paul Choudary: “…Platform companies have a very strong core built around data, machine learning, and a central infrastructure. But they rapidly innovate around it to try and test new things in the market and that helps them open themselves for further innovation in the ecosystem. Governments can learn to become more modular and more agile, the way platform companies are. Modularity in architecture is a very fundamental part of being a platform company; both in terms of your organizational architecture, as well as your business model architecture.

The second thing that governments can learn from a platform company is that successful platform companies are created with intent. They are not created by just opening out what you have available. If you look at the current approach of applying platform thinking in government, a common approach is just to take data and open it out to the world. However, successful platform companies first create a shaping strategy to shape-out and craft a direction of vision for the ecosystem in terms of what they can achieve by being on the platform. They then provision the right tools and services that serve the vision to enable success for the ecosystem[1] . And only then do they open up their infrastructure. It’s really important that you craft the right shaping strategy and use that to define the rights tools and services before you start pursuing a platform implementation.

In my work with governments, I regularly find myself stressing the importance of thinking as a market maker rather than as a service provider. Governments have always been market makers but when it comes to technology, they often take the service provider approach.

In your book, you used San Francisco City Government and Data.gov as examples of infusing platform thinking in government. But what are some global examples of governments, countries infusing platform thinking around the world?

One of the best examples is from my home country Singapore, which has been at the forefront of converting the nation into a platform. It has now been pursuing platform strategy both overall as a nation by building a smart nation platform, and also within verticals. If you look particularly at mobility and transportation, it has worked to create a central core platform and then build greater autonomy around how mobility and transportation works in the country. Other good examples of governments applying this are Dubai, South Korea, Barcelona; they are all countries and cities that have applied the concept of platforms very well to create a smart nation platform. India is another example that is applying platform thinking with the creation of the India stack, though the implementation could benefit from better platform governance structures and a more open regulation around participation….(More)”.

The role of Open Data in driving sustainable mobility in nine smart cities

Curated on Posted on by Stefaan Verhulst

Paper by Piyush Yadav et al: “In today’s era of globalization, sustainable mobility is considered as a key factor in the economic growth of any country. With the emergence of open data initiatives, there is tremendous potential to improve mobility. This paper presents findings of a detailed analysis of mobility open data initiatives in nine smart cities – Amsterdam, Barcelona, Chicago, Dublin, Helsinki, London, Manchester, New York and San Francisco. The paper discusses the study of various sustainable indicators in the mobility domain and its convergence with present open datasets. Specifically, it throws light on open data ecosystems in terms of their production and consumption. It gives a comprehensive view of the nature of mobility open data with respect to their formats, interactivity, and availability. The paper details the open datasets in terms of their alignment with different mobility indicators, publishing platforms, applications and API’s available. The paper discusses how these open datasets have shown signs of fostering organic innovation and sustainable growth in smart cities with impact on mobility trends. The results of the work can be used to inform the design of data driven sustainable mobility in smart cities to maximize the utilization of available open data resources….(More)”.