Case study by Gabriel Kuris and Steven S. Strauss at Innovations for Successful Societies: “In 2011, voters in Chicago elected Rahm Emanuel, a 51-year-old former Chicago congressman, as their new mayor. Emanuel inherited a city on the upswing after years of decline but still marked by high rates of crime and poverty, racial segregation, and public distrust in government. The Emanuel administration hoped to harness the city’s trove of digital data to improve Chicagoans’ health, safety, and quality of life. During the next several years, Chief Data Officer Brett Goldstein and his successor Tom Schenk led innovative uses of city data, ranging from crisis management to the statistical targeting of restaurant inspections and pest extermination. As their teams took on more-sophisticated projects that predicted lead-poisoning risks and Escherichia coli outbreaks and created a citywide network of ambient sensors, the two faced new concerns about normative issues like privacy, ethics, and equity. By 2018, Chicago had won acclaim as a smarter city, but was it a fairer city? This case study discusses some of the approaches the city developed to address those challenges and manage the societal implications of cutting-edge technologies….(More)”.
The rise of policy innovation labs: A catalog of policy innovation labs across Canada
Report by the Centre for Policy Innovation and Public Engagement (CPIPE): “In recent years, governments all over the world have been embracing new and innovative ways to develop public policies and design public services, from crowdsourcing to human-centred design thinking. This trend in government innovation has led to the rise of the Policy Innovation Lab (PIL): individual units, both inside and outside of government, that apply the traditional principles of scientific laboratories – experimentation, testing, and measurement – to social problems.
PILs are an increasingly important development in public policy making, with a variety of methods and approaches to building relationships between governments, organizations, and citizens, and generating ideas and designing policy. Yet, these labs are under-researched: many are established without a full understanding of their role and value to the policy community. We aim to address this knowledge gap, and create opportunities where policy innovators can make connections with their peers and learn about the current practices and applications of policy innovation from one another.
This report identifies the innovation labs in Canada, profiling their methodologies, projects, and partners, mapping the policy innovation landscape across the country. Each one-page summary provides a profile for each lab, and highlights the existing innovation practices and networks in the public, academic, non-profit, and private sectors, and identifies methodological and ideological trends across the different labs and networks.
This report is the first of its kind in North America. In this highly dynamic space, new labs are emerging and disappearing all the time. The purpose of this report is to put a spotlight on policy innovations and their successes, and to build and strengthen connections between researchers, policymakers, and policy innovators. Through a strengthened and sustained community of practice, we hope to see governments continue to embrace new approaches for effective policymaking…(More)”.
With real-time decisions, Citi Bike breaks the cycle of empty stations
Melanie Lefkowitz at Cornell Chronicle: “Cornell research has improved bike sharing in New York and other cities, providing tools to ensure bikes are available when and where they’re needed through a crowdsourcing system that uses real-time information to make decisions.
Citi Bike redistributes its bicycles around New York City using a program called Bike Angels, based on research by David Shmoys, the Laibe/Acheson Professor of Business Management and Leadership Studies in the School of Operations Research and Information Engineering.
Through Bike Angels, which Shmoys helped Citi Bike develop three years ago, cyclists earn points adding up to free rides and other prizes by using or returning bikes at certain high-need stations. Originally, Bike Angels awarded points for the same pattern of stations every morning, and a different fixed pattern each afternoon rush; now the program uses an algorithm that continually updates the pattern of stations for which users earn points.
“The ability to make decisions that are sensitive to exactly what are today’s conditions enables us to be much more effective in assigning those points,” said Shmoys, who is also associate director of Cornell’s Institute for Computational Sustainability.
With co-authors Hangil Chung ’18 and Daniel Freund, Ph.D. ’18, Shmoys wrote “Bike Angels: An Analysis of Citi Bike’s Incentive Program,” a detailed report showing the effectiveness of this approach. …(More)”.
How to Prevent Winner-Takes-All Democracy
Kaushik Basu at Project Syndicate: “Democracy is in crisis. Fake news – and fake allegations of fake news – now plagues civil discourse, and political parties have proved increasingly willing to use xenophobia and other malign strategies to win elections. At the same time, revisionist powers like Vladimir Putin’s Russia have been stepping up their efforts to interfere in elections across the West. Rarely has the United States witnessed such brazen attacks on its political system; and rarely has the world seen such lows during peacetime….
How can all of this be happening in democracies, and what can be done about it?
On the first question, one hypothesis is that new digital technologies are changing the structural incentives for corporations, political parties, and other major institutions. Consider the case of corporations. The wealth of proprietary data on consumer preferences and behavior is producing such massive returns to scale that a few giants are monopolizing markets. In other words, markets are increasingly geared toward a winner-take-all game: multiple corporations can compete, but to the victor go the spoils.1
Electoral democracy is drifting in the same direction. The benefits of winning an election have become so large that political parties will stoop to new lows to clinch a victory. And, as with corporations, they can do so with the help of data on electoral preferences and behavior, and with new strategies to target key constituencies.
This poses a dilemma for well-meaning democratic parties and politicians. If a “bad” party is willing to foment hate and racism to bolster its chances of winning, what is a “good” party to do? If it sticks to its principles, it could end up ceding victory to the “bad” party, which will do even more harm once it is in office. A “good” party may thus try to forestall that outcome by taking a step down the moral ladder, precipitating a race to the bottom. This is the problem with any winner-takes-all game. When second place confers no benefits, the cost of showing unilateral restraint can grow intolerably high.
But this problem is not as hopeless as it appears. In light of today’s crisis of democracy, we would do well to revisit Václav Havel’s seminal 1978 essay “The Power of the Powerless.” First published as samizdat that was smuggled out of Czechoslovakia, the essay makes a simple but compelling argument. Dictatorships and other seemingly omnipotent forms of authoritarianism may look like large, top-down structures, but in the final analysis, they are merely the outcome of ordinary individuals’ beliefs and choices. Havel did not have the tools of modern economic theory to demonstrate his argument formally. In my new book The Republic of Beliefs, I show that the essence of his argument can be given formal structure using elementary game theory. This, in turn, shows that ordinary individuals have moral options that may be unavailable to the big institutional players….(More)”.
An Overview of National AI Strategies
Medium Article by Tim Dutton: “The race to become the global leader in artificial intelligence (AI) has officially begun. In the past fifteen months, Canada, China, Denmark, the EU Commission, Finland, France, India, Italy, Japan, Mexico, the Nordic-Baltic region, Singapore, South Korea, Sweden, Taiwan, the UAE, and the UK have all released strategies to promote the use and development of AI. No two strategies are alike, with each focusing on different aspects of AI policy: scientific research, talent development, skills and education, public and private sector adoption, ethics and inclusion, standards and regulations, and data and digital infrastructure.
This article summarizes the key policies and goals of each strategy, as well as related policies and initiatives that have announced since the release of the initial strategies. It also includes countries that have announced their intention to develop a strategy or have related AI policies in place….(More)”.
World War Web
Special issue of Foreign Affairs: “The last few decades have witnessed the growth of an American-sponsored Internet open to all. But that was then; conditions have changed.
History is filled with supposed lost utopias, and there is no greater cliché than to see one’s own era as a lamentable decline from a previous golden age. Sometimes, however, clichés are right. And as we explored the Internet’s future for this issue’s lead package, it became clear this was one of those times. Contemplating where we have come from digitally and where we are heading, it’s hard not to feel increasingly wistful and nostalgic.
The last few decades have witnessed the growth of an American-sponsored Internet open to all, and that has helped tie the world together, bringing wide-ranging benefits to billions. But that was then; conditions have changed.
Other great powers are contesting U.S. digital leadership, pushing their own national priorities. Security threats appear and evolve constantly. Platforms that were supposed to expand and enrich the marketplace of ideas have been hijacked by trolls and bots and flooded with disinformation. And real power is increasingly concentrated in the hands of a few private tech giants, whose self-interested choices have dramatic consequences for the entire world around them.
Whatever emerges from this melee, it will be different from, and in many ways worse than, what we have now.
Adam Segal paints the big picture well. “The Internet has long been an American project,” he writes. “Yet today, the United States has ceded leadership in cyberspace to China.” What will happen if Beijing continues its online ascent? “The Internet will be less global and less open. A major part of it will run Chinese applications over Chinese-made hardware. And Beijing will reap the economic, diplomatic, national security, and intelligence benefits that once flowed to Washington.”
Nandan Nilekani, a co-founder of Infosys, outlines India’s unique approach to these issues, which is based on treating “digital infrastructure as a public good and data as something that citizens deserve access to.” Helen Dixon, Ireland’s data protection commissioner, presents a European perspective, arguing that giving individuals control over their own data—as the General Data Protection Regulation, the EU’s historic new regulatory effort, aims to do—is essential to restoring the Internet’s promise. And Karen Kornbluh, a veteran U.S. policymaker, describes how the United States dropped the digital ball and what it could do to pick it up again.
Finally, Michèle Flournoy and Michael Sulmeyer explain the new realities of cyberwarfare, and Viktor Mayer-Schönberger and Thomas Ramge consider the problems caused by Big Tech’s hoarding of data and what can be done to address it.
A generation from now, people across the globe will no doubt revel in the benefits the Internet has brought. But the more thoughtful among them will also lament the eclipse of the founders’ idealistic vision and dream of a world connected the way it could—and should— have been….(More)”.
China’s Aggressive Surveillance Technology Will Spread Beyond Its Borders
Already there are reports that Zimbabwe, for example, is turning to Chinese firms to implement nationwide facial-recognition and surveillance programs, wrapped into China’s infrastructure investments and a larger set of security agreements as well, including for policing online communication. The acquisition of black African faces will help China’s tech sector improve its overall data set.
Malaysia, too, announced new partnerships this spring with China to equip police with wearable facial-recognition cameras. There are quiet reports of Arab Gulf countries turning to China not just for the drone technologies America has denied but also for the authoritarian suite of surveillance, recognition, and data tools perfected in China’s provinces. In a recent article on Egypt’s military-led efforts to build a new capital city beyond Cairo’s chaos and revolutionary squares, a retired general acting as project spokesman declared, “a smart city means a safe city, with cameras and sensors everywhere. There will be a command center to control the entire city.” Who is financing construction? China.
While many governments are making attempts to secure this information, there have been several alarming stories of data leaks. Moreover, these national identifiers create an unprecedented opportunity for state surveillance at scale. What about collecting biometric information in nondemocratic regimes? In 2016, the personal details of nearly 50 million people in Turkey were leaked….
China and other determined authoritarian states may prove undeterrable in their zeal to adopt repressive technologies. A more realistic goal, as Georgetown University scholar Nicholas Wright has argued, is to sway countries on the fence by pointing out the reputational costs of repression and supporting those who are advocating for civil liberties in this domain within their own countries. Democracy promoters (which we hope will one day again include the White House) will also want to recognize the coming changes to the authoritarian public sphere. They can start now in helping vulnerable populations and civil society to gain greater technological literacy to advocate for their rights in new domains. It is not too early for governments and civil society groups alike to study what technological and tactical countermeasures exist to circumvent and disrupt new authoritarian tools.
Everyone will have to approach these developments with the humbling recognition that Silicon Valley is not the only game in town. Regardless of what happens stateside or in Europe, China will have formidable and growing indigenous capabilities to export to the rest of the world.
Seven years ago, techno-optimists expressed hope that a wave of new digital tools for social networking and self-expression could help young people in the Middle East and elsewhere to find their voices. Today, a new wave of Chinese-led technological advances threatens to blossom into what we consider an “Arab spring in reverse”—in which the next digital wave shifts the pendulum back, enabling state domination and repression at a staggering scale and algorithmic effectiveness.
Americans are absolutely right to be urgently focused on countering Russian weaponized hacking and leaking as its primary beneficiary sits in the Oval Office. But we also need to be more proactive in countering the tools of algorithmic authoritarianism that will shape the worldwide future of individual freedom….(More)”.
Americans Want to Share Their Medical Data. So Why Can’t They?
Eleni Manis at RealClearHealth: “Americans are willing to share personal data — even sensitive medical data — to advance the common good. A recent Stanford University study found that 93 percent of medical trial participants in the United States are willing to share their medical data with university scientists and 82 percent are willing to share with scientists at for-profit companies. In contrast, less than a third are concerned that their data might be stolen or used for marketing purposes.
However, the majority of regulations surrounding medical data focus on individuals’ ability to restrict the use of their medical data, with scant attention paid to supporting the ability to share personal data for the common good. Policymakers can begin to right this balance by establishing a national medical data donor registry that lets individuals contribute their medical data to support research after their deaths. Doing so would help medical researchers pursue cures and improve health care outcomes for all Americans.
Increased medical data sharing facilitates advances in medical science in three key ways. First, de-identified participant-level data can be used to understand the results of trials, enabling researchers to better explicate the relationship between treatments and outcomes. Second, researchers can use shared data to verify studies and identify cases of data fraud and research misconduct in the medical community. For example, one researcher recently discovered a prolific Japanese anesthesiologist had falsified data for almost two decades. Third, shared data can be combined and supplemented to support new studies and discoveries.
Despite these benefits, researchers, research funders, and regulators have struggled to establish a norm for sharing clinical research data. In some cases, regulatory obstacles are to blame. HIPAA — the federal law regulating medical data — blocks some sharing on grounds of patient privacy, while federal and state regulations governing data sharing are inconsistent. Researchers themselves have a proprietary interest in data they produce, while academic researchers seeking to maximize publications may guard data jealously.
Though funding bodies are aware of this tension, they are unable to resolve it on their own. The National Institutes of Health, for example, requires a data sharing plan for big-ticket funding but recognizes that proprietary interests may make sharing impossible….(More)”.
#TrendingLaws: How can Machine Learning and Network Analysis help us identify the “influencers” of Constitutions?
Unicef: “New research by scientists from UNICEF’s Office of Innovation — published today in the journal Nature Human Behaviour — applies methods from network science and machine learning to constitutional law. UNICEF Innovation Data Scientists Alex Rutherford and Manuel Garcia-Herranz collaborated with computer scientists and political scientists at MIT, George Washington University, and UC Merced to apply data analysis to the world’s constitutions over the last 300 years. This work sheds new light on how to better understand why countries’ laws change and incorporate social rights…
Data science techniques allow us to use methods like network science and machine learning to uncover patterns and insights that are hard for humans to see. Just as we can map influential users on Twitter — and patterns of relations between places to predict how diseases will spread — we can identify which countries have influenced each other in the past and what are the relations between legal provisions.
One way UNICEF fulfills its mission is through advocacy with national governments — to enshrine rights for minorities, notably children, formally in law. Perhaps the most renowned example of this is the International Convention on the Rights of the Child (ICRC).
Constitutions, such as Mexico’s 1917 constitution — the first to limit the employment of children — are critical to formalizing rights for vulnerable populations. National constitutions describe the role of a country’s institutions, its character in the eyes of the world, as well as the rights of its citizens.
From a scientific standpoint, the work is an important first step in showing that network analysis and machine learning technique can be used to better understand the dynamics of caring for and protecting the rights of children — critical to the work we do in a complex and interconnected world. It shows the significant, and positive policy implications of using data science to uphold children’s rights.
What the Research Shows:Through this research, we uncovered:
- A network of relationships between countries and their constitutions.
- A natural progression of laws — where fundamental rights are a necessary precursor to more specific rights for minorities.
- The effect of key historical events in changing legal norms….(More)”.
Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject
Nick Couldry and Ulises Mejias in Television & New Media (TVNM): “...Data colonialism combines the predatory extractive practices of historical colonialism with the abstract quantification methods of computing. Understanding Big Data from the Global South means understanding capitalism’s current dependence on this new type of appropriation that works at every point in space where people or things are attached to today’s infrastructures of connection. The scale of this transformation means that it is premature to map the forms of capitalism that will emerge from it on a global scale. Just as historical colonialism over the long-run provided the essential preconditions for the emergence of industrial capitalism, so over time, we can expect that data colonialism will provide the preconditions for a new stage of capitalism that as yet we can barely imagine, but for which the appropriation of human life through data will be central.
Right now, the priority is not to speculate about that eventual stage of capitalism, but to resist the data colonialism that is under way. This is how we understand Big Data from the South. Through what we call ‘data relations’ (new types of human relations which enable the extraction of data for commodification), social life all over the globe becomes an ‘open’ resource for extraction that is somehow ‘just there’ for capital. These global flows of data are as expansive as historic colonialism’s appropriation of land, resources, and bodies, although the epicentre has somewhat shifted. Data colonialism involves not one pole of colonial power (‘the West’), but at least two: the USA and China. This complicates our notion of the geography of the Global South, a concept which until now helped situate resistance and disidentification along geographic divisions between former colonizers and colonized. Instead, the new data colonialism works both externally — on a global scale — and internally on its own home populations. The elites of data colonialism (think of Facebook) benefit from colonization in both dimensions, and North-South, East-West divisions no longer matter in the same way.
It is important to acknowledge both the apparent similarities and the significant differences between our argument and the many preceding critical arguments about Big Data…(More)”