China harnesses big data to buttress the power of the state


James Kynge in the Financial Times: “…Over the period of “reform and opening” since the late 1970s, China has generally sought to “bide its time and hide its strength”. But no longer. At the congress, Xi Jinping, the president, presented “socialism with Chinese characteristics” as a “a new choice” for developing nations to follow. But what lends heft to this globalist intent are technological advances that are already invigorating the Chinese economy and may also help to address some of the historic failings of the country’s polity.

The data revolution is fusing with China’s party-state to create a potential “techno-tatorship”; a hybrid strain in which rigid political control can coexist with ample free-market flexibility….

First of all, he said, the big ecommerce companies, such as Alibaba, Tencent and JD.com, are obliged to share their data with central authorities such as the People’s Bank of China (PBoC), the central bank. Then the PBoC shares the data with about 50 state-owned banks, creating a database that covers about 400m people, detailing their payment history, creditworthiness and even networks of social contacts, the official said.

“We have already seen that the number of bad debts being built up by households has come down sharply since we launched this system,” said the official. “People really care about their credit scores because those with bad scores have reduced access to financial services.”…
To be sure, data-centric approaches to governance can have shortcomings. The data can be ignored or manipulated by humans, or privileged institutions can lobby for special treatment using old fashioned political leverage. But some Chinese see a big opportunity. Economists Wang Binbin and Li Xiaoyan argue in a paper that the marriage of big data and central planning creates a potent new hybrid….(More)”.

Growing government innovation labs: an insider’s guide


Report by UNDP and Futurgov: “Effective and inspirational labs exist in many highly developed countries. In Western Europe, MindLab (Denmark) and The Behavioural Insights Team (UK) push their governments to re-imagine public services. In Asia, the Innovation Bureau in Seoul, South Korea, co-designs better services with citizens.

However, this guide is aimed towards those working in the development context. The authors believe their collective experience of running labs in Eurasia, Asia and the Middle East is directly transferrable to other regions who face similar challenges, for example, moving from poverty to inequality, or from a recent history of democratisation towards more open government.

This report does not offer a “how-to” of innovation techniques — there are plenty of guides out there. Instead, we give the real story of how government innovation labs develop in regions like ours: organic and people-driven, often operating under the radar until safe to emerge. We share a truthful  examination of the twists and turns of seeding, starting up and scaling labs, covering the challenges we faced and our failures, as much as our successes. …(More)”.

Information Governance in Japan: Towards a Comparative Paradigm


Book by Kenji E. KushidaYuko Kasuya and Eiji Kawabata: “The history of human civilization has been about managing information, from hunting and gathering through contemporary times. In modern societies, information flows are central to how individuals and societies interact with governments, economies, and other countries. Despite this centrality of information, information governance—how information flows are managed—has not been a central concern of scholarship. We argue that it should be, especially now that digitization has dramatically altered the amount of information generated, how it can be transmitted, and how it can be used.

This book examines various aspects of information governance in Japan, utilizing comparative and historical perspectives. The aim is threefold: 1) to explore Japan’s society, politics, and economy through a critical but hitherto under-examined vantage that we believe cuts to the core of what modern societies are built with—information; 2) articulate a set of components which can be used to analyze other countries from the vantage of information governance; and 3) provide frameworks of reference to analyze each component.

This book is the product of a multidisciplinary, multinational collaboration between scholars based in the US and Japan. Each are experts in their own fields (economics, political science, information science, law, library science), and were brought together in two workshops to develop, explore, and analyze the conception and various of facets of information governance. This book is frontier research by proposing and taking this conception of information governance as a framework of analysis.

The introduction sets up the analysis by providing background and a framework for understanding the conception of information governance. Part I focuses on the management of government-held information. Part II examines information central to economic activity. Part III explores information flows crucial to politics and social life….(More)”.

The Death of Public Knowledge? How Free Markets Destroy the General Intellect


Book edited by Aeron Davis: “...argues for the value and importance of shared, publicly accessible knowledge, and suggests that the erosion of its most visible forms, including public service broadcasting, education, and the network of public libraries, has worrying outcomes for democracy.

With contributions from both activists and academics, this collection of short, sharp essays focuses on different aspects of public knowledge, from libraries and education to news media and public policy. Together, the contributors record the stresses and strains placed upon public knowledge by funding cuts and austerity, the new digital economy, quantification and target-setting, neoliberal politics, and inequality. These pressures, the authors contend, not only hinder democracies, but also undermine markets, economies, and social institutions and spaces everywhere.

Covering areas of international public concern, these polemical, accessible texts include reflections on the fate of schools and education, the takeover of public institutions by private interests, and the corruption of news and information in the financial sector. They cover the compromised Greek media during recent EU negotiations, the role played by media and political elites in the Irish property bubble, the compromising of government policy by corporate interests in the United States and Korea, and the squeeze on public service media in the United Kingdom, New Zealand, and the United States.

Individually and collectively, these pieces spell out the importance of maintaining public, shared knowledge in all its forms, and offer a rallying cry for doing so, asserting the need for strong public, financial, and regulatory support….(More)”

Artificial Intelligence for Citizen Services and Government


Paper by Hila Mehr: “From online services like Netflix and Facebook, to chatbots on our phones and in our homes like Siri and Alexa, we are beginning to interact with artificial intelligence (AI) on a near daily basis. AI is the programming or training of a computer to do tasks typically reserved for human intelligence, whether it is recommending which movie to watch next or answering technical questions. Soon, AI will permeate the ways we interact with our government, too. From small cities in the US to countries like Japan, government agencies are looking to AI to improve citizen services.

While the potential future use cases of AI in government remain bounded by government resources and the limits of both human creativity and trust in government, the most obvious and immediately beneficial opportunities are those where AI can reduce administrative burdens, help resolve resource allocation problems, and take on significantly complex tasks. Many AI case studies in citizen services today fall into five categories: answering questions, filling out and searching documents, routing requests, translation, and drafting documents. These applications could make government work more efficient while freeing up time for employees to build better relationships with citizens. With citizen satisfaction with digital government offerings leaving much to be desired, AI may be one way to bridge the gap while improving citizen engagement and service delivery.

Despite the clear opportunities, AI will not solve systemic problems in government, and could potentially exacerbate issues around service delivery, privacy, and ethics if not implemented thoughtfully and strategically. Agencies interested in implementing AI can learn from previous government transformation efforts, as well as private-sector implementation of AI. Government offices should consider these six strategies for applying AI to their work: make AI a part of a goals-based, citizen-centric program; get citizen input; build upon existing resources; be data-prepared and tread carefully with privacy; mitigate ethical risks and avoid AI decision making; and, augment employees, do not replace them.

This paper explores the various types of AI applications, and current and future uses of AI in government delivery of citizen services, with a focus on citizen inquiries and information. It also offers strategies for governments as they consider implementing AI….(More)”

How AI Is Crunching Big Data To Improve Healthcare Outcomes


PSFK: “The state of your health shouldn’t be a mystery, nor should patients or doctors have to wait long to find answers to pressing medical concerns. In PSFK’s Future of Health Report, we dig deep into the latest in AI, big data algorithms and IoT tools that are enabling a new, more comprehensive overview of patient data collection and analysis. Machine support, patient information from medical records and conversations with doctors are combined with the latest medical literature to help form a diagnosis without detracting from doctor-patient relations.

The impact of improved AI helps patients form a baseline for well-being and is making changes all across the healthcare industry. AI not only streamlines intake processes and reduces processing volume at clinics, it also controls input and diagnostic errors within a patient record, allowing doctors to focus on patient care and communication, rather than data entry. AI also improves pattern recognition and early diagnosis by learning from multiple patient data sets.

By utilizing deep learning algorithms and software, healthcare providers can connect various libraries of medical information and scan databases of medical records, spotting patterns that lead to more accurate detection and greater breadth of efficiency in medical diagnosis and research. IBM Watson, which has previously been used to help identify genetic markers and develop drugs, is applying its neural learning networks to help doctors correctly diagnose heart abnormalities from medical imaging tests. By scanning thousands of images and learning from correct diagnoses, Watson is able to increase diagnostic accuracy, supporting doctors’ cardiac assessments.

Outside of the doctor’s office, AI is also being used to monitor patient vitals to help create a baseline for well-being. By monitoring health on a day-to-day basis, AI systems can alert patients and medical teams to abnormalities or changes from the baseline in real time, increasing positive outcomes. Take xbird, a mobile platform that uses artificial intelligence to help diabetics understand when hypoglycemic attacks will occur. The AI combines personal and environmental data points from over 20 sensors within mobile and wearable devices to create an automated personal diary and cross references it against blood sugar levels. Patients then share this data with their doctors in order to uncover their unique hypoglycemic triggers and better manage their condition.

In China, meanwhile, web provider Baidu has debuted Melody, a chat-based medical assistant that helps individuals communicate their symptoms, learn of possible diagnoses and connect to medical experts….(More)”.

China seeks glimpse of citizens’ future with crime-predicting AI


, Yingzhi Yang and Sherry Fei Ju in the Financial Times: “China, a surveillance state where authorities have unchecked access to citizens’ histories, is seeking to look into their future with technology designed to predict and prevent crime. Companies are helping police develop artificial intelligence they say will help them identify and apprehend suspects before criminal acts are committed. “If we use our smart systems and smart facilities well, we can know beforehand . . . who might be a terrorist, who might do something bad,” Li Meng, vice-minister of science and technology, said on Friday.

Facial recognition company Cloud Walk has been trialling a system that uses data on individuals’ movements and behaviour — for instance visits to shops where weapons are sold — to assess their chances of committing a crime. Its software warns police when a citizen’s crime risk becomes dangerously high, allowing the police to intervene. “The police are using a big-data rating system to rate highly suspicious groups of people based on where they go and what they do,” a company spokesperson told the Financial Times. Risks rise if the individual “frequently visits transport hubs and goes to suspicious places like a knife store”, the spokesperson added. China’s authoritarian government has always amassed personal data to monitor and control its citizens — whether they are criminals or suspected of politically sensitive activity. But new technology, from phones and computers to fast-developing AI software, is amplifying its capabilities. These are being used to crack down on even the most minor of infractions — facial recognition cameras, for instance, are also being used to identify and shame jaywalkers, according to state media. Mr Li said crime prediction would become an important use for AI technology in the government sphere.

China’s crime-prediction technology relies on several AI techniques, including facial recognition and gait analysis, to identify people from surveillance footage. In addition, “crowd analysis” can be used to detect “suspicious” patterns of behaviour in crowds, for example to single out thieves from normal passengers at a train stations. As well as tracking people with a criminal history, Cloud Walk’s technology is being used to monitor “high-risk” places such as hardware stores…(More)”

Government at a Glance 2017


OECD: “Government at a Glance 2017 provides the latest available data on public administrations in OECD countries. Where possible, it also reports data for Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation, and South Africa. This edition contains new indicators on public sector emploympent, institutions, budgeting practices and procedures, regulatory governance, risk management and communication, open government data and public sector innovation. This edition also includes for the first time a number of scorecards comparing the level of access, responsiveness and quality of services in three key areas: health care, education and justice.

Each indicator in the publication is presented in a user-friendly format, consisting of graphs and/or charts illustrating variations across countries and over time, brief descriptive analyses highlighting the major findings conveyed by the data, and a methodological section on the definition of the indicator and any limitations in data comparability. A database containing qualitative and quantitative indicators on government is available on line. It is updated twice a year as new data are released. The database, countries fact sheets and other online supplements can be found at www.oecd.org/gov/govataglance.htm.”

Lessons from Airbnb and Uber to Open Government as a Platform


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 Prospects & Limits of Deliberative Democracy


Introduction by  and  of Special Issue of Daedalus:Democracy is under siege. Approval ratings for democratic institutions in most countries around the world are at near-record lows. The number of recognized democratic countries in the world is no longer expanding after the so-called Third Wave of democratic transitions. Indeed, there is something of a “democratic recession.” Further, some apparently democratic countries with competitive elections are undermining elements of liberal democracy: the rights and liberties that ensure freedom of thought and expression, protection of the rule of law, and all the protections for the substructure of civil society that may be as important for making democracy work as the electoral process itself. The model of party competition-based democracy – the principal model of democracy in the modern era – seems under threat.

That model also has competition. What might be called “meritocratic authoritarianism,” a model in which regimes with flawed democratic processes nevertheless provide good governance, is attracting attention and some support. Singapore is the only successful extant example, although some suggest China as another nation moving in this direction. Singapore is not a Western-style party- and competition-based democracy, but it is well-known for its competent civil servants schooled in making decisions on a cost-benefit basis to solve public problems, with the goals set by elite consultation with input from elections rather than by party competition.

Public discontent makes further difficulties for the competitive model. Democracies around the world struggle with the apparent gulf between political elites who are widely distrusted and mobilized citizens who fuel populism with the energy of angry voices. Disillusioned citizens turning against elites have produced unexpected election results, including the Brexit decision and the 2016 U.S. presidential election.

The competitive elections and referenda of most current democracies depend on mobilizing millions of voters within a context of advertising, social media, and efforts to manipulate as well as inform public opinion. Competing teams want to win and, in most cases, are interested in informing voters only when it is to their advantage. The rationale for competitive democracy, most influentially developed by the late economist Joseph Schumpeter, held that the same techniques of advertising used in the commercial sphere to get people to buy products can be expected in the political sphere. On this view, we should not expect a “genuine” public will, but rather “a manufactured will” that is just a by-product of political competition.

Yet the ideal of democracy as the rule of “the people” is deeply undermined when the will of the people is in large part manufactured. The legitimacy of democracy depends on some real link between the public will and the public policies and office-holders who are selected. Although some have criticized this “folk theory of democracy” as empirically naive, its very status as a folk theory reflects how widespread this normative expectation is.5 To the extent that leaders manufacture the public will, the normative causal arrow goes in the wrong direction. If current democracies cannot produce meaningful processes of public will formation, the legitimacy claims of meritocratic autocracies or even more fully autocratic systems become comparatively stronger.

Over the last two decades, another approach to democracy has become increasingly prominent. Based on greater deliberation among the public and its representatives, deliberative democracy has the potential, at least in theory, to respond to today’s current challenges. If the many versions of a more deliberative democracy live up to their aspirations, they could help revive democratic legitimacy, provide for more authentic public will formation, provide a middle ground between widely mistrusted elites and the angry voices of populism, and help fulfill some of our common normative expectations about democracy.

Can this potential be realized? In what ways and to what extent? Deliberative democracy has created a rich literature in both theory and practice. This issue of Dædalus assesses both its prospects and limits. We include advocates as well as critics. As deliberative democrats, our aim is to stimulate public deliberation about deliberative democracy, weighing arguments for and against its application in different contexts and for different purposes.

How can deliberative democracy, if it were to work as envisaged by its supporters, respond to the challenges just sketched? First, if the more-deliberative institutions that many advocate can be applied to real decisions in actual ongoing democracies, arguably they could have a positive effect on legitimacy and lead to better governance. They could make a better connection between the public’s real concerns and how they are governed. Second, these institutions could help fill the gap between distrusted elites and angry populists. Elites are distrusted in part because they seem and often are unresponsive to the public’s concerns, hopes, and values. Perhaps, the suspicion arises, the elites are really out for themselves. On the other hand, populism stirs up angry, mostly nondeliberative voices that can be mobilized in plebescitary campaigns, whether for Brexit or for elected office. In their contributions to this issue, both Claus Offe and Hélène Landemore explore the crisis of legitimacy in representative government, including the clash between status quo – oriented elites and populism. Deliberative democratic methods open up the prospect of prescriptions that are both representative of the entire population and based on sober, evidence-based analysis of the merits of competing arguments. Popular deliberative institutions are grounded in the public’s values and concerns, so the voice they magnify is not the voice of the elites. But that voice is usually also, after deliberation, more evidence-based and reflective of the merits of the major policy arguments. Hence these institutions fill an important gap.

How might popular deliberative democracy, if it were to work as envisaged by its supporters, fulfill normative expectations of democracy, thought to be unrealistic by critics of the “folk theory”? The issue turns on the empirical possibility that the public can actually deliberate. Can the people weigh the trade-offs? Can they assess competing arguments? Can they connect their deliberations with their voting preferences or other expressions of preference about what should be done? Is the problem that the people are not competent, or that they are not in the right institutional context to be effectively motivated to participate? These are empirical questions, and the controversies about them are part of our dialogue.

This issue includes varying definitions, approaches, and contexts. The root notion is that deliberation requires “weighing” competing arguments for policies or candidates in a context of mutually civil and diverse discussion in which people can decide on the merits of arguments with good information. Is such a thing possible in an era of fake news, social media, and public discussions largely among the like-minded? These are some of the challenges facing those who might try to make deliberative democracy practical….(More)”