Exploring digital government transformation in the EU


Analysis of the state of the art and review of literature by Gianluca Misuraca et al: “This report presents the… results of the review of literature, based on almost 500 academic and grey literature sources, as well as the analysis of digital government policies in the EU Member States provide a synthetic overview of the main themes and topics of the digital government discourse.

The report depicts the variety of existing conceptualisations and definitions of the digital government phenomenon, measured and expected effects of the application of more disruptive innovations and emerging technologies in government, as well as key drivers and barriers for transforming the public sector. Overall, the literature review shows that many sources appear overly optimistic with regard to the impact of digital government transformation, although the majority of them are based on normative views or expectations, rather than empirically tested insights.

The authors therefore caution that digital government transformation should be researched empirically and with a due differentiation between evidence and hope. In this respect, the report paves the way to in-depth analysis of the effects that can be generated by digital innovation in public sector organisations. A digital transformation that implies the redesign of the tools and methods used in the machinery of government will require in fact a significant change in the institutional frameworks that regulate and help coordinate the governance systems in which such changing processes are implemented…(More)”.

Dreamocracy – Collective Intelligence for the Common Good


About: “Dreamocracy is a think-and-do-tank that fosters collective intelligence / creativity for the common good through analysis, advice to organisations, and by developing and implementing innovative stakeholder management experiments.  

Dreamocracy aims to contribute to democracy’s reinvention and future. As Harvard scholar Yascha Mounk stresses, democracy in many parts of the world is at risk of “deconsolidation.” Possible collapse is signalled by the convergence of people’s dissatisfaction with democracy; their willingness to consider non-democratic forms of government as possible alternatives; and the rise in populist parties, anti-system movements and demagogues in government.

In order to ensure a bright future for democracy in service to society, Dreamocracy believes collective intelligence done well is essential to address the following three terms of our proposed “trust-in-government equation”:

TRUST = Process legitimacy + Output legitimacy + Emotions legitimacy….(More)”.

How randomised trials became big in development economics


Seán Mfundza Muller, Grieve Chelwa, and Nimi Hoffmann at the Conversation: “…One view of the challenge of development is that it is fundamentally about answering causal questions. If a country adopts a particular policy, will that cause an increase in economic growth, a reduction in poverty or some other improvement in the well-being of citizens?

In recent decades economists have been concerned about the reliability of previously used methods for identifying causal relationships. In addition to those methodological concerns, some have argued that “grand theories of development” are either incorrect or at least have failed to yield meaningful improvements in many developing countries.

Two notable examples are the idea that developing countries may be caught in a poverty trap that requires a “big push” to escape and the view that institutions are key for growth and development.

These concerns about methods and policies provided a fertile ground for randomised experiments in development economics. The surge of interest in experimental approaches in economics began in the early 1990s. Researchers began to use “natural experiments”, where for example random variation was part of a policy rather than decided by a researcher, to look at causation.

But it really gathered momentum in the 2000s, with researchers such as the Nobel awardees designing and implementing experiments to study a wide range of microeconomic questions.

Randomised trials

Proponents of these methods argued that a focus on “small” problems was more likely to succeed. They also argued that randomised experiments would bring credibility to economic analysis by providing a simple solution to causal questions.

These experiments randomly allocate a treatment to some members of a group and compare the outcomes against the other members who did not receive treatment. For example, to test whether providing credit helps to grow small firms or increase their likelihood of success, a researcher might partner with a financial institution and randomly allocate credit to applicants that meet certain basic requirements. Then a year later the researcher would compare changes in sales or employment in small firms that received the credit to those that did not.

Randomised trials are not a new research method. They are best known for their use in testing new medicines. The first medical experiment to use controlled randomisation occurred in the aftermath of the second world war. The British government used it to assess the effectiveness of a drug for tuberculosis treatment.

In the early 20th century and mid-20th century American researchers had used experiments like this to examine the effects of various social policies. Examples included income protection and social housing.

The introduction of these methods into development economics also followed an increase in their use in other areas of economics. One example was the study of labour markets.

Randomised control trials in economics are now mostly used to evaluate the impact of social policy interventions in poor and middle-income countries. Work by the 2019 Nobel awardees – Michael Kremer, Abhijit Banerjee and Esther Duflo – includes experiments in Kenya and India on teacher attendancetextbook provisionmonitoring of nurse attendance and the provision of microcredit.

The popularity, among academics and policymakers, of the approach is not only due to its seeming ability to solve methodological and policy concerns. It is also due to very deliberate, well-funded advocacy by its proponents….(More)”.

Platform policy and regulation: towards a radical democratic turn


Paper by Bart Cammaerts and Robin Mansell: “This article considers challenges to policy and regulation presented by the dominant digital platforms. A radical democratic framing of the deliberative process is developed to acknowledge the full complexity of power relations that are in play in policy and regulatory debates and this view is contrasted with a liberal democratic perspective.

We show how these different framings have informed historical and contemporary approaches to the challenges presented by conflicting interests in economic value and a range of public values in the context of media content, communication infrastructure and digital platform policy and regulation. We argue for an agonistic approach to digital platform policy and regulatory debate so as to encourage a denaturalization of the prevailing logics of commercial datafication. We offer some suggestions about how such a generative discourse might be encouraged in such a way that it starts to yield a new common sense about the further development of digital platforms; one that might favor a digital ecology better attuned to consumer and citizen interests in democratic societies….(More)”.

Quadratic Payments: A Primer


Blogpost by Vitalik Buterin: “If you follow applied mechanism design or decentralized governance at all, you may have recently heard one of a few buzzwords: quadratic votingquadratic funding and quadratic attention purchase. These ideas have been gaining popularity rapidly over the last few years, and small-scale tests have already been deployed: the Taiwanese presidential hackathon used quadratic voting to vote on winning projects, Gitcoin Grants used quadratic funding to fund public goods in the Ethereum ecosystem, and the Colorado Democratic party also experimented with quadratic voting to determine their party platform.

To the proponents of these voting schemes, this is not just another slight improvement to what exists. Rather, it’s an initial foray into a fundamentally new class of social technology which, has the potential to overturn how we make many public decisions, large and small. The ultimate effect of these schemes rolled out in their full form could be as deeply transformative as the industrial-era advent of mostly-free markets and constitutional democracy. But now, you may be thinking: “These are large promises. What do these new governance technologies have that justifies such claims?”…(More)”.

A World With a Billion Cameras Watching You Is Just Around the Corner


Liza Lin and Newley Purnell at the Wall Street Journal: “As governments and companies invest more in security networks, hundreds of millions more surveillance cameras will be watching the world in 2021, mostly in China, according to a new report.

The report, from industry researcher IHS Markit, to be released Thursday, said the number of cameras used for surveillance would climb above 1 billion by the end of 2021. That would represent an almost 30% increase from the 770 million cameras today. China would continue to account for a little over half the total.

Fast-growing, populous nations such as India, Brazil and Indonesia would also help drive growth in the sector, the report said. The number of surveillance cameras in the U.S. would grow to 85 million by 2021, from 70 million last year, as American schools, malls and offices seek to tighten security on their premises, IHS analyst Oliver Philippou said.

Mr. Philippou said government programs to implement widespread video surveillance to monitor the public would be the biggest catalyst for the growth in China. City surveillance also was driving demand elsewhere.

“It’s a public-safety issue,” Mr. Philippou said in an interview. “There is a big focus on crime and terrorism in recent years.”

The global security-camera industry has been energized by breakthroughs in image quality and artificial intelligence. These allow better and faster facial recognition and video analytics, which governments are using to do everything from managing traffic to predicting crimes.

China leads the world in the rollout of this kind of technology. It is home to the world’s largest camera makers, with its cameras on street corners, along busy roads and in residential neighborhoods….(More)”.

Public Entrepreneurship and Policy Engineering


Essay by Beth Noveck at Communications of the ACM: “Science and technology have progressed exponentially, making it possible for humans to live longer, healthier, more creative lives. The explosion of Internet and mobile phone technologies have increased trade, literacy, and mobility. At the same time, life expectancy for the poor has not increased and is declining.

As science fiction writer William Gibson famously quipped, the future is here, but unevenly distributed. With urgent problems from inequality to climate change, we must train more passionate and innovative people—what I call public entrepreneurs—to learn how to leverage new technology to tackle public problems. Public problems are those compelling and important challenges where neither the problem is well understood nor the solution agreed upon, yet we must devise and implement approaches, often from different disciplines, in an effort to improve people’s lives….(More)”.

Regulating Artificial Intelligence


Book by Thomas Wischmeyer and Timo Rademacher: “This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that currently shape or restrict the design or use of AI, and develops policy recommendations for those areas in which regulation is most urgently needed. By gathering contributions from scholars who are experts in their respective fields of legal research, it demonstrates that AI regulation is not a specialized sub-discipline, but affects the entire legal system and thus concerns all lawyers. 

Machine learning-based technology, which lies at the heart of what is commonly referred to as AI, is increasingly being employed to make policy and business decisions with broad social impacts, and therefore runs the risk of causing wide-scale damage. At the same time, AI technology is becoming more and more complex and difficult to understand, making it harder to determine whether or not it is being used in accordance with the law. In light of this situation, even tech enthusiasts are calling for stricter regulation of AI. Legislators, too, are stepping in and have begun to pass AI laws, including the prohibition of automated decision-making systems in Article 22 of the General Data Protection Regulation, the New York City AI transparency bill, and the 2017 amendments to the German Cartel Act and German Administrative Procedure Act. While the belief that something needs to be done is widely shared, there is far less clarity about what exactly can or should be done, or what effective regulation might look like. 

The book is divided into two major parts, the first of which focuses on features common to most AI systems, and explores how they relate to the legal framework for data-driven technologies, which already exists in the form of (national and supra-national) constitutional law, EU data protection and competition law, and anti-discrimination law. In the second part, the book examines in detail a number of relevant sectors in which AI is increasingly shaping decision-making processes, ranging from the notorious social media and the legal, financial and healthcare industries, to fields like law enforcement and tax law, in which we can observe how regulation by AI is becoming a reality….(More)”.

The Crowd and the Cosmos: Adventures in the Zooniverse


Book by Chris Lintott: “The world of science has been transformed. Where once astronomers sat at the controls of giant telescopes in remote locations, praying for clear skies, now they have no need to budge from their desks, as data arrives in their inbox. And what they receive is overwhelming; projects now being built provide more data in a few nights than in the whole of humanity’s history of observing the Universe. It’s not just astronomy either – dealing with this deluge of data is the major challenge for scientists at CERN, and for biologists who use automated cameras to spy on animals in their natural habitats. Artificial intelligence is one part of the solution – but will it spell the end of human involvement in scientific discovery?

No, argues Chris Lintott. We humans still have unique capabilities to bring to bear – our curiosity, our capacity for wonder, and, most importantly, our capacity for surprise. It seems that humans and computers working together do better than computers can on their own. But with so much scientific data, you need a lot of scientists – a crowd, in fact. Lintott found such a crowd in the Zooniverse, the web-based project that allows hundreds of thousands of enthusiastic volunteers to contribute to science.

In this book, Lintott describes the exciting discoveries that people all over the world have made, from galaxies to pulsars, exoplanets to moons, and from penguin behavior to old ship’s logs. This approach builds on a long history of so-called “citizen science,” given new power by fast internet and distributed data. Discovery is no longer the remit only of scientists in specialist labs or academics in ivory towers. It’s something we can all take part in. As Lintott shows, it’s a wonderful way to engage with science, yielding new insights daily. You, too, can help explore the Universe in your lunch hour…(More)”.

The Downside of Tech Hype


Jeffrey Funk at Scientific American: “Science and technology have been the largest drivers of economic growth for more than 100 years. But this contribution seems to be declining. Growth in labor productivity has slowed, corporate revenue growth per research dollar has fallen, the value of Nobel Prize–winning research has declined, and the number of researchers needed to develop new molecular entities (e.g., drugs) and same percentage improvements in crop yields and numbers of transistors on a microprocessor chip (commonly known as Moore’s Law) has risen. More recently, the percentage of profitable start-ups at the time of their initial public stock offering has dropped to record lows, not seen since the dot-com bubble and start-ups such as Uber, Lyft and WeWork have accumulated losses much larger than ever seen by start-ups, including Amazon.

Although the reasons for these changes are complex and unclear, one thing is certain: excessive hype about new technologies makes it harder for scientists, engineers and policy makers to objectively analyze and understand these changes, or to make good decisions about new technologies.

One driver of hype is the professional incentives of venture capitalists, entrepreneurs, consultants and universities. Venture capitalists have convinced decision makers that venture capitalist funding and start-ups are the new measures of their success. Professional and business service consultants hype technology for both incumbents and start-ups to make potential clients believe that new technologies make existing strategies, business models and worker skills obsolete every few years.

Universities are themselves a major source of hype. Their public relations offices often exaggerate the results of research papers, commonly implying that commercialization is close at hand, even though the researchers know it will take many years if not decades. Science and engineering courses often imply an easy path to commercialization, while misleading and inaccurate forecasts from Technology Review and Scientific American make it easier for business schools and entrepreneurship programs to claim that opportunities are everywhere and that incumbent firms are regularly being disrupted. With a growth in entrepreneurship programs from about 16 in 1970 to more than 2,000 in 2014, many young people now believe that being an entrepreneur is the cool thing to be, regardless of whether they have a good idea.

Hype from these types of experts is exacerbated by the growth of social media, the falling cost of website creation, blogging, posting of slides and videos and the growing number of technology news, investor and consulting websites….(More)”.