Illuminating GDP


Money and Banking: “GDP figures are ‘man-made’ and therefore unreliable,” reported remarks of Li Keqiang (then Communist Party secretary of the northeastern Chinese province of Liaoning), March 12, 2007.

Satellites are great. It is hard to imagine living without them. GPS navigation is just the tip of the iceberg. Taking advantage of the immense amounts of information collected over decades, scientists have been using satellite imagery to study a broad array of questions, ranging from agricultural land use to the impact of climate change to the geographic constraints on cities (see here for a recent survey).

One of the most well-known economic applications of satellite imagery is to use night-time illumination to enhance the accuracy of various reported measures of economic activity. For example, national statisticians in countries with poor information collection systems can employ information from satellites to improve the quality of their nationwide economic data (see here). Even where governments have relatively high-quality statistics at a national level, it remains difficult and costly to determine local or regional levels of activity. For example, while production may occur in one jurisdiction, the income generated may be reported in another. At a sufficiently high resolution, satellite tracking of night-time light emissions can help address this question (see here).

But satellite imagery is not just an additional source of information on economic activity, it is also a neutral one that is less prone to manipulation than standard accounting data. This makes it is possible to use information on night-time light to monitor the accuracy of official statistics. And, as we suggest later, the willingness of observers to apply a “satellite correction” could nudge countries to improve their own data reporting systems in line with recognized international standards.

As Luis Martínez inquires in his recent paper, should we trust autocrats’ estimates of GDP? Even in relatively democratic countries, there are prominent examples of statistical manipulation (recall the cases of Greek sovereign debt in 2009 and Argentine inflation in 2014). In the absence of democratic checks on the authorities, Martínez finds even greater tendencies to distort the numbers….(More)”.

Constitutional Democracy and Technology in the age of Artificial Intelligence


Paul Nemitz at Royal Society Philosophical Transactions: “Given the foreseeable pervasiveness of Artificial Intelligence in modern societies, it is legitimate and necessary to ask the question how this new technology must be shaped to support the maintenance and strengthening of constitutional democracy.

This paper first describes the four core elements of today’s digital power concentration, which need to be seen in cumulation and which, seen together, are both a threat to democracy and to functioning markets. It then recalls the experience with the lawless internet and the relationship between technology and the law as it has developed in the internet economy and the experience with GDPR before it moves on to the key question for AI in democracy, namely which of the challenges of AI can be safely and with good conscience left to ethics, and which challenges of AI need to be addressed by rules which are enforceable and encompass the legitimacy of democratic process, thus laws.

The paper closes with a call for a new culture of incorporating the principles of Democracy, Rule of law and Human Rights by design in AI and a three level technological impact assessment for new technologies like AI as a practical way forward for this purpose….(More).

The political origins of transparency reform: insights from the Italian case


Paper by Fabrizio Di Mascio,  Alessandro Natalini and Federica Cacciatore: This research contributes to the expanding literature on the determinants of government transparency. It uncovers the dynamics of transparency in the Italian case, which shows an interesting reform trajectory: until the late 1980s no transparency provisions existed; since then, provisions have dramatically increased under the impulse of changing patterns of political competition.

The analysis of the Italian case highlights that electoral uncertainty for incumbents is a double-edged sword for institutional reform: on the one hand, it incentivizes the adoption of ever-growing transparency provisions; on the other, it jeopardizes the implementation capacity of public agencies by leading to severe administrative burdens….(More)”.

European science funders ban grantees from publishing in paywalled journals


Martin Enserink at Science: “Frustrated with the slow transition toward open access (OA) in scientific publishing, 11 national funding organizations in Europe turned up the pressure today. As of 2020, the group, which jointly spends about €7.6 billion on research annually, will require every paper it funds to be freely available from the moment of publication. In a statement, the group said it will no longer allow the 6- or 12-month delays that many subscription journals now require before a paper is made OA, and it won’t allow publication in so-called hybrid journals, which charge subscriptions but also make individual papers OA for an extra fee.

The move means grantees from these 11 funders—which include the national funding agencies in the United Kingdom, the Netherlands, and France as well as Italy’s National Institute for Nuclear Physics—will have to forgo publishing in thousands of journals, including high-profile ones such as NatureScienceCell, and The Lancet, unless those journals change their business model. “We think this could create a tipping point,” says Marc Schiltz, president of Science Europe, the Brussels-based association of science organizations that helped coordinate the plan. “Really the idea was to make a big, decisive step—not to come up with another statement or an expression of intent.”

The announcement delighted many OA advocates. “This will put increased pressure on publishers and on the consciousness of individual researchers that an ecosystem change is possible,” says Ralf Schimmer, head of Scientific Information Provision at the Max Planck Digital Library in Munich, Germany. Peter Suber, director of the Harvard Library Office for Scholarly Communication, calls the plan “admirably strong.” Many other funders support OA, but only the Bill & Melinda Gates Foundation applies similarly stringent requirements for “immediate OA,” Suber says. The European Commission and the European Research Council support the plan; although they haven’t adopted similar requirements for the research they fund, a statement by EU Commissioner for Research, Science and Innovation Carlos Moedas suggests they may do so in the future and urges the European Parliament and the European Council to endorse the approach….(More)”.

Message and Environment: a framework for nudges and choice architecture


Paper by Luca Congiu and Ivan Moscati in Behavioural Public Policy: “We argue that the diverse components of a choice architecture can be classified into two main dimensions – Message and Environment – and that the distinction between them is useful in order to better understand how nudges work. In the first part of this paper, we define what we mean by nudge, explain what Message and Environment are, argue that the distinction between them is conceptually robust and show that it is also orthogonal to other distinctions advanced in the nudge literature. In the second part, we review some common types of nudges and show they target either Message or Environment or both dimensions of the choice architecture. We then apply the Message–Environment framework to discuss some features of Amazon’s website and, finally, we indicate how the proposed framework could help a choice architect to design a new choice architecture….(More)”.

Understanding Data Use: Building M&E Systems that Empower Users


Paper by Susan Stout, Vinisha Bhatia, and Paige Kirby: “We know that Monitoring and Evaluation (M&E) aims to support accountability and learning, in order to drive better outcomes…The paper, Understanding Data Use: Building M&E Systems that Empower Users, emphasizes how critical it is for decision makers to consider users’ decision space – from the institutional all the way to technical levels – in achieving data uptake.

Specifically, we call on smart mapping of this decision space – what do intended M&E users need, and what institutional factors shape those needs? With this understanding, we can better anticipate what types of data are most useful, and invest in systems to support data-driven decision making and better outcomes.

Mapping decision space is essential to understanding M&E data use. And as we’ve explored before, the development community has the opportunity to unlock existing resources to access more and better data that fits the needs of development actors to meet the SDGs….(More)”.

Crowdsourcing – a New Paradigm of Organisational Learning of Public Organisation


Paper by Regina Lenart-Gansiniec and Łukasz Sułkowski: “Crowdsourcing is one of the new themes that has appeared in the last decade. Considering its potential, more and more organisations reach for it. It is perceived as an innovative method that can be used for problem solving, improving business processes, creating open innovations, building a competitive advantage, and increasing transparency and openness of the organisation. Crowdsourcing is also conceptualised as a source of a knowledge-based organisation. The importance of crowdsourcing for organisational learning is seen as one of the key themes in the latest literature in the field of crowdsourcing. Since 2008, there has been an increase in the interest of public organisations in crowdsourcing and including it in their activities.

This article is a response to the recommendations in the subject literature, which states that crowdsourcing in public organisations is a new and exciting research area. The aim of the article is to present a new paradigm that combines crowdsourcing levels with the levels of learning. The research methodology is based on an analysis of the subject literature and exemplifications of organisations which introduce crowdsourcing. This article presents a cross-sectional study of four Polish municipal offices that use four types of crowdsourcing, according to the division by J. Howe: collective intelligence, crowd creation, crowd voting, and crowdfunding. Semi-structured interviews were conducted with the management personnel of those municipal offices. The research results show that knowledge acquired from the virtual communities allows the public organisation to anticipate changes, expectations, and needs of citizens and to adapt to them. It can therefore be considered that crowdsourcing is a new and rapidly developing organisational learning paradigm….(More)”

Origin Privacy: Protecting Privacy in the Big-Data Era


Paper by Helen Nissenbaum, Sebastian Benthall, Anupam Datta, Michael Carl Tschantz, and Piot Mardziel: “Machine learning over big data poses challenges for our conceptualization of privacy. Such techniques can discover surprising and counteractive associations that take innocent looking data and turns it into important inferences about a person. For example, the buying carbon monoxide monitors has been linked to paying credit card bills, while buying chrome-skull car accessories predicts not doing so. Also, Target may have used the buying of scent-free hand lotion and vitamins as a sign that the buyer is pregnant. If we take pregnancy status to be private and assume that we should prohibit the sharing information that can reveal that fact, then we have created an unworkable notion of privacy, one in which sharing any scrap of data may violate privacy.

Prior technical specifications of privacy depend on the classification of certain types of information as private or sensitive; privacy policies in these frameworks limit access to data that allow inference of this sensitive information. As the above examples show, today’s data rich world creates a new kind of problem: it is difficult if not impossible to guarantee that information does notallow inference of sensitive topics. This makes information flow rules based on information topic unstable.

We address the problem of providing a workable definition of private data that takes into account emerging threats to privacy from large-scale data collection systems. We build on Contextual Integrity and its claim that privacy is appropriate information flow, or flow according to socially or legally specified rules.

As in other adaptations of Contextual Integrity (CI) to computer science, the parameterization of social norms in CI is translated into a logical specification. In this work, we depart from CI by considering rules that restrict information flow based on its origin and provenance, instead of on it’s type, topic, or subject.

We call this concept of privacy as adherence to origin-based rules Origin Privacy. Origin Privacy rules can be found in some existing data protection laws. This motivates the computational implementation of origin-based rules for the simple purpose of compliance engineering. We also formally model origin privacy to determine what security properties it guarantees relative to the concerns that motivate it….(More)”.

‘To own or not to own?’ A study on the determinants and consequences of alternative intellectual property rights arrangements in crowdsourcing for innovation contests


Paper by Nuran Acur, Mariangela Piazza and Giovanni Perrone: “Firms are increasingly engaging in crowdsourcing for innovation to access new knowledge beyond their boundaries; however, scholars are no closer to understanding what guides seeker firms in deciding the level at which to acquire rights from solvers and the effect that this decision has on the performance of crowdsourcing contests.

Integrating Property Rights Theory and the problem solving perspective whist leveraging exploratory interviews and observations, we build a theoretical framework to examine how specific attributes of the technical problem broadcast affect the seekers’ choice between alternative intellectual property rights (IPR) arrangements that call for acquiring or licensing‐in IPR from external solvers (i.e. with high and low degrees of ownership respectively). Each technical problem differs in the knowledge required to be solved as well as in the stage of development it occurs of the innovation process and seeker firms pay great attention to such characteristics when deciding about the IPR arrangement they choose for their contests.

In addition, we analyze how this choice between acquiring and licensing‐in IPR, in turn, influences the performance of the contest. We empirically test our hypotheses analyzing a unique dataset of 729 challenges broadcast on the InnoCentive platform from 2010 to 2016. Our results indicate that challenges related to technical problems in later stages of the innovation process are positively related to the seekers’ preference toward IPR arrangements with a high level of ownership, while technical problems involving a higher number of knowledge domains are not.

Moreover, we found that IPR arrangements with a high level of ownership negatively affect solvers’ participation and that IPR arrangement plays a mediating role between the attributes of the technical problem and the solvers’ self‐selection process. Our article contributes to the open innovation and crowdsourcing literature and provides practical implications for both managers and contest organizers….(More)”.

Citizen science, public policy


Paper by Christi J. GuerriniMary A. Majumder,  Meaganne J. Lewellyn, and Amy L. McGuire in Science: “Citizen science initiatives that support collaborations between researchers and the public are flourishing. As a result of this enhanced role of the public, citizen science demonstrates more diversity and flexibility than traditional science and can encompass efforts that have no institutional affiliation, are funded entirely by participants, or continuously or suddenly change their scientific aims.

But these structural differences have regulatory implications that could undermine the integrity, safety, or participatory goals of particular citizen science projects. Thus far, citizen science appears to be addressing regulatory gaps and mismatches through voluntary actions of thoughtful and well-intentioned practitioners.

But as citizen science continues to surge in popularity and increasingly engage divergent interests, vulnerable populations, and sensitive data, it is important to consider the long-term effectiveness of these private actions and whether public policies should be adjusted to complement or improve on them. Here, we focus on three policy domains that are relevant to most citizen science projects: intellectual property (IP), scientific integrity, and participant protections….(More)”.