Paper by Jan Eeckhout & Laura Veldkamp: “Might firms’ use of data create market power? To explore this hypothesis, we craft a model in which economies of scale in data induce a data-rich firm to invest in producing at a lower marginal cost and larger scale. However, the model uncovers much richer interactions between data, welfare and market power. Data affects risk, firm size and the composition of the goods firms produce, all of which affect markups. The tradeoff between these forces depends on the level of aggregation at which markups are measured. Empirical researchers who measure markups at the product level, firm level or industry level come to different conclusions about trends and cyclical fluctuations in markups. Our results reconcile and re-interpret these facts. The divergence between product, firm and industry markups can be a sign that firms are using data to reallocate production to the goods consumers want most….(More)”.
Understanding Public Participation as a Mechanism Affecting Government Fiscal Outcomes: Theory and Evidence from Participatory Budgeting
Paper by Jinsol Park, J S Butler, and Nicolai Petrovsky: “This study aims to advance our knowledge about the role of public participation in formulating budgetary decisions of local governments. By focusing on participatory budgeting as a prominent form of public participation in the budgetary process, we posit that participatory budgeting serves two important roles in aligning the fiscal outcomes of local governments with citizen preferences: (1) increased transparency of the local budget and (2) improved budget literacy of citizens. This study investigates a link between participatory budgeting and the fiscal outcomes of local governments by utilizing data drawn from Korean local governments for seven fiscal years. Employing instrumental variable regression to address endogeneity, there is strong evidence that public participation and deliberation during the participatory budgeting process have a positive association with the fiscal balance. There is also weak evidence that the authority delegated to participatory budgeting participants affects the fiscal balance. The findings of this study imply that it is the quality of public participation that matters in holding the government accountable for its fiscal decisions…(More)”.
Trust but Verify: Validating New Measures for Mapping Social Infrastructure in Cities
Paper by Timothy Fraser et al: “Scholars and policymakers increasingly recognize the value of social capital – the connections that generate and enable trust among people – in responding to and recovering from shocks and disasters. However, some communities have more social infrastructure, that is, sites that produce and maintain social capital, than others. Community centers, libraries, public pools, and parks serve as locations where people can gather, interact, and build social ties. Much research on urban spaces relies on Google maps because of its ubiquity and this article tests the degree to which it can accurately, reliably, and effectively capture social infrastructure. In this study, we map the social infrastructure of Boston using Google Maps Places API and then ground truth our measures, mapping social infrastructure on street corners with in-person site observations to evaluate the accuracy of available data. We find that though we may need to use multi-vectored measurement when trying to capture social infrastructure, Google maps serve as reliable measurements with a predictable, acceptable margin of error…(More)”.
The Accountable Bureaucrat
Paper by Anya Bernstein and Cristina Rodriguez: “Common wisdom has it that, without close supervision by an elected official, administrative agencies are left unaccountable to the people they regulate. For both proponents and detractors of the administrative state, agency accountability thus hangs on the concentrated power of the President. This Article presents a different vision. Drawing on in-depth interviews with officials from numerous agencies, we argue that everyday administrative practices themselves support accountability—an accountability of a kind that elections alone cannot achieve. The electoral story focuses on the aspect of accountability that kicks in as a sanction after decisions have already been made. We propose instead that the ongoing justification of policy positions to multiple audiences empowered to evaluate and challenge them forms the heart of accountability in a republican democracy. The continual process of reason-giving, testing, and adaptation instantiates the values that make accountability normatively attractive: deliberation, inclusivity, and responsiveness.
Our interviews reveal three primary features of the administrative state that support such accountability. First, political appointees and career civil servants, often presented as conflictual, actually enact complementary decisionmaking modalities. Appointees do not impose direct presidential control but imbue agencies with a diffuse, differentiated sense of abstract political values. Civil servants use expertise and experience to set the parameters within which decisions can be made. The process of moving these differing but interdependent approaches toward a decision promotes deliberation. Second, agencies work through a networked spiderweb of decisionmaking that involves continual justification and negotiation among numerous groups. This claim stands in stark contrast to the strict hierarchy often attributed to government bureaucracy: we show how the principal-agent model, frequently used to analyze agencies, obscures more than it reveals. The dispersion of decisionmaking power, we claim, promotes pluralistic inclusivity and provides more support for ongoing accountability than a concentration in presidential hands would. Finally, many two-way avenues connect agencies to the people and situations they regulate. Those required by law, like notice-and-comment rulemaking, supplement numerous other interaction formats that agencies create. These multiple avenues support agency responsiveness to the views of affected publics and the realities of the regulated world….(More)”.
Accelerating ethics, empathy, and equity in geographic information science
Paper by T. A. Nelson, F. Goodchild and D. J. Wright: “Science has traditionally been driven by curiosity and followed one goal: the pursuit of truth and the advancement of knowledge. Recently, ethics, empathy, and equity, which we term “the 3Es,” are emerging as new drivers of research and disrupting established practices. Drawing on our own field of GIScience (geographic information science), our goal is to use the geographic approach to accelerate the response to the 3Es by identifying priority issues and research needs that, if addressed, will advance ethical, empathic, and equitable GIScience. We also aim to stimulate similar responses in other disciplines. Organized around the 3Es we discuss ethical issues arising from locational privacy and cartographic integrity, how our ability to build knowledge that will lead to empathy can be curbed by data that lack representativeness and by inadvertent inferential error, and how GIScientists can lead toward equity by supporting social justice efforts and democratizing access to spatial science and its tools. We conclude with a call to action and invite all scientists to join in a fundamentally different science that responds to the 3Es and mobilizes for change by engaging in humility, broadening measures of excellences and success, diversifying our networks, and creating pathways to inclusive education. Science united around the 3Es is the right response to this unique moment where society and the planet are facing a vast array of challenges that require knowledge, truth, and action…(More)”
The Issue of Proxies and Choice Architectures. Why EU Law Matters for Recommender Systems
Paper by Mireille Hildebrandt: “Recommendations are meant to increase sales or ad revenue, as these are the first priority of those who pay for them. As recommender systems match their recommendations with inferred preferences, we should not be surprised if the algorithm optimizes for lucrative preferences and thus co-produces the preferences they mine. This relates to the well-known problems of feedback loops, filter bubbles, and echo chambers. In this article, I discuss the implications of the fact that computing systems necessarily work with proxies when inferring recommendations and raise a number of questions about whether recommender systems actually do what they are claimed to do, while also analysing the often-perverse economic incentive structures that have a major impact on relevant design decisions. Finally, I will explain how the choice architectures for data controllers and providers of AI systems as foreseen in the EU’s General Data Protection Regulation (GDPR), the proposed EU Digital Services Act (DSA) and the proposed EU AI Act will help to break through various vicious circles, by constraining how people may be targeted (GDPR, DSA) and by requiring documented evidence of the robustness, resilience, reliability, and the responsible design and deployment of high-risk recommender systems (AI Act)…(More)”.
Responsiveness of open innovation to COVID-19 pandemic: The case of data for good
Paper by Francesco Scotti, Francesco Pierri, Giovanni Bonaccorsi, and Andrea Flori: “Due to the COVID-19 pandemic, countries around the world are facing one of the most severe health and economic crises of recent history and human society is called to figure out effective responses. However, as current measures have not produced valuable solutions, a multidisciplinary and open approach, enabling collaborations across private and public organizations, is crucial to unleash successful contributions against the disease. Indeed, the COVID-19 represents a Grand Challenge to which joint forces and extension of disciplinary boundaries have been recognized as main imperatives. As a consequence, Open Innovation represents a promising solution to provide a fast recovery. In this paper we present a practical application of this approach, showing how knowledge sharing constitutes one of the main drivers to tackle pressing social needs. To demonstrate this, we propose a case study regarding a data sharing initiative promoted by Facebook, the Data For Good program. We leverage a large-scale dataset provided by Facebook to the research community to offer a representation of the evolution of the Italian mobility during the lockdown. We show that this repository allows to capture different patterns of movements on the territory with increasing levels of detail. We integrate this information with Open Data provided by the Lombardy region to illustrate how data sharing can also provide insights for private businesses and local authorities. Finally, we show how to interpret Data For Good initiatives in light of the Open Innovation Framework and discuss the barriers to adoption faced by public administrations regarding these practices…(More)”.
Information aggregation and collective intelligence beyond the wisdom of crowds
Paper by Tatsuya Kameda, Wataru Toyokawa & R. Scott Tindale: “In humans and other gregarious animals, collective decision-making is a robust behavioural feature of groups. Pooling individual information is also fundamental for modern societies, in which digital technologies have exponentially increased the interdependence of individual group members. In this Review, we selectively discuss the recent human and animal literature, focusing on cognitive and behavioural mechanisms that can yield collective intelligence beyond the wisdom of crowds. We distinguish between two group decision-making situations: consensus decision-making, in which a group consensus is required, and combined decision-making, in which a group consensus is not required. We show that in both group decision-making situations, cognitive and behavioural algorithms that capitalize on individual heterogeneity are the key for collective intelligence to emerge. These algorithms include accuracy or expertise-weighted aggregation of individual inputs and implicit or explicit coordination of cognition and behaviour towards division of labour. These mechanisms can be implemented either as ‘cognitive algebra’, executed mainly within the mind of an individual or by some arbitrating system, or as a dynamic behavioural aggregation through social interaction of individual group members. Finally, we discuss implications for collective decision-making in modern societies characterized by a fluid but auto-correlated flow of information and outline some future directions….(More)”.
Citizen science and environmental justice: exploring contradictory outcomes through a case study of air quality monitoring in Dublin
Paper by Fiadh Tubridy et al: “Citizen science is advocated as a response to a broad range of contemporary societal and ecological challenges. However, there are widely varying models of citizen science which may either challenge or reinforce existing knowledge paradigms and associated power dynamics. This paper explores different approaches to citizen science in the context of air quality monitoring in terms of their implications for environmental justice. This is achieved through a case study of air quality management in Dublin which focuses on the role of citizen science in this context. The evidence shows that the dominant interpretation of citizen science in Dublin is that it provides a means to promote awareness and behaviour change rather than to generate knowledge and inform new regulations or policies. This is linked to an overall context of technocratic governance and the exclusion of non-experts from decision-making. It is further closely linked to neoliberal governance imperatives to individualise responsibility and promote market-based solutions to environmental challenges. Last, the evidence highlights that this model of citizen science risks compounding inequalities by transferring responsibility and blame for air pollution to those who have limited resources to address it. Overall, the paper highlights the need for critical analysis of the implications of citizen science in different instances and for alternative models of citizen science whereby communities would contribute to setting objectives and determining how their data is used…(More)”.
Innovation Indicators
Paper by Fred Gault and Luc Soete: “Innovation indicators support research on innovation and the development of innovation policy. Once a policy has been implemented, innovation indicators can be used to monitor and evaluate the result, leading to policy learning. Producing innovation indicators requires an understanding of what innovation is. There are many definitions in the literature, but innovation indicators are based on statistical measurement guided by international standard definitions of innovation and of innovation activities.
Policymakers are not just interested in the occurrence of innovation but in the outcome. Does it result in more jobs and economic growth? Is it expected to reduce carbon emissions, to advance renewable energy production and energy storage? How does innovation support the Sustainable Development Goals? From the innovation indicator perspective, innovation can be identified in surveys, but that only shows that there is, or there is not, innovation. To meet specific policy needs, a restriction can be imposed on the measurement of innovation. The population of innovators can be divided into those meeting the restriction, such as environmental improvements, and those that do not. In the case of innovation indicators that show a change over time, such as “inclusive innovation,” there may have to be a baseline measurement followed by a later measurement to see if inclusiveness is present, or growing, or not. This may involve social as well as institutional surveys. Once the innovation indicators are produced, they can be made available to potential users through databases, indexes, and scoreboards. Not all of these are based on the statistical measurement of innovation. Some use proxies, such as the allocation of financial and human resources to research and development, or the use of patents and academic publications. The importance of the databases, indexes, and scoreboards is that the findings may be used for the ranking of “innovation” in participating countries, influencing their behavior. While innovation indicators have always been influential, they have the potential to become more so. For decades, innovation indicators have focused on innovation in the business sector, while there have been experiments on measuring innovation in the public (general government sector and public institutions) and the household sectors. Historically, there has been no standard definition of innovation applicable in all sectors of the economy (business, public, household, and non-profit organizations serving households sectors). This changed with the Oslo Manual in 2018, which published a general definition of innovation applicable in all economic sectors. Applying a general definition of innovation has implications for innovation indicators and for the decisions that they influence. If the general definition is applied to the business sector, it includes product innovations that are made available to potential users rather than being introduced on the market. The product innovation can be made available at zero price, which has influence on innovation indicators that are used to describe the digital transformation of the economy. The general definition of innovation, the digital transformation of the economy, and the growing importance of zero price products influence innovation indicators…(More)”.