Paper by Zhuang Liu, Michael Sockin & Wei Xiong: “This paper develops a foundation for a consumer’s preference for data privacy by linking it to the desire to hide behavioral vulnerabilities. Data sharing with digital platforms enhances the matching efficiency for standard consumption goods, but also exposes individuals with self-control issues to temptation goods. This creates a new form of inequality in the digital era—algorithmic inequality. Although data privacy regulations provide consumers with the option to opt out of data sharing, these regulations cannot fully protect vulnerable consumers because of data-sharing externalities. The coordination problem among consumers may also lead to multiple equilibria with drastically different levels of data sharing by consumers. Our quantitative analysis further illustrates that although data is non-rival and beneficial to social welfare, it can also exacerbate algorithmic inequality…(More)”.
Big data proves mobility is not gender-neutral
Blog by Ellin Ivarsson, Aiga Stokenberg and Juan Ignacio Fulponi: “All over the world, there is growing evidence showing that women and men travel differently. While there are many reasons behind this, one key factor is the persistence of traditional gender norms and roles that translate into different household responsibilities, different work schedules, and, ultimately, different mobility needs. Greater overall risk aversion and sensitivity to safety issues also play an important role in how women get around. Yet gender often remains an afterthought in the transport sector, meaning most policies or infrastructure investment plans are not designed to take into account the specific mobility needs of women.
The good news is that big data can help change that. In a recent study, the World Bank Transport team combined several data sources to analyze how women travel around the Buenos Aires Metropolitan Area (AMBA), including mobile phone signal data, congestion data from Waze, public transport smart card data, and data from a survey implemented by the team in early 2022 with over 20,300 car and motorcycle users.
Our research revealed that, on average, women in AMBA travel less often than men, travel shorter distances, and tend to engage in more complex trips with multiple stops and purposes. On average, 65 percent of the trips made by women are shorter than 5 kilometers, compared to 60 percent among men. Also, women’s hourly travel patterns are different, with 10 percent more trips than men during the mid-day off-peak hour, mostly originating in central AMBA. This reflects the larger burden of household responsibilities faced by women – such as picking children up from school – and the fact that women tend to work more irregular hours…(More)” See also Gender gaps in urban mobility.
Judging Nudging: Understanding the Welfare Effects of Nudges Versus Taxes
Paper by John A. List, Matthias Rodemeier, Sutanuka Roy & Gregory K. Sun: “While behavioral non-price interventions (“nudges”) have grown from academic curiosity to a bona fide policy tool, their relative economic efficiency remains under-researched. We develop a unified framework to estimate welfare effects of both nudges and taxes. We showcase our approach by creating a database of more than 300 carefully hand-coded point estimates of non-price and price interventions in the markets for cigarettes, influenza vaccinations, and household energy. While nudges are effective in changing behavior in all three markets, they are not necessarily the most efficient policy. We find that nudges are more efficient in the market for cigarettes, while taxes are more efficient in the energy market. For influenza vaccinations, optimal subsidies likely outperform nudges. Importantly, two key factors govern the difference in results across markets: i) an elasticity-weighted standard deviation of the behavioral bias, and ii) the magnitude of the average externality. Nudges dominate taxes whenever i) exceeds ii). Combining nudges and taxes does not always provide quantitatively significant improvements to implementing one policy tool alone…(More)”.
AI-assisted diplomatic decision-making during crises—Challenges and opportunities
Article by Neeti Pokhriyal and Till Koebe: “Recent academic works have demonstrated the efficacy of employing or integrating “non-traditional” data (e.g., social media, satellite imagery, etc) for situational awareness tasks…
Despite these successes, we identify four critical challenges unique to the area of diplomacy that needs to be considered within the growing AI and diplomacy community going ahead:
1. First, decisions during crises are almost always taken using limited or incomplete information. There may be deliberate misuse and obfuscation of data/signals between different parties involved. At the start of a crisis, information is usually limited and potentially biased, especially along socioeconomic and rural-urban lines as crises are known to exacerbate the vulnerabilities already existing in the populations. This requires AI tools to quantify and visualize calibrated uncertainty in their outputs in an appropriate manner.
2. Second, in many cases, human lives and livelihoods are at stake. Therefore, any forecast, reasoning, or recommendation provided by AI assistance needs to be explainable and transparent for authorized users, but also secure against unauthorized access as diplomatic information is often highly sensitive. The question of accountability in case of misleading AI assistance needs to be addressed beforehand.
3. Third, in complex situations with high stakes but limited information, cultural differences and value-laden judgment driven by personal experiences play a central role in diplomatic decision-making. This calls for the use of learning techniques that can incorporate domain knowledge and experience.
4. Fourth, diplomatic interests during crises are often multifaceted, resulting in deep mistrust in and strategic misuse of information. Social media data, when used for consular tasks, has been shown to be susceptible to various d-/misinformation campaigns, some by the public, others by state actors for strategic manipulation…(More)”
What do data portals do? Tracing the politics of online devices for making data public
Paper by Jonathan Gray: “The past decade has seen the rise of “data portals” as online devices for making data public. They have been accorded a prominent status in political speeches, policy documents, and official communications as sites of innovation, transparency, accountability, and participation. Drawing on research on data portals around the world, data portal software, and associated infrastructures, this paper explores three approaches for studying the social life of data portals as technopolitical devices: (a) interface analysis, (b) software analysis, and (c) metadata analysis. These three approaches contribute to the study of the social lives of data portals as dynamic, heterogeneous, and contested sites of public sector datafication. They are intended to contribute to critically assessing how participation around public sector datafication is invited and organized with portals, as well as to rethinking and recomposing them…(More)”.
Evidence Gap Maps as Critical Information Communication Devices for Evidence-based Public Policy
Paper by Esteban Villa-Turek et al: “The public policy cycle requires increasingly the use of evidence by policy makers. Evidence Gap Maps (EGMs) are a relatively new methodology that helps identify, process, and visualize the vast amounts of studies representing a rich source of evidence for better policy making. This document performs a methodological review of EGMs and presents the development of a working integrated system that automates several critical steps of EGM creation by means of applied computational and statistical methods. Above all, the proposed system encompasses all major steps of EGM creation in one place, namely inclusion criteria determination, processing of information, analysis, and user-friendly communication of synthesized relevant evidence. This tool represents a critical milestone in the efforts of implementing cutting-edge computational methods in usable systems. The contribution of the document is two-fold. First, it presents the critical importance of EGMs in the public policy cycle; second, it justifies and explains the development of a usable tool that encompasses the methodological phases of creation of EGMs, while automating most time-consuming stages of the process. The overarching goal is the better and faster information communication to relevant actors like policy makers, thus promoting well-being through better and more efficient interventions based on more evidence-driven policy making…(More)”.
The People and the Experts
Paper by William D. Nordhaus & Douglas Rivers: “Are speculators driving up oil prices? Should we raise energy prices to slow global warming? The present study takes a small number of such questions and compares the views of economic experts with those of the public. This comparison uses a panel of more than 2000 respondents from YouGov with the views of the panel of experts from the Initiative on Global Markets at the Chicago Booth School. We found that most of the US population is at best modestly informed about major economic questions and policies. The low level of knowledge is generally associated with the intrusion of ideological, political, and religious views that challenge or deny the current economic consensus. The intruding factors are highly heterogeneous across questions and sub-populations and are much more diverse than the narrowness of public political discourse would suggest. Many of these findings have been established for scientific subjects, but they appear to be equally important for economic views…(More)”.
Randomized Regulation: The Impact of Minimum Quality Standards on Health Markets
Paper by Guadalupe Bedoya, Jishnu Das & Amy Dolinger: “We report results from the first randomization of a regulatory reform in the health sector. The reform established minimum quality standards for patient safety, an issue that has become increasingly salient following the Ebola and COVID-19 epidemics. In our experiment, all 1348 health facilities in three Kenyan counties were classified into 273 markets, and the markets were then randomly allocated to treatment and control groups. Government inspectors visited health facilities and, depending on the results of their inspection, recommended closure or a timeline for improvements. The intervention increased compliance with patient safety measures in both public and private facilities (more so in the latter) and reallocated patients from private to public facilities without increasing out-of-pocket payments or decreasing facility use. In treated markets, improvements were equally marked throughout the quality distribution, consistent with a simple model of vertical differentiation in oligopolies. Our paper thus establishes the use of experimental techniques to study regulatory reforms and, in doing so, shows that minimum standards can improve quality across the board without adversely affecting utilization…(More)”.
Mapping the discourse on evidence-based policy, artificial intelligence, and the ethical practice of policy analysis
Paper by Joshua Newman and Michael Mintrom: “Scholarship on evidence-based policy, a subset of the policy analysis literature, largely assumes information is produced and consumed by humans. However, due to the expansion of artificial intelligence in the public sector, debates no longer capture the full range concerns. Here, we derive a typology of arguments on evidence-based policy that performs two functions: taken separately, the categories serve as directions in which debates may proceed, in light of advances in technology; taken together, the categories act as a set of frames through which the use of evidence in policy making might be understood. Using a case of welfare fraud detection in the Netherlands, we show how the acknowledgement of divergent frames can enable a holistic analysis of evidence use in policy making that considers the ethical issues inherent in automated data processing. We argue that such an analysis will enhance the real-world relevance of the evidence-based policy paradigm….(More)”
Spatial data trusts: an emerging governance framework for sharing spatial data
Paper by Nenad Radosevic et al: “Data Trusts are an important emerging approach to enabling the much wider sharing of data from many different sources and for many different purposes, backed by the confidence of clear and unambiguous data governance. Data Trusts combine the technical infrastructure for sharing data with the governance framework of a legal trust. The concept of a data Trust applied specifically to spatial data offers significant opportunities for new and future applications, addressing some longstanding barriers to data sharing, such as location privacy and data sovereignty. This paper introduces and explores the concept of a ‘spatial data Trust’ by identifying and explaining the key functions and characteristics required to underpin a data Trust for spatial data. The work identifies five key features of spatial data Trusts that demand specific attention and connects these features to a history of relevant work in the field, including spatial data infrastructures (SDIs), location privacy, and spatial data quality. The conclusions identify several key strands of research for the future development of this rapidly emerging framework for spatial data sharing…(More)”.