The Behavioral Scientists Working Toward a More Peaceful World

Interview by Heather Graci: “…Nation-level data doesn’t help us understand community-level conflict. Without understanding community-level conflict, it becomes much harder to design policies to prevent it.

Cikara: “So much of the data that we have is at the level of the nation, when our effects are all happening at very local levels. You see these reports that say, “In Germany, 14 percent of the population is immigrants.” It doesn’t matter at the national level, because they’re not distributed evenly across the geography. That means that some communities are going to be at greater risk for conflict than others. But that sort of local variation and sensitivity to it, at least heretofore, has really been missing from the conversation on the research side. Even when you’re in the same place, in the same country within the same state, the same canton, there can still be a ton of variation from neighborhood to neighborhood. 

“The other thing that we know matters a lot is not just the diversity of these neighborhoods but the segregation of them. It turns out that these kinds of prejudices and violence are less likely to break out in those places where it’s both diverse and people are interdigitated with how they live. So it’s not just the numbers, it’s also the spatial organization. 

“For example, in Singapore, because so much of the real estate is state-owned, they make it so that people who are coming from different countries can’t cluster together because they assign them to live separate from one another in order to prevent these sorts of enclaves. All these structural and meta-level organizational features have really, really important inputs for intergroup dynamics and psychology.”..(More)”.

Why policy failure is a prerequisite for innovation in the public sector

Blog by Philipp Trein and Thenia Vagionaki: “In our article entitled, “Why policy failure is a prerequisite for innovation in the public sector,” we explore the relationship between policy failure and innovation within public governance. Drawing inspiration from the “Innovator’s Dilemma,”—a theory from the management literature—we argue that the very nature of policymaking, characterized by myopia of voters, blame avoidance by decisionmakers, and the complexity (ill-structuredness) of societal challenges, has an inherent tendency to react with innovation only after failure of existing policies.  

Our analysis implies that we need to be more critical of what the policy process can achieve in terms of public sector innovation. Cognitive limitations tend to lead to a misperception of problems and inaccurate assessment of risks by decision makers according to the “Innovator’s Dilemma”.  This problem implies that true innovation (non-trivial policy changes) are unlikely to happen before an existing policy has failed visibly. However, our perspective does not want to paint a gloomy picture for public policy making but rather offers a more realistic interpretation of what public sector innovation can achieve. As a consequence, learning from experts in the policy process should be expected to correct failures in public sector problem-solving during the political process, rather than raise expectations beyond what is possible. 

The potential impact of our findings is profound. For practitioners and policymakers, this insight offers a new lens through which to evaluate the failure and success of public policies. Our work advocates a paradigm shift in how we perceive, manage, and learn from policy failures in the public sector, and for the expectations we have towards learning and the use of evidence in policymaking. By embracing the limitations of innovation in public policy, we can better manage expectations and structure the narrative regarding the capacity of public policy to address collective problems…(More)”.

The Character of Consent

Book by Meg Leta Jones about The History of Cookies and the Future of Technology Policy: “Consent pop-ups continually ask us to download cookies to our computers, but is this all-too-familiar form of privacy protection effective? No, Meg Leta Jones explains in The Character of Consent, rather than promote functionality, privacy, and decentralization, cookie technology has instead made the internet invasive, limited, and clunky. Good thing, then, that the cookie is set for retirement in 2024. In this eye-opening book, Jones tells the little-known story of this broken consent arrangement, tracing it back to the major transnational conflicts around digital consent over the last twenty-five years. What she finds is that the policy controversy is not, in fact, an information crisis—it’s an identity crisis.

Instead of asking how people consent, Jones asks who exactly is consenting and to what. Packed into those cookie pop-ups, she explains, are three distinct areas of law with three different characters who can consent. Within (mainly European) data protection law, the data subject consents. Within communication privacy law, the user consents. And within consumer protection law, the privacy consumer consents. These areas of law have very different histories, motivations, institutional structures, expertise, and strategies, so consent—and the characters who can consent—plays a unique role in those areas of law….(More)”.

Framework for Governance of Indigenous Data (GID)

Framework by The National Indigenous Australians Agency (NIAA): “Australian Public Service agencies now have a single Framework for working with Indigenous data.

The National Indigenous Australians Agency will collaborate across the Australian Public Service to implement the Framework for Governance of Indigenous Data in 2024.

Commonwealth agencies are expected to develop a seven-year implementation plan, guided by four principles:

  1. Partner with Aboriginal and Torres Strait Islander people
  2. Build data-related capabilities
  3. Provide knowledge of data assets
  4. Build an inclusive data system

The Framework represents the culmination of over 18 months of co-design effort between the Australian Government and Aboriginal and Torres Strait Islander partners. While we know we have some way to go, the Framework serves as a significant step forward to improve the collection, use and disclosure of data, to better serve Aboriginal and Torres Strait Islander priorities.

The Framework places Aboriginal and Torres Strait Islander peoples at its core. Recognising the importance of authentic engagement, it emphasises the need for First Nations communities to have a say in decisions affecting them, including the use of data in government policy-making.

Acknowledging data’s significance in self-determination, the Framework provides a stepping stone towards greater awareness and acceptance by Australian Government agencies of the principles of Indigenous Data Sovereignty.

It offers practical guidance on implementing key aspects of data governance aligned with both Indigenous Data Sovereignty principles and the objectives of the Australian Government…(More)”.

Can Artificial Intelligence Bring Deliberation to the Masses?

Chapter by Hélène Landemore: “A core problem in deliberative democracy is the tension between two seemingly equally important conditions of democratic legitimacy: deliberation, on the one hand, and mass participation, on the other. Might artificial intelligence help bring quality deliberation to the masses? The answer is a qualified yes. The chapter first examines the conundrum in deliberative democracy around the trade-off between deliberation and mass participation by returning to the seminal debate between Joshua Cohen and Jürgen Habermas. It then turns to an analysis of the 2019 French Great National Debate, a low-tech attempt to involve millions of French citizens in a two-month-long structured exercise of collective deliberation. Building on the shortcomings of this process, the chapter then considers two different visions for an algorithm-powered form of mass deliberation—Mass Online Deliberation (MOD), on the one hand, and Many Rotating Mini-publics (MRMs), on the other—theorizing various ways artificial intelligence could play a role in them. To the extent that artificial intelligence makes the possibility of either vision more likely to come to fruition, it carries with it the promise of deliberation at the very large scale….(More)”

Artificial Intelligence Opportunities for State and Local Departments Of Transportation

Report by the National Academies of Sciences, Engineering, and Medicine: “Artificial intelligence (AI) has revolutionized various areas in departments of transportation (DOTs), such as traffic management and optimization. Through predictive analytics and real-time data processing, AI systems show promise in alleviating congestion, reducing travel times, and enhancing overall safety by alerting drivers to potential hazards. AI-driven simulations are also used for testing and improving transportation systems, saving time and resources that would otherwise be needed for physical tests…(More)”.

Handbook of Public Participation in Impact Assessment

Book edited by Tanya Burdett and A. John Sinclair: “… provides a clear overview of how to achieve meaningful public participation in impact assessment (IA). It explores conceptual elements, including the democratic core of public participation in IA, as well as practical challenges, such as data sharing, with diverse perspectives from 39 leading academics and practitioners.

Critically examining how different engagement frameworks have evolved over time, this Handbook underlines the ways in which tokenistic approaches and wider planning and approvals structures challenge the implementation of meaningful public participation. Contributing authors discuss the impact of international agreements, legislation and regulatory regimes, and review commonly used professional association frameworks such as the International Association for Public Participation core values for practice. They demonstrate through case studies what meaningful public participation looks like in diverse regional contexts, addressing the intentions of being purposeful, inclusive, transformative and proactive. By emphasising the strength of community engagement, the Handbook argues that public participation in IA can contribute to enhanced democracy and sustainability for all…(More)”.

How to optimize the systematic review process using AI tools

Paper by Nicholas Fabiano et al: “Systematic reviews are a cornerstone for synthesizing the available evidence on a given topic. They simultaneously allow for gaps in the literature to be identified and provide direction for future research. However, due to the ever-increasing volume and complexity of the available literature, traditional methods for conducting systematic reviews are less efficient and more time-consuming. Numerous artificial intelligence (AI) tools are being released with the potential to optimize efficiency in academic writing and assist with various stages of the systematic review process including developing and refining search strategies, screening titles and abstracts for inclusion or exclusion criteria, extracting essential data from studies and summarizing findings. Therefore, in this article we provide an overview of the currently available tools and how they can be incorporated into the systematic review process to improve efficiency and quality of research synthesis. We emphasize that authors must report all AI tools that have been used at each stage to ensure replicability as part of reporting in methods….(More)”.

Misuse versus Missed use — the Urgent Need for Chief Data Stewards in the Age of AI

Article by Stefaan Verhulst and Richard Benjamins: “In the rapidly evolving landscape of artificial intelligence (AI), the need for and importance of Chief AI Officers (CAIO) are receiving increasing attention. One prominent example came in a recent memo on AI policy, issued by Shalanda Young, Director of the United States Office of Management and Budget. Among the most important — and prominently featured — recommendations were a call, “as required by Executive Order 14110,” for all government agencies to appoint a CAIO within 60 days of the release of the memo.

In many ways, this call is an important development; not even the EU AI Act is requiring this of public agencies. CAIOs have an important role to play in the search for a responsible use of AI for public services that would include guardrails and help protect the public good. Yet while acknowledging the need for CAIOs to safeguard a responsible use of AI, we argue that the duty of Administrations is not only to avoid negative impact, but also to create positive impact. In this sense, much work remains to be done in defining the CAIO role and considering their specific functions. In pursuit of these tasks, we further argue, policymakers and other stakeholders might benefit from looking at the role of another emerging profession in the digital ecology–that of Chief Data Stewards (CDS), which is focused on creating such positive impact for instance to help achieve the UN’s SDGs. Although the CDS position is itself somewhat in flux, we suggest that CDS can nonetheless provide a useful template for the functions and roles of CAIOs.

Image courtesy of Advertising Week

We start by explaining why CDS are relevant to the conversation over CAIOs; this is because data and data governance are foundational to AI governance. We then discuss some particular functions and competencies of CDS, showing how these can be equally applied to the governance of AI. Among the most important (if high-level) of these competencies is an ability to proactively identify opportunities in data sharing, and to balance the risks and opportunities of our data age. We conclude by exploring why this competency–an ethos of positive data responsibility that avoids overly-cautious risk aversion–is so important in the AI and data era…(More)”

The Social Value of Hurricane Forecasts

Paper by Renato Molina & Ivan Rudik: “What is the impact and value of hurricane forecasts? We study this question using newly-collected forecast data for major US hurricanes since 2005. We find higher wind speed forecasts increase pre-landfall protective spending, but erroneous under-forecasts increase post-landfall damage and rebuilding expenditures. Our main contribution is a new theoretically-grounded approach for estimating the marginal value of forecast improvements. We find that the average annual improvement reduced total per-hurricane costs, inclusive of unobserved protective spending, by $700,000 per county. Improvements since 2007 reduced costs by 19%, averaging $5 billion per hurricane. This exceeds the annual budget for all federal weather forecasting…(More)”.