Open government, civic tech and digital platforms in Latin America: A governance study of Montevideo’s urban app ‘Por Mi Barrio’


Paper by Carolina Aguerre and Carla Bonina: “Digital technologies have a recognised potential to build more efficient, credible, and innovative public institutions in Latin America. Despite progress, digital transformation in Latin American governments remains limited. In this work, we explore a peculiar yet largely understudied opportunity in the region: pursuing digital government transformation as a collaborative process between the government and civil society organisations. To do so, we draw from information systems research on digital government and platforms for development, complemented with governance theory from political science and conduct an interpretive in-depth case study of an urban reporting platform in Montevideo called ‘Por Mi Barrio’. The study reveals three mutually reinforced orders of governance in the trajectory of the project and explain how the collaboration unfolded over time: (i) a technical decision to use open platform architectures; (ii) the negotiation of formal and informal rules to make the project thrive and (iii) a shared, long-term ideology around the value of open technologies and technical sovereignty grounded in years of political history. Using a contextual explanation approach, our study helps to improve our understanding on the governance of collaborative digital government platforms in Latin America, with specific contributions to practice…(More)”.

A systematic analysis of digital tools for citizen participation


Paper by Bokyong Shin et al: “Despite the increasing use of digital tools for citizen participation, their ecosystem and functionality remain underexplored. What digital tools exist, and how do they help citizens engage in policymaking? This article addresses this gap by examining the supply side of digital tools for citizen participation. We compiled a comprehensive dataset of 116 digital tools from three public repositories. Using the collective intelligence genome framework, adapted for the e-participation context, we systematically examined the dynamics and trends of these tools through cluster analyses. Our findings highlight the potential of digital participatory tools to facilitate the flow of information from citizens to governments using advanced technologies. However, a prominent deficiency was identified in disseminating accountability information to citizens regarding how policy decisions are made, realised, and assessed. These findings offer valuable insights and notable gaps in the digital tool ecosystem…(More)”.

The societal impact of Open Science: a scoping review


Report by Nicki Lisa Cole, Eva Kormann, Thomas Klebel, Simon Apartis and Tony Ross-Hellauer: “Open Science (OS) aims, in part, to drive greater societal impact of academic research. Government, funder and institutional policies state that it should further democratize research and increase learning and awareness, evidence-based policy-making, the relevance of research to society’s problems, and public trust in research. Yet, measuring the societal impact of OS has proven challenging and synthesized evidence of it is lacking. This study fills this gap by systematically scoping the existing evidence of societal impact driven by OS and its various aspects, including Citizen Science (CS), Open Access (OA), Open/FAIR Data (OFD), Open Code/Software and others. Using the PRISMA Extension for Scoping Reviews and searches conducted in Web of Science, Scopus and relevant grey literature, we identified 196 studies that contain evidence of societal impact. The majority concern CS, with some focused on OA, and only a few addressing other aspects. Key areas of impact found are education and awareness, climate and environment, and social engagement. We found no literature documenting evidence of the societal impact of OFD and limited evidence of societal impact in terms of policy, health, and trust in academic research. Our findings demonstrate a critical need for additional evidence and suggest practical and policy implications…(More)”.

From Waves to Ecosystems: The Next Stage of Democratic Innovation


Paper by Josh Lerner: “Anti-democratic movements are surging around the world, threatening to undermine elections and replace them with oligarchy. Pro-democracy movements mainly focus on defending elections, even though most people think that elections alone are inadequate. While elections dominate current thinking about democracy, the history and future of democracy is much broader. For over 5,000 years, people have built up competing waves of electoral, direct, deliberative, and participatory democracy. We are now seeing a transition, however, from waves to ecosystems. Rather than seeking one single solution to our ailing democracy, a new generation of democracy reformers is weaving together different democratic practices into balanced democratic ecosystems. This white paper provides a roadmap for this emerging next stage of democratic innovation. It reviews the limitations of elections, the different waves of democratic innovation and efforts to connect them, and key challenges and strategies for building healthy ecosystems of democracy…(More)”.

Government + research + philanthropy: How cross-sector partnerships can improve policy decisions and action


Paper by Jenni Owen: “Researchers often lament that government decision-makers do not generate or use research evidence. People in government often lament that researchers are not responsive to government’s needs. Yet there is increasing enthusiasm in government, research, and philanthropy sectors for developing, investing in, and sustaining government-research partnerships that focus on government’s use of evidence. There is, however, scant guidance about how to do so. To help fill the gap, this essay addresses (1) Why government-research partnerships matter; (2) Barriers to developing government-research partnerships; (3) Strategies for addressing the barriers; (4) The role of philanthropy in government-research partnerships. The momentum to develop, invest in, and sustain cross-sector partnerships that advance government’s use of evidence is exciting. It is especially encouraging that there are feasible and actionable strategies for doing so…(More)”.

Governance in silico: Experimental sandbox for policymaking over AI Agents


Paper by Denisa Reshef Keraa, Eilat Navonb and Galit Well: “The concept of ‘governance in silico’ summarizes and questions the various design and policy experiments with synthetic data and content in public policy, such as synthetic data simulations, AI agents, and digital twins. While it acknowledges the risks of AI-generated hallucinations, errors, and biases, often reflected in the parameters and weights of the ML models, it focuses on the prompts. Prompts enable stakeholder negotiation and representation of diverse agendas and perspectives that support experimental and inclusive policymaking. To explore the prompts’ engagement qualities, we conducted a pilot study on co-designing AI agents for negotiating contested aspects of the EU Artificial Intelligence Act (EU AI Act). The experiments highlight the value of an ‘exploratory sandbox’ approach, which fosters political agency through direct representation over AI agent simulations. We conclude that such ‘governance in silico’ exploratory approach enhances public consultation and engagement and presents a valuable alternative to the frequently overstated promises of evidence-based policy…(More)”.

Is Software Eating the World?


Paper by Sangmin Aum & Yongseok Shin: “When explaining the declining labor income share in advanced economies, the macro literature finds that the elasticity of substitution between capital and labor is greater than one. However, the vast majority of micro-level estimates shows that capital and labor are complements (elasticity less than one). Using firm- and establishment-level data from Korea, we divide capital into equipment and software, as they may interact with labor in different ways. Our estimation shows that equipment and labor are complements (elasticity 0.6), consistent with other micro-level estimates, but software and labor are substitutes (1.6), a novel finding that helps reconcile the macro vs. micro-literature elasticity discord. As the quality of software improves, labor shares fall within firms because of factor substitution and endogenously rising markups. In addition, production reallocates toward firms that use software more intensively, as they become effectively more productive. Because in the data these firms have higher markups and lower labor shares, the reallocation further raises the aggregate markup and reduces the aggregate labor share. The rise of software accounts for two-thirds of the labor share decline in Korea between 1990 and 2018. The factor substitution and the markup channels are equally important. On the other hand, the falling equipment price plays a minor role, because the factor substitution and the markup channels offset each other…(More)”.

Enrolling Citizens: A Primer on Archetypes of Democratic Engagement with AI


Paper by Wanheng Hu and Ranjit Singh: “In response to rapid advances in artificial intelligence, lawmakers, regulators, academics, and technologists alike are sifting through technical jargon and marketing hype as they take on the challenge of safeguarding citizens from the technology’s potential harms while maximizing their access to its benefits. A common feature of these efforts is including citizens throughout the stages of AI development and governance. Yet doing so is impossible without a clear vision of what citizens ideally should do. This primer takes up this imperative and asks: What approaches can ensure that citizens have meaningful involvement in the development of AI, and how do these approaches envision the role of a “good citizen”?

The primer highlights three major approaches to involving citizens in AI — AI literacy, AI governance, and participatory AI — each of them premised on the importance of enrolling citizens but envisioning different roles for citizens to play. While recognizing that it is largely impossible to come up with a universal standard for building AI in the public interest, and that all approaches will remain local and situated, this primer invites a critical reflection on the underlying assumptions about technology, democracy, and citizenship that ground how we think about the ethics and role of public(s) in large-scale sociotechnical change. ..(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)”.


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)”.