Recurring Series

Research Radar

Showing 15 of 42 results in series "Research Radar"

Research Radar

Turning 20 Years of Community Board Data Into Searchable Public Knowledge

Local government generates enormous amounts of public knowledge, but much of it remains buried in disconnected PDFs and difficult-to-navigate archives. This post explores how the Block Party team used AI, semantic search, and human expertise to build a searchable archive of 17 years of Manhattan Community Board 3 resolutions, making local government decisions, institutional memory, and civic participation more accessible to residents, journalists, and public officials.

Published on Jun 9, 2026 by Sarah Sachs and Tal Roded

Research Radar

Research Radar: 10 Things Public Officials Should Know About AI Data Centers

AI data centers are arriving in communities long before most public institutions have figured out how to govern them. Drawing on recent analysis, fieldwork, and an InnovateUS workshop, Deborah Stine examines the questions public officials are now confronting around electricity, water, jobs, infrastructure, public trust, and community impact. She argues that AI data centers are far more than technology projects; they are major public policy decisions that will shape how communities experience the AI economy.

Published on Jun 2, 2026 by Dr. Deborah Stine

Research Radar

Research Radar: The Six-Word Problem: Will Voice Improve How We Research the Impacts of AI?

AI for Impact Fellows Sai Punith Kolla and Swaapnika Chowdary Cherukuru built Public Voice, a lightweight voice-based feedback tool designed to capture concrete examples of how learners apply AI in practice. The piece explores the design challenge behind the tool, why voice responses may produce richer evidence than text surveys, and what it means to measure whether public-sector AI training is translating into real workflow change.

Published on May 26, 2026 by Sai Punith Kolla and Swaapnika Chowdary Cherukuru

Research Radar

The Reports Nobody Reads: How San Francisco Used AI to Declutter Its Municipal Code

In a new piece for the Rethinking Regulation series, Dane Gambrell examines how San Francisco used a custom AI tool developed with Stanford’s RegLab to scan 16 million words of municipal code and identify hundreds of outdated and duplicative reporting requirements across city government. The effort ultimately produced a 351-page ordinance proposing the deletion or consolidation of 174 mandates. The piece offers a grounded look at how AI can help governments make sprawling bureaucratic systems more legible and manageable.

Published on May 19, 2026 by Dane Gambrell

Research Radar

Zero-Click Government: Omakase or Loss of Agency?

In the afterword to Gustavo Maia’s forthcoming book Zero-Click Government, Beth Simone Noveck explores the democratic risks and possibilities of anticipatory governance. While supporting efforts to reduce the administrative burdens placed on citizens, she argues that traditional requests and applications also served as an important democratic feedback signal, one that anticipatory systems risk losing when governments act on inferred demand. Her response examines what kinds of participation, transparency, contestation, and institutional learning are needed if public action is increasingly shaped by data and AI.

Published on May 13, 2026 by Beth Simone Noveck

Research Radar

Research Radar: AI as a Multiplier for Evidence-Informed Policy

A new WHO discussion paper explores how AI can accelerate research synthesis and keep evidence continuously up to date. Elana Banin welcomes the push to use AI to strengthen the evidence-to-policy pipeline, but argues the more consequential question is whether AI will redefine what counts as evidence in the first place. The harder constraint will ultimately be institutional, as most health workers lack the training and infrastructure to adopt these tools. Government decision-makers must start building the processes to test AI outputs against frontline knowledge and the capacity to make that adoption defensible.

Published on May 5, 2026 by Elana Banin

Research Radar

Rethinking Regulation: How Virginia Used AI to Streamline Its Regulatory Code

A new entry in our Rethinking Regulation series, this in-depth case study by Dane Gambrell includes an interview with Reeve Bull, who led the state’s regulatory modernization effort. It traces how Virginia used AI to review decades of accumulated rules, cut regulatory requirements by over a third, and make them clearer and more accessible. It shows how governments can pair strong institutional processes with AI to modernize regulation and improve how it works for the public.

Published on Apr 28, 2026 by Dane Gambrell

Research Radar

How we used AI to lift the voices of California state employees

Using AI to analyze over 2,400 employee comments, California’s Engaged California team found that the challenge wasn’t the scale of the data, but making sense of complex, layered input without oversimplifying it. Their experience shows why human judgment remains essential, from building taxonomies to catching errors, as results can shift significantly depending on how AI is applied and what people choose to trust and prioritize.

Published on Apr 21, 2026 by Summer Mothwood

Research Radar

The New Human Resilience Challenges Posed by AI

In “Building a Human Resilience Infrastructure for the AI Age,” based on insights from 386 global experts, a warning emerges: the greatest risk is not a single catastrophic event, but a slow drift toward diminished human agency, fragmented reality, and growing dependence on automated systems. Lee Raine and Janna Anderson reflect on how, as AI becomes society’s invisible operating system, individual resilience is no longer enough. The report argues for urgent, coordinated action to build resilience as shared infrastructure across governments, institutions, and communities to ensure people can still question, contest, and shape the systems increasingly shaping them.

Published on Apr 13, 2026 by Lee Rainie and Janna Anderson

Research Radar

Research Radar: StatGPT and the Fourth Wave of Open Data

Stefaan Verhulst and Adam Zable argue that the biggest challenge in open data is no longer access, but usability, as official statistics remain difficult to find, interpret, and apply. Drawing on the International Monetary Fund’s StatGPT new research, it shows how artificial intelligence could transform access through natural language interfaces, while warning that accuracy and trust depend on retrieving authoritative data rather than generating answers. The article situates this shift within a broader “Fourth Wave of Open Data,” calling for new data systems and governance approaches that make information truly usable and reliable.

Published on Apr 7, 2026 by Dr. Stefaan Verhulst and Adam Zable

Research Radar

The Next Frontier: AI, Equity, and the Future of Public Benefits

Millions of Americans miss out on health and food assistance benefits due to fragmented systems and complex enrollment processes. This piece explores how Link Health, in partnership with the AI for Impact program, is combining AI tools with human navigators to rethink how public benefits are delivered in healthcare settings. It argues that the next frontier is better evidence. States should fund research to compare enrollment approaches, portal design, and navigator support to determine which improve health outcomes and guide smarter public investment.

Published on Mar 31, 2026 by Timothy Scheinert, Austin Tsai, Ar’Sheill Monsanto and Alister Martin

Research Radar

What We Learned from 50 Experts About Designing Democratic Engagement in the AI Era

More than 50 practitioners, researchers, and civic technologists from 24 countries reviewed the draft curriculum for Designing Democratic Engagement for the AI Era, providing over 300 comments and suggestions. The feedback highlighted the need for clearer guidance on institutional readiness, trust, inclusion, and the risks and limits of AI in public participation. This post summarizes the key themes that emerged, explains how AI tools were used to synthesize the feedback, and outlines the next steps in developing the course.

Published on Mar 17, 2026 by Dane Gambrell

Research Radar

The Case for Civic AI Compacts with Higher Education

Cities often treat nearby universities as occasional partners rather than strategic collaborators. But as artificial intelligence reshapes local economies and public services, that relationship may need to change. Drawing on a new policy brief, The AI Lab Next Door, Neil Kleiman argues that city–university “compacts” can transform transactional ties into intentional partnerships, helping communities harness the growing AI capacity already taking shape on college campuses.

Published on Mar 17, 2026 by Neil Kleiman

Research Radar

Assembly Required: A Conversation with Lorelei Kelly on Deliberative Technology and Congressional Reform

In this conversation with Elana Banin, Lorelei Kelly argues that rebuilding democratic resilience requires redesigning the institutional infrastructure connecting citizens to Congress. Drawing on constitutional history and emerging technologies, she explores how deliberative technology and AI could help revive the First Amendment’s promises of assembly and petition for the digital age.

Published on Mar 10, 2026 by Elana Banin

Research Radar

Research Radar: Academics Are Sounding the Alarm on AI Adoption. Who's Listening?

A new paper urges universities to resist the uncritical adoption of AI, arguing that existing research integrity standards already prohibit much of what institutions are normalizing. Beth Simone Noveck's diagnosis is sharp: vendor dependency, opacity, and hype are reshaping public institutions from the inside. But for governments, refusal isn’t an option. The real question is not whether to adopt AI, but who controls it and on what terms.

Published on Feb 24, 2026 by Beth Simone Noveck