Showing 15 of 271 results

Is Your Parliament Transparent or Just Performing? Making Public Data Understandable Opens the Door to Citizen Engagement
AI Tools

Is Your Parliament Transparent or Just Performing? Making Public Data Understandable Opens the Door to Citizen Engagement

Political Watch’s “What Our Representatives Do” tool (QHLD) organizes thousands of congressional initiatives into clear, searchable themes, making political priorities visible, comparable, and actionable. By exposing imbalances like the 198 initiatives on squatting versus just 54 on social housing, QHLD shows how structured, understandable data can reconnect citizens with their representatives. Yet the project also highlights a global challenge for civic tech: limited funding, slow adoption, and the high cost of responsible AI integration. Making democracy legible is possible, but only if we invest in tools designed to share power, not just document it.

Published on Nov 26, 2025 by Celia Zafra and Pablo Martín

Solving Public Problems with Artificial Intelligence
AI and Problem Solving

Solving Public Problems with Artificial Intelligence

The Solving Public Problems course has helped learners worldwide tackle complex challenges. The course teaches how to leverage technology, data, and collective wisdom in our communities to design powerful solutions to contemporary problems. Now, Beth Simone Noveck is exploring how to remake it for the AI era, using technology to make problem-solving skills easier to learn without losing the human connection at its core. Your input is needed!

Published on Nov 25, 2025 by Beth Simone Noveck

Big Tech Wants AI Without Rules. Here’s How Workers are Fighting Back
AI and Labor

Big Tech Wants AI Without Rules. Here’s How Workers are Fighting Back

AI is reshaping the workplace faster than public policy can keep up, often in ways that expand corporate power, weaken worker rights, and undermine democratic oversight. But across sectors, workers and unions are showing that this trajectory isn’t inevitable. Through collective bargaining, policy advocacy, and new uses of AI for organizing, they’re securing real guardrails on surveillance, algorithmic management, and job displacement. This piece explores how worker power will determine whether AI serves people or replaces them.

Published on Nov 24, 2025 by Dane Gambrell

Foundations for the Digital Commons
AI for Governance

Foundations for the Digital Commons

In late October, the Roux Institute hosted Foundations for the Digital Commons with Bernstein Shur and RadicalxChange, convening technologists, policymakers, civic innovators, journalists, and funders to chart a path for renewing the digital systems that underpin democratic life. Over two days, participants examined practical models, from information flows and large-scale deliberation to data governance, while outlining actionable pathways for building modern digital infrastructure. Held in Maine, a state defined by democratic reforms and pragmatic problem-solving, the gathering reinforced a central insight that institutional design, more than technology, will determine whether digital innovation ultimately strengthens public trust

Published on Nov 19, 2025 by Matt Prewitt and Matthew Victor

Research Radar: An Economy of AI Agents
Research Radar

Research Radar: An Economy of AI Agents

AI agents are beginning to make market-shaping decisions. Hadfield and Koh’s new study reveals why this shift is significant. Current agents do not reason like economists, do not reflect human preferences, and do not fit into accountability structures. As governments experiment with agents in benefits, procurement, and infrastructure, Elana Banin reflects on the policy challenge of re-designing the rules before agents erode the market foundations on which democratic governance relies.

Published on Nov 18, 2025 by Elana Banin

Why “Good Guys” Shouldn’t Use AI like the “Bad Guys”: The Failure of Predictive Policing
AI and Public Safety

Why “Good Guys” Shouldn’t Use AI like the “Bad Guys”: The Failure of Predictive Policing

This essay argues that predictive policing continues to fail not because police departments lack data, but because they are using the wrong kind of data, in the wrong way. Applying low-stakes commercial algorithms to high-stakes decisions can produce dangerous false positives, reinforce biased patterns, and erode public trust in policing. Using examples from Plainfield, NJ, and Chicago, the piece illustrates how predictive systems replicate past police behavior rather than accurately forecasting crime, thereby creating self-reinforcing feedback loops. It contrasts these failures with diagnostic approaches in Oakland and Richmond that utilize data to understand harm, guide outreach, and reduce violence without relying on algorithmic surveillance. The core argument is that policing needs better mirrors, not crystal balls.

Published on Nov 17, 2025 by Mihir Kshirsagar

Designing AI for Trust: Lessons from Tarjimly’s Translation Platform for Humanitarian Action
AI and Problem Solving

Designing AI for Trust: Lessons from Tarjimly’s Translation Platform for Humanitarian Action

When refugees needed language support, Tarjimly turned everyday volunteers into lifelines. In this reflection, CEO Atif Javed traces how the platform evolved from a Facebook Messenger experiment into a global translation network, one now partially powered by AI. His key lesson is that designing for trust means using technology to amplify, not replace, human empathy in moments of crisis.

Published on Nov 12, 2025 by Atif Javed

Governing AI: The Air Force’s AI Land Rush
Governing AI

Governing AI: The Air Force’s AI Land Rush

The Air Force is quietly auctioning off slices of its bases for private AI data centers. They call it innovation; it looks like privatization. Fifty-year leases, 3,000 acres of military land, and no public say. If this is how we build the future, who’s really in command?

Published on Nov 9, 2025 by Beth Simone Noveck

Global AI Watch: Brazil’s Experiment in AI-Powered Participation
AI for Governance

Global AI Watch: Brazil’s Experiment in AI-Powered Participation

When Brazil's federal government launched its 2023 Participatory Pluriannual Plan, the response was massive: 1.4 million participants submitted over 8,200 proposals through the Brasil Participativo platform. But volume creates a challenge, as manually processing thousands of contributions is slow and resource-intensive, often causing valuable insights to slip through the cracks. Now, Brazil is pioneering an open-source AI system that automatically analyzes citizen feedback, generates comprehensive reports, and tracks which suggestions made it into final policies. The result is a new model for democratic intelligence, one that transforms the flood of public input into structured, actionable knowledge without losing the nuance of individual voices.

Published on Nov 5, 2025 by Christiana Freitas and Ricardo Poppi

Research Radar: The Emperor's New Agents - Why AI Won't Fix Broken Government
Research Radar

Research Radar: The Emperor's New Agents - Why AI Won't Fix Broken Government

The Agentic State is an ambitious and inspiring blueprint for rebuilding government around AI agents that can act and decide autonomously. It powerfully diagnoses real failures in how the public sector designs, delivers, and manages services. While AI is giving us ways to accelerate change, the prescribed cure may be premature: most of what’s broken in government requires organizational reform, not automation.

Published on Nov 4, 2025 by Beth Simone Noveck

The AI Fish Counter: Teaching Ourselves to Use AI—Before It Uses Us
AI and Problem Solving

The AI Fish Counter: Teaching Ourselves to Use AI—Before It Uses Us

The danger isn’t that AI will make us dumber—it’s that governments, companies, and schools won’t make us smarter with it. As policymakers stall and corporations automate, the burden of using AI wisely now falls on us. Like shoppers at the fish counter, we need to learn to read the labels—to know what’s safe, what’s risky, and how to choose well.

Published on Nov 3, 2025 by Beth Simone Noveck

How Governments are Using AI
AI and Problem Solving

How Governments are Using AI

Public service professionals from across the globe have come together to learn from one another how to use AI to improve governance. From St. Louis cutting hiring times from 12 to 2 months, Hamburg analyzing 11,000 public comments in days, and New Jersey reducing Spanish-language form completion from 4 hours to 25 minutes, it becomes clear that AI works for democracy when we build the foundation first.

Published on Oct 30, 2025 by Elana Banin

Governing the Undefined: Why the Debate Over Superintelligence Misses the Point
Governing AI

Governing the Undefined: Why the Debate Over Superintelligence Misses the Point

As headlines warn of “superintelligent AI” threatening human extinction, a new open letter reignites familiar fears. But beneath the apocalyptic rhetoric lies a deeper problem. The narrative around artificial superintelligence, long embraced by Big Tech, diverts attention from the real and immediate challenges of AI and how our democratic institutions can address them.

Published on Oct 29, 2025 by Dane Gambrell

Re-thinking AI: How a Group of Civic Technologists Discovered the Power of AI to Rebuild Trust in Government

Re-thinking AI: How a Group of Civic Technologists Discovered the Power of AI to Rebuild Trust in Government

After two years of research, the RethinkAI collaborative released Making AI Work for the Public—a comprehensive field review of how U.S. governments adopt AI. Since 2019, over 1,600 AI-related bills have been introduced, but most focus on guardrails, not proactive strategy. Meanwhile, cities are piloting translation tools, engagement platforms, and predictive systems, often led by Chief Information Officers, taking on new strategic roles. The report challenges civic tech’s efficiency-first legacy and proposes a new governance model—ALT: Adapt to anticipate needs, Listen to understand communities, and build Trust through two-way accountability.

Published on Oct 27, 2025 by Neil Kleiman, Mai-Ling Garcia and Eric Gordon

How Hamburg is Turning Resident Comments into Actionable Insight
AI and Public Engagement

How Hamburg is Turning Resident Comments into Actionable Insight

Officials in Hamburg had long struggled with the fact that while citizens submitted thousands of comments on planning projects, only a fraction could realistically be read and processed. Making sense of feedback from a single engagement could once occupy five full-time employees for more than a week and chill any desire to do a follow-up conversation. Learn about how Hamburg built its own open source artificial intelligence to make sense of citizen feedback on a scale and speed that was once unimaginable.

Published on Oct 22, 2025 by Beth Simone Noveck