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UPCOMING

Mechanism design for public goods.

Funding, impact evaluation, broad listening, and resource allocation in the age of AI. A full-day workshop following UN Open Source Week 2026 · Columbia University, New York · Second week of August 2026.

Low Memorial Library at Columbia University

Family Tang Hall · Columbia Engineering Innovation Hub

Organizers

  • Prof. Lily XuIEOR, Columbia · Co-director, EAAMO
  • Dr. David Daogainforest.earth · PL R&D

Motivation

The allocation of scarce resources to shared ends, such as research funding, humanitarian assistance, maintenance of critical digital infrastructure, and stewardship of the global commons, is the central problem of mechanism design for social good. Across these domains, a common pattern has emerged. The populations that rely on these resources are growing, the volume of claims on them is growing faster, and the human expertise required to evaluate those claims is not growing at all. Grant panels are overloaded, scientific peer review is strained to the point of visible failure, humanitarian agencies triage under severe informational constraints, and the maintainers of open source software report being overwhelmed by the cost of reviewing contributions they did not solicit.

The diffusion of AI systems has sharpened each of these pressures simultaneously. Large language models have lowered the marginal cost of producing plausible allocation proposals (e.g. grants, papers, code contributions) while leaving the cost of their evaluation essentially unchanged. This is a structural shock to the incentive and allocation mechanisms on which public goods provision depended in the past.

The same systems have also made it cheaper to listen. Broad listening uses language models and clustering to read and structure free-form input from thousands of people at once. Tools like Polis, Talk to the City, and Kouchou AI (広聴AI) have been used in elections, city government, and public consultation, and are surveyed in the Broad Listening book. What is still missing is the connection to allocation: how the voices these tools surface should shape who gets funded. That question sits at the center of this workshop.

Workshop aims

This workshop brings mechanism designers, theoretical computer scientists, and empirically-oriented researchers of impact evaluation and funding allocation together with practitioners who operate real allocation systems at scale, including practitioners of digital democracy and broad listening. The goal is a shared research agenda: not a consensus statement, but a structured map of open problems, promising designs, and the evidence we would need to discriminate between them.

Output: a workshop report summarising the research threads and the state of the evidence.

Research questions

  1. 01 · Ex-ante versus ex-post allocation

    What are the comparative properties of prospective allocation mechanisms (including quadratic and matching-fund designs) versus retrospective, impact-based reward mechanisms, under realistic assumptions about evaluator capacity, measurement error, and strategic behavior? When do hybrid schemes dominate, and at what operational cost?

  2. 02 · Impact evaluation at scale

    How should the outcomes of funded work be measured, attributed, and rewarded when the volume of funded projects grows faster than the supply of qualified evaluators? What mechanisms can credibly distinguish impactful work from plausible-looking work, especially when results unfold over years, and which designs transfer across domains?

  3. 03 · Evaluation under AI-mediated contribution

    How should provenance, attribution, and reviewer effort be incorporated into allocation mechanisms when a growing share of submitted material is machine-generated? What mechanisms can preserve informativeness when the cost of producing plausible submissions approaches zero, and signal scarcity must be engineered rather than assumed?

  4. 04 · Broad listening and collective input

    How should the output of broad-listening tools feed into allocation mechanisms, so that funding decisions track what affected communities actually say? What can mechanism design learn from deployments of Polis, Talk to the City, and Kouchou AI in elections, local government, and public consultation, and where do those deployments still fall short on incentives, legitimacy, and auditability?

Format

Invited talks and a structured working session. Speakers from mechanism design, theoretical computer science, impact-evaluation research, empirical work on scientific and development funding, digital public infrastructure policy, and digital democracy and broad listening; plus practitioners engaged with the UN Office for Digital and Emerging Technologies and affiliated agencies.

Expected outcomes

An openly published workshop report that surveys the research agenda produced by the four threads, identifies tractable near-term empirical work, and names the allocation mechanisms for which better evidence is most urgently needed.

To propose a talk, register interest, or co-sponsor:

daviddao at protocol.ai