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Sprint projectJun 21, 2026Sao Paulo

A criação de uma coalização de políticas públicas baseadas em evidências no Brasil: auxiliando na construção de um alicerce político para avançar em uma agenda…

Fernando Moreno, Vitor Douglas Andrade · Team CoalizaoPPBE

Submitted to Global South AI Safety Hackathon. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: A criação de uma coalização de políticas públicas baseadas em evidências no Brasil: auxiliando na construção de um alicerce político para avançar em uma agenda…

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Mudanças duradouras em política pública dependem, em democracias, de coalizões políticas amplas capazes de atravessar ciclos eleitorais. Partindo dessa premissa, e da centralidade de evidências científicas robustas para uma gestão pública eficiente, este artigo propõe a criação de uma Coalizão Brasileira de Políticas Públicas Baseadas em Evidências, fruto da parceria entre as comunidades em torno da Associação Brasileira de Psicologia Baseada em Evidências (ABPBE) e do Altruísmo Eficaz Brasil (AEBr). Melhorar a tomada de decisões institucionais já foi tida como uma das questões mais relevantes pelo guia de carreiras 80.000 hours e pela comunidade do Altruísmo Eficaz, ainda que tal atuação tenha sido despriorizada em avaliações mais recentes. De todo modo, entendemos que a coalizão pode ser em si meritória no desenvolvimento institucional do país e constituir um alicerce político proveitoso para avançar pautas longoprazistas mais complexas, como segurança de IA e prevenção de pandemias. O artigo detalha o desenho institucional proposto para a Coalizão: seus princípios norteadores, grupos de trabalho temáticos, critérios de seleção de pautas, metodologia de avaliação de políticas (eficácia e riscos, pertinência dos objetivos, eficiência e sustentabilidade intertemporal), produção de notas técnicas, estratégias de comunicação e incidência e mecanismos de governança e prestação de contas. Como trabalho futuro, indicam-se os próximos passos para a efetiva implantação da Coalizão no segundo semestre de 2026, incluindo captação de recursos e recrutamento de voluntários e profissionais dedicados.

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

  1. The project presents a well-structured strategy for strengthening institutional capacity and building consensus around AI governance. Its political and organizational approach provides an important perspective for the region. To increase its direct contribution to AI Safety, the initiative should be complemented with a dedicated technical workstream focused on auditing, risk evaluation, and system oversight, creating a stronger connection between institutional strategy and concrete risk mitigation mechanisms.

  2. The article does a good job of defending the point "a coalition between EA Brasil and ABPBE would be potentially valuable", but the high-level approach to the question makes it hard to answer things like:

    - How would this work in practice? Should specific departments be created? Should just a few EAs apply to ABPBE?

    - What's the scope of the initial collaboration? How could we test the willingness of different parties to engage together?

    Overall, I feel it's a good idea on what feels like a relatively unexplored domain, though (as flagged by the authors) a bunch more work needs to be done before it can be put into action

  3. The main weakness of the work is its theory of change. AI safety appears as a distant, future beneficiary rather than the object of the proposal, and no model is offered for why a generic evidence-based policy coalition would translate into concrete advances in AI safety or governance. The underlying assumption, that it is worth first building general institutional capacity because it would later help the AI agenda, is very large and remains undemonstrated, with the aggravating factor that the coalition spreads across many areas, which makes it much harder to measure the proposal's efficacy.

    A second limitation is that the manuscript provides almost no evidence that the mechanism works. It also fails to answer its strongest objection, since the authors cite that 80,000 Hours deprioritized improving institutional decision-making for its execution difficulty and respond only by invoking "fit" without demonstrating it. Finally, the related-work section relies almost entirely on Effective Altruism sources and would benefit from broadening the literature to include the existing advances in evidence-based public policy in Brazil, which the text neither maps nor distinguishes itself from.

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Cite this project

@misc{moreno2026criacao,
  title = {{A criação de uma coalização de políticas públicas baseadas em evidências no Brasil: auxiliando na construção de um alicerce político para avançar em uma agenda longoprazista e de governança de IA}},
  author = {Fernando Moreno and Vitor Douglas Andrade},
  year = {2026},
  month = jun,
  note = {Submitted to Global South AI Safety Hackathon, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/a-criao-de-uma-coalizao-de-polticas-pblicas-baseadas-em-evidncias-no-brasil-auxiliando-na-construo-de-um-alicerce-poltico-para-avanar-em-uma-agenda-longoprazista-e-de-governana-de-ia-8of1}},
  url = {https://apartresearch.com/sprints/projects/a-criao-de-uma-coalizao-de-polticas-pblicas-baseadas-em-evidncias-no-brasil-auxiliando-na-construo-de-um-alicerce-poltico-para-avanar-em-uma-agenda-longoprazista-e-de-governana-de-ia-8of1}
}

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