facct-topic-selection

GitHub

辅助判断负责任AI项目应投稿至ACM FAccT还是其他会议。核心标准是公平、问责或透明是否为核心贡献且社会技术框架原生。提供路由表,指导根据信号选择ML、HCI、法律政策或伦理等更合适的 venue。

FAccT-Skills/skills/facct-topic-selection/SKILL.md brycewang-stanford/Awesome-Journal-Skills

Trigger Scenarios

决定学术论文的投稿会议 评估负责任AI项目的适用性 区分FAccT与其他AI会议的差异

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-topic-selection -g -y
More Options

Non-standard path

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-topic-selection -g -y

Use without installing

npx skills use brycewang-stanford/Awesome-Journal-Skills@facct-topic-selection

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-topic-selection -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "name": "facct-topic-selection",
    "description": "Use when deciding whether a responsible-AI project belongs at ACM FAccT or should route to a pure-ML venue (NeurIPS\/ICML\/ICLR), an HCI venue (CHI\/CSCW), a law\/policy venue, or an AI-ethics venue (AIES), by testing whether fairness, accountability, or transparency is a first-class contribution and whether the interdisciplinary framing is native rather than bolted on."
}

FAccT Topic Selection

Decide the venue before drafting. ACM FAccT — the Conference on Fairness, Accountability, and Transparency — is the flagship interdisciplinary responsible-AI venue. Its reviewer pool spans computer science, law, the social sciences, the humanities, and policy, and its defining demand is that fairness, accountability, or transparency (FAccT) is a first-class contribution, not a fairness paragraph appended to a systems result. A technically strong paper whose real center is a new model, a new interaction technique, or a doctrinal legal argument — with FAccT concerns merely gestured at — is respected and then rejected as out of scope.

The routing question that matters most

The decisive question is rarely "does this touch fairness/AI?" but "is a fairness, accountability, or transparency question the actual contribution, and is the sociotechnical framing native?" FAccT uniquely rewards work that takes the social and the technical as inseparable. A paper that would lose nothing if you deleted the equity framing belongs elsewhere; a paper whose whole point is who is harmed, who is accountable, or what can be made legible belongs here.

Sibling-venue routing table

Signal in your project Better home Why
Fairness/accountability/transparency is the contribution; social + technical are entangled ACM FAccT The interdisciplinary responsible-AI flagship; FAccT concerns are first-class
A new model/algorithm whose fairness angle is a secondary evaluation NeurIPS / ICML / ICLR ML flagships; a fairness metric alone does not make it FAccT
A new interaction technique or system; the study is about use more than justice/power CHI / CSCW HCI flagships; FAccT wants the accountability/harm question central
Primarily doctrinal legal analysis or regulatory design for a legal readership Law reviews / policy venues FAccT welcomes law, but wants cross-disciplinary reach, not doctrine alone
AI-ethics argument aimed at a philosophy/ethics readership AIES and adjacent Overlapping sibling; FAccT leans empirical + sociotechnical + policy-facing
Critical/qualitative/participatory engagement better as a session than a paper FAccT CRAFT track Participatory and world-building formats live in CRAFT, not the paper track

Contribution shapes FAccT rewards

FAccT is genuinely pluralistic — the following are all native, and a good program mixes them:

  • Algorithmic fairness / interpretability method — a new measure, algorithm, or auditing technique for bias, recourse, explainability, or transparency, evaluated on real data (the fairness-metrics lineage).
  • Empirical audit — measuring disparate performance or harm in a deployed or commercial system across subgroups (the Gender Shades lineage).
  • Documentation / accountability infrastructure — datasheets, model cards, data statements, audit frameworks, and impact-assessment tooling that change how the field builds and reports (the Model Cards / Datasheets lineage).
  • Critical / conceptual / position work — an argument that reframes what the field takes for granted about harm, power, or measurement (the Stochastic Parrots lineage).
  • Qualitative / sociotechnical study — interviews, ethnography, or a case study of how a system affects an affected community or institution, with sound method.
  • Law & policy — legal, regulatory, or governance analysis that engages the technical substrate and reaches a mixed audience.

The two sharpening tests

  • Delete-the-equity test: remove every sentence about fairness, accountability, transparency, harm, or power. If a complete, publishable contribution remains, the FAccT framing is decoration — route to the ML/HCI/legal home of the surviving core. If nothing coherent remains without it, FAccT is right.
  • Mixed-reviewer test: imagine your paper read by a computer scientist, a lawyer, and a qualitative social scientist at once. FAccT-shaped work gives each of them something to hold and survives all three; a paper that only one of them can evaluate is usually a sibling-venue paper wearing a FAccT title.

Interdisciplinary rigor, not interdisciplinary gesture

Fit is necessary but not sufficient. FAccT reviewers penalize thin interdisciplinarity: a CS paper that cites one sociology book without method, or a critical paper that name-drops an algorithm it never engages. Whichever lane you sit in, meet that lane's standard of rigor — statistical care and honest baselines for a method/audit paper; coding schemes, saturation, and reflexivity for a qualitative paper; doctrinal precision for a legal paper — and then connect it across the divide.

Cheap reconnaissance before committing

[Scope]   scan the last two FAccT programs (facctconference.org, ACM DL, dblp db/conf/fat) for
          your topic -> several recent papers = a reviewer pool exists; none = opening or mismatch
[Focus areas] can you name a primary + secondary FAccT focus area (algorithm development; data &
          algorithm evaluation; applications; human factors; privacy & security; law; policy;
          critical/humanistic/social-scientific) that genuinely fit? -> if not, reconsider the venue
[Audience] would a lawyer AND a computer scientist both find a contribution? -> that dual pull is
          the FAccT signature; a single-discipline pull points to a sibling venue

Decision procedure

[Who is affected] whose fairness/accountability/transparency changes if the claim holds?
[Contribution type] method / audit / documentation-infra / critical-conceptual / qualitative / law-policy
[First-class check] delete-the-equity test -> does a contribution survive without the FAccT framing?
[Interdisciplinary check] mixed-reviewer test -> do a CS + a law + a social-science reader each hold something?
[Format check] is it a paper, or a participatory session? -> paper track vs CRAFT
[Verdict] FAccT paper track / FAccT CRAFT / sibling venue (NeurIPS/ICML/CHI/AIES/law), one-line reason

Run this before the writing skills; a wrong venue decision wastes every later step. When the verdict is FAccT, continue with facct-workflow for the calendar and facct-writing-style for the paper shape.

Version History

  • 9f86f09 Current 2026-07-19 15:44

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