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facct-topic-selection

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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-Skills/skills/facct-topic-selection/SKILL.md

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# 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
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