# Facct Topic Selection > 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. - Skill: `thedixitjain/facct-topic-selection` (Agent Skill) - Install (CLI): `npx skillmds add thedixitjain/facct-topic-selection` - Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/facct-topic-selection/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: thedixitjain (https://skillmd.com/u/thedixitjain) - Updated: 2026-09-08 - Page: https://skillmd.com/skills/thedixitjain/facct-topic-selection --- # 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 ```text [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 ```text [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. --- **Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `FAccT-Skills/skills/facct-topic-selection/SKILL.md`