Facct writing style

FAccT Writing Style

Use this when revising the main paper. FAccT papers are read by a deliberately mixed panel — a computer scientist, a lawyer, and a qualitative social scientist may each land on your paper — so the writing must make a fairness, accountability, or transparency contribution legible to all three and must be honest about who is affected and how. The failure this skill prevents is a paper that is excellent inside one discipline and illegible or naive to the others.

Revision rules

• Lead with the FAccT contribution. The first page names the socio-technical problem, who bears the harm or holds the accountability, why the current state is inadequate, the contribution (method, audit, framework, critique, study, or legal analysis), and what changes for people — before any model or doctrinal detail.
• Scope claims to a population, not the world. "Reduces bias" is not a FAccT claim; "reduces the false-positive-rate gap between groups A and B on dataset D, under measure M" is. Name the subgroups, the fairness/transparency construct, and the operationalization.
• Argue limitations and adverse impacts; do not recite them. State the harms, failure modes, and who could be hurt if the work is deployed or misread — and what you did about each. A boilerplate "limitations" paragraph is a tell that the author has not stressed their own claims. This is also where the Adverse Impacts endmatter statement earns its keep.
• Make the interdisciplinarity native. If you borrow a construct from law or the social sciences, use it the way that field uses it, cite its real origin, and carry it through the analysis — not as a one-line garnish.
• Respect the acmart page budget as a design constraint. FAccT 2026 allows up to 14 content pages (+1 endmatter page; 15 if Revised/accepted), references unlimited — generous but finite. A paper that only fits by shrinking its limitations or method is over-scoped.
• Preserve mutual anonymity in self-citations, system names, acknowledgements, funding, and — critically — keep the Positionality statement out of the anonymous submission entirely.

The FAccT paper skeleton

Section	Job it must do	Common failure
Intro	Sociotechnical problem, who is affected, contribution, what changes — first page	Leads with a model/benchmark, not a harm or accountability question
Background / motivation	Why this matters now, grounded across the relevant disciplines	Motivation by assertion; one-discipline framing
Approach / method / argument	The technique, study design + protocol, or the conceptual/legal argument	Method too thin to re-run, or critique with no engagement with the artifact
Findings / evaluation	Disaggregated results, coded themes, or a defended argument	Aggregate-only numbers that hide subgroup harm
Limitations & adverse impacts	The harms and threats that actually bite, each bounded	Generic list untethered from this work
Related work	Cross-disciplinary, delta-first positioning	Cites only one lane; misses the obvious neighbor in another field

Sentence-level rewrites

Draft pattern	FAccT-safe rewrite
"Our method is fair."	"our method equalizes <metric> across <groups> on <dataset>, within <bound>; residual gaps in §5"
"We improve transparency."	"we surface <what> to <whom> for <decision>, and we test whether they can act on it"
"The model is accurate on a large dataset."	"accuracy disaggregated by <subgroup> (Table 2); the largest error falls on <group>"
"This raises ethical concerns."	"this risks <specific harm> to <specific population>; we mitigate by <action>, residual risk in the Adverse Impacts statement"
"Prior work is limited."	"<work> measured X but not the deployment outcome Y that governs harm; we measure Y"

Limitations-and-harm discipline

[Construct]     does the fairness/transparency metric mean what you claim for the affected group?
[Population]    which groups are in and out of scope; who is invisible in your data?
[Deployment]    what goes wrong if this ships or is cited as license to deploy? who is hurt?
[Reflexivity]   whose standpoint shaped the framing? (state it in Positionality upon acceptance)
-> for each that bites: state it, then state the mitigation, next to the affected result

Vignette: compressing an audit paper

A draft auditing a commercial system, with aggregate accuracy up front and a short ethics paragraph at the end: move the disaggregated subgroup results to the first result table, put the worst-affected group in the abstract, argue the construct-validity threat (does your proxy for the protected attribute mean what you claim?) beside that table, and move method minutiae to supplementary. The test of a good cut: a mixed reviewer can answer "who is harmed, by how much, and how sure are we?" from the body alone.

Output format

[Writing diagnosis] clear / under-motivated / over-claimed / single-discipline / harm-blind / over-scoped
[First-page fix] <new framing leading with the FAccT contribution and who is affected>
[Claim audit] <claim -> population + construct + operationalization -> scoped? yes/no>
[Harm fix] <adverse impact that bites -> mitigation to add, placed by the result>
[Anonymity edits] <system names / self-citations / positionality kept out of the anonymous PDF>