Use this for the material that backs a FAccT paper's transparency and accountability claims. Note the venue difference up front: FAccT does not run the SIGSOFT-style ACM Artifact Review and Badging track that software-engineering venues use, and it does not hand out Available/Functional/ Reusable/Reproduced badges. 待核实: confirm on the current Author Guide whether any optional artifact/reproducibility appendix or badge scheme has been added for your cycle. What FAccT does have is a strong norm of accountability documentation — datasheets, model cards, data statements, audit trails, and impact assessments — plus released code and data. Treat those genres as your artifact and make each one credible on its own.
| Genre | What it documents | When your paper needs it |
|---|---|---|
| Datasheet for a dataset | Motivation, composition, collection, preprocessing, uses, distribution, maintenance | You release or rely on a dataset |
| Model card | Intended use, training data, evaluation disaggregated by group, ethical considerations, limits | You release or audit a model |
| Data statement (for language data) | Speaker/annotator demographics, curation rationale, language variety | You build or study a text/NLP corpus |
| Audit / evaluation report | Method, subgroup metrics, thresholds, what was and was not tested | Your contribution is an audit |
| Impact / risk assessment | Foreseeable harms, affected populations, mitigations, residual risk | Deployment or dual-use is plausible |
Pick the genres your claims actually require; a model audit with no model card, or a dataset paper with no datasheet, reads as incomplete to this community.
[Provenance] where the data/model came from, when, under what terms and consent
[Composition] who/what is in it, who is absent, and the resulting blind spots
[Disaggregation] evaluation broken out by protected/affected subgroup, with uncertainty
[Intended use] what it is for — and an explicit "off-label" / do-not-use list
[Limits & harms] known failure groups and foreseeable adverse impacts, not just accuracy
[Maintenance] who updates it, how issues are reported, how long it persists
[License] a clear license for released code/data so others can lawfully reuse it
The artifact's job at FAccT is to make the paper's accountability claims checkable. Every disparity, harm, or transparency benefit the paper asserts should be traceable into the documentation or released analysis. A model card whose disaggregated numbers disagree with the paper's table, or an impact assessment that omits the harm a reviewer can foresee, undercuts the paper more than having no artifact at all.
A paper auditing a commercial classifier ships: a datasheet for the evaluation dataset (how assembled, subgroup composition, consent basis); a model card-style report for the audited system as the authors understand it (intended use, disaggregated error, failure groups); the audit code with pinned data and seeds regenerating each subgroup table; and a short impact assessment naming who is harmed by both the system and by publishing the audit, with mitigations. All anonymized for review, all public and licensed at camera-ready, all consistent with the paper's tables.
[Genres needed] <datasheet / model card / data statement / audit report / impact assessment>
[Artifact role] anonymized review version / public release
[Contents] <provenance / disaggregation / intended-use / limits / license>
[Claim mapping] <paper harm claim -> where in the documentation/analysis it is checkable? yes/no>
[Consistency] <artifact numbers match the paper's tables? yes/no>
[Fixes before upload] <ordered list, kept anonymous for review>