ACM Conference on Fairness, Accountability, and Transparency (FACCT)

Areas of Interest
We welcome submissions in the following areas:

Algorithm Development e.g. Fairness; Interpretable and explainable models; Causality; Data collection and curation

Data and Algorithm Evaluation e.g. Metrics; Audits; Evaluations, both quantitative and qualitative

Applications e.g. Natural Language Processing; Computer vision; Health; Information retrieval; Recommender systems; Programming languages; Databases

Human Factors e.g. Human-computer interaction; Humans-in-the-loop; Information visualization; UX design; Community or participatory-research design

Privacy and Security e.g. Formal approaches; Privacy-preserving models; Usable privacy and security

Law e.g. Data protection; Non-discrimination; Fair Procedures; Human Rights; Oversight mechanisms

Policy e.g. Organizational governance; Codes of ethics; models from historically marginalized perspectives

Historical and Cultural Critiques e.g. Interrogating foundational concepts; Bridging critical concepts across fields; Historical perspectives on FAccT issues

Philosophy e.g. Philosophical foundations of machine learning; values in scientific inquiry; social epistemology; moral, legal and political philosophy of data and AI

Social Sciences e.g. AAlgorithms and computing in organizations and institutions, including education; Social and cultural shaping of algorithmic phenomena; algorithmic impacts on social phenomena

We especially welcome contributions that incorporate perspectives and investigations on FAccT that are relevant to or grounded in the cultures, norms, laws, and/or sociopolitical systems from regions that are usually not featured prominently at FAccT, which has so far been composed mainly of North American and European scholarship.