Generated by GPT-5-mini| ACM Conference on Fairness, Accountability, and Transparency | |
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| Name | ACM Conference on Fairness, Accountability, and Transparency |
| Abbreviation | FAccT |
| Discipline | Computer science; Ethics; Law |
| Publisher | Association for Computing Machinery |
| First | 2018 |
| Frequency | Annual |
| Country | International |
ACM Conference on Fairness, Accountability, and Transparency is an annual academic conference focusing on algorithmic fairness, accountability, and transparency. The conference convenes researchers, practitioners, and policymakers from institutions such as the Association for Computing Machinery, Stanford University, Massachusetts Institute of Technology, University of California, Berkeley, and Carnegie Mellon University alongside participants from Google, Microsoft, Facebook, OpenAI, and IBM Research. Organizers and contributors have included figures affiliated with Harvard University, Princeton University, Yale University, Oxford University, and Cambridge University.
The conference was established in response to growing scholarly and public concern intersecting work from NeurIPS, ICML, KDD (conference), CHI (conference), and AAAI Conference on Artificial Intelligence. Early meetings drew keynote speakers connected to European Commission, United States Congress, United Nations, World Bank, and European Court of Human Rights discussions on algorithmic governance. Founding participants came from research centers such as AI Now Institute, Data & Society Research Institute, Berkman Klein Center, Alan Turing Institute, and Max Planck Society. Over successive editions the program has incorporated collaborations with IEEE Standards Association, National Institute of Standards and Technology, Office of Technology Assessment, Council of Europe, and civil society groups like Electronic Frontier Foundation, Amnesty International, and Human Rights Watch.
The conference spans topics bridging technical and social domains including algorithmic auditing, fairness metrics, explainability, and accountability mechanisms discussed by scholars from Columbia University, New York University, Duke University, University of Washington, and University of Toronto. Papers routinely reference legal frameworks such as General Data Protection Regulation, California Consumer Privacy Act, Equality Act 2010, and court decisions from Supreme Court of the United States and European Court of Justice. Cross-disciplinary work involves partnerships with Brookings Institution, RAND Corporation, Pew Research Center, Center for Democracy & Technology, and Open Data Institute. Themes have included bias in automated decision-making impacting sectors represented by United Nations Educational, Scientific and Cultural Organization, World Health Organization, International Labour Organization, and Intelligent Transport Systems research.
The conference is governed by program chairs and an organizing committee drawn from universities and industry labs such as ETH Zurich, Technical University of Munich, Seoul National University, Tsinghua University, Peking University, Alibaba Group, and Tencent. Steering committees have included members affiliated with Royal Society, National Academy of Sciences, Academia Europaea, and professional societies including Association for Computing Machinery and Institute of Electrical and Electronics Engineers. Peer review policies reference standards used by Proceedings of the ACM, Nature, Science (journal), and ethical guidelines aligned with bodies such as UNESCO and World Economic Forum. Funding and sponsorship have come from foundations like the Bill & Melinda Gates Foundation, Ford Foundation, MacArthur Foundation, and corporate partners including Amazon Web Services and NVIDIA.
Typical programs include peer-reviewed paper presentations, poster sessions, workshops, tutorials, and panels featuring speakers from The White House, European Parliament, UK Parliament, Canadian House of Commons, and regulatory agencies like Federal Trade Commission, Competition and Markets Authority, and Data Protection Commission. Satellite events have featured collaborations with SIGCHI, SIGKDD, SIGPLAN, and SIGMOD communities. Workshops have been organized by research groups from MIT Media Lab, Stanford HAI, Princeton Center for Information Technology Policy, and Berkeley AI Research (BAIR). The conference also hosts reproducibility tracks and interdisciplinary tutorials involving contributors from Johns Hopkins University, Brown University, University of Pennsylvania, and Northwestern University.
Proceedings are published under the auspices of the Association for Computing Machinery and indexed alongside other conferences such as NeurIPS, ICLR, and EMNLP. Accepted papers have later appeared in journals including Communications of the ACM, Journal of Machine Learning Research, AI & Society, and law reviews at Harvard Law School, Columbia Law School, and Stanford Law School. Artifact evaluation and data-sharing practices have engaged repositories like arXiv, Zenodo, ICPSR, and institutional archives at MIT Libraries and Harvard Dataverse.
The conference has influenced policy debates involving European Commission Directorate-General for Competition, United States Department of Justice, UK Information Commissioner's Office, and standards discussions at ISO and IEEE Standards Association. Researchers presenting at the conference have received recognition linking to awards from ACM SIGKDD, ACM SIGCHI, IJCAI, AAAI, and fellowships such as MacArthur Fellowship and Rhodes Scholarship held by contributors. Critiques have come from scholars associated with Cato Institute, Heritage Foundation, and commentators in outlets like The New York Times, The Guardian, Wired (magazine), and MIT Technology Review. The conference continues to serve as a nexus connecting academia, industry, civil society, and government institutions including OECD and G7 dialogues on technology policy.
Category:Academic conferences