Joining the Network
Do you have an upcoming workshop, special issue, or similar event centered around FAccT topics? We invite you to apply to have it considered a part of the network.
Requirements and Process
Fill out the application form,
and the Network Co-Chairs will consider your application and get in touch with you.
To be part of the ACM FAccT Network, your event must:
- Engage with FAccT topics in a central way. For examples, see previous events below.
- Have an open call for participation — i.e., not only for invited participants.
- Adopt a Code of Conduct. (Workshops attached to ACM-sponsored events are automatically subject to the ACM Policy Against Harassment.)
- Disseminate a summary/report after the event (which can range in format from a brief Medium post to a more detailed publication).
When you become part of the ACM FAccT Network:
- We’ll help spread the word about your event to the FAccT community via the network web site, FAccT social media, and in a monthly digest sent to the FAT-ANNOUNCE listserv.
- We’ll help give visibility to your event outcomes (workshop reports or other documents).
- Association with ACM FAccT helps communicate the scope/intent of the event to participants.
These opportunities are upcoming and are currently accepting submissions:
Upcoming Events and Publications
These opportunities are no longer accepting submissions; look out for their outcomes soon! Upcoming events may still be open for participation.
Past Network Events
These opportunities have happened — look through them for interesting work!
- Fairness, Accountability, and Transparency, in Educational Data (Mining), a workshop at the International Conference on Educational Data Mining.
- Law & Machine Learning Workshop, a workshop at ICML 2020.
- Participatory Approaches to Machine Learning, a workshop at ICML 2020.
- Workshop on Human Interpretability in Machine Learning (WHI), a workshop at ICML 2020.
- Bias in Automatic Knowledge Graph Construction, a workshop at AKBC 2020.
- Explainable User Models and Personalized Systems (ExUM), a workshop at UMAP 2020.
- Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2020), a workshop at UMAP 2020.
- International Workshop on Algorithmic Bias in Search and Recommendation (BIAS 2020), a workshop at ECIR 2020. [report]
- AI@Work, a workshop in Amsterdam (March 5-6, 2020).
- Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies, a workshop at IUI 2020 (March 17, 2020).
- 2nd Workshop on Fairness, Accountability, Transparency, Ethics, and Society on the Web (FATES 2020), a workshop at The Web Conference 2020 (Apr. 20-21, 2020). [report][videos][proceedings]
- Human-Centered Approaches to Fair and Responsible AI, a workshop at CHI 2020.
- HUMAINT Winter School on Fairness, Accountability, and Transparency in AI, in Seville, Spain the week before ACM FAT* 2020.
- Fair ML for Health, a workshop at NeurIPS 2019 (Dec. 14, 2019).
- Machine Learning for the Developing World: Challenges and Risks, a workshop at NeurIPS 2019 (Dec. 13, 2019). [proceedings] [session videos]
- Human-Centric Machine Learning, a workshop at NeurIPS 2019 (Dec. 13, 2019).
- Contestability in Algorithmic Systems, a workshop at CSCW 2019 (Nov. 9). [workshop report]
- AI Fairness for People with Disabilities, a workshop at ASSETS 2019 (Oct. 27, 2019)
- 1st Symposium on Biases in Human Computation and Crowdsourcing, a symposium to be held in Sheffield, UK (Oct. 21-22, 2019). [workshop report]
- Workshop on Designing Human-Centric MIR Systems, a workshop at ISMIR 2019 (Nov. 2). [proceedings]
- Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR) at SIGIR 2019 (July 25, 2019) [report]
Older Workshops and Events
These are various events held prior to the founding of the ACM FAccT Network which may be of similar interest. We present them here for historical purposes.
- Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), NIPS 2014, ICML 2015, DTL 2016, KDD 2017
- Fairness in User Modeling, Adaptation and Personalization (FairUMAP), UMAP 2018 and 2019
- International Workshop on Software Fairness (FairWare), ICSE 2018
- Workshop on Responsible Recommendation (FAT/Rec), RECSYS 2017 and 2018
- Workshop on Data and Algorithmic Bias, CIKM 2017
- Singapore Workshop on Fairness, Accountability and Transparency in AI and Big Data, 2017
- Ethics in Natural Language Processing, EACL 2017
- Workshop on Fairness, Accountability, and Transparency on the Web, WWW 2017
- Special Session on Explainability of Learning Machines, IJCNN 2017
- Workshop on Data and Algorithmic Transparency (DAT), 2016
- The Human Use of Machine Learning: An Interdisciplinary Workshop, IEEE SMC
- International Workshop on Privacy and Discrimination in Data Mining, IEEE ICDM 2016
- Machine Learning and the Law, NIPS 2016
- Interpretable Machine Learning for Complex Systems, NIPS 2016
- Workshop on Human Interpretability in Machine Learning, ICML 2016
- Workshop on the Ethics of Online Experimentation, WSDM 2016
- Auditing Algorithms From the Outside: Methods and Implications, ICWSM 2015
- Discrimination and Privacy-Aware Data Mining, IEEE ICDM 2012
- Workshop on Novelty and Diversity in Recommender Systems, ACM RECSYS 2011
- Governing Algorithms
- Auditing Algorithms NSF Workshop