Joining the Network
Do you have an upcoming workshop, special issue, or similar event centered around FAT* 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 FAT* Network, your event must:
- Engage with FAT* 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 FAT* Network:
- We’ll help spread the word about your event to the FAT* community via the network web site, FAT* 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 FAT* 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.
- HUMAINT Winter School on Fairness, Accountability, and Transparency in AI, in Seville, Spain the week before FAT*.
- Fair ML for Health, a workshop to be held at NeurIPS 2019 (Dec. 14, 2019).
- Machine Learning for the Developing World: Challenges and Risks, a workshop to be held at NeurIPS 2019 (Dec. 13, 2019).
- Human-Centric Machine Learning, a workshop to be held at NeurIPS 2019 (Dec. 13, 2019).
- AI@Work, a workshop in Amsterdam (March 5-6, 2020).
These opportunities have happened — look through them for interesting work!
- Contestability in Algorithmic Systems, a workshop at CSCW 2019 (Nov. 9).
- 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 on Designing Human-Centric MIR Systems, a workshop at ISMIR 2019 (Nov. 2).
- Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR) at SIGIR 2019 (July 25, 2019)
Older Workshops and Events
These are various events held prior to the founding of the ACM FAT* 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