FAT* is a multi-disciplinary conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.
Artificial intelligence, automation, and machine learning are being adopted in a growing number of contexts. Fueled by big data, these systems filter, sort, score, recommend, personalize, and otherwise shape human experiences of socio-technical systems. Although these systems bring myriad benefits, they also contain inherent risks, such as codifying and entrenching biases; reducing accountability and hindering due process; and increasing the information assymmetry between data producers and data holders.
FAT* is an annual conference dedicating to bringing together a diverse community to investigate and tackle issues in this emerging area. FAT* builds upon several years of successful workshops on the topics of fairness, accountability, transparency, ethics, and interpretability in machine learning, recommender systems, the web, and other technical disciplines.
The inaugural 2018 FAT* Conference will be held February 23 and 24th, 2018 at New York University, NYC. Details will be announced at https://www.fatconference.org/2018/index.html.