Personalized recommendations have become an essential part of our life and work. While paying attention to the effect of personalized recommendations, users are at the same time paying more attention to their fairness problems. This report summarized international research related to the fairness of personalized recommendations. Besides, a discussion was made on the definition of fairness from different levels and perspectives including result and process fairness, individual and group fairness, single and equal sharing fairness, consistent and calibration fairness, non-jealous and counterfactual fairness. In addition, we introduced and analyzed the subjects and objects of fairness, the causes of fairness, and the measurement methods of fairness.
Expert report
Investigating Fairness of Personalized Recommendation
Min Zhang, Professor, DCST, Tsinghua UniversityExpert Introduction
Min Zhang, an Professor at the Department of Computer Science and Technology (DCST), Tsinghua University, the Deputy Director at the State Key Laboratory of Intelligent Technology and Systems (LITS) and at the MOE-Key Laboratory of Media and Networking respectively, Tsinghua University, an Editorial Board Member of the Association for Computing Machinery (ACM) Transaction on Information Systems (TOIS) and a Director of the Chinese Information Processing Society of China (CIPSC), is also a member of the Information Retrieval Technical Committee and the Social Media Computing Committee of CIPSC, the Professional Committee of Machine Learning and the Professional Committee of Artificial Psychology and Artificial Emotion of the Chinese Association for Artificial Intelligence (CAAI), and the Chinese Information Technology Committee of the China Computer Federation (CCF). She specializes in information retrieval, personalized recommendations, user behavior analysis, and machine learning. She has participated in multiple projects as a leader covering projects from the National Key Research and Development Program of China, the National Natural Science Foundation of China, and the Ministry of Education of the Republic of China (hereinafter referred to as the Ministry of Education). She has also won the College Outstanding Teaching Award in Computing (2018), the First Prize of the Beijing Science and Technology Award (2015), and the Tsinghua University Outstanding Teaching Award (2007).