Profiling and Representation

Explore cutting-edge research on profiling and representation in machine learning and artificial intelligence during this 47-minute conference session from the ACM FAT* 2019 conference. Delve into four thought-provoking presentations covering crucial topics such as semantic representation bias in high-stakes settings, fair representation in crowdsourced recommendations, the profiling potential of computer vision, and rich subgroup fairness in machine learning. Gain insights from leading researchers as they discuss the challenges and implications of algorithmic profiling and representation across various domains. Examine case studies, empirical analyses, and theoretical frameworks that address the complex interplay between technology, fairness, and society.

FAT* 2019: Profiling and Representation