To Be, Or Not To Be?: Regulating Impossible AI in the United States

MK Sharma - arXiv preprint arXiv:2408.01440, 2024 - arxiv.org
Many AI systems are deployed even when they do not work. Some AI will simply never be
able to perform the task it claims to perform. We call such systems Impossible AI. This paper …

[PDF][PDF] FairSense: Long-Term Fairness Analysis of ML-Enabled Systems

Y She, S Biswas, C Kästner, E Kang - sumonbis.github.io
Algorithmic fairness of machine learning (ML) models has raised significant concern in the
recent years. Many testing, verification, and bias mitigation techniques have been proposed …