On Responsible Machine Learning Datasets Emphasizing Fairness, Privacy And Regulatory Norms With Examples In Biometrics And Healthcare

This article discusses the importance of responsible machine learning datasets in ensuring the integrity and trustworthiness of AI algorithms. Through an audit of computer vision datasets, the study highlights the universal susceptibility to fairness, privacy, and regulatory compliance issues. The authors emphasize the need for revising dataset creation methodologies in light of global advancements in data protection legislation.