449: Fairness in A.I.
Super Data Science: ML & AI Podcast with Jon Krohn
00:00
Addressing Bias in AI: Fairness and Accountability
This chapter explores the complexities of bias in machine learning, with a focus on the importance of transparency and ethical standards for AI practitioners. Discussions emphasize the need for organizational accountability, stakeholder engagement, and enhanced regulations to ensure fairness, particularly in controversial domains like facial recognition. The conversation highlights educational initiatives and the pressing need for diverse representation in data sets, advocating for reforms that promote equitable outcomes in technology.
Transcript
Play full episode
