ML Bias Insights
Dylan challenges the focus on bias in hiring, questioning the relevance of outdated data in training ML models for current HR practices. Kanjun agrees, emphasizing the importance of aligning system behavior with desired outcomes rather than a trade-off between fairness and accuracy.In this clip
From this podcast
Generally Intelligent
Episode 10: Dylan Hadfield-Menell, UC Berkeley/MIT, on the value alignment problem in AI
Related Questions
Is data quality overlooked in machine learning as discussed in the episode Machine Learning Done Wrong and the clip Uncovering Data Insights?
Can AI have biases as discussed in the episode Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4 and the clip Bias in Machine Learning?
Are there biases in AI as discussed in the episode Richard Socher — The Challenges of Making ML Work in the Real World and the clip Addressing AI Bias?