• AI increasingly shapes health and justice decisions, but bias remains a critical challenge. • UC Berkeley’s Emma Pierson develops fair algorithms to reduce racial and gender bias. • She created a test detecting racial discrimination in policing algorithms. • Pierson works on disease‑risk models that avoid reproducing human bias. • Her goal: use AI to build a healthier, more equitable society. • Personal experience with BRCA1 gene motivates her focus on precision health.

Article Summaries:

  • UC Berkeley assistant professor Emma Pierson is tackling bias in AI systems that influence health care and criminal‑justice decisions. She has developed a statistical test that distinguishes racial discrimination from other causes in police traffic‑stop data and is applying similar methods to disease‑risk algorithms to reduce gender and racial bias. Pierson’s work, funded by the Zhang Family Endowed Professorship, spans the Berkeley AI Research Lab, Computational Precision Health, and the Center for Human‑Compatible AI. A former physics student whose own BRCA1 mutation spurred her interest, she now aims to use machine learning to create fairer, healthier outcomes.

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