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The Equity Paradox In Predictive Public Health

Forbes Councils Member Arpan Saxena argues that while AI can improve predictive public health, it risks exacerbating health inequities if deployed without human context. Saxena warns that algorithms trained on biased data may reinforce disparities, making human oversight essential for equitable healthcare outcomes.

read1 min views30 publishedJul 27, 2026
The Equity Paradox In Predictive Public Health
Image: Machinebrief (auto-discovered)

By Arpan Saxena, Forbes Councils MemberSource:

Forbes InnovationHere's why human context remains essential, even as AI becomes a larger part of healthcare decision-making.

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source & further reading
machinebrief.com — original article How Social Media Platforms Are Identifying AI Content OpenAI pulls out of Caltech math hackathon after mathematicians issue open letter criticizing AI math 'slop' Anthropic details bad actors’ efforts to misuse its AI for bioweapons
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