{"slug": "the-equity-paradox-in-predictive-public-health", "title": "The Equity Paradox In Predictive Public Health", "summary": "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.", "body_md": "# The Equity Paradox In Predictive Public Health\n\nBy Arpan Saxena, Forbes Councils MemberSource:\n\n[Forbes Innovation](https://www.forbes.com/innovation/)Here's why human context remains essential, even as AI becomes a larger part of healthcare decision-making.\n\nGet AI news in your inbox\n\nDaily digest of what matters in AI.", "url": "https://wpnews.pro/news/the-equity-paradox-in-predictive-public-health", "canonical_source": "https://www.machinebrief.com/news/the-equity-paradox-in-predictive-public-health-4ydh", "published_at": "2026-07-27 12:30:00+00:00", "updated_at": "2026-07-27 13:57:50.829154+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-ethics", "ai-policy"], "entities": ["Arpan Saxena", "Forbes"], "alternates": {"html": "https://wpnews.pro/news/the-equity-paradox-in-predictive-public-health", "markdown": "https://wpnews.pro/news/the-equity-paradox-in-predictive-public-health.md", "text": "https://wpnews.pro/news/the-equity-paradox-in-predictive-public-health.txt", "jsonld": "https://wpnews.pro/news/the-equity-paradox-in-predictive-public-health.jsonld"}}