Episode

Episode 3: Limitations of AI in Life Sciences

Podcast
From Models to Medicine
Published
Apr 1, 2026
Duration seconds
2218
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/kami-think-tank/episodes/Episode-3-Limitations-of-AI-in-Life-Sciences-e3h761h
Audio
https://anchor.fm/s/110164688/podcast/play/117724657/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-2-31%2F4d35fac8-ed6e-503c-575f-15ed760634d9.mp3
JSON
/v1/public/podcasts/from-models-to-medicine-7769799/episodes/episode-3-limitations-of-ai-in-life-sciences
Markdown
/podcast/from-models-to-medicine-7769799/episode-3-limitations-of-ai-in-life-sciences.md

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Summary

In this episode of From Models to Medicine, we sit down with Rachel Thomas to discuss the growing gap between AI hype and scientific reality in the life sciences. The conversation highlights the hidden costs of poor data quality and the necessity of domain expertise, featuring deep dives into real-world AI missteps, from a flawed enzyme classification paper to an app's mishandling of long-COVID data.