The Danger of Data You Can’t Interpret
More data sounds good until it starts making everyone anxious, confused, or falsely confident.In this conversation, Brian Berridge, Nick Kelley, and Szczepan Baran explore how data shapes decisions across drug discovery, safety assessment, clinical translation, AI, digital health, and wearable monitoring. They discuss why legacy datasets are often not truly AI-ready, why context of use matters, and why the wrong data can create risk instead of reducing it.A practical, skeptical discussion for anyone working at the messy intersection of biomedical research, AI, translation, and decision-making.
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