Healthcare's existing data schemas, built for billing and efficiency, inadvertently limit the perception of health to discrete events rather than continuous signals. AI's ability to relentlessly optimize within defined spaces, as demonstrated by Andrej Karpathy's AutoResearch, highlights the critical importance of these schemas, referred to as 'program.md'. If these schemas are flawed, AI will efficiently optimize for the wrong outcomes, underscoring the need for systems that can identify and learn from the limitations of current data ontologies. AI
IMPACT AI's ability to optimize within defined data schemas highlights the critical need to refine healthcare ontologies for better patient care.
RANK_REASON The article is an opinion piece discussing the implications of AI on healthcare data structures, drawing parallels to AI research projects.
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