Why AI tools need clearer guardrails in high-stakes health research

News-Medical berichtet ueber Why AI tools need clearer guardrails in high-stakes health research. AI-enabled research tools can accelerate health research, but their data-science roots may clash with epidemiological workflows built around prespecified designs, causal reasoning, bias control, and reproducibility. The article argues that researchers should integrate AI cautiously, using clear workflow boundaries, peer review of AI outputs, and sustained human accountability. As AI tools enter clinical and population health research, this paper warns that speed alone is not enough, and shows why expert oversight, causal logic, and transparent workflows remain essential for trustworthy science.

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