AI research draws parallels between medicine and ML for enhanced reliability

A new paper published on arXiv explores the parallels between medicine and machine learning (ML) to establish more reliable ML systems. The research uses Hesse's work to frame the process of clinical translation as a generative analogy for building ML systems. By interpreting clinical translation warrants in reliabilist terms, the paper proposes a novel form of ML reliabilism that complements existing philosophical accounts of artificial intelligence. AI

IMPACT Proposes a new framework for building more reliable machine learning systems by drawing parallels with medical translation.

RANK_REASON The cluster contains an academic paper discussing theoretical aspects of AI and ML. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• artificial intelligence
• arXiv
• Hesse
• machine learning
• medicine
• ML reliabilism
• philosophy of artificial intelligence

• paper
• safety
• other

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