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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 →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI research draws parallels between medicine and ML for enhanced reliability

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

  1. arXiv cs.AI TIER_1 English(EN) · Emanuele Ratti, Lena Zuchowski ·

    What Can Artificial Intelligence Learn from Medicine? Generative Analogies and Reliable Machine Learning Systems

    arXiv:2608.18186v1 Announce Type: cross Abstract: In the past few years, machine learning (ML) has been widely (and to an extent, successfully) implemented in medicine. However, uncertainties surrounding ML have made it difficult to establish the bases of its epistemic and method…