Relative explainability and double standards in medical decision-making

Ethics and Information Technology, vol. 24

Abstract

Abstract The increased presence of medical AI in clinical use raises the ethical question which standard of explainability is required for an acceptable and responsible implementation of AI-based applications in medical contexts. In this paper, we elaborate on the emerging debate surrounding the standards of explainability for medical AI. For this, we first distinguish several goods explainability is usually considered to contribute to the use of AI in general, and medical AI in specific. Second, we propose to understand the value of explainability relative to other available norms of explainable decision-making. Third, in pointing out that we usually accept heuristics and uses of bounded rationality for medical decision-making by physicians, we argue that the explainability of medical decisions should not be measured against an idealized diagnostic process, but according to practical considerations. We conclude, fourth, to resolve the issue of explainability-standards by relocating the issue to the AI’s certifiability and interpretability.

Authors 3

1. Hendrik Kempt corresponding Aachen Applied Ethics Group

   RWTH Aachen University

   Affiliation as printed

   Applied Ethics Group, RWTH Aachen University, Aachen, Germany

   Applied Ethics Group, RWTH Aachen University, Theaterplatz 14, 52062, Aachen, Germany

2. Jan‐Christoph Heilinger Aachen Applied Ethics Group

   RWTH Aachen University

   Affiliation as printed

   Applied Ethics Group, RWTH Aachen University, Aachen, Germany

   Applied Ethics Group, RWTH Aachen University, Theaterplatz 14, 52062, Aachen, Germany

3. Saskia Kathi Nagel Aachen Applied Ethics Group

   RWTH Aachen University

   Affiliation as printed

   Applied Ethics Group, RWTH Aachen University, Aachen, Germany

   Applied Ethics Group, RWTH Aachen University, Theaterplatz 14, 52062, Aachen, Germany