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Responsibility, second opinions and peer-disagreement: ethical and epistemological challenges of using AI in clinical diagnostic contexts

Hendrik Kempt, Saskia K. Nagel

2021Journal of Medical Ethics83 citationsDOIOpen Access PDF

Abstract

In this paper, we first classify different types of second opinions and evaluate the ethical and epistemological implications of providing those in a clinical context. Second, we discuss the issue of how artificial intelligent (AI) could replace the human cognitive labour of providing such second opinion and find that several AI reach the levels of accuracy and efficiency needed to clarify their use an urgent ethical issue. Third, we outline the normative conditions of how AI may be used as second opinion in clinical processes, weighing the benefits of its efficiency against concerns of responsibility attribution. Fourth, we provide a 'rule of disagreement' that fulfils these conditions while retaining some of the benefits of expanding the use of AI-based decision support systems (AI-DSS) in clinical contexts. This is because the rule of disagreement proposes to use AI as much as possible, but retain the ability to use human second opinions to resolve disagreements between AI and physician-in-charge. Fifth, we discuss some counterarguments.

Topics & Concepts

NormativeAttributionContext (archaeology)CognitionPsychologyEpistemologyComputer scienceEngineering ethicsSocial psychologyPsychiatryPhilosophyBiologyPaleontologyEngineeringArtificial Intelligence in Healthcare and EducationClinical Reasoning and Diagnostic SkillsEthics in Clinical Research
Responsibility, second opinions and peer-disagreement: ethical and epistemological challenges of using AI in clinical diagnostic contexts | Litcius