Machine learning applications in healthcare and the role of informed consent: Ethical and practical considerations

Giorgia Lorenzini*, David Martin Shaw, Laura Arbelaez Ossa, Bernice Simone Elger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Informed consent is at the core of the clinical relationship. With the introduction of machine learning (ML) in healthcare, the role of informed consent is challenged. This paper addresses the issue of whether patients must be informed about medical ML applications and asked for consent. It aims to expose the discrepancy between ethical and practical considerations, while arguing that this polarization is a false dichotomy: in reality, ethics is applied to specific contexts and situations. Bridging this gap and considering the whole picture is essential for advancing the debate. In the light of the possible future developments of the situation and the technologies, as well as the benefits that informed consent for ML can bring to shared decision-making, the present analysis concludes that it is necessary to prepare the ground for a possible future requirement of informed consent for medical ML.
Original languageEnglish
Number of pages6
JournalClinical Ethics
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • Ethics
  • healthcare
  • informed consent
  • machine learning
  • shared decision-making
  • transparency

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