On the ethics of algorithmic decision-making in healthcare

In recent years, a plethora of high-profile scientific publications has been reporting about machine learning algorithms outperforming clinicians in medical diagnosis or treatment recommendations. This has spiked interest in deploying relevant algorithms with the aim of enhancing decision-making in healthcare. In this paper, we argue that instead of straightforwardly enhancing the decision-making capabilities of clinicians and healthcare institutions, deploying machines learning algorithms entails trade-offs at the epistemic and the normative level. Whereas involving machine learning might improve the accuracy of medical diagnosis, it comes at the expense of opacity when trying to assess the reliability of…

• DF
  Deutsche Forschungsgemeinschaft

  Awards: BE5601/4-1, 390727645, EXC 2064/1 – Project number 390727645, EXC 2064
• BF
  Bundesministerium für Bildung und Forschung

  Awards: FKZ 01GQ1601, 01IS18039A, 01GQ1601