Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept
Meier LJ, Hein A, Diepold K, Buyx A (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 22
Pages Range: 4-20
Journal Issue: 7
DOI: 10.1080/15265161.2022.2040647
Abstract
Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence?.
Involved external institutions
Germany (DE)How to cite
APA:
Meier, L.J., Hein, A., Diepold, K., & Buyx, A. (2022). Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept. American Journal of Bioethics, 22(7), 4-20. https://doi.org/10.1080/15265161.2022.2040647
MLA:
Meier, Lukas J., et al. "Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept." American Journal of Bioethics 22.7 (2022): 4-20.
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