Ethics of the algorithmic prediction of goal of care preferences: from theory to practice.
Andrea FerrarioSophie GloecklerNikola Biller-AndornoPublished in: Journal of medical ethics (2022)
Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients' values and goals of care, which often requires input from clinicians and loved ones. Although the use of algorithms to predict patients' most likely preferred treatment has been discussed in the medical ethics literature, no example has been realised in clinical practice. This is due, arguably, to the lack of a structured approach to the epistemological, ethical and pragmatic challenges arising from the design and use of such algorithms. The present paper offers a new perspective on the problem by suggesting that preference predicting AIs be viewed as sociotechnical systems with distinctive life-cycles. We explore how both known and novel challenges map onto the different stages of development, highlighting interdisciplinary strategies for their resolution.
Keyphrases
- artificial intelligence
- healthcare
- decision making
- machine learning
- end stage renal disease
- big data
- newly diagnosed
- deep learning
- ejection fraction
- public health
- chronic kidney disease
- palliative care
- prognostic factors
- clinical practice
- quality improvement
- peritoneal dialysis
- clinical trial
- patient reported outcomes
- study protocol
- global health
- single molecule
- replacement therapy
- health information