Embedded ethics: a proposal for integrating ethics into the development of medical AI.
Stuart McLennanAmelia FiskeDaniel TigardRuth MüllerSami HaddadinAlena BuyxPublished in: BMC medical ethics (2022)
The emergence of ethical concerns surrounding artificial intelligence (AI) has led to an explosion of high-level ethical principles being published by a wide range of public and private organizations. However, there is a need to consider how AI developers can be practically assisted to anticipate, identify and address ethical issues regarding AI technologies. This is particularly important in the development of AI intended for healthcare settings, where applications will often interact directly with patients in various states of vulnerability. In this paper, we propose that an 'embedded ethics' approach, in which ethicists and developers together address ethical issues via an iterative and continuous process from the outset of development, could be an effective means of integrating robust ethical considerations into the practical development of medical AI.
Keyphrases
- artificial intelligence
- big data
- healthcare
- machine learning
- deep learning
- public health
- end stage renal disease
- decision making
- chronic kidney disease
- mental health
- climate change
- magnetic resonance imaging
- newly diagnosed
- randomized controlled trial
- peritoneal dialysis
- computed tomography
- prognostic factors
- patient reported