BMC Medical Ethics & BMC Medical Informatics and Decision Making are calling for submissions to our Collection on Ethics of Artificial Intelligence in Health and Medicine.
Today, there is a need to bring up within the scientific and clinical community a discussion about the impact of AI on medical decision making. In particular, machine learning methods have seen an impressive expansion in the last few years, and this has not come without issues and ethical questions, notably regarding the data embedded bias and the role that AI-based methods may have in unwillingly inducing inequalities in health care.
Metrics such as fairness, accountability, lack or mitigation of bias, and explainability are major aspects that impact the perception and use of machine learning methods in ethically-sensitive fields such as medicine, and machine learning methods endowed with these features might play a significant role in overcoming mistrust, although they could not guarantee trust.
This collection welcomes studies focused on technical assessment and evaluation of AI-based medical decision making methods with regards to these ethics-relevant features, as well as more theoretical considerations on the medical use of AI-based methods. This includes but is not limited to the presentation of novel AI-based methods able to fulfill such ethical requirements and tools able to mitigate issues like bias, the elaboration of novel ethics-relevant metrics, research on attitudes and perceptions of physicians and the public on AI implementation, ethics surrounding AI-associated privacy and surveillance, and ethical challenges surrounding implementation of medical AI.
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