Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

Abstract

This is a condensed summary of an international multisociety statement on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists, and American Association of Physicists in Medicine. AI has great potential to increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and biases. Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues. Currently, there is little experience using AI for patient care in diverse clinical settings. Extensive research is needed to understand how to best deploy AI in clinical practice. This statement highlights our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders in a just manner. We believe AI should respect human rights and freedoms, including dignity and privacy. It should be designed for maximum transparency and dependability. Ultimate responsibility and accountability for AI remains with its human designers and operators for the foreseeable future. The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes.

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers

“…Reference any previous studies that used the same dataset and specify how the current study differs. Adhere to ethical guidelines to assure that the study is conducted appropriately; describe the ethics review and informed consent (19). Provide links to data sources and/or images, if available.…”

Artificial intelligence: Who is responsible for the diagnosis?

“…The recent North America and European multi-society paper about "Ethics of artificial intelligence in radiology" reports the risk of the automation bias [17].…”

Artificial Intelligence in Radiology—Ethical Considerations

“…Under the EU General Data Protection Regulation (GDPR), patients own and control their own sensitive and/or identifiable data, and must give explicit consent for data re-use or sharing [12]. In other parts of the world, individual rights may be superseded by the collective societal welfare, or ownership of imaging data may reside with the entity performing the imaging [6], making data access easier. Under GDPR rules, patients must give their consent if their imaging studies are to be used to train an AI algorithm, and that consent may need to take a dynamic form, being varied or re-obtained for each version of the algorithm [6].…”

“…In other parts of the world, individual rights may be superseded by the collective societal welfare, or ownership of imaging data may reside with the entity performing the imaging [6], making data access easier. Under GDPR rules, patients must give their consent if their imaging studies are to be used to train an AI algorithm, and that consent may need to take a dynamic form, being varied or re-obtained for each version of the algorithm [6]. These legal restrictions can inhibit AI research in some parts of the world relative to others, skewing the academic and commercial playing field.…”

“…This paper explains some of the ethical difficulties of which we are presently aware, and some of the measures we may take to protect against misuse of AI. Association of Physicists in Medicine (AAPM) together wrote a multi-society statement of the ethics of AI in radiology, published as a summary in four leading journals (Insights into Imaging [5], JACR, Radiology and CARJ), with the full statement published on the societies' websites [6]. The statement considered ethical issues that may arise from many aspects of deep learning, with specific reference to radiology applications.…”