Ethical Dilemmas in the Use of Artificial Intelligence in Breast Cancer Diagnosis and Treatment (Addressing Issues of Bias, Transferability, and Patient Trust in Breast Cancer AI)

Abstract

Breast cancer care is becoming one of the main areas of development of artificial intelligence (AI), with applications including screening and diagnosis, risk calculation, disease progression, clinical decision support, management planning, and precision medicine. This paper will review the ethical, legal, and social implications of these developments, including the values embedded in algorithms, evaluation of results, issues of bias, data ownership, confidentiality, and consent, as well as legal, moral, and professional responsibilities. Additionally, we also need to consider the potential impact on patients, including trust in healthcare, as well as explaining the reasons why AI is being implemented quickly. Resolving this challenge requires the involvement of professionals, governments and regulators, health care providers, and patients, regarding the imposition of conditions on implementation, and preventive monitoring systems to ensure development does not move too quickly ahead of evaluation and discussion.