{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:55:06Z","timestamp":1776401706866,"version":"3.51.2"},"reference-count":40,"publisher":"Georg Thieme Verlag KG","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Clin Colon Rectal Surg"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) is rapidly transforming surgical care, offering unprecedented capabilities in diagnostics, planning, and intraoperative guidance. However, its integration into clinical practice raises complex ethical challenges that must be addressed to ensure responsible and equitable use. This chapter aims to explore the ethical implications of AI in surgery through the lens of the four foundational principles of medical ethics: autonomy, beneficence, nonmaleficence, and justice. Respecting patient autonomy requires clinicians to disclose all relevant information and ensure understanding of a proposed intervention (or AI tool) for a patient to make an informed, voluntary decision. Numerous studies have shown that both patients and clinicians often lack sufficient understanding of AI tools, complicating efforts to explain their intended function, or obtain truly informed consent for their use in patient care. This has the potential to diminish trust in the patient\u2013clinician relationship and must be considered when using AI tools. AI's potential to uphold beneficence is evident in its ability to enhance surgical precision and outcomes. Yet, its reliance on historical data introduces risks of bias and error, threatening the principle of nonmaleficence. In this chapter, we explore these topics further to highlight the need for robust oversight and clinician involvement to prevent harm to patients. When biased data are used to train an AI tool, it may lead to unequal care across patient populations\u2014i.e., exacerbating existing disparities in health care. Additionally, the lack of clear accountability for AI-driven errors raises legal and ethical concerns about liability\u2014whether it lies with clinicians, health care institutions, or developers. To ethically integrate AI into surgical practice, the chapter calls for comprehensive frameworks that ensure transparency, data integrity, clinician and patient education, and regulatory oversight. These measures are essential to safeguard patient welfare as AI continues to reshape the future of surgical care.<\/jats:p>","DOI":"10.1055\/a-2769-0687","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T23:30:16Z","timestamp":1768087816000},"page":"169-173","source":"Crossref","is-referenced-by-count":1,"title":["Ethical Considerations for the Use of Artificial Intelligence Tools in Surgery"],"prefix":"10.1055","volume":"39","author":[{"given":"Nicole","family":"Meredyth","sequence":"additional","affiliation":[{"name":"Department of Surgery, Northwestern Memorial Hospital, Chicago, Illinois, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paola A.","family":"Barrios","sequence":"additional","affiliation":[{"name":"Department of Surgery, Northwestern Memorial Hospital, Chicago, Illinois, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"194","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"key":"ref1","first-page":"47","volume-title":"Principles of Biomedical Ethics: Reflections on a Work in Progress","author":"J F Childress","year":"2003"},{"issue":"09","key":"ref2","doi-asserted-by":"crossref","first-page":"3111","DOI":"10.3390\/jcm14093111","article-title":"Balancing ethics and innovation: can artificial intelligence safely transform emergency surgery? A narrative perspective","volume":"14","author":"B De Simone","year":"2025","journal-title":"J Clin Med"},{"key":"ref3","volume-title":"Principles of Biomedical Ethics","author":"T Beauchamp","year":"1986","edition":"3rd ed."},{"issue":"06","key":"ref4","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1136\/jme.21.6.332","article-title":"Not just autonomy\u2013the principles of American biomedical ethics","volume":"21","author":"S Holm","year":"1995","journal-title":"J Med Ethics"},{"issue":"04","key":"ref5","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1017\/S0963180111000259","article-title":"Informed consent: its history, meaning, and present challenges","volume":"20","author":"T L Beauchamp","year":"2011","journal-title":"Camb Q Healthc Ethics"},{"issue":"08","key":"ref6","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1001\/jama.2010.1208","article-title":"The shared decision-making continuum","volume":"304","author":"A A Kon","year":"2010","journal-title":"JAMA"},{"key":"ref7","volume-title":"A History and Theory of Informed Consent","author":"R R Faden","year":"1986"},{"issue":"02","key":"ref8","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.jamcollsurg.2019.10.001","article-title":"(Under)valuing surgical informed consent","volume":"230","author":"N A Meredyth","year":"2020","journal-title":"J Am Coll Surg"},{"issue":"04","key":"ref9","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1016\/j.jamcollsurg.2008.12.012","article-title":"Informed consent and the surgeon","volume":"208","author":"R Childers","year":"2009","journal-title":"J Am Coll Surg"},{"issue":"05","key":"ref10","doi-asserted-by":"crossref","first-page":"e2210309","DOI":"10.1001\/jamanetworkopen.2022.10309","article-title":"Perspectives of patients about artificial intelligence in health care","volume":"5","author":"D Khullar","year":"2022","journal-title":"JAMA Netw Open"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"105945","DOI":"10.1016\/j.ijmedinf.2025.105945","article-title":"Knowledge, attitude, and practice of primary care physicians toward clinical AI-assisted digital health technologies: systematic review and meta-analysis","volume":"201","author":"H M Abdulazeem","year":"2025","journal-title":"Int J Med Inform"},{"issue":"04","key":"ref12","doi-asserted-by":"crossref","first-page":"e092624","DOI":"10.1136\/bmjopen-2024-092624","article-title":"Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review","volume":"15","author":"C EA Scipion","year":"2025","journal-title":"BMJ Open"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","article-title":"Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI","volume":"58","author":"A B Arrieta","year":"2020","journal-title":"Inf Fusion"},{"issue":"03","key":"ref14","first-page":"421","article-title":"Regulating black-box medicine","volume":"116","author":"W N Price II","year":"2017","journal-title":"Mich Law Rev"},{"issue":"11","key":"ref15","doi-asserted-by":"crossref","first-page":"e37478","DOI":"10.2196\/37478","article-title":"Considering clinician competencies for the implementation of artificial intelligence-based tools in health care: findings from a scoping review","volume":"10","author":"K V Garvey","year":"2022","journal-title":"JMIR Med Inform"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"830345","DOI":"10.3389\/fpsyg.2022.830345","article-title":"Inclusion of clinicians in the development and evaluation of clinical artificial intelligence tools: a systematic literature review","volume":"13","author":"S Tulk Jesso","year":"2022","journal-title":"Front Psychol"},{"issue":"02","key":"ref17","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1177\/1460458219874641","article-title":"Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: an integrative review","volume":"26","author":"L Shinners","year":"2020","journal-title":"Health Informatics J"},{"issue":"12","key":"ref18","doi-asserted-by":"crossref","first-page":"e33540","DOI":"10.2196\/33540","article-title":"How clinicians perceive artificial intelligence-assisted technologies in diagnostic decision making: mixed methods approach","volume":"23","author":"H Hah","year":"2021","journal-title":"J Med Internet Res"},{"issue":"01","key":"ref19","doi-asserted-by":"crossref","first-page":"9312","DOI":"10.1038\/s41598-025-94335-0","article-title":"International expert consensus on the current status and future prospects of artificial intelligence in metabolic and bariatric 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