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Aims: To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners.

Methods: We implemented a literature-validated questionnaire to examine the knowledge, attitudes, and practices of the target population during the period between April and August 2023. Themes of ethical debate included privacy breaches, consent, ownership, augmented biases, epistemology, and accountability. Participants' responses were showcased using descriptive statistics and compared between groups using t-test or ANOVA.

Results: We included 466 participants. The greater majority of respondents were interns and residents (50.2%), followed by medical students (38.0%). Most participants were affiliated with university institutions (62.4%). In terms of privacy, participants acknowledged that Big Data and AI were susceptible to privacy breaches (39.3%); however, 59.0% found such breaches justifiable under certain conditions. For ethical debacles involving informed consent, 41.6% and 44.6% were aware that obtaining informed consent posed an ethical limitation in Big Data and AI applications and denounced the concept of "broad consent", respectively. In terms of ownership, 49.6% acknowledged that data cannot be owned yet accepted that institutions could hold a quasi-control of such data (59.0%). Less than 50% of participants were aware of Big Data and AI's abilities to augment or create new biases in healthcare. Furthermore, participants agreed that researchers, institutions, and legislative bodies were responsible for ensuring the ethical implementation of Big Data and AI. Finally, while demonstrating limited experience with using such technology, participants generally had positive views of the role of Big Data and AI in complementing healthcare.

Conclusion: Jordanian medical students, physicians in training and senior practitioners have limited awareness of the ethical risks associated with Big Data and AI. Institutions are responsible for raising awareness, especially with the upsurge of such technology.

Titel:	Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study.
Autor/in / Beteiligte Person:	Al-Ani, A ; Rayyan, A ; Maswadeh, A ; Sultan, H ; Alhammouri, A ; Asfour, H ; Alrawajih, T ; Al Sharie, S ; Al Karmi, F ; Al-Azzam, AM ; Mansour, A ; Al-Hussaini, M
Link:	Full Text Finder (Volltext)
Zeitschrift:	BMC medical ethics, Jg. 25 (2024-02-17), Heft 1, S. 18
Veröffentlichung:	London : BioMed Central, [2000-, 2024
Medientyp:	academicJournal
ISSN:	1472-6939 (electronic)
DOI:	10.1186/s12910-024-01008-0
Schlagwort:	Humans Cross-Sectional Studies Big Data Artificial Intelligence Jordan Morals Students, Medical Physicians
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [BMC Med Ethics] 2024 Feb 17; Vol. 25 (1), pp. 18. <i>Date of Electronic Publication: </i>2024 Feb 17. MeSH Terms: Students, Medical* ; Physicians* ; Humans ; Cross-Sectional Studies ; Big Data ; Artificial Intelligence ; Jordan ; Morals Comments: Erratum in: BMC Med Ethics. 2024 Mar 5;25(1):27. (PMID: 38443918) References: Balazka D, Rodighiero D. Big data and the little big bang: an epistemological (R)evolution. Frontiers in Big Data. 2020;3:31. (PMID: 10.3389/fdata.2020.00031336934047931920) ; Boyd D, Crawford K. Critical questions for big data. Inf Commun Soc. 2012;15:662–79. (PMID: 10.1080/1369118X.2012.678878) ; Uprichards E. Focus: Big Data, Little Questions? Discover Society. 2013. https://archive.discoversociety.org/2013/10/01/focus-big-data-little-questions/ . Accessed 29 Oct 2023. ; Benke K, Benke G. Artificial intelligence and big data in public health. 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Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study.