{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T14:45:05Z","timestamp":1792075505168,"version":"4.4.0"},"reference-count":54,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["WORK: A Journal of Prevention, Assessment &amp; Rehabilitation"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The use of artificial intelligence (AI) in workplace disability contexts is expanding, raising important ethical concerns. Existing frameworks, such as the OECD Framework for the Classification of AI Systems, provide structure for understanding AI applications but lack an explicit focus on ethics in relation to disability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review examines ethical issues arising from the use of AI for employees with disabilities and aims to interpret the OECD framework through an explicit ethics lens.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a systematic review of 23 peer-reviewed studies identified through PRISMA-guided searches. Using the OECD AI framework as a foundation, we developed an extended multidimensional framework consisting of five interconnected domains: (1) Context, (2) People, (3) Data &amp; Input, (4) AI Model, and (5) Task &amp; Output and analyzed through the lens of ethics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Four recurring ethical concerns were identified: (1) automation bias, (2) data privacy and informed consent, (3) discrimination and inequitable access to opportunities, and (4) AI governance gaps. Ethical risks were found to be context-dependent, disproportionately affecting disabled workers, and exacerbated by biased or incomplete data and opaque AI models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This review provides a structured synthesis of current evidence and highlights the need for responsible and inclusive AI practices. We propose key directions for research and practice, including algorithmic audits, inclusive testing, transparent data practices, interdisciplinary oversight, and worker-centered governance. Integrating ethics throughout a multidimensional framework offers a roadmap for advancing equitable AI in workplace disability contexts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/10519815261491693","type":"journal-article","created":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T18:19:41Z","timestamp":1791915581000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence and disability in the workplace: A systematic review of ethical issues"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0777-209X","authenticated-orcid":false,"given":"Jennifer Jihae","family":"Park","sequence":"first","affiliation":[{"name":"University of Cincinnati"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cho Hyun","family":"Park","sequence":"additional","affiliation":[{"name":"Purdue University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sunyoung","family":"Park","sequence":"additional","affiliation":[{"name":"Louisiana State University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,13]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1080\/09585192.2025.2492867"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1111\/1744-7941.12392"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1177\/15344843241273231"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2024.117560"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bushor.2024.02.002"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/su15107905"},{"key":"e_1_3_2_8_2","first-page":"55","article-title":"Ethical considerations in telehealth and artificial intelligence for work-related musculoskeletal disorders: a scoping review","volume":"78","author":"Karaibrahimoglu A","year":"2024","unstructured":"Karaibrahimoglu A, Ince F, Hassanzadeh G, et al. Ethical considerations in telehealth and artificial intelligence for work-related musculoskeletal disorders: a scoping review. Work 2024; 78: 55\u201370.","journal-title":"Work"},{"key":"e_1_3_2_9_2","first-page":"1282","article-title":"Preventing discrimination in the automated targeting of job advertisements","volume":"34","author":"Dalenberg DJ.","year":"2018","unstructured":"Dalenberg DJ. Preventing discrimination in the automated targeting of job advertisements. 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