Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/185846
Título: Algorithm Delegation
Autor: Wagner, Rafael Luis
Pinto, Diego Costa
Hildebrand, Diogo
Pacheco, Natália Araújo
Dhillon, Gurpreet
Herter, Marcia Maurer
Palavras-chave: artificial intelligence
delegation
embedded AI
human-AI agency
medical services
psychological distance
Applied Psychology
Marketing
SDG 3 - Good Health and Well-being
SDG 8 - Decent Work and Economic Growth
Data: Nov-2025
Resumo: Integrating insights from psychological distance and human-AI agency theories, this research explores embedded AI — algorithms physically integrated into tangible devices as a novel mechanism to help overcome resistance towards medical AI. Across four studies, including a large text-mining (n = 224,433 reviews) and three controlled experiments (n = 677 participants), we show that embedded AI reduces psychological distance between consumers and AI (Study 2B), which in turn enhances willingness to delegate medical decisions to algorithms (Studies 1-3). We further demonstrate that consumers expect better health outcomes when delegating decisions to embedded AI (Studies 2A, 2B, and 3). Moderation analysis further shows that these effects weaken when an analytical mode is primed using numerical accuracy information (Study 3). Our findings contribute to ongoing discussions on overcoming resistance to medical AI and offer implications for the design of AI-based technologies in medical services.
Descrição: Wagner, R. L., Pinto, D. C., Hildebrand, D., Pacheco, N. A., Dhillon, G., & Herter, M. M. (2025). Algorithm Delegation: How Embedded AI Facilitates Agency Transference in Medical Services. Psychology and Marketing, 42(11), 2902-2921. https://doi.org/10.1002/mar.70016 --- %ABS3% --- Funding: ENSILIS ‐ Educação e Formação Unipessoal, Fundação Para a Ciência e Tecnologia (FCT) (2024.07397. IACDC, UIDB/04152/2020), and European Health and Digital Executive Agency (HaDEA) (101219225).
Peer review: yes
URI: http://hdl.handle.net/10362/185846
DOI: https://doi.org/10.1002/mar.70016
ISSN: 0742-6046
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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