Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory

Nidhi Singh, Monika Jain, Muhammad Mustafa Kamal, Rahul Bodhi and Bhumika Gupta

Technological Forecasting and Social Change, 2024, vol. 198, issue C

Abstract: AI is transforming healthcare system with many innovations in diagnosis, drug research and advancement in medical treatments. But there are several concerns and dilemmas related to data misuse, AI efficiency for critical diagnostic services, users' resistance, investment costs, funding issues, and so on that have been raised by many previous studies on the effective integration of AI in clinical settings. Using paradox theory in the organisational settings, the present study discusses several technological paradoxes associated with the adoption of AI in healthcare. In this regard, the study examines the views of diverse medical practitioners about using AI services for several medical needs. The study analyses the efficacy and limitations of AI services which develop several ethical dilemmas in the mind of medical practitioners and also suggest a few strategies for the adoption. Using grounded theory approach, the study collected views of 62 medical practitioners on these dimensions. The primary drivers to the adoption identified in the present study are: ease of use, automation efficacy, diagnostic accuracy, and cost efficiency. A lack of training and education, cultural and religious considerations, privacy issues and work insecurity are some of the concerns highlighted by the medical staffs. The study inferred a few paradoxes or ethical dilemmas of practitioners which need attentions. The study contributes to the existing literature on paradox theory and AI, and identifies a few under-discussed areas, drivers, and barriers of AI services are highlighted in the paper, which may lead to ethical concerns and steer AI adoption in healthcare.

Keywords: AI; Drivers; Barriers; Dilemmas; AI strategy; Health system; Adoption (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:198:y:2024:i:c:s0040162523006522

DOI: 10.1016/j.techfore.2023.122967

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