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

医疗保健 抗性(生态学) 知识管理 扎根理论 心理学 工程伦理学 业务 管理科学 社会学 计算机科学 定性研究 经济 政治学 工程类 法学 生态学 生物 社会科学
作者
Nidhi Singh,Monika Jain,Muhammad Mustafa Kamal,Rahul Bodhi,Bhumika Gupta
出处
期刊:Technological Forecasting and Social Change [Elsevier]
卷期号:198: 122967-122967 被引量:58
标识
DOI:10.1016/j.techfore.2023.122967
摘要

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.
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