IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v198y2024ics0040162523006522.html
   My bibliography  Save this article

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

Author

Listed:
  • Singh, Nidhi
  • Jain, Monika
  • Kamal, Muhammad Mustafa
  • Bodhi, Rahul
  • Gupta, Bhumika

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.

Suggested Citation

  • Singh, Nidhi & Jain, Monika & Kamal, Muhammad Mustafa & Bodhi, Rahul & Gupta, Bhumika, 2024. "Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:tefoso:v:198:y:2024:i:c:s0040162523006522
    DOI: 10.1016/j.techfore.2023.122967
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523006522
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122967?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    2. Jussupow, Ekaterina & Spohrer, Kai & Heinzl, Armin & Gawlitza, Joshua, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 137446, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    4. Magda Hercheui & Gianluca Mech, 2021. "Factors Affecting The Adoption Of Artificial Intelligence In Healthcare," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 15(1), pages 77-88.
    5. Sipior, Janice C., 2020. "Considerations for development and use of AI in response to COVID-19," International Journal of Information Management, Elsevier, vol. 55(C).
    6. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    7. Lee, Sang M. & Lee, DonHee, 2021. "Opportunities and challenges for contactless healthcare services in the post-COVID-19 Era," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Siala, Haytham & Wang, Yichuan, 2022. "SHIFTing artificial intelligence to be responsible in healthcare: A systematic review," Social Science & Medicine, Elsevier, vol. 296(C).
    9. Bamel, Umesh & Talwar, Shalini & Pereira, Vijay & Corazza, Laura & Dhir, Amandeep, 2023. "Disruptive digital innovations in healthcare: Knowing the past and anticipating the future," Technovation, Elsevier, vol. 125(C).
    10. Gruetzemacher, Ross & Dorner, Florian E. & Bernaola-Alvarez, Niko & Giattino, Charlie & Manheim, David, 2021. "Forecasting AI progress: A research agenda," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    11. Du, Shuili & Xie, Chunyan, 2021. "Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities," Journal of Business Research, Elsevier, vol. 129(C), pages 961-974.
    12. Aarthi Raghavan & Mehmet Akif Demircioglu & Araz Taeihagh, 2021. "Public Health Innovation through Cloud Adoption: A Comparative Analysis of Drivers and Barriers in Japan, South Korea, and Singapore," IJERPH, MDPI, vol. 18(1), pages 1-30, January.
    13. Lee, Changhun & Lim, Chiehyeon, 2021. "From technological development to social advance: A review of Industry 4.0 through machine learning," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    14. Dicuonzo, Grazia & Donofrio, Francesca & Fusco, Antonio & Shini, Matilda, 2023. "Healthcare system: Moving forward with artificial intelligence," Technovation, Elsevier, vol. 120(C).
    15. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl & Joshua Gawlitza, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Information Systems Research, INFORMS, vol. 32(3), pages 713-735, September.
    16. He, Wu & Zhang, Zuopeng (Justin) & Li, Wenzhuo, 2021. "Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic," International Journal of Information Management, Elsevier, vol. 57(C).
    17. Cubric, Marija, 2020. "Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study," Technology in Society, Elsevier, vol. 62(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kahouli, Bassem & Omri, Anis & Afi, Hatem, 2024. "Technological innovations and health performance: Effects and transmission channels," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    2. Issa, Helmi & Jaber, Jad & Lakkis, Hussein, 2024. "Navigating AI unpredictability: Exploring technostress in AI-powered healthcare systems," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    3. Singh, Kuldeep & Chatterjee, Sheshadri & Mariani, Marcello, 2024. "Applications of generative AI and future organizational performance: The mediating role of explorative and exploitative innovation and the moderating role of ethical dilemmas and environmental dynamis," Technovation, Elsevier, vol. 133(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christoph Riedl & Eric Bogert, 2024. "Effects of AI Feedback on Learning, the Skill Gap, and Intellectual Diversity," Papers 2409.18660, arXiv.org.
    2. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    3. Kevin Bauer & Andrej Gill, 2024. "Mirror, Mirror on the Wall: Algorithmic Assessments, Transparency, and Self-Fulfilling Prophecies," Information Systems Research, INFORMS, vol. 35(1), pages 226-248, March.
    4. Mi, Yunlong & Wang, Zongrun & Quan, Pei & Shi, Yong, 2024. "A semi-supervised concept-cognitive computing system for dynamic classification decision making with limited feedback information," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1123-1138.
    5. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    6. Prikshat, Verma & Islam, Mohammad & Patel, Parth & Malik, Ashish & Budhwar, Pawan & Gupta, Suraksha, 2023. "AI-Augmented HRM: Literature review and a proposed multilevel framework for future research," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    7. Goutier, Marc & Diebel, Christopher & Adam, Martin & Benlian, Alexander, 2024. "Proactive and Reactive Help from Intelligent Agents in Identity-Relevant Tasks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142985, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Roppelt, Julia Stefanie & Kanbach, Dominik K. & Kraus, Sascha, 2024. "Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors," Technology in Society, Elsevier, vol. 76(C).
    9. Di Vaio, Assunta & Hassan, Rohail & Alavoine, Claude, 2022. "Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    10. Erdem Dogukan Yilmaz & Christian Peukert, 2024. "Who Benefits from AI? Project-Level Evidence on Labor Demand, Operations and Profitability," CESifo Working Paper Series 11321, CESifo.
    11. Haque, AKM Bahalul & Islam, A.K.M. Najmul & Mikalef, Patrick, 2023. "Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    12. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    13. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).
    14. Nasir, Osama & Javed, Rana Tallal & Gupta, Shivam & Vinuesa, Ricardo & Qadir, Junaid, 2023. "Artificial intelligence and sustainable development goals nexus via four vantage points," Technology in Society, Elsevier, vol. 72(C).
    15. Kevin Bauer & Moritz von Zahn & Oliver Hinz, 2023. "Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing," Information Systems Research, INFORMS, vol. 34(4), pages 1582-1602, December.
    16. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    17. Iva Gregurec & Martina Tomičić Furjan & Katarina Tomičić-Pupek, 2021. "The Impact of COVID-19 on Sustainable Business Models in SMEs," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    18. Tinglong Dai & Sridhar Tayur, 2022. "Designing AI‐augmented healthcare delivery systems for physician buy‐in and patient acceptance," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4443-4451, December.
    19. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    20. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:198:y:2024:i:c:s0040162523006522. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.