IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v25y2023i3d10.1007_s10796-022-10276-3.html
   My bibliography  Save this article

An Assessment of the Barriers Impacting Responsible Artificial Intelligence

Author

Listed:
  • Mohammad I. Merhi

    (Indiana University South Bend)

Abstract

Responsible Artificial Intelligence (AI) has recently gained a lot of attention, especially in the last few years. Scholars have conducted systematic literature reviews to gain more knowledge about responsible AI. However, no study has collected and evaluated the most significant barriers to responsible AI. We filled this gap in the literature by identifying eleven barriers and categorized them, using the Technology-Organization-Environment framework, into three categories. We collected data from seven experts and used the analytical hierarchy process to evaluate the importance of the barriers. The results indicated that technology, as a category, is the most important. The findings also recommended that data quality is the most vital among all eleven barriers. We offered eleven propositions as a theoretical contribution for future researchers in terms of conceptual development. We discussed the implications of the findings for research and practice.

Suggested Citation

  • Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:3:d:10.1007_s10796-022-10276-3
    DOI: 10.1007/s10796-022-10276-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-022-10276-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-022-10276-3?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. Nishant, Rohit & Kennedy, Mike & Corbett, Jacqueline, 2020. "Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda," International Journal of Information Management, Elsevier, vol. 53(C).
    2. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    3. Thomas L. Saaty, 1986. "Axiomatic Foundation of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 32(7), pages 841-855, July.
    4. STAHL, Bernd Carsten, 2022. "Responsible innovation ecosystems: Ethical implications of the application of the ecosystem concept to artificial intelligence," International Journal of Information Management, Elsevier, vol. 62(C).
    5. Borges, Aline F.S. & Laurindo, Fernando J.B. & Spínola, Mauro M. & Gonçalves, Rodrigo F. & Mattos, Claudia A., 2021. "The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions," International Journal of Information Management, Elsevier, vol. 57(C).
    6. Anol Bhattacherjee & Neset Hikmet, 2007. "Physicians' resistance toward healthcare information technology: a theoretical model and empirical test," European Journal of Information Systems, Taylor & Francis Journals, vol. 16(6), pages 725-737, December.
    7. Teo, Thompson S.H. & Lin, Sijie & Lai, Kee-hung, 2009. "Adopters and non-adopters of e-procurement in Singapore: An empirical study," Omega, Elsevier, vol. 37(5), pages 972-987, October.
    8. James Zou & Londa Schiebinger, 2018. "AI can be sexist and racist — it’s time to make it fair," Nature, Nature, vol. 559(7714), pages 324-326, July.
    9. Effy Vayena & Alessandro Blasimme & I Glenn Cohen, 2018. "Machine learning in medicine: Addressing ethical challenges," PLOS Medicine, Public Library of Science, vol. 15(11), pages 1-4, November.
    10. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    11. Bernd W. Wirtz & Jan C. Weyerer & Carolin Geyer, 2019. "Artificial Intelligence and the Public Sector—Applications and Challenges," International Journal of Public Administration, Taylor & Francis Journals, vol. 42(7), pages 596-615, May.
    Full references (including those not matched with items on IDEAS)

    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. Issa Helmi & Lakkis Hussein & Dakroub Roy & Jaber Jad, 2023. "Examining User Engagement and Experience in Agritech," International Journal of Contemporary Management, Sciendo, vol. 59(2), pages 17-32, June.
    2. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    3. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
    4. Nam, Jinyoung & Kim, Junghwan & Jung, Yoonhyuk, 2023. "Understandings of the AI business ecosystem in South Korea: AI startups' perspective," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278005, International Telecommunications Society (ITS).
    5. Abou-Foul, Mohamad & Ruiz-Alba, Jose L. & López-Tenorio, Pablo J., 2023. "The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 157(C).
    6. Athanasios Polyportis & Nikolaos Pahos, 2024. "Navigating the perils of artificial intelligence: a focused review on ChatGPT and responsible research and innovation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    7. René Riedl, 2022. "Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2021-2051, December.
    8. Alexandru Constantin Ciobanu & Gabriela Meè˜Nièšä‚, 2021. "Ai Ethics In Business €“ A Bibliometric Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 28, pages 169-202, December.
    9. 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).
    10. Banai, Reza, 2010. "Evaluation of land use-transportation systems with the Analytic Network Process," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 85-112.
    11. Stefan Feuerriegel & Mateusz Dolata & Gerhard Schwabe, 2020. "Fair AI," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 379-384, August.
    12. Guh, Yuh-Yuan, 1997. "Introduction to a new weighting method -- Hierarchy consistency analysis," European Journal of Operational Research, Elsevier, vol. 102(1), pages 215-226, October.
    13. Cui, Ye & E, Hanyu & Pedrycz, Witold & Fayek, Aminah Robinson, 2022. "A granular multicriteria group decision making for renewable energy planning problems," Renewable Energy, Elsevier, vol. 199(C), pages 1047-1059.
    14. Xiaoxia Li, 2022. "Research on the Development Level of Rural E-Commerce in China Based on Analytic Hierarchy and Systematic Clustering Method," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    15. Michael Vössing & Niklas Kühl & Matteo Lind & Gerhard Satzger, 2022. "Designing Transparency for Effective Human-AI Collaboration," Information Systems Frontiers, Springer, vol. 24(3), pages 877-895, June.
    16. Alim Al Ayub Ahmed & Sugandha Agarwal & IMade Gede Ariestova Kurniawan & Samuel P. D. Anantadjaya & Chitra Krishnan, 2022. "Business boosting through sentiment analysis using Artificial Intelligence approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 699-709, March.
    17. Feras A. Batarseh & Munisamy Gopinath & Anderson Monken, 2020. "Artificial Intelligence Methods for Evaluating Global Trade Flows," International Finance Discussion Papers 1296, Board of Governors of the Federal Reserve System (U.S.).
    18. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    19. Danijela Tuljak-Suban & Patricija Bajec, 2022. "A Hybrid DEA Approach for the Upgrade of an Existing Bike-Sharing System with Electric Bikes," Energies, MDPI, vol. 15(21), pages 1-23, October.
    20. Formaneck, Steven D. & Cozzarin, Brian P., 2013. "Technology adoption and training practices as a constrained shortest path problem," Omega, Elsevier, vol. 41(2), pages 459-472.

    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:spr:infosf:v:25:y:2023:i:3:d:10.1007_s10796-022-10276-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.