IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v25y2023i1d10.1007_s10796-022-10352-8.html
   My bibliography  Save this article

The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge

Author

Listed:
  • Antoine Harfouche

    (Paris Nanterre University)

  • Bernard Quinio

    (Paris Nanterre University)

  • Mario Saba

    (Business School Lausanne)

  • Peter Bou Saba

    (Léonard de Vinci Pôle Universitaire)

Abstract

Artificial intelligence (AI) has increased the ability of organizations to accumulate tacit and explicit knowledge to inform management decision-making. Despite the hype and popularity of AI, there is a noticeable scarcity of research focusing on AI's potential role in enriching and augmenting organizational knowledge. This paper develops a recursive theory of knowledge augmentation in organizations (the KAM model) based on a synthesis of extant literature and a four-year revised canonical action research project. The project aimed to design and implement a human-centric AI (called Project) to solve the lack of integration of tacit and explicit knowledge in a scientific research center (SRC). To explore the patterns of knowledge augmentation in organizations, this study extends Nonaka's SECI (socialization, externalization, combination, and internalization) model by incorporating the human-in-the-loop Informed Artificial Intelligence (IAI) approach. The proposed design offers the possibility to integrate experts' intuition and domain knowledge in AI in an explainable way. The findings show that organizational knowledge can be augmented through a recursive process enabled by the design and implementation of human-in-the-loop IAI. The study has important implications for research and practice.

Suggested Citation

  • Antoine Harfouche & Bernard Quinio & Mario Saba & Peter Bou Saba, 2023. "The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge," Information Systems Frontiers, Springer, vol. 25(1), pages 55-70, February.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:1:d:10.1007_s10796-022-10352-8
    DOI: 10.1007/s10796-022-10352-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-022-10352-8
    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/s10796-022-10352-8?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. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    2. Shrestha, Yash Raj & Krishna, Vaibhav & von Krogh, Georg, 2021. "Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges," Journal of Business Research, Elsevier, vol. 123(C), pages 588-603.
    3. Ikujiro Nonaka, 1994. "A Dynamic Theory of Organizational Knowledge Creation," Organization Science, INFORMS, vol. 5(1), pages 14-37, February.
    4. Sanjay K. Sahay & Nihita Goel & Murtuza Jadliwala & Shambhu Upadhyaya, 2021. "Advances in Secure Knowledge Management in the Artificial Intelligence Era," Information Systems Frontiers, Springer, vol. 23(4), pages 807-810, August.
    5. 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).
    6. Popadiuk, Silvio & Choo, Chun Wei, 2006. "Innovation and knowledge creation: How are these concepts related?," International Journal of Information Management, Elsevier, vol. 26(4), pages 302-312.
    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. Denis Dennehy & Anastasia Griva & Nancy Pouloudi & Yogesh K. Dwivedi & Matti Mäntymäki & Ilias O. Pappas, 2023. "Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI," Information Systems Frontiers, Springer, vol. 25(1), pages 1-7, February.

    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. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Chen, Kuan-Yang & Huan, Tzung-Cheng, 2022. "Explore how SME family businesses of travel service industry use market knowledge for product innovation," Journal of Business Research, Elsevier, vol. 151(C), pages 519-530.
    3. Venkitachalam, Krishna & Willmott, Hugh, 2017. "Strategic knowledge management—Insights and pitfalls," International Journal of Information Management, Elsevier, vol. 37(4), pages 313-316.
    4. 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.
    5. Shivam Gupta & Sachin Modgil & Choong-Ki Lee & Uthayasankar Sivarajah, 2023. "The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry," Information Systems Frontiers, Springer, vol. 25(3), pages 1179-1195, June.
    6. Tyagi, Satish & Cai, Xianming & Yang, Kai & Chambers, Terrence, 2015. "Lean tools and methods to support efficient knowledge creation," International Journal of Information Management, Elsevier, vol. 35(2), pages 204-214.
    7. Samuli Laato & Matti Mäntymäki & A. K.M. Najmul Islam & Sami Hyrynsalmi & Teemu Birkstedt, 2023. "Trends and Trajectories in the Software Industry: implications for the future of work," Information Systems Frontiers, Springer, vol. 25(2), pages 929-944, April.
    8. Brea, Edgar & Ford, Jerad A., 2023. "No silver bullet: Cognitive technology does not lead to novelty in all firms," Technovation, Elsevier, vol. 122(C).
    9. Jurado Zambrano, Diego Armando & Mosquera Carrascal, Adriana & Espinal Marulanda, John Jairo, 2023. "Relación entre la gestión del conocimiento y la innovación en el sector público: una revisión de literatura," Revista Tendencias, Universidad de Narino, vol. 24(2), pages 197-230, July.
    10. Balakrishnan, Janarthanan & Abed, Salma S. & Jones, Paul, 2022. "The role of meta-UTAUT factors, perceived anthropomorphism, perceived intelligence, and social self-efficacy in chatbot-based services?," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    11. Lu, Jinfeng & Dimov, Dimo, 2023. "A system dynamics modelling of entrepreneurship and growth within firms," Journal of Business Venturing, Elsevier, vol. 38(3).
    12. Olunifesi Adekunle Suraj, 2016. "Managing Telecommunications for Development: An Analysis of Intellectual Capital in Nigerian Telecommunication Industry," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 1-30, March.
    13. Soufiane Mezzourh & Walid A Nakara, 2009. "Governance and innovation : A Knowledge-based approach [La gouvernance de l'innovation : une approche par la connaissance]," Post-Print halshs-01955966, HAL.
    14. M. Max Evans & Ilja Frissen & Anthony K. P. Wensley, 2018. "Organisational Information and Knowledge Sharing: Uncovering Mediating Effects of Perceived Trustworthiness Using the PROCESS Approach," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-29, March.
    15. Chris Kimble & José Braga Vasconcelos & Álvaro Rocha, 2016. "Competence management in knowledge intensive organizations using consensual knowledge and ontologies," Information Systems Frontiers, Springer, vol. 18(6), pages 1119-1130, December.
    16. Maurizio Zollo, 1998. "Strategies or Routines ? Knowledge Codification, Path-Dependence and the Evolution of Post-Acquisition Integration Practices in the U.S. Banking Industry," Center for Financial Institutions Working Papers 97-10, Wharton School Center for Financial Institutions, University of Pennsylvania.
    17. Duniesky Feitó Madrigal & Alejandro Mungaray Lagarda & Michelle Texis Flores, 2016. "Factors associated with learning management in Mexican micro-entrepreneurs," Estudios Gerenciales, Universidad Icesi, vol. 32(141), pages 381-386, December.
    18. Yildiz, H. Emre & Murtic, Adis & Zander, Udo, 2024. "Re-conceptualizing absorptive capacity: The importance of teams as a meso-level context," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    19. David Vallat, 2015. "Une alternative au dualisme État-Marché : l’économie collaborative, questions pratiques et épistémologiques," Working Papers halshs-01249308, HAL.
    20. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.

    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:1:d:10.1007_s10796-022-10352-8. 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.