Tools for exploring the unknowable : intuition vs. artificial intelligence

Tools

Dörfler, Viktor and Bas, Alina (2020) Tools for exploring the unknowable : intuition vs. artificial intelligence. In: Academy of Management Annual Conference 2020, 2020-08-07 - 2020-08-11, Vancouver.

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Abstract

Our inquiry began by attempting to understand whether there are contexts in which human intuition consistently outperforms Artificial Intelligence (AI) in producing successful pathways for action. In order to figure this out, in this paper we distinguish between known, unknown (but knowable), and unknowable situations, using the Knightian uncertainty as our departure point. It appears that in the known realm, AI can outperform intuition, if used properly, while in the unknown both intuition and AI can be useful. By processing the data and identifying patters, AI can make an unknown setting known. In the unknowable realm, intuition, particularly intuitive wayfinding, may be our most promising mode of exploring, as AI does not have enough to work with. Therefore, we are particularly curious to explore whether human intuition may be a better tool than AI for exploring the unknowable, and we suggest that this is where intuition research should focus in the near future.

ORCID iDs

Dörfler, Viktor ORCID logoORCID: https://orcid.org/0000-0001-8314-4162 and Bas, Alina;
  • Item type:Conference or Workshop Item(Paper)
    ID code:72610
    Dates:
    Date
    Event
    11 August 2020
    Published
    1 April 2020
    Accepted
    13 January 2020
    Submitted
    Notes:The 2020 physical meeting of the Academy of Management scheduled for 7-11 August 2020 in Vancouver has been cancelled due to the Coronavirus (COVID-19) pandemic. A 2020 virtual Annual Meeting is in development
    Subjects:Science > Mathematics > Computer software
    Department:Strathclyde Business School > Management Science
    Depositing user: Pure Administrator
    Date deposited:08 Jun 2020 14:59
    Last modified:11 Nov 2024 17:02
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/72610
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