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Artificial Intelligence: impacts of explainability on value creation and decision making

Author

Listed:
  • Taoufik El Oualidi

    (IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])

Abstract

Over the last few years, companies' investment in new AI systems has seen a strong and constant progression. However, except for the Big Tech, the use of AI is still marginal at this stage, and seems to spark cautiousness and apprehension. A potential reason for this hesitation may be linked to a lack of trust related in particular to the so-called black box AI technologies such as deep learning. This is why our research objective is to explore the effects of explainability on trust in these new AI-based digital systems with which the users can either interact or directly accept its results in case of fully autonomous system. More precisely, in the perspective of an industrialized use of AI, we would like to study the role of explainability for stakeholders in the decision-making process as well as in value creation.

Suggested Citation

  • Taoufik El Oualidi, 2022. "Artificial Intelligence: impacts of explainability on value creation and decision making," Post-Print hal-04103938, HAL.
    • Handle: RePEc:hal:journl:hal-04103938
    DOI: 10.1007/978-3-031-05760-1_57
    as

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