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An integrative theoretical framework for responsible artificial intelligence
[Un cadre théorique intégratif pour une intelligence artificielle responsable]

Author

Listed:
  • Ahmad Haidar

    (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], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])

Abstract

The rapid integration of Artificial Intelligence (AI) into various sectors has yielded significant benefits, such as enhanced business efficiency and customer satisfaction, while posing challenges, including privacy concerns, algorithmic bias, and threats to autonomy. In response to these multifaceted issues, this study proposes a novel integrative theoretical framework for Responsible AI (RAI), which addresses four key dimensions: technical, sustainable development, responsible innovation management, and legislation. The responsible innovation management and the legal dimensions form the foundational layers of the framework. The first embeds elements like anticipation and reflexivity into corporate culture, and the latter examines AI-specific laws from the European Union and the United States, providing a comparative perspective on legal frameworks governing AI. The study's findings may be helpful for businesses seeking to responsibly integrate AI, developers who focus on creating responsibly compliant AI, and policymakers looking to foster awareness and develop guidelines for RAI.

Suggested Citation

  • Ahmad Haidar, 2024. "An integrative theoretical framework for responsible artificial intelligence [Un cadre théorique intégratif pour une intelligence artificielle responsable]," Post-Print hal-04364949, HAL.
    • Handle: RePEc:hal:journl:hal-04364949
    DOI: 10.4018/ijdsgbt.334844
    Note: View the original document on HAL open archive server: https://hal.science/hal-04364949v1
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