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Combining Purpose-Based Governance and Regulation to Control Risks Associated with Generative Artificial Intelligence: An Analysis of OpenAI

Author

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  • Kevin Levillain

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Blanche Segrestin

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Armand Hatchuel

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Jérémy Lévêque

    (CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

The governance of artificial intelligence companies presents unprecedented challenges at the intersection of rapid innovation, systemic risks, and accountability. This conceptual article proposes a "dual regulation" model combining technical standards with mandated governance structures, analyzing OpenAI's governance evolution through the lens of the French société à mission framework. We trace OpenAI's trajectory from its 2015 nonprofit founding through its 2025 restructuring, which established a safety and security committee with extensive information rights and authority to halt model releases. Comparing this structure with the société à mission's mission committee reveals a distinctive regulatory approach: governance regulation that creates legally enforceable governance obligations rather than voluntary commitments. This model addresses key limitations in existing approaches by separating business oversight from mission accountability, combining expertise with operational access, and creating feedback loops between organizational learning and evolving regulatory standards. The analysis suggests implications for purpose-driven legal forms transitioning from voluntary to mandatory requirements in high-risk sectors.

Suggested Citation

  • Kevin Levillain & Blanche Segrestin & Armand Hatchuel & Jérémy Lévêque, 2026. "Combining Purpose-Based Governance and Regulation to Control Risks Associated with Generative Artificial Intelligence: An Analysis of OpenAI," Post-Print hal-05695853, HAL.
  • Handle: RePEc:hal:journl:hal-05695853
    Note: View the original document on HAL open archive server: https://minesparis-psl.hal.science/hal-05695853v1
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