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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM41811
Volume:
9 |
2 |
Feb 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Artificial Intelligence (AI) has emerged as a transformative force across industries, yet concerns regarding its ethical implications and long-term societal impact remain prevalent. OpenAI, a leading AI research entity, sought to balance profit motives with public welfare by adopting a unique corporate governance model—a hybrid structure that combines elements of a non-profit and a capped-profit entity. However, recent events, including the abrupt removal and subsequent reinstatement of CEO Sam Altman, have exposed significant flaws in this governance framework. This paper critically examines OpenAI’s corporate governance model against conventional U.S. corporate governance norms and the principles outlined in the Indian Companies Act, 2013. It evaluates the structural motivations behind OpenAI’s governance experiment, identifies the shortcomings that led to internal instability, and discusses potential remedies. Key criticisms include the unchecked power of independent directors, the failure to adequately safeguard investor interests, and the inability to prevent informal corporate power from influencing decision-making. Furthermore, the study explores the feasibility of replicating OpenAI’s governance model within the Indian legal landscape, analysing its compatibility with Section 8 companies and fiduciary obligations under Indian corporate law. By applying a pragmatist paradigm and leveraging qualitative analysis, this paper argues that OpenAI’s governance structure, while innovative, ultimately failed to insulate the organization from external pressures or ensure AI safety. The findings suggest that sustainable AI governance requires a more balanced approach—one that integrates investor accountability, external scrutiny, and legally enforceable commitments to ethical AI development.
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Publication Date
2/24/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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