August 1, 2025IAES International Journal of Artificial IntelligenceOpen Access

Unpacking the drivers of artificial intelligence regulation: driving forces and critical controls in artificial intelligence governance

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Effective governance requires a nuanced approach to address challenges in artificial intelligence regulation, supporting balanced innovation.
Data governance and human oversight serve as critical controls in AI regulatory frameworks, guiding ethical and practical implementation.
Market-driven, state-driven, and rights-driven regulatory approaches reveal differing motivations that shape AI governance models and their effectiveness.
International cooperation is emphasized as a necessary aspect to tackle the rapid technological changes affecting governance structures.

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Implication

This article reveals essential controls and driving forces behind artificial intelligence regulation, suggesting international cooperation is vital for effective governance.

Cite This Study

Atoum et al. (2025) studied this question.

synapsesocial.com/papers/68af782c7567bf4f94ff094e https://doi.org/10.11591/ijai.v14.i4.pp2655-2666

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Implication

This article reveals essential controls and driving forces behind artificial intelligence regulation, suggesting international cooperation is vital for effective governance.

Unpacking the drivers of artificial intelligence regulation: driving forces and critical controls in artificial intelligence governance

Key Points

Discussion

Implication

Cite This Study

Unpacking the drivers of artificial intelligence regulation: driving forces and critical controls in artificial intelligence governance

Key Points

Discussion

Implication

Cite This Study

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