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A Social Disruptiveness-Based Approach to AI Governance: Complementing the Risk-Based Approach of the AI Act
Samuela Marchiori1, Jeroen K G Hopster2, Anna Puzio3
1Department of Values, Technology and Innovation, Delft University of Technology, Delft, The Netherlands. s.marchiori@tudelft.nl.
Adequate AI governance needs more than risk assessment. A social disruptiveness-based approach, complementing the AI Act, addresses AI's broader societal and ethical impacts for better regulation.
Area of Science:
- Socio-technical systems
- AI governance
- Legal regulation
Background:
- The European Union's AI Act employs a risk-based approach to regulate AI systems.
- Existing AI governance frameworks may not fully capture the broader socio-technical implications of AI.
- Societal and ethical concerns arise from AI's disruptive potential beyond legal risk.
Purpose of the Study:
- To propose a 'social disruptiveness-based' approach to AI governance.
- To complement the AI Act's risk-based framework with a focus on societal impact.
- To enhance the governance of AI and other socially disruptive technologies.
Main Methods:
- Analysis of the AI Act's risk-based approach.
- Conceptualization of a social disruptiveness-based governance framework.
- Integration of legal, ethical, and human practice considerations.
Main Results:
- A dual approach combining risk-based and social disruptiveness-based assessments offers a more nuanced understanding of AI's societal impact.
- Social disruptiveness highlights impacts not easily addressed by legal regulation alone.
- This integrated approach can improve the governance of AI systems.
Conclusions:
- Effective AI governance requires addressing both legal risks and broader social disruptions.
- Integrating a social disruptiveness lens enhances the comprehensiveness of AI regulation.
- This framework supports adaptive governance in a dynamic socio-technical landscape.
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