AI safety is not merely about preventing harm; it involves a holistic understanding that encompasses trustworthiness, responsibility, and the complex interactions between technology and society. Participants in the AI value chain, which includes regulators, civil society, technologists, and other stakeholders, must confront the central question of whether safety is an isolated goal or a component of broader frameworks of trust and accountability…
The Socio-Technical Framework
The socio-technical perspective originated from early research focused on coal mining and labor studies in Britain…
- The social system surrounding technology: It is vital to assess AI systems not only for their technical specifications but also for their societal interactions.
- Problem selection: The widespread perception of AI as a panacea for complex global challenges must consider underlying socio-political dynamics.
- Power inequalities: Analyzing how power distribution affects AI’s lifecycle is crucial for ensuring inclusive governance.
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- Policy Design
- Societal Impact