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Governance Studies ›› 2023, Vol. 39 ›› Issue (5): 111-127.

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Practical Orientation of AI Governance Principles: Reliability, Accountability and Collaboration

Zhou Jiangwei, Zhao Yu   

  • Received:2023-05-09 Online:2023-09-15 Published:2023-11-01
  • Contact: Zhao Yu

Abstract:

Artificial intelligence has created an unavoidable governance gap as it is rapidly deployed and applied. In the quest for agile governance, many principles of a ‘soft law’ nature have emerged around the world. This study analyzed the governance principles announced in 88 texts and focused on their practical guidelines. We found that underneath their diverse claims, there was a common domain of questions. What technical characteristics should AI systems meet? How should we deal with the social consequences of this technology? What forms of social organization should be used for governance practices? Although tension remains among the claims of different principles around these questions, it is undeniable that a consensus-based framework for action has been developed in the field of AI governance. Based on our textual analysis, the principles can be grouped into three codes of practice: reliability, accountability and collaboration, which respond to each of these questions. The principles of reliability and accountability set two sets of complementary governance goals: constructing technology systems that meet expectations and address the social consequences of technology. The principle of collaboration explores what social action structures can support and guarantee the achievement of these goals. These goals form the framework for action on AI governance.

Key words: artificial intelligence, governance principles, reliability, accountability, collaboration

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