The content presents a practical multilevel governance framework for autonomous and intelligent systems (AIS) to address the challenges posed by the rapid development and wide-scale deployment of these technologies. The framework consists of six linked decision-making levels, from the international and national policy-making levels to the individual developer level.
At each level, relevant actors are identified, and their decisions are guided by a variety of governance tools, including both hard law and soft law measures. The framework enables the establishment of formal governance mechanisms that connect the different levels, facilitating information flow, participation, and enforcement. This allows for comprehensive oversight of AIS development processes and risk assessment, as well as the evolution of governance tools in response to emerging challenges.
The framework incorporates principles of agile governance, such as iterative policymaking, regulatory sandboxes, and collaborative approaches. It also emphasizes the importance of bridging gaps between actors through shared understanding of terminology and concepts. Additional good practices, like structured risk assessment and foresight analysis, complement the framework to ensure effective and adaptive governance of AIS.
The application of the framework is demonstrated with a focus on the industry and standard-setting perspective, highlighting how it can be used to coordinate actors, tools, and mechanisms across the different levels to enable responsible AIS development and deployment.
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arxiv.org
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