Wulf A. Kaal (University of St. Thomas – School of Law (Minnesota)) has posted “AI Governance” on SSRN. Here is the abstract:
In the rapidly evolving landscape of artificial intelligence (AI), governance frameworks are increasingly pivotal. As AI technologies become more complex and integral to various sectors, the mechanisms to oversee and regulate these systems must evolve correspondingly. Traditional governance approaches often rely on static, predefined rules that may not adapt quickly enough to the pace of AI development or the nuanced challenges it presents. These conventional methods, largely reactive or fixed to ex-post solutions, are proving insufficient for the dynamic nature of AI technologies.
The proposed AI governance system integrates decentralized web3 community governance and federated communication platforms, forming a sophisticated framework for dynamic, anticipatory, and participatory oversight of AI development. Key components include a federated forum platform structured as a Weighted Directed Acyclic Graph (WDAG), and specialized smart contracts for managing tasks and validation. This setup not only facilitates real-time consensus-building and decision-making via web3 community governance but also supports a scalable, transparent communication network. Validation Pools and Reputation tokens within this framework play crucial roles in maintaining an updated and responsive governance system, reflecting the collective decisions and ethical standards of the community.
This system’s effectiveness is demonstrated through applications like medical diagnosis AI and autonomous driving AI, where each development stage is captured as vertices in the WDAG, documenting key compliance and operational metrics. Directed edges in this graph link these stages to relevant legal and ethical standards, with assigned weights emphasizing areas critical for compliance and safety. The dynamic nature of WDAG allows for continuous updates and integration of new regulations or ethical guidelines, ensuring AI governance remains current with technological and societal shifts. This model thus ensures AI systems are not only technologically advanced but also ethically aligned and legally compliant, effectively balancing innovation with responsible governance.