CYAIJan 10, 2020

Should Artificial Intelligence Governance be Centralised? Design Lessons from History

arXiv:2001.03573v158 citations
AI Analysis

This addresses the problem of designing effective international governance structures for AI, which is incremental as it builds on historical analogies without proposing a new solution.

The paper examines whether AI governance should be centralized internationally by analyzing historical regimes, concluding that centralization involves trade-offs and its success depends on specific design details, with fragmentation likely to persist for now.

Can effective international governance for artificial intelligence remain fragmented, or is there a need for a centralised international organisation for AI? We draw on the history of other international regimes to identify advantages and disadvantages in centralising AI governance. Some considerations, such as efficiency and political power, speak in favour of centralisation. Conversely, the risk of creating a slow and brittle institution speaks against it, as does the difficulty in securing participation while creating stringent rules. Other considerations depend on the specific design of a centralised institution. A well-designed body may be able to deter forum shopping and ensure policy coordination. However, forum shopping can be beneficial and a fragmented landscape of institutions can be self-organising. Centralisation entails trade-offs and the details matter. We conclude with two core recommendations. First, the outcome will depend on the exact design of a central institution. A well-designed centralised regime covering a set of coherent issues could be beneficial. But locking-in an inadequate structure may pose a fate worse than fragmentation. Second, for now fragmentation will likely persist. This should be closely monitored to see if it is self-organising or simply inadequate.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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