Should Artificial Intelligence Governance be Centralised? Design Lessons from History
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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.
Original language | English |
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Title of host publication | AIES '20: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society |
Number of pages | 7 |
Publisher | Association for Computing Machinery |
Publication date | Feb 2020 |
Pages | 228-234 |
ISBN (Electronic) | 9781450371100 |
DOIs | |
Publication status | Published - Feb 2020 |
Bibliographical note
Peter Cihon, Matthijs M. Maas, and Luke Kemp. 2020. Should Artificial Intelligence Governance be Centralised? Design Lessons from History. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES ’20). Association for Computing Machinery, New York, NY, USA, 228–234. DOI:https://doi.org/10.1145/3375627.3375857
Links
- https://arxiv.org/abs/2001.03573
Final published version
ID: 241310794