Aiming for AI Interoperability: Challenges and Opportunities
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
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| _version_ | 1866908903126597632 |
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| author | Faveri, Benjamin Shank, Craig Whitt, Richard Dawson, Phillip |
| author_facet | Faveri, Benjamin Shank, Craig Whitt, Richard Dawson, Phillip |
| contents | The Aiming for AI Interoperability report investigates the ongoing challenge of achieving regulatory and technical AI interoperability as national and global AI governance efforts are proliferating. Here, technical interoperability is the ability of AI systems and networks to function together, and regulatory interoperability is the consistency and overlap of rules across jurisdictions and sectors. This report observes an accelerating trend that many governments, standard-setting bodies, and private firms are drafting, implementing, or passing new AI laws, policies, and frameworks at a staggering pace, resulting in fragmentation and confusion for both private and public sector actors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_14512 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Aiming for AI Interoperability: Challenges and Opportunities Faveri, Benjamin Shank, Craig Whitt, Richard Dawson, Phillip Computers and Society The Aiming for AI Interoperability report investigates the ongoing challenge of achieving regulatory and technical AI interoperability as national and global AI governance efforts are proliferating. Here, technical interoperability is the ability of AI systems and networks to function together, and regulatory interoperability is the consistency and overlap of rules across jurisdictions and sectors. This report observes an accelerating trend that many governments, standard-setting bodies, and private firms are drafting, implementing, or passing new AI laws, policies, and frameworks at a staggering pace, resulting in fragmentation and confusion for both private and public sector actors. |
| title | Aiming for AI Interoperability: Challenges and Opportunities |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2601.14512 |