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RECONCILING TRADE SECRETS AND AI PUBLIC TRANSPARENCY

Perry Keller & Tanya Aplin

Cambridge Law Journal2026https://doi.org/10.1017/s0008197325101086article
ABDC A*
Weight
0.50

Abstract

Poor public understanding of artificial intelligence (AI) systems has become a matter of acute concern. Even when lacking expert technical knowledge, there are good democratic, economic and other societal reasons for ensuring that the public right to know operates effectively in the AI era. Yet, the trade-secret claims of AI providers and deployers are widely seen as a potential barrier to information disclosure rights and duties, which has provoked calls for areas of significant public interest to be carved out from the protections of trade-secrets law. Such transparency carve-outs are, however, likely to lead to uncertainty, over-inclusion and ineffectiveness. In this article, we argue that the dynamic, public-driven character of the right to know can be better secured through third-party participation and public-interest stewardship innovations in AI transparency.

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https://doi.org/https://doi.org/10.1017/s0008197325101086

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@article{perry2026,
  title        = {{RECONCILING TRADE SECRETS AND AI PUBLIC TRANSPARENCY}},
  author       = {Perry Keller & Tanya Aplin},
  journal      = {Cambridge Law Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/s0008197325101086},
}

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RECONCILING TRADE SECRETS AND AI PUBLIC TRANSPARENCY

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.