Unverified50% confidenceOpinionExact time
Vendors building their own benchmarks has become the norm in AI releases, but credibility is disputed, because the test sets, scoring criteria and data distributions are not public, making external reproduction impossible.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedIsolated AI benchmark scores lacking third-party verification are almost without reference value; credible results require reproduction by independent organizations and traceable testing environments.74% similarVerifiedThe current AI safety assessment mechanism has yet to form a mandatory review process with legal binding force, and relies more on voluntary cooperation from vendors.73% similarUnverifiedRegarding the issue of agent identity verification and human authorization, no widely adopted open standard has yet emerged in the industry.73% similarUnverifiedPrivately held benchmark test data is not publicly available, meaning models cannot have seen the evaluation set during training, which more accurately reflects generalization ability and avoids leaderboard contamination.72% similarUnverifiedThe industry still lacks a unified safety evaluation standard for mental health AI, and the testing methods and disclosure levels of various products vary significantly.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1010981API
curl https://kongchang.com/api/v1/knowledge/claims/1010981MCP
get_claim(id=1010981)