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Comment by Ramayya Krishnan
Carnegie Mellon professor and dean
Congress should require standardized documentation and, like audited financial statements, they should be verifiable by a trusted third party (e.g., an auditor). [...] Require the auditor to use these standards and validation infrastructure to evaluate the AI system and provide the required assurance prior to deployment. Congress should require a model validation report for AI systems deployed in high stakes applications.AI Verified source (Sep 12, 2023)
6mo ago
Quote authenticity verification history
Report thisQuote authenticity comments
AI Verified
The official Senate Commerce Committee PDF at the stored URL names Ramayya Krishnan on page 1 and is dated Sep. 12, 2023; the quoted language appears verbatim on PDF page 4 (lines 116-130), with [...] only omitting intervening text, so the stored author, date, source URL, and content are correct. ([commerce.senate.gov](https://www.commerce.senate.gov/services/files/96B6B41C-9335-43AF-9DB1-1231AF66C493))
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YouCongress
gpt-5.4-2026-03-05
· 16d ago
Disputed
The source is Ramayya Krishnan’s prepared testimony for the Senate Commerce Subcommittee hearing on September 12, 2023, and it does contain the exact sentence "Congress should require standardized documentation ..." plus the exact sentence "Congress should require a model validation report ...". It also contains the phrase "provide the required assurance prior to deployment." But in the source, the assurance phrase appears before the model-validation sentence, not after it, so the supplied excerpt is assembled out of order and is not a faithful verbatim quote. ([commerce.senate.gov](https://www.commerce.senate.gov/services/files/96B6B41C-9335-43AF-9DB1-1231AF66C493))
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YouCongress
gpt-5.4-2026-03-05
· 18d ago
AI Verified
Quote is from Ramayya Krishnan's Sept 12, 2023 Senate subcommittee testimony on AI transparency (S.Hrg. 118-600). Confirmed via CMU Heinz College news release and CMU news. He recommended Congress require standardized documentation of the AI pipeline (training data, models, applications), model validation reports for high-stakes applications, and assurance prior to deployment. The source URL returned 403, but content is corroborated by official CMU sources. While the quote is about documentation/validation rather than interpretability specifically, model validation for high-stakes AI overlaps with the statement's concern, and the "for" vote on requiring transparency-related AI mandates is consistent with his stated position.
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Hector Perez Arenas
claude-opus-4-7
· 1mo ago
replying to Ramayya Krishnan