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Per-claim provenance."}],"not_medical_advice":true},"slug":"proven-work-evidence-law-case","title":"AI output is entering court — the evidence rules being drafted demand the record proven work keeps","register":"standard","tags":[],"updated_at":"2026-08-03T18:23:19.696Z","body_excerpt":"*When output from an AI system is offered as evidence in an American court, what must its proponent bring? The federal rule-writers are answering that in public right now, in the agenda books of the Advisory Committee on Evidence Rules. This page states the leading academic framework precisely, quotes the rule proposals verbatim from the primary sources, marks exactly where the rulemaking stands, and shows the one working object — the proven work object defined at [[proven-work]] — that already supplies the per-instance reliability record the drafts demand. No legal background is assumed.*\n\n## The problem the rules answer\n\nRule 901(a) of the Federal Rules of Evidence says that to authenticate an item, the proponent must produce \"evidence sufficient to support a finding that the item is what the proponent claims it is.\" For a photograph, a witness who was there can say so. For AI output — a chatbot transcript, a machine-drafted report, a synthesized voice recording — no human can say it from personal knowledge, because no human produced the thing. The rules were written for a world in which every exhibit had a person behind it.\n\nThe gap splits in two. **Acknowledged** AI-generated evidence: both sides know the item came from an AI system; the fight is whether the system is reliable enough for its output to be trusted in this case. **Unacknowledged** AI-generated evidence: one side claims an ordinary-looking recording or image is a deepfake; the fight is who must prove what, to what standard, before the jury sees it.\n\n## The framework: Grimm, Grossman & Cormack (2021)\n\nThe anchor text is \"Artificial Intelligence as Evidence,\" 19 Nw. J. Tech. & Intell. Prop. 9 (2021), by three authors, and all three matter: Judge Paul W. Grimm, then a sitting U.S. District Judge in Maryland (on the federal bench 1997–2022, now at Duke Law); Maura R. Grossman, a research professor of computer science at the University of Waterloo who is also a lawyer and a working e-discovery special master; and Gordon V. Cormack, professor emeritus of computer science at Waterloo. It is the most-cited treatment of AI evidence in the legal literature.\n\nIts operative contribution is six threshold questions a lawyer or judge confronting AI evidence should work through, summarized in the Mississippi Law Journal:\n\n1. What problem was the AI created to solve — to assess accuracy of output, reliability, and whether its use conforms to its purpose?\n2. How was the AI developed, and by whom — to evaluate the competence, biases, and motivations of the developers?\n3. Was the validity and reliability of the AI sufficiently tested, and under what testing protocols?\n4. Is the manner in which the AI operates explainable, so it can be understood by counsel, the court, and the jury and validated under the rules of evidence?\n5. What are the risks of harm if AI evidence of uncertain trustworthiness is admitted?\n6. Timing — given their complexity, these issues should be resolved pretrial where possible.\n\n## The two rule proposals\n\nGrimm and Grossman carried two amendment proposals to the Advisory Committee on Evidence Rules; the committee's October 2023 agenda book prints the first verbatim. Amended Rule 901(b)(9) would read:\n\n> (9) Evidence about a Process or System. For an item generated by a process or system: (A) evidence describing it and showing that it produces a reliable result; and (B) if the proponent concedes that — or the proponent provides a factual basis for suspecting that — the item was generated by artificial intelligence, additional evidence that: (i) describes the software or program that was used; and (ii) shows that it produced reliable results **in this instance**.\n\nThat is the acknowledged track. The unacknowledged track is a proposed new Rule 901(c) for potential deepfakes: the opponent must first supply evidence sufficient to support a jury finding of fabrication (Rule 104(b)); only then does the burden shift to the proponent to establish genuineness by a pre","ranking":"safety-first (interaction_risk/limitations), then quote-gated effective_weight","claims":[{"id":"c1","text":"Federal Rule of Evidence 901(a) requires the proponent to produce evidence sufficient to support a finding that the item is what the proponent claims it is — for AI output, no witness was there.","tier":"primary","section":"The problem the rules answer","interaction_risk":false,"status":"active","source_ids":["s1"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c2","text":"The Advisory Committee's 901(b)(9) proposal (October 2023 agenda book) would demand evidence describing the process and showing it produces a valid and reliable result — in this instance.","tier":"primary","section":"The rule proposals","interaction_risk":false,"status":"active","source_ids":["s2"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c3","text":"The November 2025 agenda book carries the Rule 707 text and vote for machine-generated evidence, with draft 901(c) held in reserve.","tier":"primary","section":"The rule proposals","interaction_risk":false,"status":"active","source_ids":["s3"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c4","text":"Grimm, Grossman and Cormack's framework makes per-instance reliability — not general system reputation — the operative question for AI evidence.","tier":"primary","section":"The framework","interaction_risk":false,"status":"active","source_ids":["s1","s8"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false},{"id":"c5","text":"The record the drafts demand already has regulatory ancestors: FDA Part 11 audit trails (1997) and SEC Rule 613 order-lifecycle records — kept for the agency, not the courtroom stranger.","tier":"primary","section":"The lineage","interaction_risk":false,"status":"active","source_ids":["s6","s7"],"retracted_at":null,"retraction_reason":null,"challenged_by":[],"effective_weight":0.1,"quote_gated":false}],"sources":[{"id":"s1","url":"https://scholarlycommons.law.northwestern.edu/njtip/vol19/iss1/2/","title":"Grimm, Grossman & Cormack, 'Artificial Intelligence as Evidence' (2021)","claim_ids":[],"hash":"474f5881463a771d2addcafd9c14e6a698dda5a8cb743fc0c03a4d82174e3d42"},{"id":"s2","url":"https://www.uscourts.gov/sites/default/files/2023-10_evidence_rules_agenda_book_final_10-5.pdf","title":"October 2023 Evidence Rules agenda book — the 901(b)(9) proposal","claim_ids":[],"hash":"cb85d89df4b3a2bd46b40c2f93f07622be69a7b1f0f9f9015510928ad0a168c5"},{"id":"s3","url":"https://www.uscourts.gov/sites/default/files/document/2025-11_evidence_rules_commitee_agenda_book_final.pdf","title":"November 2025 agenda book — Rule 707 text and vote, draft 901(c) in reserve","claim_ids":[],"hash":"4d460efc4c8b7213c5150bf21f2849fd7220a37cd181a443b2eee02154523eaa"},{"id":"s4","url":"https://www.mississippilawjournal.org/wp-content/uploads/2024/07/93.5-Miss.-L.J.-1005_Losavio_FINAL.pdf","title":"Losavio, 93 Miss. 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