{"resourceId":"federal-evidence-committee-rule-707-901c-ai-oct15-20261007","versions":[{"version":"external-0ea8afa86fd006c13a9ae66287e29e5af94be7717a97d657e788258e60666135","resource":{"id":"federal-evidence-committee-rule-707-901c-ai-oct15-20261007","title":"Federal evidence rules committee heads into Oct. 15 with AI Rule 707 withdrawn for revision and the draft deepfake Rule 901(c) still unapproved, as DOJ calls 901(c) not ready","organization":"Advisory Committee on Evidence Rules, Judicial Conference of the United States","sector":"Courts / federal evidence rulemaking","geography":"United States (federal courts)","publishedAt":"Agenda book for the Oct. 15, 2026 meeting (file dated Sept. 23, 2026)","publicationDate":"2026-09-23","eventDate":"2026-10-15","sourceName":"U.S. Courts (uscourts.gov)","sourceLabel":"Advisory Committee on Evidence Rules agenda book, Oct. 15, 2026","sourceUrl":"https://www.uscourts.gov/sites/default/files/document/2026-10_evidence_rules_agenda_book_9-23_final.pdf","evidenceClass":"standards-guidance","outcomeClass":"emerging","topics":["governance-procurement","data-security","operating-model"],"finding":"The agenda book for the Oct. 15, 2026 Advisory Committee on Evidence Rules meeting states that the committee, after two hearings and more than 70 written comments, voted at its last meeting to withdraw proposed Rule 707 (machine-generated evidence offered without an expert) as published and submit a modified proposal for further study. It has also prepared but not finally approved a new Rule 901(c), under which an opponent must first produce evidence sufficient to support a finding that an item is a deepfake, after which the proponent must show it is more likely than not authentic. The committee will hear expert panels on both topics on Oct. 15. Draft May 2026 minutes reproduced in the book record DOJ's view that 901(c) is not ready for publication, that its notice provision would routinely be excused for criminal defendants, and that existing rules are adequate for deepfake claims.","sledRelevance":"Directly affects how police-generated AI outputs (transcripts, enhancements, analytics) and alleged deepfakes are admitted in criminal trials; state courts often follow federal evidence rule changes.","evidence":"Primary judicial rulemaking document: meeting agenda, reporter's memoranda and draft minutes. It records committee status and positions, not outcomes; the Oct. 15 decisions are not yet known.","architectureImplications":"Agencies that produce machine-generated evidence should expect expert-reliability scrutiny and should preserve inputs, model versions and processing logs to support it.","governanceImplications":"Rulemaking is deliberately slow: no AI-specific federal rule is in force, and courts continue to apply existing authentication and expert rules case by case.","securityPrivacyImplications":"Deepfake challenges put a premium on chain of custody and provenance records for body-camera, CCTV and digital evidence.","caveats":"Status as of the agenda book; the committee may change direction on Oct. 15. The DOJ position comes from draft minutes of the prior meeting. Publication date inferred from the file name. Federal rules do not bind state courts.","streamIds":["public-safety"],"roles":{"sales":"Sales framing: the federal evidence committee is not ready to write AI-specific rules, so admissibility of police AI outputs will be fought case by case. Discovery should ask agencies and prosecutors how they document AI-processed evidence and whether they have faced deepfake challenges. A bounded engagement is an evidence-provenance readiness review; do not claim a federal AI evidence rule is in force or imminent.","engineering":"Engineering framing: whatever the committee decides, machine-generated evidence will need a reliability foundation. Engineers should keep originals, log every AI transformation with model and version, hash media at capture and make processing reproducible. For deepfake defenses, provenance metadata from capture to court matters more than detection scores. Proof is a mock foundation package for one evidence type.","delivery":"Delivery framing: prosecutor and agency teams should prepare foundation templates for AI-processed evidence and a response playbook for deepfake claims. Ownership sits with prosecutors' offices and agency evidence units, with court liaisons tracking Oct. 15 outcomes. Risks include relying on proposals that change, uneven defense resources and losing originals."},"roleDetails":{"sales":{"customerProblem":"Agencies increasingly offer AI-processed evidence and face deepfake claims without a settled federal rule.","stakeholders":["Prosecutors' offices","Public defenders","Police evidence and digital forensics units","Court administrators","State evidence rule committees"],"discoveryQuestions":["Which evidence types are processed by AI before trial?","Are originals and processing logs preserved?","Have deepfake authenticity challenges arisen?","Who tracks federal and state evidence rule changes?"],"valueHypothesis":"Provenance and documentation practices reduce the risk of exclusion regardless of how Rules 707 and 901(c) end up.","potentialEngagement":"Evidence-provenance readiness review and foundation templates for one AI-processed evidence type.","unsupportedClaims":["That Rule 707 or 901(c) is in effect","Outcome of the Oct. 15 meeting","That detection tools settle authenticity","That state courts will adopt the rules"]},"engineering":{"fit":"Applies to any agency producing transcripts, enhancements, analytics or other machine outputs used as evidence.","architectureIntegration":"Capture devices, evidence management platforms and AI processing tools must preserve originals, hashes and transformation logs through to discovery.","prerequisites":["Hashing at ingest","Versioned AI processing logs","Retention of originals","Discovery export capability"],"constraints":["No AI-specific federal rule in force","State rules vary","Vendor tools may not expose model details","Defense access to methods"],"security":"Protect chain of custody with hashing and access logs; record who ran which model on which file.","proofOfValue":["Assemble a mock reliability foundation for an AI transcript","Verify hashes match from capture to export","Confirm originals are retained for all AI-processed files","Test whether vendor can provide method documentation"]},"delivery":{"work":"Build foundation templates and provenance practices for AI-processed evidence and a deepfake-challenge playbook.","dependencies":["Vendor documentation","Evidence platform logging","Prosecutor input","Oct. 15 committee outcome"],"ownership":"Prosecutors' offices and agency evidence units, with court liaison tracking rulemaking.","skillsAdoption":"Attorneys and analysts need training on reliability foundations and authenticity disputes.","governanceCheckpoints":["Review after Oct. 15 meeting","Policy on retaining originals","Annual review of rule changes"],"acceptanceCriteria":["Proposed: foundation template ready for each AI-processed evidence type","Proposed: 100% of AI-processed files retain original and hash","Proposed: playbook updated within 60 days of committee action"],"risks":["Rules change after templates are built","Vendors cannot document methods","Defense resource gaps","Loss of original media"]}},"retrievedAt":"2026-10-08T02:55:07Z","enrichedAt":"2026-10-08T02:59:04Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Prosecutors, defenders and lab analysts need training on AI evidence foundations; public defenders may lack forensic authentication resources.","procurementImplications":"Evidence tools that alter or analyze media should document methods and keep originals, because admissibility may hinge on explaining the process.","operatingModelImplications":"Agencies and prosecutors should plan for case-by-case reliability hearings rather than a bright-line rule in the near term.","sourceVerification":{"openedUrl":"https://www.uscourts.gov/sites/default/files/document/2026-10_evidence_rules_agenda_book_9-23_final.pdf","referenceExcerpt":"After review, the Committee at the last meeting voted to withdraw the proposed rule as issued for public comment","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}