Program Details
2026-10-28 12:00:00
Over 1,000+ webinars
Course Overview
2026-10-28 12:00:00
2h CLE Credits
Intermediate
2
12:00 pm - 1:00 pm ESTThis session examines proposed Federal Rule of Evidence 707, the first federal evidence rule written specifically for output generated by machines, as it is being redrafted. Published for public comment in August 2025 and drawing more than 70 written comments by the February 16, 2026, deadline, the rule was not advanced in its original form at the Advisory Committee’s May 7, 2026, meeting. The Committee instead narrowed the proposal from all “machine-generated evidence” to “artificial intelligence,” added guidance on reproducibility and independent evaluation, and set a mini-conference for October 15, 2026. Attorneys will learn what the revised proposal covers and excludes, how the Rule 702(a)–(d) reliability factors translate to a system whose credentials are training data rather than education and experience, and why the “simple scientific instruments” carve-out drew the criticism it did. Attendees will leave able to advise clients and try cases under the reasoning of Rule 707 today, using existing Rules 702, 703, and 901, before the rule is finalized.
Jonathan M. RedgraveBenjamin M. Redgrave 1:10 pm - 2:10 pm ESTThis session turns proposed Rule 707 into trial practice. Whether the rule is adopted in 2027 or later, the reliability showing it describes is the showing courts are already demanding: Kohls v. Ellison, Concord Music Group v. Anthropic, Matter of Weber, and Ferlito v. Harbor Freight together sketch what a judge will accept and what gets struck. Attorneys will learn how to assemble the foundation record for AI-derived evidence, including validation studies, published error rates, model and version control, training-data provenance, and vendor cooperation secured by contract before the dispute, and how to dismantle an opponent’s showing through operator and vendor discovery, black-box gap requests, and a targeted motion in limine. Attendees will leave with a foundation checklist, a machine-evidence discovery set, an in-limine framework, and the objection language that preserves the issue for appeal.
Jonathan M. RedgraveBenjamin M. RedgraveJonathan M. Redgrave is a Partner at Redgrave LLP, where he chairs the firm’s Executive Committee, and is one of the nation’s leading eDiscovery and Information Law attorneys. He represents Fortune 100 companies worldwide on discovery and information management challenges in complex litigation, particularly matters involving novel technologies. He is especially well suited to this program: he has taken part in rules reform efforts on the Federal Rules of Evidence, advises clients on the intersection of AI and machine learning with legal requirements, and is frequently retained as a testifying expert on the preservation, collection, and production of electronically stored information, bringing both a rulemaking perspective and a courtroom view of how electronic evidence is tested.
Benjamin M. Redgrave is Senior Counsel at Redgrave LLP in Chicago, with an extensive background in Information Law issues arising in complex civil litigation and corporate information management. He supports clients through every stage of discovery in complex matters, from preparing protective orders and ESI protocols to managing large-scale document review and production, drafting privilege logs, and handling exhibits and litigation support for jury trials. That hands-on work makes him a strong fit for this program’s trial-practice session: drafting ESI protocols, designing preservation strategies and legal holds, and helping defend spoliation motions are the building blocks of the foundation record and discovery plan that AI-generated evidence demands.
Jonathan M. Redgrave is a Partner at Redgrave LLP, where he chairs the firm’s Executive Committee, and is one of the nation’s leading eDiscovery and Information Law attorneys. He represents Fortune 100 companies worldwide on discovery and information management challenges in complex litigation, particularly matters involving novel technologies. He is especially well suited to this program: he has taken part in rules reform efforts on the Federal Rules of Evidence, advises clients on the intersection of AI and machine learning with legal requirements, and is frequently retained as a testifying expert on the preservation, collection, and production of electronically stored information, bringing both a rulemaking perspective and a courtroom view of how electronic evidence is tested.
Benjamin M. Redgrave is Senior Counsel at Redgrave LLP in Chicago, with an extensive background in Information Law issues arising in complex civil litigation and corporate information management. He supports clients through every stage of discovery in complex matters, from preparing protective orders and ESI protocols to managing large-scale document review and production, drafting privilege logs, and handling exhibits and litigation support for jury trials. That hands-on work makes him a strong fit for this program’s trial-practice session: drafting ESI protocols, designing preservation strategies and legal holds, and helping defend spoliation motions are the building blocks of the foundation record and discovery plan that AI-generated evidence demands.
Requirements
The Alabama State Bar MCLE Commission requires attorneys to complete 12 credits, including 1 ethics, by December 31 of each year. All credits must be reported by February 15 of the following year. A maximum of 12 credits, including 1 ethics credit, may be carried over for 1 year only.
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