Extract from the Monica Delgado’s article “AI-Generated Evidence in Litigation: New York State and Federal Perspectives”
Artificial intelligence (AI) is transforming litigation by introducing novel forms of evidence, from deepfake videos to AI-assisted financial analysis and algorithmic decision-making tools. These technologies challenge traditional admissibility standards, compelling courts to adapt evidentiary doctrines to ensure fairness and reliability.
For New York practitioners, mastering these evolving standards will be critical to both excluding unreliable AI-generated evidence or advocating for its admission while safeguarding valid claims.
As AI reshapes forensic analysis and judicial processes, understanding its evidentiary risks is essential for in-house and outside counsel in New York’s legal landscape.
This article examines New York State courts’ application of the Frye standard and procedural rules under the Civil Practice Law and Rules (CPLR), contrasted with federal courts’ reliance on Rules 702, 901, and 403 of the Federal Rules of Evidence (FRE).
Drawing on recent case law, including In the Matter of the Accounting by Weber,2024 NY Slip Op 24258 (Sur. Ct. 2024) and In the Matter of Armani V., 76 Misc. 3d 1213(A) (Fam. Ct. Kings Cnty. 2022), it highlights judicial struggles to integrate AI into evidentiary frameworks.
