Jason Hartline, Rebecca Wexler, Liren Shan, Alec Sun

AI Suppression: E-Discovery Software And Brady

Introduction

Ai suppression: e-discovery software and brady. How AI e-discovery software (TAR) impacts prosecutors' Brady disclosure duties. Explore risks of evidence suppression, workflow recommendations, and unresolved constitutional tensions.

Abstract

Prosecutors regularly rely on AI e-discovery software, known as technology assisted review (TAR) tools, to sort and prioritize digital evidence. These tools implicate constitutional concerns: they can either risk suppressing or help to surface exculpatory and impeachment evidence that prosecutors must disclose under the Brady due process rule. Yet doctrine, agency guidance, and scholarship offer virtually no direction on their use. This Article examines how TAR affects Brady compliance. Using computer science simulations on synthetic data sets, we show that TAR can either hide or help to expose Brady evidence, depending on how it is configured and the configurations of evidence to which it is applied. From these results we derive three TAR workflow recommendations: prosecutors should run TAR separately for inculpatory and Brady evidence; TAR coding of Brady material should be permitted even when active searching is constitutionally contested; and procurement guidelines should favor flexible classifiers. Our examination of TAR also highlights unresolved tensions in Brady doctrine: whether liability attaches when the prosecution possesses but does not know about Brady evidence; how Brady interacts with Fourth Amendment privacy protections; and whether Brady should be limited to preventing suppression, as current doctrine states, or expanded into a full duty to assist defense investigations. We argue that Brady liability should apply strictly to all Brady evidence in the control of the prosecution team, regardless of whether anyone on the team knows or has reason to suspect that it exists.

Review

The article "AI Suppression: E-Discovery Software And Brady" addresses a critical and under-examined intersection of artificial intelligence, digital evidence, and constitutional due process in the criminal justice system. It highlights how Technology Assisted Review (TAR) tools, increasingly used by prosecutors to manage vast amounts of digital evidence, present significant challenges to *Brady* disclosure requirements. The authors compellingly argue that despite the widespread reliance on these AI tools, there is a striking absence of doctrinal guidance, agency directives, or scholarly analysis on their proper use, creating a concerning vacuum where the potential for either suppressing or surfacing exculpatory and impeachment evidence remains largely unaddressed. This timely examination underscores a pressing need for clear guidelines to ensure fair trials in the digital age. To bridge this gap, the article employs a novel methodological approach, utilizing computer science simulations on synthetic data sets to model how TAR tools interact with various configurations of evidence. A key finding is that TAR's impact on *Brady* compliance is highly contingent: it can either effectively hide or help to expose *Brady* material depending on its internal configuration and the nature of the data it processes. From these empirical insights, the authors derive three practical and actionable recommendations for prosecutorial workflows. They advocate for separate TAR runs for inculpatory and *Brady* evidence, suggest that *Brady* material coding should be permissible even when active searching is constitutionally contested, and recommend procurement guidelines that prioritize flexible AI classifiers to optimize the discovery of exculpatory information. Beyond its practical recommendations, the article provocatively unearths deeper, unresolved tensions within existing *Brady* doctrine. It forces a re-evaluation of fundamental questions, such as whether prosecutorial liability should attach when *Brady* evidence is possessed but its existence is unknown, how *Brady* obligations interact with Fourth Amendment privacy protections, and whether the rule should expand beyond merely preventing suppression to encompass a broader duty to assist defense investigations. The authors take a clear stance on one of these tensions, arguing persuasively for a strict liability standard where *Brady* obligations apply to all exculpatory evidence within the prosecution's control, irrespective of whether any team member had actual knowledge or suspicion of its existence. This comprehensive analysis makes a significant contribution by both offering concrete solutions for current practice and instigating a vital re-examination of foundational constitutional principles in the era of AI-driven legal processes.

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