AI system architecture • retraining behavior • data lineage

AI Systems Analysis for High-Stakes Litigation

Technical strategy and system-level analysis for cases involving machine learning and algorithmic decision systems.

I work with litigation teams to analyze how AI systems are built, trained, versioned, and deployed, so technical claims can be tested, challenged, and clearly explained. The focus is on the mechanics of model behavior under scrutiny: retraining drift, data lineage, logging integrity, reproducibility, and architectural decision points that matter in disputes.

Request a 20-Minute Technical Briefing
Attorney reviewing technical analysis of an AI system used in litigation

What I Do

When AI systems become central to liability, discrimination, intellectual property, or product claims, legal arguments often move faster than technical clarity. I help counsel identify the system-level questions that actually determine how a model behaves, and where it may fail.

Technical Issue Mapping

  • Translate pleadings and early expert themes into concrete system-level questions.
  • Identify architectural assumptions embedded in the model and surrounding services.
  • Surface hidden technical dependencies that may affect liability or damages.

Model Behavior & Retraining Analysis

  • Evaluate version drift and retraining cycles relevant to the period in dispute.
  • Assess stability and reproducibility of outputs over time.
  • Analyze data pipeline and configuration changes that may affect outcomes.

Discovery Strategy Support

  • Identify critical logs, model artifacts, configuration files, and documentation.
  • Assess reproducibility risks given available artifacts and logging practices.
  • Highlight gaps in training data traceability and model governance relevant to claims.

Pre-Expert Strategic Framing

  • Clarify technical issues before expert reports are drafted.
  • Stress-test emerging technical narratives against how the system actually operates.
  • Support internal case strategy discussions with system-level framing that complements litigation strategy and expert testimony, rather than replacing either.

When to Call

Early technical clarity often prevents strategic missteps later in litigation.

Approach

The work begins with architecture, not headlines. I focus on how the system was actually built, what data it depended on, how it evolved, and whether its outputs can be reliably reproduced. The emphasis is on structured analysis of implementation details, not broad claims about “AI risk” or “algorithmic bias.”

Where appropriate, I produce concise technical memoranda outlining:

The goal is technical clarity that stands up under scrutiny.

About

I focus on understanding machine learning systems at a structural level and analyzing how they behave when examined closely. The work sits at the intersection of AI system design and litigation strategy, with an emphasis on how implementation details affect legal arguments once systems are challenged.

I am particularly interested in how retraining cycles, evolving datasets, architectural decisions, and documentation practices shape what can be said about model behavior in court. I work independently and selectively on matters where technical depth is likely to have a material impact on case strategy.

Request a Technical Briefing

If you are handling a matter where an AI system plays a central role, I offer a short initial technical discussion to identify potential system-level issues worth deeper review.

Schedule Briefing

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Security & Confidentiality

  • NDA available upon request.
  • Secure document transfer.
  • Attorney-client privilege considerations respected.