Practice area
AI system failure expert witness
Technical analysis and expert testimony for litigation involving AI software failures, product defects, performance misrepresentations, and technical aspects of AI product liability matters.
Request an AI failure expertWhat is an AI system failure expert?
An AI system failure expert witness provides technical analysis, expert reports, and testimony to assist triers of fact in legal proceedings where an AI software system fails, underperforms, or produces harmful outputs. These technical assessments inform commercial disputes, product liability matters, professional negligence claims, and government contracting disputes, while legal conclusions and determinations of liability remain the province of the court.
The expert investigates the technical causes of the failure, evaluates system design and testing methodology, and assesses whether developer representations about capabilities were supported by technical evidence. Documented and methodologically transparent analysis ensures that technical findings can be properly evaluated during judicial review.
Key litigation scenarios
Commercial AI software disputes
A business deploys an AI system that fails to perform as represented in vendor sales materials or contracts. The expert considers system design, testing methodology, and technical factors relevant to whether performance claims were supported.
AI-assisted medical decisions
An AI diagnostic or clinical decision support system produces incorrect recommendations that contribute to patient harm. The expert examines system design, validation methodology, and technical considerations regarding system behavior.
Autonomous and semi-autonomous systems
An AI system with autonomous or semi-autonomous capabilities, such as a vehicle, drone, or industrial robot, experiences operational failures. The expert investigates technical factors and evaluates developer safety testing practices.
AI hallucination and reliability failures
A generative AI system produces false, misleading, or unexpected outputs, including hallucinated facts, fabricated citations, or operational errors. The expert analyzes system behavior, risk documentation, and deployed safeguards.
Government AI system failures
An AI system deployed by a government agency or contractor fails to meet technical specifications. The expert evaluates system architecture, development processes, and technical representations.
Failure analysis methodology
AI system failure analysis involves methodical investigation of system design, development, testing, deployment, and operation. Thorough documentation and methodological transparency ensure that technical analyses can be properly evaluated by courts assessing admissibility.
- System architecture review: structured analysis of system design, components, and technical decisions made during development
- Requirements traceability: evaluation of how system design addressed stated requirements and operational use cases
- Testing and validation review: assessment of developer testing practices and how potential failure modes were addressed
- Failure mode analysis: technical investigation of specific system incidents, root causes, and contributing factors
- Technical context assessment: evaluation of system behavior relative to the technical state of the art and developer documentation
- Representation evaluation: technical analysis of whether developer claims regarding system capabilities were supported by verifiable evidence
Current issue
Operational evidence after system failure
After an AI system fails, the most useful evidence is frequently operational: logs, alerts, version history, release notes, monitoring results, override records, and change-management material.
A technical review can use those records to distinguish a design issue from data drift, deployment conditions, operator conduct, or a later modification to the system.
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