Publication Date

12-1-2026

Document Type

Article

Publication Title

Forensic Science International Synergy

Volume

13

DOI

10.1016/j.fsisyn.2026.100725

Abstract

Forensic testimony is where science meets the courtroom, and it is one of the critical forensic skills taught largely by apprenticeship. An examiner who overstates a match, mishandles a probability, or cannot support a method under direct or cross-examination can weaken the evidence in precisely the cases that rely on it. Yet in most forensic laboratories, testimony preparation remains largely informal, mentor-dependent, and unscalable. Consequently, many practitioners first face rigorous cross-examination at trial. To address this gap, HelixCross, an alpha-stage, publicly accessible, prompt-engineered large language model (LLM) agent, was developed. It uses retrieval-augmented generation (RAG) to simulate defense counsel cross-examination and provide structured coaching on demand. Deployed on two LLM platforms to widen access, it pairs a phase-based curriculum with a synthetic DNA case, a scripted cross-plan with embedded fallacy traps, and a ten-dimension coaching rubric. The initial curriculum targets recurrent problems in DNA testimony, including likelihood-ratio interpretation, proposition discipline, activity-level overreach, probabilistic-genotyping assumptions, and unwarranted certainty. This paper describes the architecture, training assets, and governance considerations. Evaluation to date consists of informal functional testing by the developers and a few early-stage users, without predefined acceptance criteria, independent ratings, or learner outcome data. Testing also exposed platform-dependency risks, including session-state failure after a vendor-side model update. HelixCross is therefore presented as a transparent development-stage tool and curriculum package intended to enhance the resilience, clarity, accuracy, and scientific integrity of forensic expert testimony – a contribution that a follow up phase of controlled evaluation is required to demonstrate.

Keywords

Expert testimony, Forensic science, Large language model, Probabilistic genotyping, Simulation-based education

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Department

Justice Studies

Download

Share

COinS