Keynote flags potential and risks of virtual trials, algorithms and deepfakes

Symposium keynote (Adam Benferrado) · February 13, 2026

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Summary

Benferrado proposed using virtual trials and algorithmic tools to blind jurors and reduce bias but warned about opaque risk tools, algorithmic discrimination, and the rising threat of fabricated audio/video and synthetic DNA.

At the symposium, Adam Benferrado explored technological pathways and risks for reforming adjudication. He said that virtual trials using neutral avatars or prerecording could hide irrelevant attributes from jurors and boost participation by making service more flexible. "If a factor like race isn't relevant to determining guilt, jurors should not know the defendant's race," he said.

Benferrado noted existing precedents for limiting bias — allowing translators, covering prejudicial tattoos, and using video testimony for vulnerable witnesses — and argued that virtual platforms and prerecording could extend those efforts to reduce appearance-based biases and juror fatigue. He discussed consumer VR hardware (Google's Daydream View) and examples of clinical VR (the company Limbix) to demonstrate the technology's accessibility.

At the same time, he cautioned that algorithmic tools and automation carry risks: opaque risk-assessment systems like COMPAS have been shown to predict higher recidivism rates for Black defendants, he said, and algorithms can reproduce human biases if not transparent. He also warned that advances in synthetic media and genetic manipulation mean that video, audio, and DNA evidence may be convincingly fabricated. He cited a startup, Liabird, as an example of technology that can mimic voices after short samples and flagged the need for technological safeguards such as incorruptible stamps or blockchain tracking for evidentiary integrity.

Benferrado acknowledged legal questions about hearsay rules, the Sixth Amendment right to confrontation, and courtroom demeanor if avatars or prerecording were widely used. He urged research, transparency in algorithm design, and piloted experiments before large-scale implementation.