Video and photographic evidence will never be the same again.
getty
A man spent more than five years in prison for a double murder he didn’t commit. Not because the evidence was planted. It’s not because the witness lied. That’s because the trial judge looked at the pixelated surveillance camera footage, compared it to a photo of the defendant, and determined that the blurred figure on the screen was the gunman.
No forensic video examiner was hired. Scientific methodology was not applied. The judge just looked on.
In January, the Alberta Court of Appeal unanimously overturned Gerald Benn’s two murder convictions in Republican v. Benn, finding what it called “serious flaws” in the judge’s analysis. Surveillance camera footage was low resolution and pixelated. The trial judge acknowledged as much, but without using any of the training, tools, or protocols required for forensic video analysis, he conducted his own visual comparisons and drew identification conclusions from them anyway.
The Court of Appeal’s full judgment covers more ground than video analysis alone, but the key here is the failure of the video. The judge evaluated the pixelated surveillance footage without forensic methodology, without qualified examiners, and without any ordering that would prevent a predetermined conclusion from reaching the outcome. This single gap contributed to a verdict that the Court of Appeal found unreasonable. That’s not unusual either.
Video evidence was not obvious
Benn’s lawsuit originated in Canada, but the lack of evidence it uncovered is not a Canadian problem. More than 80 percent of U.S. trials now include some level of video evidence, according to a 2025 report released by the University of Colorado Boulder’s Visual Evidence Laboratory. But there are no mandatory federal standards that dictate how that evidence should be analyzed.
NIST’s Forensic Video Inspection Workflow Standard remains in its proposed form, has not been finalized, and is not required. While the Justice Department has issued uniform language for testimony and reports covering DNA, fingerprints, and even firearms, there is no equivalent guidance for forensic video analysis. While we rely more heavily on video evidence than ever before, regulations on video evidence are less stringent than in most other forensic fields.
The assumption that creates this gap is that videos are self-explanatory. To enable anyone to watch the video and understand what is shown there. What is skipped is whether the footage was shot, stored, and transmitted in a way that preserves what actually happened. whether the resolution supports the conclusions drawn; Whether the person making the evaluation has a scientific basis for the identification.
This is what was supposed to happen in Ben’s case. A qualified forensic video examiner would have independently evaluated the surveillance footage before examining known images of the suspect. The order is important. This is how you prevent your brain from finding what it’s already looking for.
Untrained eyes see video evidence incorrectly
The research on this is consistent, and the results are not positive for the way courts currently operate.
A 2021 study published in Forensic Science International: Digital Investigation tested 53 digital forensic examiners on the same evidence. Examiners given incriminating context found more incriminating traces than when given neutral or innocent context. In none of the 53 cases could we find all relevant traces. These were experts trained to handle the same evidence. The study’s authors called for “serious and urgent” quality assurance reform in this area.
When a judge has already heard testimony, considered fingerprint evidence, and formed a working theory of the case, evaluating surveillance footage without forensic guidance puts human cognition precisely in a situation where confirmation bias takes hold. The science on this is well documented and applies regardless of your experience or intentions.
A National Institute of Justice study that analyzed 732 wrongful conviction cases found that most forensic errors were not made by forensic scientists at all. Investigators and prosecutors erred by discounting, ignoring, or misrepresenting exculpatory forensic results. When examiners made mistakes, they were usually related to insufficient scientific evidence or organizational failures in training or governance. The study also found that about half of wrongful convictions could have been avoided at trial through improved technology, testimony standards, and practice standards. There was a methodology to do it right. There was no need for the system to use it.
AI does not cause this problem. That makes it explode.
I have worked in the field of digital forensics for about 20 years. Ben’s case is not surprising. What has changed is the stakes.
Courts are being asked to evaluate video evidence without the standard infrastructure that exists in other forensic fields. The system never developed a framework of guidance that would provide judges, lawyers, insurers, and investigators with reliable tools for their evaluation. That same unprepared system now faces something far more demanding. Even if the footage isn’t accurate, generative AI can produce footage that looks crisper, sharper, and more distinct than anything ever recorded by a surveillance camera. The distance between “looking convincing” and “being accurate” has never been greater, and that distance is being measured by people who were already working without a reliable framework for making that judgment.
We are already seeing it come to fruition. In a 2024 Washington state triple murder case, the defense presented surveillance video that was “enhanced” using the company’s AI software, which clearly alerted the company to the forensic use of its products. The defense expert was a filmmaker with no forensic training.
A qualified prosecuting attorney testified that the AI created what he called an “illusion of clarity.” The video wasn’t actually more accurate, but it looked clearer. Although the judge excluded the evidence, the fact that it reached that stage should be a concern to all lawyers, insurance companies, and investigators involved in cases involving digital footage.
Still, the only thing you can trust is your device
If the authenticity of a video is in question, the only answer is the device that recorded it. Metadata embedded at the time of capture, file system artifacts, and application logs on the source device can confirm whether the footage is original, whether it has been processed, re-encoded, or manipulated, and whether what is being presented in court matches what was actually recorded on the device. That analysis requires physical equipment, forensically appropriate collection, and trained examiners to interpret what the data shows.
AI-enhanced and AI-generated footage completely breaks the visual record. Pixel data no longer reflects what the sensor captures. But device records don’t lie if they’re saved. Source device custody is no longer a procedural formality. In a world where generative AI can create more convincing footage than actual surveillance video, this is the last reliable starting point for forensic video examinations.
Before AI, this mistake cost Gerald Benn five years of his life. Once AI is embedded in the evidence chain, there is no room for error.
monday morning playbook
Industry standards exist for forensic video analysis. Qualified judges exist. What isn’t there is a requirement to use them.
For lawyers, this means hiring qualified digital forensics experts rather than IT staff or investigators or filmmakers using media players when video evidence is central to a case.
For insurance professionals, this means incorporating forensic reviews into claims evaluation protocols before disputes escalate to litigation. A video that may seem simple at the coordination stage can become the centerpiece of a lawsuit if the underlying analysis is not properly conducted.
For any organization that touches digital evidence, this means understanding that “we saw it and it seemed obvious” has never been the appropriate standard, and will never be the appropriate standard in the AI era.
Gerald Benn lost five years of his life. The families of the two murdered people have yet to receive justice. No one could win here. This fix wasn’t a breakthrough technology or a multibillion-dollar effort. Fixes were always available. Qualified experts, sound methodology, and a willingness to follow expert guidance rather than intuition.
Calling a qualified video forensics expert was always the right decision. The AI simply made it the only call.
