What happened
It was reported that CrimeRadar, an app published by Scoopz Inc. and linked to the news app NewsBreak, uses AI to monitor publicly available police radio across the United States, transcribe the audio into text, and generate crime alerts that it pushes to residents nearby. In December 2025 a BBC Verify investigation found that the app had sent false alerts about serious crimes to communities in several US states by misinterpreting ordinary radio traffic. In one case in Bend, Oregon, the app’s transcription system misread routine radio traffic as a serious crime and issued an alert that caused alarm. A resident in Minnesota said an alert had defamed him.
It was then reported that CrimeRadar acknowledged what it called serious transcription issues that had led to inaccurate information being sent out, apologised for the distress caused, said it had upgraded its audio processing, and announced plans to let agencies and community members submit corrections and add context to alerts. On the company’s own account, the errors came from how its AI transcribes and summarises radio traffic, and they reached residents as alerts about violent crime in named neighbourhoods before anyone caught them.
What an auditable version would have shown
An alert that a serious crime is happening nearby names a neighbourhood and reaches the people living in it. This one began as a machine transcription of police radio, and the company says that is where the errors came from. An auditable version keeps, for every alert, the original audio, the transcript it produced, how sure it was, and whether anyone confirmed it against a more reliable source before it went out. If all it has is an uncertain transcript, the alert waits. And because the audio and the transcript are kept together, a false alarm can be traced afterwards: a resident who was frightened, or the man who says he was defamed, can be shown exactly what the app heard and what it made of it, and the mistake fixed at the source instead of argued over.
Where the gap was
False alerts about violent crime reached residents, and the company says the errors came from how its AI transcribes radio traffic. A VerificationGate checks a claim like that against a more reliable source, the dispatch record rather than the app’s own transcript, before an alert is sent, so a misheard word does not turn into a neighbourhood scare. A ConductRecord keeps the audio, the transcript and whatever was sent, so a false alert can be traced back to where it started and put right, instead of leaving the people who got it to work out for themselves whether it was ever real.
What governance should have looked like
The bigger the harm an alert can cause, the surer a system should be before it sends one, and an alert about violence is about as big as it gets. A single machine transcription is not a confirmation; it is a lead that still has to be checked. Best practice would be for anything pushing public-safety alerts to confirm each one against a reliable source before it goes out, and to keep the audio, the transcript and the decision on file, so an alert can be checked, traced and corrected instead of taken on the machine’s word.
Failure Pattern: an automated system turned misread audio into public alerts about serious crime, and the errors reached residents before anyone caught them.
Governance Principle: an automated alert to the public should be confirmed against a trusted source before it is sent, not inferred from a single unreliable signal.
The reference implementation of VerificationGate and ConductRecord is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.
Sources
- CrimeRadar uses AI to monitor US police radio and has sent inaccurate alerts (BBC News, via NewsBreak)
- AI Crime App CrimeRadar Sparks Panic With False Alerts, Company Issues Apology (The Shib Daily)
- Minnesota man accuses AI crime app of defamation (InForum)