There’s no part of your life now where you can avoid the onslaught of “artificial intelligence.” Whether you’re trying to search for a recipe and sifting through AI-made summaries or listening to your cousin talk about how they’ve fired their doctor and replaced them with a chatbot, it seems now, more than ever, that AI is the solution to every problem. But, in the meantime, some people are getting hideously rich by convincing people with money and influence that they must integrate AI into their business or operations.

Enter law enforcement.

When many tech vendors see police, they see dollar signs. Law enforcement’s got deep pockets. They are under political pressure to address crime. They are eager to find that one magic bullet that finally might do away with crime for good. All of this combines to make them a perfect customer for whatever way technology companies can package machine-learning algorithms that sift through historical data in order to do recognition, analytics, or predictions.

AI in policing can take many forms that we can trace back decades–including various forms of face recognition, predictive policing, data analytics, automated gunshot recognition, etc. But this year has seen the rise of a new and troublesome development in the integration between policing and artificial intelligence: AI-generated police reports.

Egged on by companies like Truleo and Axon, there is a rapidly-growing market for vendors that use a large language model to write police reports for officers. In the case of Axon, this is done by using the audio from police body-worn cameras to create narrative reports with minimal officer input except for a prompt to add a few details here and there.

We wrote about what can go wrong when towns start letting their police write reports using AI. First and foremost, no matter how many boxes police check to say they are responsible for the content of the report, when cross examination reveals lies in a police report, officers will now have the veneer of plausible deniability by saying, “the AI wrote that part.” After all, we’ve all heard of AI hallucinations at this point, right? And don’t we all just click through terms of service without reading it carefully?

And there are so many more questions we have. Translation is an art, not a science, so how and why will this AI understand and depict things like physical conflict or important rhetorical tools of policing like the phrases, “stop resisting” and “drop the weapon,” even if a person is unarmed or is not resisting? How well does it understand sarcasm? Slang? Regional dialect? Languages other than English? Even if not explicitly made to handle these situations, if left to their own devices, officers will use it for any and all reports.

Prosecutors in Washington have even asked police not to use AI to write police reports (for now) out of fear that errors might jeopardize trials.

Countless movies and TV shows have depicted police hating paperwork and if these pop culture representations are any indicator, we should expect this technology to spread rapidly in 2025. That’s why EFF is monitoring its spread closely and providing more information as we continue to learn more about how it’s being used. 

This article is part of our Year in Review series. Read other articles about the fight for digital rights in 2024.