Police departments in Colorado, Indiana, and Oklahoma are testing an AI tool that writes police reports from body camera audio, according to The Associated Press. The tool, called Draft One, was announced in April by Axon, the police technology company also known for making tasers. Axon says Draft One uses OpenAI's GPT-4 large language model to generate reports and markets it as a productivity tool that can reduce officers' paperwork hours.
"If an officer spends half their day reporting, and we can cut that in half," Axon CEO Rick Smith told Forbes at the time, "we have an opportunity to potentially free up 25 percent of an officer's time to be back out policing."
But police reports carry more legal weight than routine paperwork, and generative AI is known for "hallucination"—a term for fabricated facts or incorrect information in synthetic text. Some departments are allowing officers to use Draft One for any kind of case, not just minor incident reports, the AP reported.
Legal Experts Question Reliance on AI
Andrew Ferguson, an American University law professor who wrote the first law review on AI-generated police reports, told the AP he is concerned that automation and the ease of the technology "would cause police officers to be sort of less careful with their writing." In his review, published last month, Ferguson wrote: "The open question is how reliance on AI-generative suspicion will distort the foundation of a legal system dependent on the humble police report."
Axon has defended the tool. Noah Spitzer-Williams, the company's AI product manager, told the AP that Axon has "access to more knobs and dials" than the "average ChatGPT user would have." He said Axon turned down GPT-4's "creativity dial," which he says limits Draft One's potential to "embellish or hallucinate" like ChatGPT does.
The debate raises questions about what may be lost as automation enters policing, where human judgment and accountability are central. Police reports serve as foundational documents in investigations and legal proceedings, and errors or biases in them can have serious consequences. As departments expand testing, the tension between efficiency and reliability remains unresolved.
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