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TRUVACE RECORD VERSION
record: TRV-2026-2663
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T16:57:54.956272Z
status: published
lens: p_space
sector: crime
headline: Public perceptions of police use of artificial intelligence to assist in generating police reports: findings from an experimental study
dek: In the context of policing, artificial intelligence (AI) and large language models (LLM) tools are being touted for their ability to reduce the amount of time officers spend writing reports while simultaneously improving their accuracy and completeness. Concerns have been raised, however, about bias, privacy, legality, inaccuracies, transparency, and the overall impact of the use of AI when generating police reports on legal proceedings and police legitimacy. Despite continued advancements in the technology and…
gain_title: (none)
problem_title: A survey experiment of US residents found only low to moderate public support for police using AI to write reports, with support rising only when people were told the tools were useful and how agencies check their accuracy.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A survey experiment of US residents found only low to moderate public support for police using AI to write reports, with support rising only when people were told the tools were useful and how agencies check their accuracy.
problem_evidence: We found low to moderate support for the use of AI
quick_read: A survey experiment in Policing and Society asked a non-probability sample of US residents whether police should use AI and large language model tools to generate police reports. It found low to moderate support overall.

Support was highest when respondents were told the tools were useful and what steps police agencies are taking to ensure their accuracy. The study tested how the information agencies share changes opinion.

The work matters because vendors promote these tools as cutting report-writing time while improving accuracy and completeness, yet concerns about bias, privacy, legality, inaccuracies and transparency remain. Because the sample was non-probability, the results may not represent all US residents.
limitation: The study used a non-probability sample of U.S. residents, so its findings may not represent the wider US public.
tag: Evidence-backed problem
key_points: The study used a survey experimental design with a non-probability sample of US residents. | Overall public support for police using AI to generate reports was low to moderate. | Support was greatest when respondents learned the tools were useful and how police agencies ensure accuracy. | The researchers tested whether trust in police or race and ethnicity changed these reactions. | Concerns cited include bias, privacy, legality, inaccuracies, transparency and effects on legal proceedings and police legitimacy.
rundown: The study addressed three questions: how much the public supports police use of AI to generate reports, how views change with the information agencies share about the technology and its use, and whether trust in police or race and ethnicity moderate those relationships.

Tools built on large language models are being promoted for reducing officers' report-writing time while improving accuracy and completeness. Critics have raised concerns about bias, privacy, legality, inaccuracies, transparency and the impact on legal proceedings and police legitimacy.

The finding that support was strongest when respondents heard about the tools' usefulness and accuracy safeguards suggests that how agencies communicate about the technology shapes public acceptance.
sources:
- peer_reviewed | Policing and Society | https://doi.org/10.1080/10439463.2026.2675429 | 2026-05-22
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