Meta AI flood of unusable abuse tips overwhelms US investigators

A New Mexico lawsuit reveals growing concerns that Meta’s AI systems create vast numbers of low-quality alerts instead of actionable leads, hindering child safety teams.
US investigators say Meta’s AI generates overwhelming volumes of unusable child abuse reports, diverting resources from genuine cases and slowing critical investigations across the country.

Investigators in the US say that AI used by Meta is flooding child protection units with large volumes of unhelpful reports, thereby draining resources rather than assisting ongoing cases.

Officers in the Internet Crimes Against Children network told a New Mexico court that most alerts generated by the company’s platforms lack essential evidence or contain material that is not criminal, leaving teams unable to progress investigations.

Meta rejects the claim that it prioritises profit, stressing its cooperation with law enforcement and highlighting rapid response times to emergency requests.

Its position is challenged by officers who say the volume of AI-generated alerts has doubled since 2024, particularly after the Report Act broadened reporting obligations.

They argue that adolescent conversations and incomplete data now form a sizeable portion of the alerts, while genuine cases of child sexual abuse material are becoming harder to detect.

Internal company documents disclosed at trial show Meta executives raising concerns as early as 2019 about the impact of end-to-end encryption on the firm’s ability to identify child exploitation and support investigators.

Child safety groups have long warned that encryption could limit early detection, even though Meta says it has introduced new tools designed to operate safely within encrypted environments.

The growing influx of unusable tips is taking a heavy toll on investigative teams. Officers in the US say each report must still be reviewed manually, despite the low likelihood of actionable evidence, and this backlog is diminishing morale at a time when they say resources have not kept pace with demand.

They warn that meaningful cases risk being delayed as units struggle with a workload swollen by AI systems tuned to avoid regulatory penalties rather than investigative value.

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