An analysis of 1,500 reports showed a shockingly high rate of error when reading license plates.
A study of close to 1,500 Flock camera reports in Roseville, California found that the cameras failed to properly detect license plates 71% of the time, reports
Tyler Lacoma for CNET.
According to Lacoma, "Mistaking one number for another, like seeing a 7 as a 1, can lead Flock cameras to incorrectly identify an innocent vehicle as one that was previously stolen. That’s exactly what happened in the California situation, where a citizen complained that the cameras were repeatedly flagging his car to police as stolen because the AI technology interpreted a 9 as an 8."
The analysis was conducted between 2023 and 2024, so Lacoma points out that the technology and the Large Language Models it uses has likely improved. "However, we’ve also seen the opposite happen: AI models can eat up bad data, especially 'recursive' data that was created by another AI, and start becoming dumber, less accurate when performing their tasks."
If Flock cameras can't be trusted, Lacoma points out, it will create more work for police departments, not less, like the company claims. "If Flock’s core services could have such a high failure rate, that’s another reason for police and sheriff departments to reconsider their use, and could make it difficult for Flock to sell new cities on its technology."
Read the full story: Flock’s AI Cameras May Have Misread Over 70% of License Plates, Creating New Headaches for Cities
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