"But that was not before the falsely accused man had his name and image widely shared. The alert sent by Citizen contained a photo and was seen by more than 861,000 people. It read: "Citizen is offering a $30,000 reward to anyone who provides information that leads to the arrest of the arson suspect."
Citizen told the Guardian in a statement it offered the cash reward "without formal coordination with the appropriate agencies".
"Once we realized this error, we immediately retracted the photo and reward offer," it said. "We are actively working to improve our internal processes to ensure this does not occur again. This was a mistake we are taking very seriously.""
"However, according to data on the force's website, 92% (2,297) of those were found to be "false positives".
South Wales police admitted that "no facial recognition system is 100% accurate", but said the technology had led to more than 450 arrests since its introduction. It also said no one had been arrested after an incorrect match."
"But an analysis by the Office of Information Technology Services issued last month "acknowledges that the risks of the use of (facial recognition technology) in an educational setting may outweigh the benefits."
The report, sought by the Legislature, noted "the potentially higher rate of false positives for people of color, non-binary and transgender people, women, the elderly, and children."
It also cited research from the nonprofit Violence Project that found that 70% of school shooters from 1980 to 2019 were current students. The technology, the report said, "may only offer the appearance of safer schools.""
"This led to claims that the software is woefully inaccurate; in fact, police had set the threshold for a match at 60%, meaning that faces do not have to be rated as that similar to be flagged up. This minimises the chance of a person of interest slipping through the net, but also makes a lot of false positives inevitable."
"In just the past few months, three cities - San Francisco, Oakland, and Somerville, Massachusetts - have passed laws to ban government use of the controversial technology, which analyzes pictures or live video of human faces in order to identify them. Cambridge, Massachusetts, is also moving toward a government ban. Congress recently held two oversight hearings on the topic and there are at least four pieces of current federal legislation to limit the technology in some way. "
"On inbuilt bias in algorithms, Sharkey said: "There are so many biases happening now, from job interviews to welfare to determining who should get bail and who should go to jail. It is quite clear that we really have to stop using decision algorithms, and I am someone who has always been very light on regulation and always believed that it stifles innovation."
"Georgetown University's Center on Privacy and Technology highlighted the April 2017 episode in Garbage In, Garbage Out, a report on what it says are flawed practices in law enforcement's use of facial recognition.
The report says security footage of the thief was too pixelated and produced no matches while high-quality images of Harrelson returned several possible matches and led to one arrest."
"Police are facing calls to halt the use of facial recognition software to search for suspected criminals in public after independent analysis found matches were only correct in a fifth of cases and the system was likely to break human rights laws."
"But even cleverest AI can be fooled with the simplest of hacks. If you write out the word "iPod" on a sticky label and paste it over the apple, Clip does something odd: it decides, with near certainty, that it is looking at a mid-00s piece of consumer electronics. In another test, pasting dollar signs over a picture of a dog caused it to be recognised as a piggy bank."
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