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Amazon Is Pushing Facial Recognition Tech That a Study Says Could Be Biased (nytimes.com)
An anonymous reader quotes a report from The New York Times: Over the last two years, Amazon has aggressively marketed its facial recognition technology to police departments and federal agencies as a service to help law enforcement identify suspects more quickly. Now a new study from researchers at the M.I.T. Media Lab has found that Amazon's system, Rekognition, had much more difficulty in telling the gender of female faces and of darker-skinned faces in photos than similar services from IBM and Microsoft. The results raise questions about potential bias that could hamper Amazon's drive to popularize the technology.
In the study, published Thursday, Rekognition made no errors in recognizing the gender of lighter-skinned men. But it misclassified women as men 19 percent of the time, the researchers said, and mistook darker-skinned women for men 31 percent of the time. Microsoft's technology mistook darker-skinned women for men just 1.5 percent of the time. For the latest study, [co-author of the study, Ms. Buolamwini, said] she sent a letter with some preliminary results to Amazon seven months ago. But she said that she hadn't heard back from Amazon, and that when she and a co-author retested the company's product a couple of months later, it had not improved. "It's not possible to draw a conclusion on the accuracy of facial recognition for any use case -- including law enforcement -- based on results obtained using facial analysis," Matt Wood, general manager of AI at Amazon Web Services, said. He added that the researchers had not tested the latest version of Rekognition, which was updated in November.
"Amazon said that in recent internal tests using an updated version of its service, the company found no difference in accuracy in classifying gender across all ethnicities," the NYT reports. The new study is scheduled to be presented Monday at an artificial intelligence and ethics conference in Honolulu.
In the study, published Thursday, Rekognition made no errors in recognizing the gender of lighter-skinned men. But it misclassified women as men 19 percent of the time, the researchers said, and mistook darker-skinned women for men 31 percent of the time. Microsoft's technology mistook darker-skinned women for men just 1.5 percent of the time. For the latest study, [co-author of the study, Ms. Buolamwini, said] she sent a letter with some preliminary results to Amazon seven months ago. But she said that she hadn't heard back from Amazon, and that when she and a co-author retested the company's product a couple of months later, it had not improved. "It's not possible to draw a conclusion on the accuracy of facial recognition for any use case -- including law enforcement -- based on results obtained using facial analysis," Matt Wood, general manager of AI at Amazon Web Services, said. He added that the researchers had not tested the latest version of Rekognition, which was updated in November.
"Amazon said that in recent internal tests using an updated version of its service, the company found no difference in accuracy in classifying gender across all ethnicities," the NYT reports. The new study is scheduled to be presented Monday at an artificial intelligence and ethics conference in Honolulu.
So the message is that the software is much more likely to be successful at apprehending guilty white people? Sorry for using a racist tag ("white") in my comment.
It does sound like it's strongly biased against white people and should be scrutinized carefully.
Lol idiots (journalists)
the company found no difference in accuracy in classifying gender across all ethnicities
Maybe the spokesperson is clueless, but ethnicity is not race. Look at people in Cuba: some appear Black, some European, some Native American, many are mixed. But all are Hispanic ethnicity.
work by recording the light reflected from objects.
Darker-toned faces reflect less visible-wavelength light.
That's just physics, not racism.
So the amount of light, and ability to resolve contrasts, edges etc, would be less.
So the image classification task might be subject to more error.
Perhaps a different spectral range would work better?
Where are we going and why are we in a handbasket?
Machine learning doesn't work like that. You feed data into it and it works out the algorithms itself.
Data can be biased. If the training set is 90% photos of white people, then the NN is going to be better at identifying white people.
But it isn't clear why bias is a problem here. If it correctly identifies a white thief 90% of the time, and a black thief 80% of the time, is it really better to "fix it" so that the white identification rate is lowered to 80%, so that it is "fair"?
Why the hell would you WANT some fucked up bezos computer to identify you as you walk down the street?
I would say it is biased against bald beardless white men. Black women get misidentified at such a high rate the tech is worthless to identify them. That is a GOOD THING FOR BLACK WOMEN!!!
Iâ(TM)m not bald and now I am definitely keeping my beard. For once, a benefit to being a black woman: you dont get tracked and stored by bezos and his evil minions.
And any amazon engineers reading this who worked on the tech, SHAME ON YOU! You could have earned just as much working on tech that is not evil and not putting it straight into the hands of evil people and everyone with a dollar.
Facebook would *never* promote a technology without thoroughly thinking through the implications. They are the pinnacle of corporate social responsibilty...
Come to think of it, that last part may actually be true.
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