Over the past year, Silicon Valley has been grappling with the way it handles our data, our elections, and our speech. Now it's got a new concern: our faces. In just the past few weeks, critics assailed Amazon for selling facial recognition technology to local police departments, and Facebook for how it gained consent from Europeans to identify people in their photos. Microsoft has endured its own share of criticism lately around the ethical uses of its technology, as employees protested a contract under which US Immigration and Customs Enforcement uses Microsoft's cloud-computing service. Microsoft says that contract did not involve facial recognition.
One year ago, Craig Federighi opened his eyes, stared into the brand-new iPhone X, and showed the world how he could unlock it with his face. Or, at least, he tried. It took the Apple executive a few attempts and one back-up phone to get the screen to unlock without a fingerprint or a passcode. But then, like magic, he was in. This was Apple's annual fall hardware show, where the company dangles its newest iPhones before the world and sets the tone for consumer products to come.
On May 14, 2019, the San Francisco government became the first major city in the United States to ban the use of facial-recognition technology (paywall) by the government and law enforcement agencies. This ban comes as a part of a broader anti-surveillance ordinance. As of May 14, the ordinance was set to go into effect in about a month. Local officials and civil advocates seem to fear the repercussions of allowing facial-recognition technology to proliferate throughout San Francisco, while supporters of the software claim that the ban could limit technological progress. In this article, I'll examine the ban that just took place in San Francisco, explore the concerns surrounding facial recognition technology, and explain why an outright ban may not be the best course of action.
A new study has found that the masks which protect people from spreading the coronavirus also have a second use, breaking facial recognition algorithms. Researchers from the National Institute of Standards and Technology have found that the best facial recognition algorithms had significantly higher error rates when trying to identify someone wearing a cloth covering. The researchers tested one-to-one matching algorithms, where a photo is compared to a different photo of the same person. This verification method is commonly used to unlock smartphones, or check passports. It drew digital masks onto the faces in a trove of border crossing photographs, and then compared those photos against another database of unmasked people seeking visas and other immigration benefits.