The writer says identification has troubling implications but I was under the impression that masking oneself to avoid being ID'd was illegal in the first place.
I mean in the old days, when the bad guys came riding into town wearing bandanas, that was prima facie (pun?) evidence they were up to no good and pretty much gave the locals license to grab their rifles and have at 'em.
I know appeals of the anti-Klan laws have gone both ways, some upholding the right to run around in masks and pointy hats and some, like "
State v. Miller, 260 Ga. 669 (1990)" saying that, in Georgia at any rate, you just can't wear stuff like that.
I lean toward the Old West interpretation myself.
Have at 'em boys.
More after the jump.
Motherboard, Sept. 6:
A new paper has troubling implications.
Protesters regularly wear disguises like bandanas and sunglasses to prevent being identified, either by law enforcement or internet sleuths. Their efforts may be no match for artificial intelligence, however.
A new paper to be presented at the IEEE International Conference on Computer Vision Workshops
(ICCVW) introduces a deep-learning algorithm—a subset of machine
learning used to detect and model patterns in large heaps of data—that
can identify an individual even when part of their face is obscured. The
system was able to correctly identify a person concealed by a scarf 67
percent of the time when they were photographed against a "complex"
background, which better resembles real-world conditions.
The deep-learning algorithm works in a novel way. The researchers,
from Cambridge University, India's National Institute of Technology, and
the Indian Institute of Science, first outlined 14 key areas of the
face, and then trained a deep-learning model to identify them. The
algorithm connects the points into a "star-net structure," and uses the
angles between the points to identify a face. The algorithm can still
identify those angles even when part of a person's mug is obscured, by
disguises including caps, scarves, and glasses.
Image: University of Cambridge/ National Institute of Technology/ Indian Institute of Science
The research has troubling implications for protestors and other
dissidents, who often work to make sure they aren't ID'd at protests and
other demonstrations by covering their faces with scarves or by wearing
sunglasses. "To be honest when I was trying to come up with this
method, I was just trying to focus on criminals," Amarjot Singh, one of
the researchers behind the paper and a Ph.D student at Cambridge
University, told me on a phone call.
Singh said he isn't sure
how to prevent the technology from being used by authoritarian regimes
in the future. "I actually don't have a good answer for how that can be
stopped," he said. "It has to be regulated somehow … it should only be
used for people who want to use it for good stuff." How to guarantee
algorithms like the one Singh developed don't get into nefarious hands
is an ongoing problem.
Zeynep Tufekci, a professor at the University of North Carolina, Chapel Hill, and a writer at The New York Times,
discussed the dubious implications of the algorithm described in the
paper on Twitter: "too many worry about what AI—as if some independent
entity—will do to us. Too few people worry what *power* will do *with*
AI," she wrote in a tweet.
Don't fret yet, though. While the algorithm described in the paper was
fairly impressive, it's definitely not reliable enough to be used by law
enforcement or anyone else. But the researchers behind the paper have
provided future academics with an important gift to do their work. One
of the problems with training machine learning models is that there
simply aren't enough
quality databases out there to train them on. But this paper provides
researchers in the field with two different databases to train
algorithms to do similar tasks, each with 2,000 images.
"This is
a minor paper; narrow, conditional results. But it's the direction
& this will be done with nation-state data—not by grad students,"
Tufecki wrote in a followup tweet.
The system described in the paper isn't capable of identifying people
wearing all types of disguises. Singh pointed out to me that the rigid
Guy Fawkes masks
often donned by members of hacking collective Anonymous would be able
to evade the algorithm, for example. He hopes one day though to be able
to ID people even wearing rigid masks. "We are trying to find ways to
explore that problem," he told me over the phone. It's worth noting that
experimental algorithms can already identify people with 99 percent accuracy based on how they walk....MORE
HT:
Marginal Revolution
The reason we have burned so many pixels on this stuff is because we thought you couldn't wear your motorcycle helmet into the bank. Hence posts such at "
Adversarial Images, Or How To Fool Machine Vision" and "
How to Hide From Cameras":
And "
Another Way To Fool The Facial Recognition Algos":
Do you know how long it takes to put that makeup on?
If just anyone can do this stuff any time they want simply by putting on a mask, where does society end up?
I'll tell you where. We go from scholarly stuff such as "
Fooling The Machine: The Byzantine Science of Deceiving Artificial Intelligence"
To this:
Just so you know, I don't actually use the make-up techniques featured
in the earlier posts. Despite the fact they have some efficacy at
fooling the camera they make you look like a moron to human observers on
the street. Better to just put on some glasses and blend into the
crowd.
Maybe just better to go with:
"Magic AI: These are the Optical Illusions that Trick, Fool, and Flummox Computers"
Researchers wearing simulated pairs of fooling glasses, and the people the facial recognition system thought they were.
Image by Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer, and Michael K. Reiter
Rant over
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