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What's the point of turning it down? I can train a superhuman-performance facial recognition model with consumer hardware sitting in my garage. The cat has been

by m0zg 8y ago

What's the point of turning it down? I can train a superhuman-performance facial recognition model with consumer hardware sitting in my garage. The cat has been out of the bag for close to a decade. What leads to abuse in this case is not the technology, but the policy, and withholding technology accomplishes nothing policy-wise simply because it's accessible to just about anyone with a GPU.

rhizome 8y ago
I can train a superhuman-performance facial recognition model with consumer hardware sitting in my garage. I don't think you can, but it depends entirely on what you mean by "superhuman performance."
- m0zg 8y ago
  Means it will distinguish faces better than a human in side-by-side testing. This is actually a thing, and it has been for a while. Humans aren't very good at telling if it's "the same guy" or not.
  - rhizome 8y ago
    Cite please, I'm guessing this is only under controlled conditions, or perhaps more aptly described as "difference recognition."
    - m0zg 8y ago
      LMGTFY: https://www.google.com/search?q=facial+recognition+exceeds+human+accuracy&oq=facial+recognition+exceeds+human+accuracy&aqs=chrome..69i57.15007j0j7&sourceid=chrome&ie=UTF-8 https://www.google.com/search?q=facial+recognition+exceeds+h... Or, if that's still too much work: http://vis-www.cs.umass.edu/lfw/results.html http://vis-www.cs.umass.edu/lfw/results.html
      - deleted 8y ago
        [deleted]
      - rhizome 8y ago
        I'll have to look into the terminology to be confident of the best match for this context, but I figure "Image-Restricted, Label-Free Outside Data Results"[1] might match the scenario where a recognizer provides a yes/no after being trained on e.g. driver's licenses (let's call it the "Super Bowl" model). None of the results appear to be greater than 95%, which I understand to be a hard ceiling for requiring human QC. Many of the other methods get you worse than 50-50 chance of false positives by the time the algo gets to 95% true positives, but not being a statistician I may be reading the results wrong, in which case I'm totally willing to be corrected. Empirically, though, we know that the Super Bowl model has never worked. 1. http://vis-www.cs.umass.edu/lfw/results.html#ImageRestrictedLF http://vis-www.cs.umass.edu/lfw/results.html#ImageRestricted...
laughinghan 8y ago
But making news for withholding that technology, thereby drawing attention to and sparking discussion about the issue, can affect public sentiment, which in turn affects policy. There's also supply and demand. Reducing supply of the technology increases its costs. Plus, it's good PR for them.
- m0zg 8y ago
  The past 20 years (along with PATRIOT act and FISA courts) show that we can "discuss" until we're blue in the face and nothing is going to change. This also seems to be remarkably bipartisan, for a change. The only set of actors that can change anything in US congress are corporate donors and PACs, and Microsoft is a donor (through its employees and PACs, don't know about directly). Reducing the supply of this particular technology is not going to increase its costs, because literally anyone with a recent GPU and some motivation can just download it from GitHub at this point. The most worrisome user of it, the US government and its various three-letter agencies, already have and extensively use this tech. Casinos have been using it for well over a decade to spot people who are "too consistently lucky". I do buy your point regarding good PR. It's just completely ineffectual wrt its stated goals.

by m0zg 8y ago

rhizome 8y ago

I can train a superhuman-performance facial recognition model with consumer hardware sitting in my garage. I don't think you can, but it depends entirely on what you mean by "superhuman performance."

m0zg 8y ago
Means it will distinguish faces better than a human in side-by-side testing. This is actually a thing, and it has been for a while. Humans aren't very good at telling if it's "the same guy" or not.
- rhizome 8y ago
  Cite please, I'm guessing this is only under controlled conditions, or perhaps more aptly described as "difference recognition."
  - m0zg 8y ago
    LMGTFY: https://www.google.com/search?q=facial+recognition+exceeds+human+accuracy&oq=facial+recognition+exceeds+human+accuracy&aqs=chrome..69i57.15007j0j7&sourceid=chrome&ie=UTF-8 https://www.google.com/search?q=facial+recognition+exceeds+h... Or, if that's still too much work: http://vis-www.cs.umass.edu/lfw/results.html http://vis-www.cs.umass.edu/lfw/results.html
    - deleted 8y ago
      [deleted]
    - rhizome 8y ago
      I'll have to look into the terminology to be confident of the best match for this context, but I figure "Image-Restricted, Label-Free Outside Data Results"[1] might match the scenario where a recognizer provides a yes/no after being trained on e.g. driver's licenses (let's call it the "Super Bowl" model). None of the results appear to be greater than 95%, which I understand to be a hard ceiling for requiring human QC. Many of the other methods get you worse than 50-50 chance of false positives by the time the algo gets to 95% true positives, but not being a statistician I may be reading the results wrong, in which case I'm totally willing to be corrected. Empirically, though, we know that the Super Bowl model has never worked. 1. http://vis-www.cs.umass.edu/lfw/results.html#ImageRestrictedLF http://vis-www.cs.umass.edu/lfw/results.html#ImageRestricted...

laughinghan 8y ago

But making news for withholding that technology, thereby drawing attention to and sparking discussion about the issue, can affect public sentiment, which in turn affects policy. There's also supply and demand. Reducing supply of the technology increases its costs. Plus, it's good PR for them.

m0zg 8y ago
The past 20 years (along with PATRIOT act and FISA courts) show that we can "discuss" until we're blue in the face and nothing is going to change. This also seems to be remarkably bipartisan, for a change. The only set of actors that can change anything in US congress are corporate donors and PACs, and Microsoft is a donor (through its employees and PACs, don't know about directly). Reducing the supply of this particular technology is not going to increase its costs, because literally anyone with a recent GPU and some motivation can just download it from GitHub at this point. The most worrisome user of it, the US government and its various three-letter agencies, already have and extensively use this tech. Casinos have been using it for well over a decade to spot people who are "too consistently lucky". I do buy your point regarding good PR. It's just completely ineffectual wrt its stated goals.