I love that as of this writing, there are only two downvotes in this entire war.
I love that as of this writing, there are only two downvotes in this entire war.
But following the surface of a sphere causes you to constantly change direction
Uppies for all of you!
Put your foot down everywhere then – it’s a fallacy to think that it’s not worth it to resist data harvesting because it already gets collected “everywhere” anyway, take one step at a time to make it harder and harder. Opting out of this is just one step.
Isn’t reducing the size of the dataset worth it? I’d rather them have a picture from three years ago than a new scan every month or two.
If you put someone on a wall hook, would they then have been hung? Likewise if I suspend my painting with a noose, has the painting been hanged?
I fucking love beans
Considering freezer storage tessellation as a deciding factor in your storage container shapes feels like putting theory way ahead of practice. But I still want them.
What would be extremely rock and roll-- punk rock, even – is donating all of the proceeds from that show to pro-union efforts.
#DonateItDave, or something
I’m here to support.
Count #1: Guilty
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Count #34: Guilty
The mishandling is indeed what I’m concerned about most. I now understand far better where you’re coming from, sincere thanks for taking the time to explain. Cheers
Thanks for the response! It sounds like you had access to a higher quality system than the worst, to be sure. Based on your comments I feel that you’re projecting the confidence in that system onto the broader topic of facial recognition in general; you’re looking at a good example and people here are (perhaps cynically) pointing at the worst ones. Can you offer any perspective from your career experience that might bridge the gap? Why shouldn’t we treat all facial recognition implementations as unacceptable if only the best – and presumably most expensive – ones are?
A rhetorical question aside from that: is determining one’s identity an application where anything below the unachievable success rate of 100% is acceptable?
Can you please start linking studies? I think that might actually turn the conversation in your favor. I found a NIST study (pdf link), on page 32, in the discussion portion of 4.2 “False match rates under demographic pairing”:
The results above show that false match rates for imposter pairings in likely real-world scenarios are much higher than those from measured when imposters are paired with zero-effort.
This seems to say that the false match rate gets higher and higher as the subjects are more demographically similar; the highest error rate on the heat map below that is roughly 0.02.
Something else no one here has talked about yet – no one is actively trying to get identified as someone else by facial recognition algorithms yet. This study was done on public mugshots, so no effort to fool the algorithm, and the error rates between similar demographics is atrocious.
And my opinion: Entities using facial recognition are going to choose the lowest bidder for their system unless there’s a higher security need than, say, a grocery store. So, we have to look at the weakest performing algorithms.
It’s a freeing feeling when you decide to put money into what you want instead of what has the biggest ROI.
You could go for unst
and drop sick rave beats
unst unst unst
Oh cool, I’ll just go beat my head in-tow a wall
Okay gang, when you come across a TODO, how do you pronounce that? Too dough?
Maybe I’m missing the joke here, but it’s the latter on Linux. Super User Do = soodoo. Not sure why it’d be different for either platform.
I don’t exhale, rather I just close off my airway to stop the big inhale. It sounds super uncomfortable to try exhaling at that point, but with some practice I have been able to stop the inhale and that mutes the sneeze considerably. Also, I can plug my nose when I feel it start to tickle and stop the sneeze entirely.