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AWS is running a nice screen here. I recall reading about Rekognition being documented as having accuracy problems when individuals in question had darker skin

AWS is running a nice screen here. I recall reading about Rekognition being documented as having accuracy problems when individuals in question had darker skin [2,3]. >> "The latest cause for concern is a study published this week by the MIT Media Lab, which found that Rekognition performed worse when identifying an individual’s gender if they were female or darker-skinned." [1] I can't really comment. Just recalled this in the memory banks and thought they might address this directly [they may have]. 1 - https://www.theverge.com/2019/1/25/18197137/amazon-rekognition-facial-recognition-bias-race-gender https://www.theverge.com/2019/1/25/18197137/amazon-rekogniti... 2- https://www.media.mit.edu/articles/amazon-is-pushing-facial-technology-that-a-study-says-could-be-biased/ https://www.media.mit.edu/articles/amazon-is-pushing-facial-... 3- https://www.marketwatch.com/story/ai-experts-take-on-amazon-after-researchers-findings-of-racial-bias-in-facial-recognition-2019-04-03 https://www.marketwatch.com/story/ai-experts-take-on-amazon-...

hpoe 6y ago
There was a discussion on HN last week that I can't find where I was enlightened to find out that one of the big problems around doing facial recognition is proper lighting and without it you can't really build good models and be able to really use the image. As an extension of this photographs of individuals with darker skin required more lighting than photographs of individuals with darker skin. I don't know all of what goes into the ML for facial recognition and I am sure there are people far smarter than me working on it (and making way more money than me to boot), but I guess my thought here is that some variation of Poe's Law applies. I know that people are quick to jump to condemn something as racist but sometimes there really are just honest mistakes. I have a hard time believing that anyone at any level of the AWS structure set out to produce a racist facial recognition, but rather it may have just been an honest over site and rather than rushing to crucify them we should instead look at it as a learning opportunity to help develop further the field of facial recognition. EDIT: I wanted to clarify that although I don't think it was done purposefully I don't think it doesn't bespeak a problem; my intention was rather to serve as a suggestion that we should sometimes temper the often strong reaction produced when labeling something racist, and focus our efforts on identifying and solving the issue rather than trying to act punitive. To forestall objections I do recognize this is an issue that does require correction, and that it does bespeak a larger societal problem that has real consequences for real people ever day, but in my experience we will get more progress by attempting to work together in a spirit of cooperation rather than a spirit of anger and vengance.
- mc32 6y ago
  I think the main thing is that even if the technology were improved and it could be proven that the biases were so low as to be negligible or that it basically identifies people equally well, the opposition would be on the technology as a tool. People want some privacy in public. A tech that can track or backtrack people's movements is kinda creepy in a few ways.
- akiselev 6y ago
  The technological implementation is almost certainly an honest mistake but the marketing and sales around it is not. We've known about the importance of lighting in photography for more than a century and the computer vision industry has been battling the issue for decades in manufacturing because metal is shiny. Kodak even used to manufacture different films to better represent non-white people and camera sensor manufacturers today have entire teams with a swarm of diverse models dedicated to accurate color reproduction of skin tones across races. It's been an ongoing issue for people of color ever since TV became a thing because those technologies were initially very poor at color reproduction as well, but that didn't stop newscasters from jumping face first into televised manhunts. We've been around this block several times before and while the quarry may change from photo accuracy to ML driven facial recognition, the hunt does not. There's no excuse for selling technology to industries facing (or creating) life and death situations when the bugs are so obvious.
- coderintherye 6y ago
  This is EXACTLY what people are trying to raise awareness of. This is implicit bias. It doesn't matter if people have "good intentions" or made "honest mistakes" if the tool is implicitly biased. This is why having a diverse team working on a project is important, because it will help call out these issues early rather than after they have been put in production. It's also not purely a technical problem, if you feed the model only pictures of white and asian male college students then it's no surprise when you get a model that biases towards recognizing white and asian male college students (which is exactly how several prominent models were trained).
  - zerocrates 6y ago
rak 6y ago
Yep the ACLU did a study about this as well: https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28 https://www.aclu.org/blog/privacy-technology/surveillance-te...

hpoe 6y ago

There was a discussion on HN last week that I can't find where I was enlightened to find out that one of the big problems around doing facial recognition is proper lighting and without it you can't really build good models and be able to really use the image. As an extension of this photographs of individuals with darker skin required more lighting than photographs of individuals with darker skin. I don't know all of what goes into the ML for facial recognition and I am sure there are people far smarter than me working on it (and making way more money than me to boot), but I guess my thought here is that some variation of Poe's Law applies. I know that people are quick to jump to condemn something as racist but sometimes there really are just honest mistakes. I have a hard time believing that anyone at any level of the AWS structure set out to produce a racist facial recognition, but rather it may have just been an honest over site and rather than rushing to crucify them we should instead look at it as a learning opportunity to help develop further the field of facial recognition. EDIT: I wanted to clarify that although I don't think it was done purposefully I don't think it doesn't bespeak a problem; my intention was rather to serve as a suggestion that we should sometimes temper the often strong reaction produced when labeling something racist, and focus our efforts on identifying and solving the issue rather than trying to act punitive. To forestall objections I do recognize this is an issue that does require correction, and that it does bespeak a larger societal problem that has real consequences for real people ever day, but in my experience we will get more progress by attempting to work together in a spirit of cooperation rather than a spirit of anger and vengance.

mc32 6y ago
I think the main thing is that even if the technology were improved and it could be proven that the biases were so low as to be negligible or that it basically identifies people equally well, the opposition would be on the technology as a tool. People want some privacy in public. A tech that can track or backtrack people's movements is kinda creepy in a few ways.
akiselev 6y ago
The technological implementation is almost certainly an honest mistake but the marketing and sales around it is not. We've known about the importance of lighting in photography for more than a century and the computer vision industry has been battling the issue for decades in manufacturing because metal is shiny. Kodak even used to manufacture different films to better represent non-white people and camera sensor manufacturers today have entire teams with a swarm of diverse models dedicated to accurate color reproduction of skin tones across races. It's been an ongoing issue for people of color ever since TV became a thing because those technologies were initially very poor at color reproduction as well, but that didn't stop newscasters from jumping face first into televised manhunts. We've been around this block several times before and while the quarry may change from photo accuracy to ML driven facial recognition, the hunt does not. There's no excuse for selling technology to industries facing (or creating) life and death situations when the bugs are so obvious.
coderintherye 6y ago
This is EXACTLY what people are trying to raise awareness of. This is implicit bias. It doesn't matter if people have "good intentions" or made "honest mistakes" if the tool is implicitly biased. This is why having a diverse team working on a project is important, because it will help call out these issues early rather than after they have been put in production. It's also not purely a technical problem, if you feed the model only pictures of white and asian male college students then it's no surprise when you get a model that biases towards recognizing white and asian male college students (which is exactly how several prominent models were trained).
- zerocrates 6y ago

rak 6y ago

Yep the ACLU did a study about this as well: https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28 https://www.aclu.org/blog/privacy-technology/surveillance-te...