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There is a case to be made about how good the AI behind emotional detection is. When you take the test, it will be accurate for some, and blissfully wrong for o

There is a case to be made about how good the AI behind emotional detection is. When you take the test, it will be accurate for some, and blissfully wrong for others. More so wrong for most. I took the test (or unknowingly took it) and it was correct for the most part. And it got some things wrong. I love dogs. The trouble is not that the AI can be wrong, it's that we will rely on its answers to make decisions. When the facial recognition software combines your facial expression and your name, while you are walking under the bridge late at night, in an unfamiliar neighborhood, and you are black; Your terrorist score is at 52%. A police car is dispatched. In 2017, my contract was not transferred to the new system. The automated system saw that an ex employee was scanning his key cards multiple times. Security was dispatched to catch the rogue employee. Now a simple questioning should have cleared things up, but the computer had already flagged me as troublesome. Long story short, I was fired. When the machine calculates your emotions, the results are unquestionable. Or, we don't know how it got to the answer, so we trust that it is right. It is a computer after all. What scares me is not how fast machine learning is being deployed to every aspect of our lives. My scare is our reaction to it.

henrikschroder 7y ago
The problem with all current "AI"-driven systems be it facial recognition, voice recognition, translating, fraud detection, navigation, whatever, is that they are not 100% right, and when they're wrong, they're hilariously devastatingly super-wrong in a way that humans are not wrong. But since the success modes are good and human-like, we assume that the failures are going to be human-like as well, but the failure-modes of these system are usually bizarre and alien. Take self-driving accidents, for example. Pretty much all of them happen in situations that no human would fail in, and that's obvious to most people, but then we're forgetting about all the other mistakes similar "AI" systems make, and don't realize that they're also failures no human would make.
- taneq 7y ago
  > in a way that humans are not wrong. I dunno... from the parent post: > you are walking under the bridge late at night, in an unfamiliar neighborhood, and you are black; Your terrorist score is at 52% That sounds like a pretty human failure mode to me.
  - owl57 7y ago
    Seems like the main game changer here is the feasibility of massive surveillance databases, not the human/"AI" decision-making. Of course non-invasive keys for those databases, like face recognition, are convenient, but if they don't work good enough I expect something like machine-readable pedestrian license plates.
  - jerf 7y ago
    Yes, it sounds like that because it was a human making up a failure mode, so it was human. Now suppose you bought 3 12-packs of Coke Zero last week, you sneezed on the frame the computer used to identify your face, the moon was waxing gibbous (which nobody even realized the AI was actually using as part of its calculations), your name is a 3 letter first name followed by a 15 letter last name, and a coincidental confluence of 25 other equally pointless things that, technically, the AI weights at non-zero. Now you're a terrorist.
    - taneq 7y ago
      That's a way better example. Neural nets are really good at picking up obscure correlations. The last letter of your first name is 'j', there are limestone blocks in the picture and you're wearing a yellow t-shirt? Terrorist for sure.
      - antisemiotic 7y ago
        Every educated AI knows that the best way to spot a criminal is too look for people staring directly at the camera, with a white rectangle below their face.
    - smallnamespace 7y ago
      To play devil's advocate though, sometimes the ML training process is picking up a signal that humans simply haven't noticed. The moon waxing gibbous is a fun example - what if moon phase were to affect our biology in subtle ways? There are plenty of things that people feel or know to be true but have trouble putting into words. That guy you know who just gives you a creepy vibe, but you can't put your finger on exactly why?
- mehrdadn 7y ago
  > Take self-driving accidents, for example. Pretty much all of them happen in situations that no human would fail in, and that's obvious to most people, but then we're forgetting about all the other mistakes similar "AI" systems make, and don't realize that they're also failures no human would make. Amen? I've tried to explain precisely this to many brilliant AI/ML folks in lots of variations, with little success. They look at me funny, as if I'm a crank for believing that that probabilities don't capture the whole story. It seems that, to far too many of them, a computer that has half the accident rate of a human is a strictly better replacement, end of story. The notion of just how spectacular the failure mode might be, or the degree of control that a human might have in the process, or any other human factor you can think of besides the accident rate, just seems like a completely nonsensical notion to many of them. For the life of me I have yet to find a way to convey this thought in a compelling manner.
  - jrumbut 7y ago
    To me, one of the best uses of this generation of AI would be as an aid to decision making. Your personal Skynet learns representations of data that help you make decisions, and watches out for worrying signs that you may be missing (perhaps based on your known mistake patterns, adapting as those change). Meanwhile, human domain experts still look at the details and are able to add their own understanding of broader context, human nature, etc. In this world, AI/ML primarily increases quality by augmenting human abilities rather than decreasing cost by automating humans out of the system. It's a smaller market maybe, but there are areas where better work can fetch a premium. I think part of this is the lack of well understood patterns for the plumbing and UI of a system like this that makes it easy and useful and non-threatening to users. It's nothing that someone couldn't figure out, but not as well paved a road as integrating a caching, search, or image processing subsystem.
    - arvinsim 7y ago
      So I guess we aim for augmentation first before shooting for a complete replacement.
      - 7y ago
PastaMonster 7y ago
So your boss is an uneducated moron that doesnt understand current AI. Did you try to explain it to the boss? You should have shamed the company online. Always a good thing to know which companies are moronic.
- AstralStorm 7y ago
  And you should've found him a convenient and well paid job. Since publicly shaming the company online, besides being ineffective, is a good way to get fired.
  - lonelappde 7y ago
    GP already was fired for accidentally triggering disclosure of the company's incompetence. Warning people not to work for a company is one of the best ways to justifiably kill a company by starving it of talent.
rland 7y ago
This is an excellent point. I can foresee a world where ML becomes a sort of "bias laundering." "Nobody knows why the machine learning module denied black people a mortgage 43% more frequently than whites, but it's 'AI' shrug" One of the biggest priorities as we shape this future needs to be a way not only for the algos to make correct decisions, but also the ability for us to interrogate the decision-making process so we can be proactive about the kind of future we want this technology to give us. Because it is coming, without a doubt.
- toyg 7y ago
  "Foresee"? "Coming"? The example you mentioned is already with us. Insurance companies and lenders already use computerized models with problematic outcomes, which are completely opaque: https://scholarworks.law.ubalt.edu/cgi/viewcontent.cgi?article=1307&context=all_fac https://scholarworks.law.ubalt.edu/cgi/viewcontent.cgi?artic... "AI" is just speeding up processes that started in the 1970s.
seanwilson 7y ago
> it was correct for the most part. And it got some things wrong. I love dogs. Seems an order of magnitude easier + more accurate to just track how long you linger each post while scrolling down a newsfeed and which ones you engaged in. MacBooks, Chrome etc. already warn you when your webcam are on anyway so if social sites started adding webcam tracking when you're only viewing the newsfeed I can't see it lasting for long.
- matmann2001 7y ago
  The fact that I lingered longer on a post doesn't indicate the polarity of my interest, just the magnitude at best.
  - seanwilson 7y ago
    Knowing that you linger longer on that topic is good enough to know that the topic is likely to get further engagement from you though - people like to spend time arguing about things that annoy them as well so you don't only want to show things that make people smile. If you interact in any way with a post, you can do sentiment analysis on the text too to figure out their thoughts on the topic. I just don't see facial analysis being that powerful over the above. You're already giving Facebook and Twitter a ton of information about what you enjoy via likes, shares and follows, without having to get into the subtleties of what it means if you half-smile or frown when you see a post.
    - whycombinater 7y ago
      Seriously why is the discussion anything but delete all tech immediately and bomb silicon valley? Too late, the ML just flagged me as being anti-ML. I'll probably be assassinated soon.
      - krageon 7y ago
        The problem is not the tech or the ML. It is the people using and creating it.
TheSpiceIsLife 7y ago
> The trouble is not that the AI can be wrong, it's that we will rely on its answers to make decisions. It's not clear to me how this is different than the current standard?
golergka 7y ago
> The trouble is not that the AI can be wrong, it's that we will rely on its answers to make decisions. And this is why mathematical statistics and probability theory should be taught in middle school (may be instead of some trigonometry and stereonometry). Not only researchers, but any decision maker, and general public too, need to understand what confidence intervals are and how normal distribution works, on an intuitive level.
- lonelappde 7y ago
  Won't help. Most practicing scientists who have been trained in statistical methods don't understand them, and just publish whatever garbage they squeeze out of SAS and then add a layer of misinterpretation on top for good measure. Statistics is fundamentally beyond the comprehension of 98% of people.
  - golergka 7y ago
    Not if you gameify it and educate them when they're about 12 years old. I don't have any sources, just a very strong gut feeling.

henrikschroder 7y ago

The problem with all current "AI"-driven systems be it facial recognition, voice recognition, translating, fraud detection, navigation, whatever, is that they are not 100% right, and when they're wrong, they're hilariously devastatingly super-wrong in a way that humans are not wrong. But since the success modes are good and human-like, we assume that the failures are going to be human-like as well, but the failure-modes of these system are usually bizarre and alien. Take self-driving accidents, for example. Pretty much all of them happen in situations that no human would fail in, and that's obvious to most people, but then we're forgetting about all the other mistakes similar "AI" systems make, and don't realize that they're also failures no human would make.

taneq 7y ago
> in a way that humans are not wrong. I dunno... from the parent post: > you are walking under the bridge late at night, in an unfamiliar neighborhood, and you are black; Your terrorist score is at 52% That sounds like a pretty human failure mode to me.
- owl57 7y ago
  Seems like the main game changer here is the feasibility of massive surveillance databases, not the human/"AI" decision-making. Of course non-invasive keys for those databases, like face recognition, are convenient, but if they don't work good enough I expect something like machine-readable pedestrian license plates.
- jerf 7y ago
  Yes, it sounds like that because it was a human making up a failure mode, so it was human. Now suppose you bought 3 12-packs of Coke Zero last week, you sneezed on the frame the computer used to identify your face, the moon was waxing gibbous (which nobody even realized the AI was actually using as part of its calculations), your name is a 3 letter first name followed by a 15 letter last name, and a coincidental confluence of 25 other equally pointless things that, technically, the AI weights at non-zero. Now you're a terrorist.
  - taneq 7y ago
    That's a way better example. Neural nets are really good at picking up obscure correlations. The last letter of your first name is 'j', there are limestone blocks in the picture and you're wearing a yellow t-shirt? Terrorist for sure.
    - antisemiotic 7y ago
      Every educated AI knows that the best way to spot a criminal is too look for people staring directly at the camera, with a white rectangle below their face.
  - smallnamespace 7y ago
    To play devil's advocate though, sometimes the ML training process is picking up a signal that humans simply haven't noticed. The moon waxing gibbous is a fun example - what if moon phase were to affect our biology in subtle ways? There are plenty of things that people feel or know to be true but have trouble putting into words. That guy you know who just gives you a creepy vibe, but you can't put your finger on exactly why?
mehrdadn 7y ago
> Take self-driving accidents, for example. Pretty much all of them happen in situations that no human would fail in, and that's obvious to most people, but then we're forgetting about all the other mistakes similar "AI" systems make, and don't realize that they're also failures no human would make. Amen? I've tried to explain precisely this to many brilliant AI/ML folks in lots of variations, with little success. They look at me funny, as if I'm a crank for believing that that probabilities don't capture the whole story. It seems that, to far too many of them, a computer that has half the accident rate of a human is a strictly better replacement, end of story. The notion of just how spectacular the failure mode might be, or the degree of control that a human might have in the process, or any other human factor you can think of besides the accident rate, just seems like a completely nonsensical notion to many of them. For the life of me I have yet to find a way to convey this thought in a compelling manner.
- jrumbut 7y ago
  To me, one of the best uses of this generation of AI would be as an aid to decision making. Your personal Skynet learns representations of data that help you make decisions, and watches out for worrying signs that you may be missing (perhaps based on your known mistake patterns, adapting as those change). Meanwhile, human domain experts still look at the details and are able to add their own understanding of broader context, human nature, etc. In this world, AI/ML primarily increases quality by augmenting human abilities rather than decreasing cost by automating humans out of the system. It's a smaller market maybe, but there are areas where better work can fetch a premium. I think part of this is the lack of well understood patterns for the plumbing and UI of a system like this that makes it easy and useful and non-threatening to users. It's nothing that someone couldn't figure out, but not as well paved a road as integrating a caching, search, or image processing subsystem.
  - arvinsim 7y ago
    So I guess we aim for augmentation first before shooting for a complete replacement.
    - 7y ago

PastaMonster 7y ago

So your boss is an uneducated moron that doesnt understand current AI. Did you try to explain it to the boss? You should have shamed the company online. Always a good thing to know which companies are moronic.

AstralStorm 7y ago
And you should've found him a convenient and well paid job. Since publicly shaming the company online, besides being ineffective, is a good way to get fired.
- lonelappde 7y ago
  GP already was fired for accidentally triggering disclosure of the company's incompetence. Warning people not to work for a company is one of the best ways to justifiably kill a company by starving it of talent.

rland 7y ago

This is an excellent point. I can foresee a world where ML becomes a sort of "bias laundering." "Nobody knows why the machine learning module denied black people a mortgage 43% more frequently than whites, but it's 'AI' shrug" One of the biggest priorities as we shape this future needs to be a way not only for the algos to make correct decisions, but also the ability for us to interrogate the decision-making process so we can be proactive about the kind of future we want this technology to give us. Because it is coming, without a doubt.

toyg 7y ago
"Foresee"? "Coming"? The example you mentioned is already with us. Insurance companies and lenders already use computerized models with problematic outcomes, which are completely opaque: https://scholarworks.law.ubalt.edu/cgi/viewcontent.cgi?article=1307&context=all_fac https://scholarworks.law.ubalt.edu/cgi/viewcontent.cgi?artic... "AI" is just speeding up processes that started in the 1970s.

seanwilson 7y ago

> it was correct for the most part. And it got some things wrong. I love dogs. Seems an order of magnitude easier + more accurate to just track how long you linger each post while scrolling down a newsfeed and which ones you engaged in. MacBooks, Chrome etc. already warn you when your webcam are on anyway so if social sites started adding webcam tracking when you're only viewing the newsfeed I can't see it lasting for long.

matmann2001 7y ago
The fact that I lingered longer on a post doesn't indicate the polarity of my interest, just the magnitude at best.
- seanwilson 7y ago
  Knowing that you linger longer on that topic is good enough to know that the topic is likely to get further engagement from you though - people like to spend time arguing about things that annoy them as well so you don't only want to show things that make people smile. If you interact in any way with a post, you can do sentiment analysis on the text too to figure out their thoughts on the topic. I just don't see facial analysis being that powerful over the above. You're already giving Facebook and Twitter a ton of information about what you enjoy via likes, shares and follows, without having to get into the subtleties of what it means if you half-smile or frown when you see a post.
  - whycombinater 7y ago
    Seriously why is the discussion anything but delete all tech immediately and bomb silicon valley? Too late, the ML just flagged me as being anti-ML. I'll probably be assassinated soon.
    - krageon 7y ago
      The problem is not the tech or the ML. It is the people using and creating it.

TheSpiceIsLife 7y ago

> The trouble is not that the AI can be wrong, it's that we will rely on its answers to make decisions. It's not clear to me how this is different than the current standard?

golergka 7y ago

> The trouble is not that the AI can be wrong, it's that we will rely on its answers to make decisions. And this is why mathematical statistics and probability theory should be taught in middle school (may be instead of some trigonometry and stereonometry). Not only researchers, but any decision maker, and general public too, need to understand what confidence intervals are and how normal distribution works, on an intuitive level.

lonelappde 7y ago
Won't help. Most practicing scientists who have been trained in statistical methods don't understand them, and just publish whatever garbage they squeeze out of SAS and then add a layer of misinterpretation on top for good measure. Statistics is fundamentally beyond the comprehension of 98% of people.
- golergka 7y ago
  Not if you gameify it and educate them when they're about 12 years old. I don't have any sources, just a very strong gut feeling.