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I have a dumb question: isn't the quality of Machine Learning dependent of the quantity and quality of training data sets ? And if were are to utilize Google

I have a dumb question: isn't the quality of Machine Learning dependent of the quantity and quality of training data sets ? And if were are to utilize Google or Microsoft for ML, then the whole world ends up uploading their datasets to these giants -- which helps these companies develop even better ML systems-- like a network effect but for data ? Would these companies not have a tremendous advantage against any challengers or competition? Would this system not lead to some sort of Oligopoly ?

alwaysanagenda 7y ago
A very smart question, and a legitimate concern as well. This is precisely why I am generally against ML / AI in use to make important decisions, from what your insurance rate "should" be to how many taxes "need" to be collected. For what it's worth, I think ML / AI will fall by the wayside when -- and only when -- companies realize it's human learning and natural intelligence, when grouped together -- run in parallel -- that is ultimately a more effective pattern-finder that will produce more meaningful data. Ever notice how fast a group of internet vigilantes can 'doxx' someone? What if that was turned on other problems? That's real human intelligence in action.
diyseguy 7y ago
Also, how do all the companies using their provided models differentiate and compete. Seems like a major oversight
mattkrause 7y ago
The quality of the question too. Some people ask ML to do patently implausible things. Can you determine whether someone is a criminal from a photo of their face? It should be INCREDIBLY obvious that the answer to that question must be "no." Even if you do manage to guess correctly, there is has to be some confound, either a technical one (criminal training data is lit differently from the non-criminal ones) or a statistical one (e.g., correlation with socioeconomic status).
- doublekill 7y ago
  Have you verified that this is impossible or was gathering evidence for your strong claim too obvious for you? It is possible to do this better than random guessing!
  - mattkrause 7y ago
    Explain the mechanism, please. It seems wildly implausible to me that someone's facial features change (let alone in a predictable way) once they've committed a crime. However, I can easily imagine this "working" by keying off things like age/race/gender, which will get you a value that's "better than chance" but isn't, really. Ditto for differences in the photos; nobody smiles in a mugshot, after all. (And yes, I know about the paper purporting to show this [https://arxiv.org/pdf/1611.04135.pdf https://arxiv.org/pdf/1611.04135.pdf] I just think it's ridiculous)
    - doublekill 7y ago
      Your facial features don't change after you do a crime (except maybe for some new prison tats). They don't need to change to keep criminal classification from head shots. Age, race, gender, income, attractiveness, testosterone levels, gang membership, attention to grooming, addiction, etc. are all predictive of crime, and part of the face picture you use. Sure, there is some bias in how you label a criminal (convicted of a crime, self-report, etc.), but prediction is possible (without exploiting leakage like smiles or lighting). Just from a hot-or-not rating I can make an educated guess of your conviction rate and sentencing length.
      - mattkrause 7y ago
        You made my point for me as you slipped from "criminal classification" to "predictive of crime". They are /NOT/ equivalent. I have absolutely no doubt that features like age, race, and gender can be associated, at a group level, with crime. I'm also sure all of these can be extracted from face images. At the same time, these data are obviously not enough to make subject-level predictions. At best, this is a prior and even that is contaminated with all kinds of systematic biases. Suppose you're hiring. You are certainly allowed—and sometimes required—to not hire criminals. If you systematically avoid hiring people with features "predictive of crime", an employment lawyer is going to slap you into tomorrow with a totally justified, slam-dunk of an employment discrimination case.
0x262d 7y ago
absolutely. this is why the break up big companies strategy doesn’t work here at all and neither does free market competition as it’s nominally supposed to.

alwaysanagenda 7y ago

A very smart question, and a legitimate concern as well. This is precisely why I am generally against ML / AI in use to make important decisions, from what your insurance rate "should" be to how many taxes "need" to be collected. For what it's worth, I think ML / AI will fall by the wayside when -- and only when -- companies realize it's human learning and natural intelligence, when grouped together -- run in parallel -- that is ultimately a more effective pattern-finder that will produce more meaningful data. Ever notice how fast a group of internet vigilantes can 'doxx' someone? What if that was turned on other problems? That's real human intelligence in action.

diyseguy 7y ago

Also, how do all the companies using their provided models differentiate and compete. Seems like a major oversight

mattkrause 7y ago

The quality of the question too. Some people ask ML to do patently implausible things. Can you determine whether someone is a criminal from a photo of their face? It should be INCREDIBLY obvious that the answer to that question must be "no." Even if you do manage to guess correctly, there is has to be some confound, either a technical one (criminal training data is lit differently from the non-criminal ones) or a statistical one (e.g., correlation with socioeconomic status).

doublekill 7y ago
Have you verified that this is impossible or was gathering evidence for your strong claim too obvious for you? It is possible to do this better than random guessing!
- mattkrause 7y ago
  Explain the mechanism, please. It seems wildly implausible to me that someone's facial features change (let alone in a predictable way) once they've committed a crime. However, I can easily imagine this "working" by keying off things like age/race/gender, which will get you a value that's "better than chance" but isn't, really. Ditto for differences in the photos; nobody smiles in a mugshot, after all. (And yes, I know about the paper purporting to show this [https://arxiv.org/pdf/1611.04135.pdf https://arxiv.org/pdf/1611.04135.pdf] I just think it's ridiculous)
  - doublekill 7y ago
    Your facial features don't change after you do a crime (except maybe for some new prison tats). They don't need to change to keep criminal classification from head shots. Age, race, gender, income, attractiveness, testosterone levels, gang membership, attention to grooming, addiction, etc. are all predictive of crime, and part of the face picture you use. Sure, there is some bias in how you label a criminal (convicted of a crime, self-report, etc.), but prediction is possible (without exploiting leakage like smiles or lighting). Just from a hot-or-not rating I can make an educated guess of your conviction rate and sentencing length.
    - mattkrause 7y ago
      You made my point for me as you slipped from "criminal classification" to "predictive of crime". They are /NOT/ equivalent. I have absolutely no doubt that features like age, race, and gender can be associated, at a group level, with crime. I'm also sure all of these can be extracted from face images. At the same time, these data are obviously not enough to make subject-level predictions. At best, this is a prior and even that is contaminated with all kinds of systematic biases. Suppose you're hiring. You are certainly allowed—and sometimes required—to not hire criminals. If you systematically avoid hiring people with features "predictive of crime", an employment lawyer is going to slap you into tomorrow with a totally justified, slam-dunk of an employment discrimination case.

0x262d 7y ago

absolutely. this is why the break up big companies strategy doesn’t work here at all and neither does free market competition as it’s nominally supposed to.