5 ms·

What people are really saying, but never will admit, is that they want AI to mirror their own biases, not to have none. That's the reason they are "cleaning" t

What people are really saying, but never will admit, is that they want AI to mirror their own biases, not to have none. That's the reason they are "cleaning" the input data.

deleted 4y ago
[deleted]
p0pcult 4y ago
I think with this response, you reveal more about yourself and your worldview, than any general truth about others.
- fallingknife 4y ago
  And with yours you reveal that you have no point at all
- joenot443 4y ago
  What exactly is the worldview you're describing here?
deleted 4y ago
[deleted]
mchaver 4y ago
I always thought it was the opposite. That we want AI to have no biases, but we have trouble avoiding it. Choosing data and cleaning is where we insert our bias.
- deleted 4y ago
  [deleted]
- fallingknife 4y ago
  What people want is for the models to show no differences between certain groups of people. That is the standard they use for "no bias." But that itself is bias, so really they just want the model output to conform to their bias that there isn't any difference.
  - p0pcult 4y ago
    In fact, the article cites the kind of bias that warrants eliminating. One example is the misidentification of people with dark skin by facial recognition technology, as this has led to the arrest or incarceration of innocent people. Not, as you completely fabricate, "show no differences between certain groups of people." You, however, are showing your bias.
  - diputsmonro 4y ago
    So what you're really saying is, it's perfectly okay for AI to have negative preconceptions and concrete impacts to certain groups of people, as long as it agrees with you on which groups are bad. How would you feel about AI models that classify all modern white people as racists based on overwhelming historical data about slavery, the KKK, etc.? Hey man, data doesn't lie.
    - zmgsabst 4y ago
      Isn’t the media doing exactly that? They fixate on white racists while ignoring (eg) the Christmas parade attack — leading to society developing a bias in their beliefs about racism. I always take these criticism of AI as confession-through-projection of the misdeeds people have engaged in already.
      - gcanyon 4y ago
        I'm gonna need a cite and some statistical analysis to back up your "media is biased" claim. One data point on an event that I easily found reporting on isn't going to cut it.
        zmgsabst 4y ago
        Will FBI crime statistics do? > In 2019, race was reported for 6,406 known hate crime offenders. Of these offenders: > 52.5 percent were White. > 23.9 percent were Black or African American. https://ucr.fbi.gov/hate-crime/2019/topic-pages/offenders https://ucr.fbi.gov/hate-crime/2019/topic-pages/offenders White people don’t commit disproportionately many hate crimes — black people do. According to the FBI.
- p0pcult 4y ago
  You're right; GP is just trying to make an unwarranted political point.
impalallama 4y ago
What are you saying? That its better to just blindly trust in the output of a blackbox AI output? That naively feeding in all possible data into an AI is the "best" way to do it? It is been well documented that blindly trusting AI just leads to it perpetuating human stereotypes and worsen flawed systems. https://dl.acm.org/doi/10.1145/3531146.3533138 https://dl.acm.org/doi/10.1145/3531146.3533138 https://www.aclu.org/news/privacy-technology/algorithms-in-health-care-may-worsen-medical-racism https://www.aclu.org/news/privacy-technology/algorithms-in-h... It's not some great insight that offering different inputs will result in different outputs and MAYBE we want to get better output with a different input.
- fallingknife 4y ago
  Assuming that a human stereotype is untrue is just as biased as assuming it is true. If you judge a model by how well it confirms your previous bias, then the model tells you nothing you didn't already know.
  - impalallama 4y ago
    - MichaelZuo 4y ago
      To be fair to the parent, prejudice means, according to the OED: preconceived opinion that is not based on reason or actual experience. So preconceived opinions based on reason or actual experience do not count as prejudice.
    - hcurtiss 4y ago
      This response is unnecessarily hostile. A machine stereotyping may have overwhelming accuracy. In that case, I would argue the machine is not wrong. It's our policy response to its outputs that may or may not be wrong. Changing the machine to disregard accurate descriptions of the real world only serves to bias the machine.
    - naasking 4y ago
diputsmonro 4y ago
I completely disagree. You're right that everyone has biases - including the authors of the AI who will therefore choose a biased training dataset. When the tool they are constructing has unparalleled power, and is very likely to negatively impact the lives of those who the authors are biased against (consciously or not), it's entirely fair for those impacted groups to be concerned. Every dataset has a skew to it, which should be accounted for during training. If the authors don't explicitly account for such things, out of ignorance or bias, then that skew, that bias, will be ingrained in the AI. For example, if I only train my AI on it's knowledge of chocolate from ads for a particular brand, it's going to have some very opinionated, very wrong ideas about chocolate. This example is silly and obvious, but similar skews happen all the time in real datasets that the authors don't have the time or expertise to recognize. When people who do have that expertise speak up, we should listen to them and fix it, not just blindly trust "the data" and whatever our fancy algorithm does with it. Garbage in, garbage out.
- visarga 4y ago
  These imbalances in the training data are there because the world generates data in an imbalanced way. Sometimes you can correct for it, other times it's impossible. You simply can't find good data for all your cases. For example in medical diagnosing or in self driving.

What people are really saying, but never will admit, is that they want AI to mirror their own biases, not to have none. That's the reason they are "cleaning" the input data.

deleted 4y ago

[deleted]

p0pcult 4y ago

I think with this response, you reveal more about yourself and your worldview, than any general truth about others.

fallingknife 4y ago
And with yours you reveal that you have no point at all
joenot443 4y ago
What exactly is the worldview you're describing here?

deleted 4y ago

[deleted]

mchaver 4y ago

I always thought it was the opposite. That we want AI to have no biases, but we have trouble avoiding it. Choosing data and cleaning is where we insert our bias.

deleted 4y ago
[deleted]
fallingknife 4y ago
What people want is for the models to show no differences between certain groups of people. That is the standard they use for "no bias." But that itself is bias, so really they just want the model output to conform to their bias that there isn't any difference.
- p0pcult 4y ago
  In fact, the article cites the kind of bias that warrants eliminating. One example is the misidentification of people with dark skin by facial recognition technology, as this has led to the arrest or incarceration of innocent people. Not, as you completely fabricate, "show no differences between certain groups of people." You, however, are showing your bias.
- diputsmonro 4y ago
  So what you're really saying is, it's perfectly okay for AI to have negative preconceptions and concrete impacts to certain groups of people, as long as it agrees with you on which groups are bad. How would you feel about AI models that classify all modern white people as racists based on overwhelming historical data about slavery, the KKK, etc.? Hey man, data doesn't lie.
  - zmgsabst 4y ago
    Isn’t the media doing exactly that? They fixate on white racists while ignoring (eg) the Christmas parade attack — leading to society developing a bias in their beliefs about racism. I always take these criticism of AI as confession-through-projection of the misdeeds people have engaged in already.
    - gcanyon 4y ago
      I'm gonna need a cite and some statistical analysis to back up your "media is biased" claim. One data point on an event that I easily found reporting on isn't going to cut it.
      - zmgsabst 4y ago
        Will FBI crime statistics do? > In 2019, race was reported for 6,406 known hate crime offenders. Of these offenders: > 52.5 percent were White. > 23.9 percent were Black or African American. https://ucr.fbi.gov/hate-crime/2019/topic-pages/offenders https://ucr.fbi.gov/hate-crime/2019/topic-pages/offenders White people don’t commit disproportionately many hate crimes — black people do. According to the FBI.
p0pcult 4y ago
You're right; GP is just trying to make an unwarranted political point.

impalallama 4y ago

What are you saying? That its better to just blindly trust in the output of a blackbox AI output? That naively feeding in all possible data into an AI is the "best" way to do it? It is been well documented that blindly trusting AI just leads to it perpetuating human stereotypes and worsen flawed systems. https://dl.acm.org/doi/10.1145/3531146.3533138 https://dl.acm.org/doi/10.1145/3531146.3533138 https://www.aclu.org/news/privacy-technology/algorithms-in-health-care-may-worsen-medical-racism https://www.aclu.org/news/privacy-technology/algorithms-in-h... It's not some great insight that offering different inputs will result in different outputs and MAYBE we want to get better output with a different input.

fallingknife 4y ago
Assuming that a human stereotype is untrue is just as biased as assuming it is true. If you judge a model by how well it confirms your previous bias, then the model tells you nothing you didn't already know.
- impalallama 4y ago
  - MichaelZuo 4y ago
    To be fair to the parent, prejudice means, according to the OED: preconceived opinion that is not based on reason or actual experience. So preconceived opinions based on reason or actual experience do not count as prejudice.
  - hcurtiss 4y ago
    This response is unnecessarily hostile. A machine stereotyping may have overwhelming accuracy. In that case, I would argue the machine is not wrong. It's our policy response to its outputs that may or may not be wrong. Changing the machine to disregard accurate descriptions of the real world only serves to bias the machine.
  - naasking 4y ago

diputsmonro 4y ago

I completely disagree. You're right that everyone has biases - including the authors of the AI who will therefore choose a biased training dataset. When the tool they are constructing has unparalleled power, and is very likely to negatively impact the lives of those who the authors are biased against (consciously or not), it's entirely fair for those impacted groups to be concerned. Every dataset has a skew to it, which should be accounted for during training. If the authors don't explicitly account for such things, out of ignorance or bias, then that skew, that bias, will be ingrained in the AI. For example, if I only train my AI on it's knowledge of chocolate from ads for a particular brand, it's going to have some very opinionated, very wrong ideas about chocolate. This example is silly and obvious, but similar skews happen all the time in real datasets that the authors don't have the time or expertise to recognize. When people who do have that expertise speak up, we should listen to them and fix it, not just blindly trust "the data" and whatever our fancy algorithm does with it. Garbage in, garbage out.

visarga 4y ago
These imbalances in the training data are there because the world generates data in an imbalanced way. Sometimes you can correct for it, other times it's impossible. You simply can't find good data for all your cases. For example in medical diagnosing or in self driving.