4 ms·

The algorithm also does "case by case" judgments. However its judgments are purely based on conditional probabilities observed from past events, which are compu

The algorithm also does "case by case" judgments. However its judgments are purely based on conditional probabilities observed from past events, which are computed using regression analysis (a relatively simple method). Human learning is enormously different from regression analysis. > I'm arguing that a desire to escape "statistics" by giving up on models and punting to the brain is futile I think we'd all agree here. The point is that both methods should always be used together, because each has huge limitations on its own.

quotemstr 9y ago
What is the brain using except conditional probabilities derived from past inputs? Why would the use of some kind of regression (which I wouldn't characterize as "relatively simple") a problem if the overall result is nevertheless more accurate than the human equivalent? We judge models by their results, not their complexity. The brain is applying some function over its inputs, after all, and we can apply that same function, either explicitly in code or implicitly via the training of some kind of model. Machines are already better than humans at other tasks for which we imagined humans exercised fine and subtle judgment: https://www.sciencedaily.com/releases/2016/04/160421133831.htm https://www.sciencedaily.com/releases/2016/04/160421133831.h..., so I see no reason to believe that bail-setting is some unapproachable problem domain. > The point is that both methods should always be usned together, because each has huge limitations on its own. I disagree. Putting a human in the loop just invites those humans to inject unstated, socially-determined biases into the decision system, and fairness and transparency dictate that we be up-front about those biases. I see no evidence that a computer model couldn't reproduce biases we considered desirable.
- dblotsky 9y ago
  > What is the brain using except conditional probabilities derived from past inputs? Hormones, reflexes, instincts, empathy, etc. Again, human inference and learning are (as of yet) insurmountably more complex than statistical regression. > regression (which I wouldn't characterize as "relatively simple" I encourage you to study brain chemistry, and compare that with any stats course ever. > Why would the use of some kind of regression (which I wouldn't characterize as "relatively simple") a problem if the overall result is nevertheless more accurate than the human equivalent? We judge models by their results, not their complexity. Because there is no way to universally judge "model results". https://en.wikipedia.org/wiki/Confusion_matrix https://en.wikipedia.org/wiki/Confusion_matrix Even a 99% true positive rate + 5% false positive rate can be worse than a 5% true positive rate and a 0% false positive rate, when you're talking about irreversible decisions. > The brain is applying some function over its inputs, after all, and we can apply that same function, either explicitly in code or implicitly via the training of some kind of model. Yes, that's very true. Executing the model is easy, and maybe even works similarly in NNs and brains. Figuring out that "some kind" part is what we formalise as "learning", and turns out is the hardest part of this equation. Again, clearly, current regression methods are nothing like human learning. Else, they'd be able to learn a language like a human, without seeing billions of annotated data points. > Machines are already better than humans at ... Neither the article nor the paper claim the machine performs better. Their strong claim is that the machine is faster. > I see no reason to believe that bail-setting is some unapproachable problem domain. I think justice is a more important domain for many people. My guess is it's because it can set precedent. > Putting a human in the loop just invites those humans to inject unstated, socially-determined biases into the decision system For drastic contrast: unstated, socially-determined biases is what prevents nuclear wars. https://en.wikipedia.org/wiki/Stanislav_Petrov https://en.wikipedia.org/wiki/Stanislav_Petrov More plainly: people have compassion, empathy, and can understand things about convicts that are (still) very difficult to encode into a computer.
  - Houshalter 9y ago
    >Hormones, reflexes, instincts, empathy, etc. Again, human inference and learning are (as of yet) insurmountably more complex than statistical regression. Complexity doesn't mean better. Humans are absolutely garbage at statistical thinking. Even simple statistical regression almost always beats human experts. Let alone more modern methods. E.g. http://zaldlab.psy.vanderbilt.edu/resources/wmg00pa.pdf http://zaldlab.psy.vanderbilt.edu/resources/wmg00pa.pdf or http://lesswrong.com/lw/3gv/statistical_prediction_rules_outperform_expert/ http://lesswrong.com/lw/3gv/statistical_prediction_rules_out...
  - joncrocks 9y ago
    I think what the parent is trying to convey is that usually when someone means when they say "this decision couldn't be done by a computer", what they mean is that "I don't really know how I'm making this decision well enough to describe it precisely enough to encode it into a set of rules." To be able to decide if something is fair, one has to be able to understand the process by which a decision is made, no? And not just a woolly, after the fact justification that a person might well invent to explain their decision. If we can't reliably look at the inputs and determine what the outputs would be, how are we able to decide if the process is 'fair'? As someone who is looking to understand a system, the argument of "But it couldn't make a human decision" triggers alarm bells of "What you mean is: It couldn't make a non-rational, unfounded, biased decision influenced by whether the person is hungry or not". Is that how important decisions should be made?
  - quotemstr 9y ago
    > Hormones, reflexes, instincts, empathy, etc. Is this the sort of hormonal influence you find desirable? http://www.economist.com/node/18557594 http://www.economist.com/node/18557594 All these factors you mention can be modeled as constant or contingent biases applied to the inputs. There is no magical aspect of the brain here. To the extent that the brain is using unstated factors to make decisions, its decision making is unfair. > I encourage you to study brain chemistry, and compare that with any stats course ever. You're hand-waving. This is not a useful discussion technique. If you have a point about how some aspect of brain chemistry produces decision outputs that are difficult to encode, please make it. Otherwise, please stop this aspect of your argument. That something is "insurmountably more complex" than some other thing doesn't make it better than that thing. Sometimes, it's just insurmountably more complex for no good reason. The blind watchmaker doesn't build elegant watches. > For drastic contrast: unstated, socially-determined biases is what prevents nuclear wars. https://en.wikipedia.org/wiki/Stanislav_Petrov https://en.wikipedia.org/wiki/Stanislav_Petrov Unstated, socially-determined biases prompted Europe to slaughter itself for 200 years in absolutely pointless wars of religion. So what?

quotemstr 9y ago

What is the brain using except conditional probabilities derived from past inputs? Why would the use of some kind of regression (which I wouldn't characterize as "relatively simple") a problem if the overall result is nevertheless more accurate than the human equivalent? We judge models by their results, not their complexity. The brain is applying some function over its inputs, after all, and we can apply that same function, either explicitly in code or implicitly via the training of some kind of model. Machines are already better than humans at other tasks for which we imagined humans exercised fine and subtle judgment: https://www.sciencedaily.com/releases/2016/04/160421133831.htm https://www.sciencedaily.com/releases/2016/04/160421133831.h..., so I see no reason to believe that bail-setting is some unapproachable problem domain. > The point is that both methods should always be usned together, because each has huge limitations on its own. I disagree. Putting a human in the loop just invites those humans to inject unstated, socially-determined biases into the decision system, and fairness and transparency dictate that we be up-front about those biases. I see no evidence that a computer model couldn't reproduce biases we considered desirable.

dblotsky 9y ago
> What is the brain using except conditional probabilities derived from past inputs? Hormones, reflexes, instincts, empathy, etc. Again, human inference and learning are (as of yet) insurmountably more complex than statistical regression. > regression (which I wouldn't characterize as "relatively simple" I encourage you to study brain chemistry, and compare that with any stats course ever. > Why would the use of some kind of regression (which I wouldn't characterize as "relatively simple") a problem if the overall result is nevertheless more accurate than the human equivalent? We judge models by their results, not their complexity. Because there is no way to universally judge "model results". https://en.wikipedia.org/wiki/Confusion_matrix https://en.wikipedia.org/wiki/Confusion_matrix Even a 99% true positive rate + 5% false positive rate can be worse than a 5% true positive rate and a 0% false positive rate, when you're talking about irreversible decisions. > The brain is applying some function over its inputs, after all, and we can apply that same function, either explicitly in code or implicitly via the training of some kind of model. Yes, that's very true. Executing the model is easy, and maybe even works similarly in NNs and brains. Figuring out that "some kind" part is what we formalise as "learning", and turns out is the hardest part of this equation. Again, clearly, current regression methods are nothing like human learning. Else, they'd be able to learn a language like a human, without seeing billions of annotated data points. > Machines are already better than humans at ... Neither the article nor the paper claim the machine performs better. Their strong claim is that the machine is faster. > I see no reason to believe that bail-setting is some unapproachable problem domain. I think justice is a more important domain for many people. My guess is it's because it can set precedent. > Putting a human in the loop just invites those humans to inject unstated, socially-determined biases into the decision system For drastic contrast: unstated, socially-determined biases is what prevents nuclear wars. https://en.wikipedia.org/wiki/Stanislav_Petrov https://en.wikipedia.org/wiki/Stanislav_Petrov More plainly: people have compassion, empathy, and can understand things about convicts that are (still) very difficult to encode into a computer.
- Houshalter 9y ago
  >Hormones, reflexes, instincts, empathy, etc. Again, human inference and learning are (as of yet) insurmountably more complex than statistical regression. Complexity doesn't mean better. Humans are absolutely garbage at statistical thinking. Even simple statistical regression almost always beats human experts. Let alone more modern methods. E.g. http://zaldlab.psy.vanderbilt.edu/resources/wmg00pa.pdf http://zaldlab.psy.vanderbilt.edu/resources/wmg00pa.pdf or http://lesswrong.com/lw/3gv/statistical_prediction_rules_outperform_expert/ http://lesswrong.com/lw/3gv/statistical_prediction_rules_out...
- joncrocks 9y ago
  I think what the parent is trying to convey is that usually when someone means when they say "this decision couldn't be done by a computer", what they mean is that "I don't really know how I'm making this decision well enough to describe it precisely enough to encode it into a set of rules." To be able to decide if something is fair, one has to be able to understand the process by which a decision is made, no? And not just a woolly, after the fact justification that a person might well invent to explain their decision. If we can't reliably look at the inputs and determine what the outputs would be, how are we able to decide if the process is 'fair'? As someone who is looking to understand a system, the argument of "But it couldn't make a human decision" triggers alarm bells of "What you mean is: It couldn't make a non-rational, unfounded, biased decision influenced by whether the person is hungry or not". Is that how important decisions should be made?
- quotemstr 9y ago
  > Hormones, reflexes, instincts, empathy, etc. Is this the sort of hormonal influence you find desirable? http://www.economist.com/node/18557594 http://www.economist.com/node/18557594 All these factors you mention can be modeled as constant or contingent biases applied to the inputs. There is no magical aspect of the brain here. To the extent that the brain is using unstated factors to make decisions, its decision making is unfair. > I encourage you to study brain chemistry, and compare that with any stats course ever. You're hand-waving. This is not a useful discussion technique. If you have a point about how some aspect of brain chemistry produces decision outputs that are difficult to encode, please make it. Otherwise, please stop this aspect of your argument. That something is "insurmountably more complex" than some other thing doesn't make it better than that thing. Sometimes, it's just insurmountably more complex for no good reason. The blind watchmaker doesn't build elegant watches. > For drastic contrast: unstated, socially-determined biases is what prevents nuclear wars. https://en.wikipedia.org/wiki/Stanislav_Petrov https://en.wikipedia.org/wiki/Stanislav_Petrov Unstated, socially-determined biases prompted Europe to slaughter itself for 200 years in absolutely pointless wars of religion. So what?