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A prior (e.g., P(recruiter|woman at tech event) = g ) is accurate if the actual portion of women at tech events who are recruiters is g. Secondly, suppose the

A prior (e.g., P(recruiter|woman at tech event) = g ) is accurate if the actual portion of women at tech events who are recruiters is g. Secondly, suppose the prior is accurate. Lets take a very simple model, suppose g_woman = 0.25 and g_man = 0.05. Further, suppose networking with a developer has a value of 1 utilon and networking with a recruiter has 0 utilons of value. If I network in order to maximize utility, based solely on my prior (i.e. ignoring any posterior info), I've added 95 utilons to the world for every 100 people I network with. If I behave irrationally and network with men and women equally, I've added only 85 utilons to the world. I've harmed 47.5 men in order to benefit 37.5 women - on net I've harmed 10 people. (If posterior information is available, then you can even increase utility beyond 95/100.) This is why math matters, and why carefully thinking things through rather than spouting incorrect soundbites (as the author does) is important.

maxerickson 11y ago
How do you go from a simple abstract model that is rhetorically convenient to actually guiding concrete behavior? If you walk into a conference and use that model you aren't using anything very meaningful to guide your behavior, you're using a model that probably isn't very true (I would presume that the modal value of networking is ~0, with the occasional valuable introduction bringing the mean up above that).
- yummyfajitas 11y ago
  Going from models to reality is basically a process of expanding the model until it accounts for enough that you are confident it will work. Also, the particular model I use only requires a mean positive utility - even if we take a model like yours, the conclusion is unchanged. Variance simply goes up, but the best option is still not talking to women.
  - maxerickson 11y ago
    How do you measure if it works or not? I mean, if you only talk to men and then measure where you derived utility, I'm not sure you've properly evaluated the model yet (if you interact with a certain percentage of women at conferences and keep track of all this in order to make sure that your model is working out properly, well then, more power to you).
    - yummyfajitas 11y ago
      I really can't write an entire textbook on Bayesian decision theory in an HN comment. Honestly, if I could, I'd write the actual textbook - we really need a good one. I'm not claiming to have a rigorously tested model of exactly who to network with at a conference. I'm claiming that ignoring base rates results in worse decisions. And if I made this point in a non-political context - e.g., "you must account for the base rate for $disease when interpreting a $disease test" - no one would be disputing it. If you or anyone else here can even present a (utilitarian) model where ignoring base rates leads to a better decision, by all means do it. I'd love to see this, though I suspect the actual outcome of such an effort will merely be the person attempting to do it gaining a much better understanding of Bayes rule.
      - maxerickson 11y ago
        My issue isn't with the point that the base rate matters, it's with the mathematricality. And I do think that is fair, if there is not a simple way of actually measuring the utility and such (re your complaint about $diseases, medicine has at least somewhat reliable tests), all the stuff about the modeling is just theatrics.
        yummyfajitas 11y ago
        Am I correct in interpreting this post as saying "I agree base rate matters, I just wish you didn't provide a toy example illustrating that?" Also, I now strongly recommend you go through the exercise I suggested. Then you'll realize that accurate tests do NOT somehow eliminate the need for models or accounting for base rates.
        maxerickson 11y ago
        Also, I now strongly recommend you go through the exercise I suggested. Then you'll realize that accurate tests do NOT somehow eliminate the need for models or accounting for base rates. I'm reaching for the opposite point. Some sort of meaningful evaluation of actual outcomes is necessary to make utilitarian decisions. If the evaluation of the outcome is arbitrary, then so is the decision.
beat 11y ago
First, morality matters. And you've forcibly ejected morality from your equation. Second, network effects matter. You're not just creating utilons for yourself, you're creating a system that creates utilons. Even within the small and inaccurate world of your invented model, you're not following through to conclusions. Third, you're making some very arbitrary assumptions, and ignoring other reasonable assumptions. For starters, do you give everyone you network with equal time? If you encounter a recruiter, do you give them the same amount of effort you would give to an engineer, or do you extract yourself and move on to the next person? The expense of equal input is not nearly as high as you're presenting here, assuming you don't "behave irrationally" and give everyone equal time whether it's effective or not. Pretending that bias and excuses are intellectual rigor by inserting arbitrary, invented numbers into an imaginary equation is just an appeal to authority fallacy.
- blfr 11y ago
  Yummyfajitas seems to be using utilitarian morality in his argument, not ejecting it altogether. That's what the concern with the net number of people harmed would suggest anyway.
  - beat 11y ago
    Not really. It looks like utilitarian morality on the surface, but it lacks a rigorous analysis of consequences (as I pointed out on at least two fronts). Utilitarian morality's bootstrap definition requires rigor in order to use it - otherwise, there's a real danger of arriving at an immoral conclusion, which means it's not utilitarian. Putting a pig in a suit doesn't make it a gentleman. Which gets back to Occam's Razor. Which is more likely... that this was a failure of insufficient rigor, or that it was using utilitarianism and math to appeal to authority? Given that there were multiple violations of rigor, Occam's Razor suggests that this wasn't utilitarian morality at all, but rather mere defensive rhetoric. Of course, this doesn't imply intent - the author might not realize that his formal-sounding justification was actually rationalization, because of a failure to understand the underlying moral issue. Which is exactly how bias works in most cases. Someone put it really well recently, in the context of racism and racist police behavior. They said racism isn't waving a Confederate flag around. Racism is looking for excuses every time the police shoot another unarmed black man. People who don't think of themselves as racist or sexist, who actually find those ideas repulsive, are actively racist and sexist all the time! This is because they don't see the bias in their own behavior.

maxerickson 11y ago

How do you go from a simple abstract model that is rhetorically convenient to actually guiding concrete behavior? If you walk into a conference and use that model you aren't using anything very meaningful to guide your behavior, you're using a model that probably isn't very true (I would presume that the modal value of networking is ~0, with the occasional valuable introduction bringing the mean up above that).

yummyfajitas 11y ago
Going from models to reality is basically a process of expanding the model until it accounts for enough that you are confident it will work. Also, the particular model I use only requires a mean positive utility - even if we take a model like yours, the conclusion is unchanged. Variance simply goes up, but the best option is still not talking to women.
- maxerickson 11y ago
  How do you measure if it works or not? I mean, if you only talk to men and then measure where you derived utility, I'm not sure you've properly evaluated the model yet (if you interact with a certain percentage of women at conferences and keep track of all this in order to make sure that your model is working out properly, well then, more power to you).
  - yummyfajitas 11y ago
    I really can't write an entire textbook on Bayesian decision theory in an HN comment. Honestly, if I could, I'd write the actual textbook - we really need a good one. I'm not claiming to have a rigorously tested model of exactly who to network with at a conference. I'm claiming that ignoring base rates results in worse decisions. And if I made this point in a non-political context - e.g., "you must account for the base rate for $disease when interpreting a $disease test" - no one would be disputing it. If you or anyone else here can even present a (utilitarian) model where ignoring base rates leads to a better decision, by all means do it. I'd love to see this, though I suspect the actual outcome of such an effort will merely be the person attempting to do it gaining a much better understanding of Bayes rule.
    - maxerickson 11y ago
      My issue isn't with the point that the base rate matters, it's with the mathematricality. And I do think that is fair, if there is not a simple way of actually measuring the utility and such (re your complaint about $diseases, medicine has at least somewhat reliable tests), all the stuff about the modeling is just theatrics.
      - yummyfajitas 11y ago
        Am I correct in interpreting this post as saying "I agree base rate matters, I just wish you didn't provide a toy example illustrating that?" Also, I now strongly recommend you go through the exercise I suggested. Then you'll realize that accurate tests do NOT somehow eliminate the need for models or accounting for base rates.
        maxerickson 11y ago
        Also, I now strongly recommend you go through the exercise I suggested. Then you'll realize that accurate tests do NOT somehow eliminate the need for models or accounting for base rates. I'm reaching for the opposite point. Some sort of meaningful evaluation of actual outcomes is necessary to make utilitarian decisions. If the evaluation of the outcome is arbitrary, then so is the decision.

beat 11y ago

First, morality matters. And you've forcibly ejected morality from your equation. Second, network effects matter. You're not just creating utilons for yourself, you're creating a system that creates utilons. Even within the small and inaccurate world of your invented model, you're not following through to conclusions. Third, you're making some very arbitrary assumptions, and ignoring other reasonable assumptions. For starters, do you give everyone you network with equal time? If you encounter a recruiter, do you give them the same amount of effort you would give to an engineer, or do you extract yourself and move on to the next person? The expense of equal input is not nearly as high as you're presenting here, assuming you don't "behave irrationally" and give everyone equal time whether it's effective or not. Pretending that bias and excuses are intellectual rigor by inserting arbitrary, invented numbers into an imaginary equation is just an appeal to authority fallacy.

blfr 11y ago
Yummyfajitas seems to be using utilitarian morality in his argument, not ejecting it altogether. That's what the concern with the net number of people harmed would suggest anyway.
- beat 11y ago
  Not really. It looks like utilitarian morality on the surface, but it lacks a rigorous analysis of consequences (as I pointed out on at least two fronts). Utilitarian morality's bootstrap definition requires rigor in order to use it - otherwise, there's a real danger of arriving at an immoral conclusion, which means it's not utilitarian. Putting a pig in a suit doesn't make it a gentleman. Which gets back to Occam's Razor. Which is more likely... that this was a failure of insufficient rigor, or that it was using utilitarianism and math to appeal to authority? Given that there were multiple violations of rigor, Occam's Razor suggests that this wasn't utilitarian morality at all, but rather mere defensive rhetoric. Of course, this doesn't imply intent - the author might not realize that his formal-sounding justification was actually rationalization, because of a failure to understand the underlying moral issue. Which is exactly how bias works in most cases. Someone put it really well recently, in the context of racism and racist police behavior. They said racism isn't waving a Confederate flag around. Racism is looking for excuses every time the police shoot another unarmed black man. People who don't think of themselves as racist or sexist, who actually find those ideas repulsive, are actively racist and sexist all the time! This is because they don't see the bias in their own behavior.