4 ms·

Since you claim that "racism and sexism are useful and predictive heuristics," does that mean mainstream society should accept/tolerate/promote such belief syst

by rmxt 11y ago

Since you claim that "racism and sexism are useful and predictive heuristics," does that mean mainstream society should accept/tolerate/promote such belief systems? Who is it exactly that you think would find these heuristics useful? Also, describing the results of any code/program written by a human as a "completely inhuman intelligence" is a tenuous claim at best.

smtddr 11y ago
Just fyi, several people have tried engaging this person in similar discussions before... https://news.ycombinator.com/item?id=8613711 https://news.ycombinator.com/item?id=8613711
- deleted 11y ago
  [deleted]
- Baghard 11y ago
  Now is this an example of predictive analytics or of human prejudice? :)
  - deleted 11y ago
    [deleted]
yummyfajitas 11y ago
I'm not taking any normative position. I'm simply pointing out that the implicit assumption underlying lots of modern beliefs - that racism/other evil beliefs lead to factually wrong beliefs - is being challenged by "racist" and "sexist" machine learning algorithms. If you want to make normative arguments, go ahead. My first principles tend to be very individualistic (I view individual humans as being the sole carriers of moral consideration), so our normative claims will likely disagree. Also, describing the results of any code/program written by a human as a "completely inhuman intelligence" is a tenuous claim at best. Clearly you've never written such systems. If they behaved remotely the way humans think my job (building them and making them usable by humans) would be vastly easier.
- rmxt 11y ago
  I understand the difference between a normative claim and a positive claim. You might not be taking a normative position explicitly, but your distaste is showing through: "allegedly come from," "obfuscate this point". I'd like to see where you go with this (both your distaste and positive statements) -- even if what you're saying is accurate/factual, what implications does that have for society at large? For the intersection of machine learning and society? Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman. Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction?
  - yummyfajitas 11y ago
    I have distaste for the anti-intellectual behavior/ideology underlying the NYT/Salon articles, and which is also visible in this comment thread. Doubly so since it's so dominant in our culture and since it is being used as a rhetorical weapon against tech. The implication for society (assuming these findings generalize) is that most likely, we cannot solve statistical disparities via unbiased processes - we can have fair treatment of individuals or statistically representative distribution of spoils, but not both. As noted above, I'm very individualistic, so I favor fair treatment of individual humans. Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman. I don't know what you mean by "inhuman". It sounds like you mean the term to be "never tainted by the ephemeral emanations of humanity". I merely mean "inhuman" as "thought processes so radically different that intuitions about a human mind are completely useless". Concretely, do you believe a random forest can somehow infer that the variable x[27] represents gender, and that to make it's sexist creator happy it should reduce the objective function in order to screw some women over? If you look at the internals of sklearn, that's just not what random forests do. Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction? I don't know what you mean by "morally satisfied". A fact about the world is either true or false. In computer science terms, I believe "morally satisfied" has type `satisfied: HumanAction -> Boolean`. Your question consists of applying `satisfied` to a value of type `WorldState` - it's a type error. In human terms, your question doesn't make sense. In terms of my own individual happiness (as distinguished from moral satisfaction), this fact reduces my happiness. Because I believe many of these facts to be true, I'm forced to either lie about my beliefs (which causes me disutility) or suffer social opprobrium from anti-intellectual types and lazy thinkers influenced by them.

by rmxt 11y ago

smtddr 11y ago

Just fyi, several people have tried engaging this person in similar discussions before... https://news.ycombinator.com/item?id=8613711 https://news.ycombinator.com/item?id=8613711

deleted 11y ago
[deleted]
Baghard 11y ago
Now is this an example of predictive analytics or of human prejudice? :)
- deleted 11y ago
  [deleted]

yummyfajitas 11y ago

I'm not taking any normative position. I'm simply pointing out that the implicit assumption underlying lots of modern beliefs - that racism/other evil beliefs lead to factually wrong beliefs - is being challenged by "racist" and "sexist" machine learning algorithms. If you want to make normative arguments, go ahead. My first principles tend to be very individualistic (I view individual humans as being the sole carriers of moral consideration), so our normative claims will likely disagree. Also, describing the results of any code/program written by a human as a "completely inhuman intelligence" is a tenuous claim at best. Clearly you've never written such systems. If they behaved remotely the way humans think my job (building them and making them usable by humans) would be vastly easier.

rmxt 11y ago
I understand the difference between a normative claim and a positive claim. You might not be taking a normative position explicitly, but your distaste is showing through: "allegedly come from," "obfuscate this point". I'd like to see where you go with this (both your distaste and positive statements) -- even if what you're saying is accurate/factual, what implications does that have for society at large? For the intersection of machine learning and society? Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman. Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction?
- yummyfajitas 11y ago
  I have distaste for the anti-intellectual behavior/ideology underlying the NYT/Salon articles, and which is also visible in this comment thread. Doubly so since it's so dominant in our culture and since it is being used as a rhetorical weapon against tech. The implication for society (assuming these findings generalize) is that most likely, we cannot solve statistical disparities via unbiased processes - we can have fair treatment of individuals or statistically representative distribution of spoils, but not both. As noted above, I'm very individualistic, so I favor fair treatment of individual humans. Appeals to authority and accomplishments aside, I don't need to have written such systems to understand, infer, and conclude things about aspects of their behavior. My point is this: something created by humans cannot be, by definition, inhuman. I don't know what you mean by "inhuman". It sounds like you mean the term to be "never tainted by the ephemeral emanations of humanity". I merely mean "inhuman" as "thought processes so radically different that intuitions about a human mind are completely useless". Concretely, do you believe a random forest can somehow infer that the variable x[27] represents gender, and that to make it's sexist creator happy it should reduce the objective function in order to screw some women over? If you look at the internals of sklearn, that's just not what random forests do. Two methodologies, the "human approach" and the "ML approach", might have radically different steps but come to the same conclusions. It would appear from your comments that you are OK with these conclusions ("An unbiased methodology produced these results, therefore, it's OK!"). Are you morally satisfied by the conclusions discussed above? Do the results of "such systems" influence your satisfaction? I don't know what you mean by "morally satisfied". A fact about the world is either true or false. In computer science terms, I believe "morally satisfied" has type `satisfied: HumanAction -> Boolean`. Your question consists of applying `satisfied` to a value of type `WorldState` - it's a type error. In human terms, your question doesn't make sense. In terms of my own individual happiness (as distinguished from moral satisfaction), this fact reduces my happiness. Because I believe many of these facts to be true, I'm forced to either lie about my beliefs (which causes me disutility) or suffer social opprobrium from anti-intellectual types and lazy thinkers influenced by them.