4 ms·

>[...] concept called equal opportunity. Here, the constraint is that of the people who can pay back a loan, the same fraction in each group should actually be

by Scea91 10y ago

>[...] concept called equal opportunity. Here, the constraint is that of the people who can pay back a loan, the same fraction in each group should actually be granted a loan. This does not seem fair to me, because if this is applied then your race (group) would determine your credit score threshold which feels discriminatory to me. I feel that, by definition, it is not discriminatory only if none of your attributes that you could be discriminated against (gender, race, ...) are taken into account at all. Maybe the concept of 'equal opportunity' is just some compromise between discrimination and making less informed decisions.

raverbashing 10y ago
Well, "theoretically" you're right In practice, the first variables to be used for classification are the ones that have a biggest effect. Then you're going to use them (from order of importance) as eliminatory or classificatory > because if this is applied then your race (group) would determine your credit score threshold which feels discriminatory to me. But the opposite is also discriminatory, which is what the article is showing. Because then you're using the same ruler to evaluate different groups, and of course the minority person with 2 jobs can't match the credit score of an Ivy-League educated WASP
tomp 10y ago
I think it's useful to figure out why there are discrepancies between two groups. For example, let's take blacks in the US. The data tells you that a black person is more likely to be a criminal than a white person. There are two possible reasons for this: (1) blacks are more prone to crime, or (2) blacks are more likely to live in circumstances that make them criminals. With access to only anecdotal data, I strongly believe that (2) is true, and that if you took into account enough circumstances (e.g. single parent, school district, income level, parents' wealth) you'd be able to remove race from your model and still arrive to the "equal opportunity" result. That way, you wouldn't discriminate based on race, but you would still help the people most needy of help (poor, uneducated, etc.). I think the same applies to colege applications and sex wage gap, which is why I strongly oppose any kind of affirmative action. Life expentancy sex gap might be a different case. IIRC, men die earlier because of some behavioural/social tendencies (working dangerous jobs, supressing emotions, risky behaviour (speeding, smoking)), so maybe there are some non-discriminatory (or at least less-discriminatory) ways of determining life expectancy (e.g. testosterone level, job description, ...). However, there are also biological differences that seem very strongly linked to the quality of being male (i.e. the Y chromosome). E.g. prostate cancer is less lethal than breast cancer, and women are more likely to get MS than men. These particular examples suggest that men should live longer, but I'm guessing there might be other gender-specific ilnesses that might reduce their (our) expected lifespan. If that's the case, I don't think it's too discriminatory to have different insurance fees for different sexes. In all such scenarios, however, there could still be broader societal goals that would override specific instances of (non-)discrimination. For exapmle, AFAIK women's health is more expensive (because of pregnancy), but having more children benefits everyone in the society (in the West), so it makes sense to "discriminate" against men by letting women pay less for their health insurance.
- corey_moncure 10y ago
  > The data tells you that a black person is more likely to be a criminal than a white person. There are two possible reasons for this: I'd like to add a third possible reason for your consideration. Since "criminality" i.e. guilt of committing a crime is determined after a process engaging the law enforcement and justice systems, we have to examine whether there are inherent biases in those systems that result in skewed statistics. For instance, do police officers selectively target blacks for monitoring and investigation? Are blacks discriminated against in the courtroom as a result of procedure or human nature?
  - zmoreira 10y ago
    This is studiable and has been studied. A study regarding police killings, for example: Do White Police Officers Unfairly Target Black Suspects? https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870189&download=yes https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870189&... Using a unique data set we link the race of police officers who kill suspects with the race of those who are killed across the United States. We have data on a total of 2,699 fatal police killings for the years 2013 to 2015. This is 1,333 more killings by police than is provided by the FBI data on justifiable police homicides. When either the violent crime rate or the demographics of a city are accounted for, we find that white police officers are not significantly more likely to kill a black suspect. For the estimates where we know the race of the officer who killed the suspect, the ratio of the rate that blacks are killed by black versus white officers is large — ranging from 3 to 5 times larger. However, because the media may under report the officer’s race when black offic-ers are involved, other results that account for the fact that a disproportionate number of the un-known race officers may be more reliable. They indicate no statistically significant difference be-tween killings of black suspects by black and white officers. Our panel data analysis that looks at killings at the police department level confirms this. These findings are inconsistent with taste-based racial discrimination against blacks by white police officers. Our estimates examining the killings of white and Hispanic suspects found no differences with respect to the races of police officers. If the police are engaged in discrimination, such discriminatory behavior should also be more difficult when body or other cameras are recording their actions. We find no evidence that body cameras affect either the number of police killings or the racial composition of those killings.
ascendingPig 10y ago
Why should it not be fair? Under this constraint, the perfect equal opportunity model would be a model that accurately represents who will pay back a loan.
deong 10y ago
But how do you do that? Race is baked into a lot of the attributes your classifier is going to find informative. Is someone a good credit risk? To decide, you look at features like past payment history, available balance, zip code, etc. Past payment history: if you're black, prior discriminatory behaviors may have limited your ability to open credit accounts, and thus you have less history to go on. Available balance has the same reasoning. Zip code correlates with race. I'd hope very few people are including an "is_black" feature in their classifiers. If you eliminate anything that is informative towards race though, you're likely going to have a classifier that doesn't work very well. The problem is that we have datasets that have arisen from a history that included significant racism, both overt and latent. There is no way to separate those effects from the data. You either get an "optimal" classifier that is racially biased in ways we don't want, or you get one that intentionally gives up some perceived performance in favor of fairness.
- deleted 10y ago
  [deleted]
- tboyd47 10y ago
  You'd be surprised. If you've ever racially identified on a standardized test, guess what, you've just set the is_black feature.

by Scea91 10y ago

raverbashing 10y ago

Well, "theoretically" you're right In practice, the first variables to be used for classification are the ones that have a biggest effect. Then you're going to use them (from order of importance) as eliminatory or classificatory > because if this is applied then your race (group) would determine your credit score threshold which feels discriminatory to me. But the opposite is also discriminatory, which is what the article is showing. Because then you're using the same ruler to evaluate different groups, and of course the minority person with 2 jobs can't match the credit score of an Ivy-League educated WASP

tomp 10y ago

I think it's useful to figure out why there are discrepancies between two groups. For example, let's take blacks in the US. The data tells you that a black person is more likely to be a criminal than a white person. There are two possible reasons for this: (1) blacks are more prone to crime, or (2) blacks are more likely to live in circumstances that make them criminals. With access to only anecdotal data, I strongly believe that (2) is true, and that if you took into account enough circumstances (e.g. single parent, school district, income level, parents' wealth) you'd be able to remove race from your model and still arrive to the "equal opportunity" result. That way, you wouldn't discriminate based on race, but you would still help the people most needy of help (poor, uneducated, etc.). I think the same applies to colege applications and sex wage gap, which is why I strongly oppose any kind of affirmative action. Life expentancy sex gap might be a different case. IIRC, men die earlier because of some behavioural/social tendencies (working dangerous jobs, supressing emotions, risky behaviour (speeding, smoking)), so maybe there are some non-discriminatory (or at least less-discriminatory) ways of determining life expectancy (e.g. testosterone level, job description, ...). However, there are also biological differences that seem very strongly linked to the quality of being male (i.e. the Y chromosome). E.g. prostate cancer is less lethal than breast cancer, and women are more likely to get MS than men. These particular examples suggest that men should live longer, but I'm guessing there might be other gender-specific ilnesses that might reduce their (our) expected lifespan. If that's the case, I don't think it's too discriminatory to have different insurance fees for different sexes. In all such scenarios, however, there could still be broader societal goals that would override specific instances of (non-)discrimination. For exapmle, AFAIK women's health is more expensive (because of pregnancy), but having more children benefits everyone in the society (in the West), so it makes sense to "discriminate" against men by letting women pay less for their health insurance.

corey_moncure 10y ago
> The data tells you that a black person is more likely to be a criminal than a white person. There are two possible reasons for this: I'd like to add a third possible reason for your consideration. Since "criminality" i.e. guilt of committing a crime is determined after a process engaging the law enforcement and justice systems, we have to examine whether there are inherent biases in those systems that result in skewed statistics. For instance, do police officers selectively target blacks for monitoring and investigation? Are blacks discriminated against in the courtroom as a result of procedure or human nature?
- zmoreira 10y ago
  This is studiable and has been studied. A study regarding police killings, for example: Do White Police Officers Unfairly Target Black Suspects? https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870189&download=yes https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870189&... Using a unique data set we link the race of police officers who kill suspects with the race of those who are killed across the United States. We have data on a total of 2,699 fatal police killings for the years 2013 to 2015. This is 1,333 more killings by police than is provided by the FBI data on justifiable police homicides. When either the violent crime rate or the demographics of a city are accounted for, we find that white police officers are not significantly more likely to kill a black suspect. For the estimates where we know the race of the officer who killed the suspect, the ratio of the rate that blacks are killed by black versus white officers is large — ranging from 3 to 5 times larger. However, because the media may under report the officer’s race when black offic-ers are involved, other results that account for the fact that a disproportionate number of the un-known race officers may be more reliable. They indicate no statistically significant difference be-tween killings of black suspects by black and white officers. Our panel data analysis that looks at killings at the police department level confirms this. These findings are inconsistent with taste-based racial discrimination against blacks by white police officers. Our estimates examining the killings of white and Hispanic suspects found no differences with respect to the races of police officers. If the police are engaged in discrimination, such discriminatory behavior should also be more difficult when body or other cameras are recording their actions. We find no evidence that body cameras affect either the number of police killings or the racial composition of those killings.

ascendingPig 10y ago

Why should it not be fair? Under this constraint, the perfect equal opportunity model would be a model that accurately represents who will pay back a loan.

deong 10y ago

But how do you do that? Race is baked into a lot of the attributes your classifier is going to find informative. Is someone a good credit risk? To decide, you look at features like past payment history, available balance, zip code, etc. Past payment history: if you're black, prior discriminatory behaviors may have limited your ability to open credit accounts, and thus you have less history to go on. Available balance has the same reasoning. Zip code correlates with race. I'd hope very few people are including an "is_black" feature in their classifiers. If you eliminate anything that is informative towards race though, you're likely going to have a classifier that doesn't work very well. The problem is that we have datasets that have arisen from a history that included significant racism, both overt and latent. There is no way to separate those effects from the data. You either get an "optimal" classifier that is racially biased in ways we don't want, or you get one that intentionally gives up some perceived performance in favor of fairness.

deleted 10y ago
[deleted]
tboyd47 10y ago
You'd be surprised. If you've ever racially identified on a standardized test, guess what, you've just set the is_black feature.