Sweeney says there are essentially three possibilities. One is that www.instantcheckmate.com has set up the arrest-mentioning ads to be served up to black identifying names. Another is that Google has somehow biased its ad serving mechanism in this way.
A more insidious explanation is that society as a whole is to blame. If Google’s Adsense service learns which ad combinations are more effective, it would first serve the arrest-related ads to all names at random. But this would change if it were to discover that click-throughs are more likely when these ads are served against a black-identifying name. In other words, the results merely reflect the discriminatory pattern of clicks from ordinary people.
Keep in mind that the professor did not write this article, which buries her methods and conclusions. In her actual paper (http://arxiv.org/abs/1301.6822) she has possible solutions in the conclusions.
Suppose you'd never heard of this study, and some conservative institution announced a finding that names associated with males (Steve, Darnell) were more likely to bring up ads mentioning arrest records than names associated with females (Emily, Latisha). Suppose the paper announcing this discovery was full of terms like "discrimination" and "fairness," and speculated about who or what was to "blame" for treating men in this discriminatory way.
Would the politically enlightened consider this increased association of men with arrest records (vs women) to be unfair bias against men? Would there be a call for a followup to determine whether it was a biased algorithm, a discriminatory corporation, or our entire anti-male sexist society that was to blame? Might they shrug it off, placing most of the blame, not on the ad system, but on the statistical behavior of men themselves?
If there is, as I suspect, a similar "bias" against men in this ad system, then any discussion of how to "fix" it should not address the question of black/white names. It ought to deal with the larger question of what to do when the data show that the probability of X given name 'A' is greater than the probability of X given name 'B'.
Thank you for the link. The conclusions seem to me to be accurately relayed by the first article, and my priors were accurate. There is still not a statement that I see of what the desired outcome should be.
Let me go ahead and spell out what I mean. Should the Google search results give the exact same % of results for each race? Should it accurately reflect the % of searches? Should it accurately reflect the % of ads put in? (Those are all 3 very different things.) If so, should Google tweak the percentage of those ads? If so, in what manner? If a combination, which combination?
The implication in the conclusion is that first one, but in that case, why does that one override the others? Might in fact be racist to hide the incidence of these searches, based on race? A case could be made for that, after all.
These are rich and interesting questions, and it does not simply go without saying what the desired outcome is.
The null hypothesis is described at the beginning of page 4, under the heading 'problem statement': Our hypothesis: no difference exists in the delivery of ads suggestive of an arrest record responding to online searches of racially associated names. Then, when presented with evidence of a pattern to the contrary, examine the pattern’s credibility, likelihood and circumstances of occurring. This hypothesis is briefly restated in the conclusion.
Methods are spelled out beginning on page 10, observations and how they compare to specific expectations are spelled out beginning on page 20. I can only infer that you didn't bother to read the paper.
Comments
Sweeney says there are essentially three possibilities. One is that www.instantcheckmate.com has set up the arrest-mentioning ads to be served up to black identifying names. Another is that Google has somehow biased its ad serving mechanism in this way.
A more insidious explanation is that society as a whole is to blame. If Google’s Adsense service learns which ad combinations are more effective, it would first serve the arrest-related ads to all names at random. But this would change if it were to discover that click-throughs are more likely when these ads are served against a black-identifying name. In other words, the results merely reflect the discriminatory pattern of clicks from ordinary people.
Keep in mind that the professor did not write this article, which buries her methods and conclusions. In her actual paper (http://arxiv.org/abs/1301.6822) she has possible solutions in the conclusions.
Suppose you'd never heard of this study, and some conservative institution announced a finding that names associated with males (Steve, Darnell) were more likely to bring up ads mentioning arrest records than names associated with females (Emily, Latisha). Suppose the paper announcing this discovery was full of terms like "discrimination" and "fairness," and speculated about who or what was to "blame" for treating men in this discriminatory way.
Would the politically enlightened consider this increased association of men with arrest records (vs women) to be unfair bias against men? Would there be a call for a followup to determine whether it was a biased algorithm, a discriminatory corporation, or our entire anti-male sexist society that was to blame? Might they shrug it off, placing most of the blame, not on the ad system, but on the statistical behavior of men themselves?
If there is, as I suspect, a similar "bias" against men in this ad system, then any discussion of how to "fix" it should not address the question of black/white names. It ought to deal with the larger question of what to do when the data show that the probability of X given name 'A' is greater than the probability of X given name 'B'.
Thank you for the link. The conclusions seem to me to be accurately relayed by the first article, and my priors were accurate. There is still not a statement that I see of what the desired outcome should be.
Let me go ahead and spell out what I mean. Should the Google search results give the exact same % of results for each race? Should it accurately reflect the % of searches? Should it accurately reflect the % of ads put in? (Those are all 3 very different things.) If so, should Google tweak the percentage of those ads? If so, in what manner? If a combination, which combination?
The implication in the conclusion is that first one, but in that case, why does that one override the others? Might in fact be racist to hide the incidence of these searches, based on race? A case could be made for that, after all.
These are rich and interesting questions, and it does not simply go without saying what the desired outcome is.
The null hypothesis is described at the beginning of page 4, under the heading 'problem statement': Our hypothesis: no difference exists in the delivery of ads suggestive of an arrest record responding to online searches of racially associated names. Then, when presented with evidence of a pattern to the contrary, examine the pattern’s credibility, likelihood and circumstances of occurring. This hypothesis is briefly restated in the conclusion.
Methods are spelled out beginning on page 10, observations and how they compare to specific expectations are spelled out beginning on page 20. I can only infer that you didn't bother to read the paper.
So you're saying that because there isn't a known solution, yet, it isn't useful to point out the problem.
That makes no sense whatsoever.