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Or that if you feed data which contains clear indicators of bias/prejudice into your ML system, it will discover those biases and prejudices and learn and incor

Or that if you feed data which contains clear indicators of bias/prejudice into your ML system, it will discover those biases and prejudices and learn and incorporate them. Got a training set which dates to when banks redlined black people? Congratulations, the model just learned not to make loans to black people! And now it's "objective", because no humans are involved in making its decisions!

barry-cotter 9y ago
If you define an objective function based on some set of predictors, none of which contains a Black variable then it is not possible for your model to discriminate against Black people because it doesn’t know if anyone is black. Assuming, ridiculously conservatively that redlining ended in 1979 any dataset will have 37 non redlined years in it, 1980-2017. Given that the further away in time a datapoint is the less weight it’s given in predicting anything redlining will have bigger all impact on any model. Asian people in the US on average have higher credit scores than white people. This is not anti-white discrimination because white and Asian are not used to determine credit score, it’s based on on-time payment, capacity used, length of credit history, types of credit used and past credit applications. There are many wonderful MOOCs and textbooks on ML, AI and statistics. If you want to understand how statistical modelling works I can recommend the Georgia TechX MicroMasters in Analytics. Don’t listen to statistically illiterate journalists.
- pdkl95 9y ago
  > redlining ended Redlining is only one of the many racists housing practices that have existed and continue to exist today.l > in 1979 Have you even done any research on this topic? From a famous article[1] about the history of racism in housing: >> In 2011, Bank of America agreed to pay $355 million to settle charges of discrimination against its Countrywide unit. The following year, Wells Fargo settled its discrimination suit for more than $175 million. But the damage had been done. In 2009, half the properties in Baltimore whose owners had been granted loans by Wells Fargo between 2005 and 2008 were vacant; 71 percent of these properties were in predominantly black neighborhoods. > 37 non redlined years Those are also years of sub-standard schools, poor job prospects, and (in some cities) toxic levels of lead paint. Growing up in that kind of environment can limit your options severely. > it is not possible for your model to discriminate against Black people because it doesn’t know if anyone is black. I always like to assume ignorance over malice, so I will simply suggest that you should do a lot more research before making this kind of claim. [1] https://www.theatlantic.com/magazine/archive/2014/06/the-case-for-reparations/361631/ https://www.theatlantic.com/magazine/archive/2014/06/the-cas...

barry-cotter 9y ago

If you define an objective function based on some set of predictors, none of which contains a Black variable then it is not possible for your model to discriminate against Black people because it doesn’t know if anyone is black. Assuming, ridiculously conservatively that redlining ended in 1979 any dataset will have 37 non redlined years in it, 1980-2017. Given that the further away in time a datapoint is the less weight it’s given in predicting anything redlining will have bigger all impact on any model. Asian people in the US on average have higher credit scores than white people. This is not anti-white discrimination because white and Asian are not used to determine credit score, it’s based on on-time payment, capacity used, length of credit history, types of credit used and past credit applications. There are many wonderful MOOCs and textbooks on ML, AI and statistics. If you want to understand how statistical modelling works I can recommend the Georgia TechX MicroMasters in Analytics. Don’t listen to statistically illiterate journalists.

pdkl95 9y ago
> redlining ended Redlining is only one of the many racists housing practices that have existed and continue to exist today.l > in 1979 Have you even done any research on this topic? From a famous article[1] about the history of racism in housing: >> In 2011, Bank of America agreed to pay $355 million to settle charges of discrimination against its Countrywide unit. The following year, Wells Fargo settled its discrimination suit for more than $175 million. But the damage had been done. In 2009, half the properties in Baltimore whose owners had been granted loans by Wells Fargo between 2005 and 2008 were vacant; 71 percent of these properties were in predominantly black neighborhoods. > 37 non redlined years Those are also years of sub-standard schools, poor job prospects, and (in some cities) toxic levels of lead paint. Growing up in that kind of environment can limit your options severely. > it is not possible for your model to discriminate against Black people because it doesn’t know if anyone is black. I always like to assume ignorance over malice, so I will simply suggest that you should do a lot more research before making this kind of claim. [1] https://www.theatlantic.com/magazine/archive/2014/06/the-case-for-reparations/361631/ https://www.theatlantic.com/magazine/archive/2014/06/the-cas...