Eksemplet er inspireret af Jonathan Vanians artikel "Unmasking A.I.'s Bias Problem":


example, a data set about auto accident claims. The data shows that accidents are more likely to take place in inner cities, where densely packed populations create more opportunities for fender benders. Inner cities also tend to have disproportionately high numbers of minorities among their residents. A deep-learning program, sifting through data in which these correlations were embedded, could “learn” that there was a relationship between belonging to a minority and having car accidents, and could build that lesson into its assumptions about all drivers of color.


I en artikel i New York Times "A.I. Is Changing Insurance" hedder det:


ProPublica found that people in minority neighborhoods paid higher car insurance premiums than residents of majority-white neighborhoods with similar risk


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