As science fiction buffs (and Tom Cruise fans) know, “Minority Report” is a short story by Philip K. Dick in which the Precrime Division of a futuristic law enforcement agency uses advanced computers (and mutants) to identify people who are going to commit crimes and then arrests and imprisons those people before the crimes are actually committed. A recent BloombergLaw report — “Machine Learning Deployed to Help EEOC Predict Discrimination” — suggests that this kind of “predictive policing” may not be science fiction for much longer:
In the not-so-distant future, machine learning may help civil-rights agencies predict who could face workplace discrimination.
Samuel Christopher Haffer, the first chief data officer hired by the Equal Employment Opportunity Commission, said his goal is to create a “distant early warning system,” examining things like “intersectionality,” or groups of similar qualities like race, gender, or ethnicity. Machine learning—the algorithmic study of past experiences to optimize, or predict, future experiences—will have a lot to do with that.
Hypothetically, this could mean the agency would be able to flag a particular group of people in a specific industry who would be susceptible to discrimination. The agency would then be able to target outreach to those workers to make them aware of their rights, he said.
“That team of social scientists and data scientists will be looking at the treasure trove of data that we have here at the agency to look at trends and patterns at the enterprise level,” Haffer told Bloomberg Law in a recent interview. …
The EEOC also is planning to partner with other federal agencies, such as the U.S. Census Bureau, Haffer said. The EEOC has memorandums of understanding with divisions within the departments of Labor, Health and Human Services, Justice, and Homeland Security, among others.
The agency hopes to better illustrate and understand worker threats to accomplish its mission “to prevent and remedy,” he said. …
The “early warning system” is still three to five years away, he said. …
