‘Algorithmic Discrimination’ Ban Bill Introduced By D.C. Attorney General
On Thursday (December 9), Washington D.C. Attorney General Karl Racine announced a groundbreaking bill to ban “algorihtmic discrimination,” which is the practice of computer algorithms that discriminate against certain people who apply for jobs, housing or a loan.
According to DCist, a letter to D.C. Council Chairman Phil Mendelson reveals the new legislation would build on the city’s existing Human Rights Act, which prohibits discrimination based on a number of protected characteristics. The Stop Discrimination by Algorithms Act cites that computer processes that use large amounts of data to produce specific predictions, results or outcomes are increasingly enmeshed in people’s lives, but can also “reflect and replicate historical bias, exacerbating existing inequalities and harming marginalized communities.”
“This so-called artificial intelligence is the engine of algorithms that are, in fact, far less smart than they are portrayed, and more discriminatory and unfair than big data wants you to know,” Racine said in a statement. “Our legislation would end the myth of the intrinsic egalitarian nature of AI.”
Cynthia Khoo, an associate at the Center on Privacy & Technology at the Georgetown Law Center, says that reliance on data for everything from ZIP codes of residence to traditional credit scores, both of which can be affected by historical patterns of discrimination, is the main source of the problem.
“If that data and those historical biases make it into these computational algorithms that are used to make important life decisions about people, such as whether to hire them, whether to rent to them, whether to approve a mortgage for them, then you basically end up with a form of technological discrimination against historically marginalized groups,” she notes.
An August investigation by The Markup revealed that lenders nationwide were 40 percent more likely to deny Latino applicants and 80 percent more likely to deny Black applicants than their white comparable applicants for loans.
Similarly, a 2015 Carnegie Mellon University study found that Google was more likely to show ads for high-paying jobs to men than to women, and in 2019, researchers reported that an algorithm used to make health care decisions in many U.S. hospitals was more likely to flag white patients for extra care than comparable Black patients.
“You see these kinds of patterns replicated across credit and finances and education, such as college admissions,” Khoo says. “So you can imagine the totality of the impact when across somebody’s life, particularly if they are Black or brown or part of a marginalized group.”
If passed, the legislation would make it illegal for companies to use discriminatory algorithms to decide education, job, access to credit, health care, housing or insurance outcomes. It’d also require companies to conduct annual audits on their algorithms, show how they’re built, and have them disclose to consumers how they’re used to make decisions. A fine of up to $10,000 would be levied if an algorithm’s decision is wrongly selected against a consumer.
