A recent study by researchers from Princeton University and USC suggests that Meta’s algorithms for presenting educational ads exhibit signs of racial bias, particularly in the delivery of ads realated to for-profit universities and those with a history of predatory marketing practices.
The researchers employed a method that uses a pair of education ads for seemingly equivalent opportunities, with one opportunity tied to a historical racial disparity that ad delivery algorithms may propagate. If the ad for the for-profit college is shown to relatively more Black users than the ad for the public college, the algorithmic choices of the platform can be considered racially discriminatory.
Korolova, one of the authors, stated that while only Meta knows how its ad algorithms work, the researchers suspect that the observed algorithmic effects are driven by proxies and other historical data Meta may rely upon, rather than the direct use of race. The findings could have legal consequences for Meta under the doctrine of disparate impact of discrimination. The researchers argue that Meta has taken a narrow view of compliance, focusing on discrimination in housing, employment, and credit ads, while not adequately addressing algorithmic bias in ad delivery more broadly.
Meta spokesperson Daniel Roberts told The Register: “Addressing fairness in ads is an industry-wide challenge and we’ve been collaborating with civil rights groups, academics, and regulators to advance fairness in our ads system. Our advertising standards do not allow advertisers to run ads that discriminate against individuals or groups of individuals based on personal attributes such as race and we are actively building technology designed to make additional progress in this area.
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