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Auditing Algorithms: A Rational Counterfactual Framework, Seung C. Lee

Journal of International Technology and Information Management

Artificial intelligence and machine learning algorithms are increasingly employed by the private and public sectors to automate simple and complex decision-making processes, but the hype has blinded people to the resulting discriminatory and biased decisions. To hold algorithms accountable for such decisions as well as to determine the underlying factors, researchers have turned to a methodological tool known as the audit study. Quite a few studies on algorithmic decision-making have made strong claims about the causality between algorithms and biased decisions. Multiple protective measures have also been enacted against the discriminatory and biased algorithmic decision-making practices. Nevertheless, they are persistent …