Before the algorithmic systems being deployed to assist with decision making in both public and private sectors came into being—and before they were shown to be harmful to various groups of people because of predictions based on presumed relationships found in data—they existed in the minds of designers, product managers, and organizations. Scholars have shown the issues with using biased data stemming from structurally unfair systems, as well as the implications of using unfair models. But also important is the ideation behind these systems, and how imaginaries shape their creation and the problems found within them. Insights Algorithmic…
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