When Accuracy Isn’t Enough: Visualization and Game Design

Modeling typically starts with defining a metric to optimize and, often, this definition of “good” leaves something out. Boosting precision can create room for discrimination, optimizing profit may reinforce inequity, and bad behavior can hide behind good performance metrics [1][2][3]. Data science offers many tools for optimization but consider defining the problem itself: what makes a solution desirable and what behaviors mean it works as intended? There’s no one answer with lots of work ongoing in this space …

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