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Mahsan Nourani

2 papers indexed

arxivcs.HCcs.AI2026-07-20

Human-in-the-Loop User Feedback Affects Perceived Accuracy and Trust, but Task Subjectivity Matters

Donald R. Honeycutt, Mahsan Nourani, Eric D. Ragan

While ML can produce complex models beyond those that a human could produce manually, incorporating human input can often improve performance beyond purely data-driven models. While this feedback could come from system designers or domain experts, in many cases, the end users who…

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arxivcs.HCcs.AI2026-07-14

"Trust Junk" Leads to Unjustified Support for Highly Discriminatory Predictive Models

Michael Correll, Lucy Havens, Mahsan Nourani

The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper, we use a crowdsourced study to show that providing accurate (but superfluous or irrelevant) data i…

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