Are Well-Calibrated Users Effective Users? Associations Between Calibration of Trust and Performance on an Automation-Aided Task

By Stephanie M. Merritt, Deborah Lee, Jennifer L. Unnerstall, Kelli Huber. 2015

75 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Social Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xinru Wang
2. Ming Yin
3. Q. Liao

In Social Psychology

1. Ming Yin
2. Xinru Wang

Citations in the corpus

• Metrics for Explainable AI: Challenges and Prospects (2018, neutral): “…et al., 2015; Hoff and Bashir 2015; Fitzhugh, Hoffman & Miller, 2011; Hoffman et al., 2009, 2013; Huynh et al., 2006; Kucala, 2013; Lee & See, 2004; Merritt and Ilgen, 2008; Merritt et al. 2013, 2015; Naone, 2009; Pop et al. 2015; Shadbolt, 2002; Wickens et al., 2015; Woods and Hollnagel 2006).”
• Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making (2021, methodology): “Finally, for RQ3 , we evaluated participants’ capability of calibrating their trust in the ML model using three main dependent variables, including their appropriate trust [51–53, 56”