Influencing Preferences for Different Types of Causal Explanation of Complex Events
By Gary Klein, L. Rasmussen, Mei-Hua Lin, Robert R. Hoffman, Jason Case. 2014
17 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Developmental and Educational Psychology, General Decision Sciences
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
- Q. Liao
- Shane T. Mueller
- Gary Klein
- Robert R. Hoffman
- William J. Clancey
- Abigail Emrey
- Yunfeng Zhang
- Rachel K. E. Bellamy
In Developmental and Educational Psychology
In General Decision Sciences
- Robert R. Hoffman
- Shane T. Mueller
- Q. Liao
- Gary Klein
- William J. Clancey
- Abigail Emrey
- Ivano Cardinale
Citations in the corpus
- Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “Individual differences research relevant to explanation includes: Fernbach, Sloman, St. Louis, and Shube (2013); Gopnik (2000); Keil (2006); Klein et al. (2014); Lipton (2000); Litman and”
- Explaining models: an empirical study of how explanations impact fairness judgment (2019, background): “For example, research shows that some prefer simple, supericial explanations and others are more deliberative and relective in their reasoning [13, 19].”