The influence of the causal background on the selection of causal explanations

By Ann L. McGill. 1991

How researchers see this paper

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

1. Shane T. Mueller
2. Robert R. Hoffman
3. Gary Klein
4. Abigail Emrey
5. William J. Clancey
6. D. Gunning
7. Sina Mohseni
8. Kejkaew Thanasuan

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): “nd to be discounted if they refer to multiple alternative possible causes that reduce the plausibility, relevance or informativeness of the preferred (Einhorn and Hogarth, 1986; Hilton and Erb, 1996; McGill, 1991; Sloman, 1994). Hypothesis: Explanations are good if they make sense in terms of the co”