The Construction of Explanations

By Ruth M. J. Byrne. 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. Bhavana Dalvi
5. Abigail Emrey
6. William J. Clancey
7. Tim Miller
8. Peter Clark

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): “…of explanation, or descriptions of properties of explanation, either as the main thesis of a paper or as preliminary or synthesized discussion (Byrne, 1991; Felton, 2017; Kass and Leake, 1987; Kulesza et al., 2015; Rosenthal et al., 2016; Sørmo, Cassens, and Aamodt, 2005; Swartout and Moore,…”
• Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, background): “Byrne [16] offers a similar argument in her computational model of explanation selection, noting that humans are model-based, not proof-based, so explanations must be relevant to a model.”
• DREAM: Uncovering Mental Models behind Language Models (2021, background): “It suggests that people solve situated problems by elaborating a mental picture of the situation, including elements that may be peripheral to a specific answer, rather than constructing a deductive proof from a few key facts to an answer (Byrne, 1991).”