Conversational processes and causal explanation.

By Denis J. Hilton. 1990

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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): “Hilton (1990, 2005); Hilton, McClure, and Sutton (2010); Klein, Rasmussen, Lin, Hoffman, and Case(2014); Krull and Anderson (1997); Lombrozo (2007, 2010, 2010); McGill (1991); Rasmussen, Nixon, and Warner (1990); Samurçay and Hoc (1996); Selfridge, Daniell, and Simmons, D. (1985); Woodward, (2005);…”
Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences (2017, background): “Most philosophers, psychologists, and cognitive scientists in this ﬁeld assert that all why–questions are contrastive (e.g. see [Hilton, 1990; Lombrozo, 2012; Miller, 2017]), and that when people ask for an explanation “ Why P ?”
Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, methodology): “Most authors in this area argue that all why–questions ask for contrastive explanations, even if the foils are not made explicit [102, 77, 69, 72, 110, 108], and that people are good at inferring the foil; e.”
The challenge of crafting intelligible intelligence (2018, background): “Social science research suggests that an explanation is best considered a social process, a conversation between explainer and explainee [15, 30].”
Explaining Explanations in AI (2018, background): “Explanations can be conceived as involving one or more explainers and explainees engaging in information transfer through dialogue, visual representation, or other means (Hilton, 1990), often to correct information or knowledge assymetry (Lim and Dey, 2009).”
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects (2020, background): “, where Q is often implicit in the context [81].”
Countering Fatalism: Causal Information in News Reports Affects Judgments About Earthquake Damage (2001, background): “This choice suggests that their judgments reflect what can be taken for granted and what is informative, in that the earthquake itself appears to be taken for granted (Grice, 1975; Hilton, 1990; McClure, 1998).”
Accounting for the effects of accountability. (1999, background): “For example, the costs of judgment inaccuracy may be offset by the social or political benefits of getting along with a conversation partner by respecting norms (Dulany & Hilton, 1991; Grice, 1975; Hilton, 1990; Rrosnick, Li, & Lehman, 1990; Schwarz, Strack, Hilton, & Naderer, 1991; Tetlock et al., ”
How People Explain Action (and Autonomous Intelligent Systems Should Too) (2017, background): “Explanation is arguably a three-value predicate: someone, a communicator, explains something to someone, an audience (Bromberger 1965; Hilton 1990).”
Spontaneous counterfactual thoughts and causal explanations (2006, background): “…on the contrast between reality and a counterfactual alternative (e.g., Hume, 1739/ 1978; Lewis, 1973; Mackie, 1974; Mill, 1843/1967) and social psychologists have suggested close links between counterfactual thoughts and causal attribution (e.g., Hilton, 1990; Lipe, 1991; McGill & Klein, 1993).”
Intuitive Theories (2020, background): “Explanations distinguish between causes and enabling conditions (Cheng & Novick, 1991; Kuhnmünch & Beller, 2005) and generally pick out events that we consider worth talking about (Hilton, 1990).”
Two Is Not Always Better Than One (2009, unknown): “In their analysis of causal explanations, Hilton, Smith, and Kim (1995) proposed that explanations are also derived through the method of agreement, which reinforce the presupposed similarities among theories and foster one’s confidence in them. From this perspective, it is not surprising that two-s”