The course of events: counterfactuals, causal sequences, and explanation

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Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences (2017, background): “…to the fact in question in the causal chain are preferred over more distal events [Miller and Gunasegaram, 1990], but people will ‘trace through’ closer events to more distal events if those distal events are human actions [Hilton et al. , 2005] or abnormal events [Hilton and Slugoski, 1986].”
Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, methodology): “t. A causal chain is a path of causes between a set of events, in which a cause from event C to event E indicates that C must occur before E. Any events without a cause are root causes. Hilton et al. [76] dene ve dierent types of causal chain, outlined in Table 2, and note that dierent causal chains”
Combinatorial Methods for Explainable AI (2020, background): “Relevant findings in this area include research showing that users may consider counterfactuals, what would have happened if some event was not present [16][17], and that only a subset of a full event chain is typically used [17].”