Explanation, imagination, and confidence in judgment.

By Derek J. Koehler. 1991

This article concerns a class of experimental manipulations that require people to generate explanations or imagine scenarios. A review of studies using such manipulations indicates that people who explain or imagine a possibility then express greater confidence in the truth of that possibility. It is argued that this effect results from the approach people take in the explanation or imagination task: They temporarily assume that the hypothesis is true and assess how plausibly it can account for the relevant evidence. From this view, any task that requires that a hypothesis be treated as if it were true is sufficient to increase confidence in the truth of that hypothesis. Such tasks cause increased confidence in the hypothesis at the expense of viable alternatives because of changes in problem representation, evidence evaluation, and information search that take place when the hypothesis is temporarily treated as if it were true.

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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): “Hypothesis: Confidence in one's understanding is enhanced if it is possible to imagine and explain a future possibility (Koehler, 1991; Krull and Anderson, 1997).”
Metrics for Explainable AI: Challenges and Prospects (2018, background): “Instances of explanation are often expressions of what will happen in the future (Koehler, 1991; Lombrozo and Carey, 2006; Mitchell, Russo & Pennington, 1989).”
Predictive Multiplicity in Classification (2019, background): “In this case, awareness of competing models with conflicting predictions would mitigate unwarranted rationalization of the model (e.g., via fairwashing [2] or explanation bias [23, 27]).”
The challenge of crafting intelligible intelligence (2018, background): “Koehler found that simply presenting an explanation for a proposition makes people think that it is more likely to be true [18].”
Counterfactuals as behavioral primes: Priming the simulation heuristic and consideration of alternatives. (2000, background): “The pattern of data also suggests that counterfactual primes crack open the door to possibilities, " breaking the inertia " of the suffocating hold of focal hypotheses, typical functions, and blind linearity (Koehler, 1991).”
Poking Counterfactual Holes in Covering Laws: Cognitive Styles and Historical Reasoning (2001, background): “Laboratory experiments repeatedly find support for the prediction—derived from Tversky and Kahneman’s (1983) classic work on the availability and simulation heuristics—that merely imagining multievent scenarios increases the perceived likelihood of the component events (Koehler 1991).”
Explainability fact sheets: a framework for systematic assessment of explainable approaches (2019, background): “Nevertheless, some research suggests that user studies cannot fully assess the effectiveness of an explanation due to a phenomenon called “The Illusion of Explanatory Depth” [46] or they can yield unexpectedly positive results as simply presenting an explanation to people makes them believe that it ”
Using Critical Thinking To Conduct Effective Searches of Online Resources. ERIC Digest. (2000, background): “Once we form an opinion, we tend to focus on sources that that support our position, and distort data to make the strongest case (Koehler, 1991).”
Predicting the Next Step of a Random Walk: Experimental Evidence of Regime-Shifting Beliefs (2002, unknown): “Both of these errors would be consistent 2See, for example, Slovic et al. (1974, p. 192), Tversky and Kahneman (1971, 1974), Kahneman and Tversky (1973), Langer (1975), Davis et al. (2000), Ross et al. (1977), Andreassen (1987, 1990), Koehler (1991), and Bloomfield et al. (2000).”
How People Explain Behavior: A New Theoretical Framework (1999, unknown): “, Bohner, Bless, Schwarz, & Strack, 1988; Weiner, 1985); consequences of explanations, such as self-interpretations of emotions (Schachter & Singer, 1962; Schwarz & Clore, 1983; Valins & Nisbett, 1972) or motivations (Lepper & Greene, 1978); and the relation between explanation and belief perseveran”
Overcoming the Inevitable Anchoring Effect: Considering the Opposite Compensates for Selective Accessibility (2000, background): “The psy cho log i cal pro cesses that medi ate these phe - nom ena (Koehler, 1991) appear to be sim i lar to those that under lie judg men tal anchor ing.”