How explanation guides belief change

Douven, Igor

doi:10.1016/j.tics.2021.07.009

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…In this sense, HIT is still within the New Paradigm, albeit firmly on the softer side of Bayesian commitments. HIT fits well with the New Paradigm's focus on knowledge-rich inference (Oaksford & Chater, 2020), although we are yet to develop implications for the social character of reasoning-the second important characteristic of the New Paradigm (Douven, 2021a;Elqayam & Over, 2013;Oaksford & Chater, 2020).…”

Section: Discussionmentioning

confidence: 72%

“…This is most easily seen, and most widely agreed upon, for abductive and analogical inference. In abductive inference, we reason to the best explanation, where explanation quality is typically understood in terms of the so-called theoretical virtues, including simplicity, mathematical elegance, scope, and coherence with background knowledge (Douven, 2017b(Douven, , 2021a. Few (if any) philosophers nowadays hold that all these notions, or even any of them, can be completely captured in formal terms.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Inference strength predicts the probability of conditionals better than conditional probability does

Douven

Elqayam

Mirabile

2022

Journal of Memory and Language

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According to the philosophical theory of inferentialism and its psychological counterpart, Hypothetical Inferential Theory (HIT), the meaning of an indicative conditional centrally involves the strength of the inferential connection between its antecedent and its consequent. This paper states, for the first time, the implications of HIT for the probabilities of conditionals. We report two experiments comparing these implications with those of the suppositional account of conditionals, according to which the probability of a conditional equals the corresponding conditional probability. A total of 358 participants were presented with everyday conditionals across three different tasks: judging the probability of the conditionals; judging the corresponding conditional probabilities; and judging the strength of the inference from antecedent to consequent. In both experiments, we found inference strength to be a much stronger predictor of the probability of conditionals than conditional probability, thus supporting HIT.

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Section: Discussionmentioning

confidence: 72%

Section: Theoretical Backgroundmentioning

confidence: 99%

Inference strength predicts the probability of conditionals better than conditional probability does

Douven

Elqayam

Mirabile

2022

Journal of Memory and Language

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“…The practice of favoring simpler explanations could also have other cognitive benefits, for example, resulting in less cognitively demanding processing, more compressed representations, and a greater sense of understanding (e.g., Pacer & Lombrozo, 2017; Scharrer et al., 2012; Wilkenfeld, 2019). It has also been argued that favoring more “virtuous” explanations (e.g., those that are simpler, or have greater explanatory power) might be beneficial for reasons related to prediction accuracy, but not because doing so approximates Bayesian inference (which minimizes long‐term inaccuracy), and instead because doing so deviates from Bayesian inference in ways that will often minimize shorter‐term inaccuracy, and thus support faster convergence to the truth (Douven, 2022; Douven, 2021; Douven, 2020; see also Pacer et al., 2013). More fully characterizing how explanatory virtues can and should inform reasoning–probabilistic or otherwise–thus remains an important question for future research.…”

Section: Discussionmentioning

confidence: 99%

Simplicity as a Cue to Probability: Multiple Roles for Simplicity in Evaluating Explanations

Vrantsidis

Lombrozo

2022

Cognitive Science

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People often face the challenge of evaluating competing explanations. One approach is to assess the explanations’ relative probabilities–for example, applying Bayesian inference to compute their posterior probabilities. Another approach is to consider an explanation's qualities or “virtues,” such as its relative simplicity (i.e., the number of unexplained causes it invokes). The current work investigates how these two approaches are related. Study 1 found that simplicity is used to infer the inputs to Bayesian inference (explanations’ priors and likelihoods). Studies 1 and 2 found that simplicity is also used as a direct cue to the outputs of Bayesian inference (the posterior probability of an explanation), such that simplicity affects estimates of posterior probability even after controlling for elicited (Study 1) or provided (Study 2) priors and likelihoods, with simplicity having a larger effect in Study 1, where posteriors are more uncertain and difficult to compute. Comparing Studies 1 and 2 also suggested that simplicity plays additional roles unrelated to approximating probabilities, as reflected in simplicity's effect on how “satisfying” (vs. probable) an explanation is, which remained largely unaffected by the difficulty of computing posteriors. Together, these results suggest that the virtue of simplicity is used in multiple ways to approximate probabilities (i.e., serving as a cue to priors, likelihoods, and posteriors) when these probabilities are otherwise uncertain or difficult to compute, but that the influence of simplicity also goes beyond these roles.

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“…As said, there may be other relevant forms of inference still. For instance, Douven et al (2021) look at conditionals such as (10) If Jim's son likes ice skating, he will like ice hockey.…”

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confidence: 99%

Inferentialism: A Manifesto

Douven

Elqayam

Krzyżanowska

2023

Palgrave Studies in Pragmatics, Language and Cognition

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In previous publications, we have proposed a new, inferentialist semantics for indicative conditionals. According to this semantics, the truth of a conditional requires the existence of a compelling argument from the conditional's antecedent together with contextually determined background premises to its consequent, where the antecedent is pivotal in the argument. In this paper, we recapitulate the position; report the progress we made over the past years, in particular highlighting the empirical support the position has garnered; and respond to criticisms that have been leveled at it.

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How explanation guides belief change

Cited by 6 publications

References 13 publications

Inference strength predicts the probability of conditionals better than conditional probability does

Inference strength predicts the probability of conditionals better than conditional probability does

Simplicity as a Cue to Probability: Multiple Roles for Simplicity in Evaluating Explanations

Inferentialism: A Manifesto

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