There are two widespread strategies for testing experimentally whether a conclusion follows naively from a sequenceof premises. The free-form response strategy (FFR) presents participants with the premises and asks them “what, if anything,follows?” In the simplest case, participants’ responses are coded as to whether they made the predicted inference. On the yes/noquestion strategy (YNQ), after presenting the premises, the researcher puts forth a sentence C and asks whether C follows fromthe premises.We compare the two methodologies with respect to six types of fallacious problems involving propositional connectives fromthe mental-models literature, to address the question of whether the methodologies are equally valid. We found that the twomethodologies overwhelmingly yield identical results. Interestingly, the exceptions we found show that in some cases FFR failsto detect an attractive fallacious conclusion that can be reliably probed with YNQ.

Work in the mental model tradition has shown that human reasoners are subject to fallacious inferences from very simple premises that have been described as tantamount to cognitive illusions (Walsh & Johnson-Laird, 2004; Khemlani & Johnson-Laird, 2009). We present four experiments that show that these phenomena are much more general and systematic than has previously been thought. Among other results, we find that premises using ‘some’ mirror premises using ‘or’ in generating fallacious inferences, showing that there are interesting facts about reasoning with quantifiers beyond syllogisms that have been the main focus in the literature. Neither mental model theory nor other familiar theories of reasoning account for the results we present. However, the novel illusory inferences we present are predicted by the erotetic theory of reasoning (Koralus and Mascarenhas, 2013). The key idea is that, by default, we reason by interpreting successive premises as questions and maximally strong answers to those questions, which generates the observed fallacies

On mental models theories, reasoners create mental representations of information which they manipulate in order toderive new conclusions. These theories have been uniquely successful at explaining a class of attractive fallacies involvingdisjunctions. The original theories have appealed to low-level matching mechanisms (Walsh & Johnson-Laird, 2004;Koralus & Mascarenhas, 2013) to compare the models of the premises and the models of the conclusion and predict ananswer. In three experiments, we show that the check for overlap in content involved in these accounts must take place ata high level of cognition in order to incorporate complex world knowledge. We introduce variants of illusory inferencesfrom disjunction whose acceptance is accurately predicted by independant measures of confidence in causal connections.We conclude that the Revised Mental Model Theory of Khemlani et al. (2018) holds promise, but cannot account for ourdata out of the box.

Although there are several representativeness-based models of the Lawyer-Engineer task, it remains unclear just why people rely on representativeness-based heuristics rather than on posterior probabilities. This is especially striking because subjects have access to the rational answer: irrational answers decrease dramatically in frequency formats (Gigerenzer&Hoffrage,1995). We argue that the availability of representativeness is explained by the fact that subjects (1) engage in question-answering behavior, as predicted by theories of linguistic semantics, and (2) recursively reason on each other’s mental states, as predicted by the Rational Speech Act Theory (Frank&Goodman,2012). To test this, in a norming study, we asked participants for frequency judgments on the components of Bayes' law, using pairs of real-world professions and related descriptions. In the main experiment, an independent group gave probability judgments on lawyers-engineers problems. We compared different models built from the normed values, and found that those incorporating (1) and (2) best predicted main-experiment responses.

We compare two perspectives on base-rate neglect (Kahneman & Tversky, 1973) in probabilistic judgment. The evidential impact perspective derives it from humans' focus on the impact of evidence on belief, rather than conditional probabilities. The Causal Models perspective derives it from humans' inability to integrate information that is causally opaque, as base-rates often are in such experiments. Because causal and evidential-impact relations are often concomitant and confounded, we designed an experiment that specifically teases apart their respective influence on probabilistic judgment. Our results support a combination of the two perspectives, with causal transparency influencing the degree to which one engages in evidential impact reasoning strategies.

Causal selection is the process whereby people decide which of several events responsible for a realized outcome should be considered as “the cause” of that outcome. A theory of causal selection requires a definition of the relevant candidates to be considered for selection. So far, the psychological literature has operated on the implicit premise that the only relevant candidates for causal selection are individual variables, corresponding to the distinct nodes of a causal network. Instead, we argue that causal judgment can recognize plural causes, featuring more than one variable. We provide evidence for the psychological relevance of plural causes by showing: (a) that plural cause judgments are influenced by the same factors that have been proven to influence causal selection judgments in general; (b) that this influence cannot be explained away by assuming that participants estimate the strength of plural cause simply by combining the strength of its individual constituents.

Building on counterfactual theories of causal-selection, according to which humans intuitively evaluate the causal responsibility of events, we developed an experimental paradigm to examine the effect of causal-selection explanations on abductive causal inference. In our experiment, participants attempted to infer the rule responsible for winning outcomes of random draws from urns with varying sampling probabilities. Participants who were provided with causal-selection judgments as explanations for the outcomes made significantly closer inferences to the rule than those relying on observations alone, or on other explanations of causal relevance. We mirror these empirical results with a computational model of inference from explanation leveraging the theories of causal selection.

We introduce purely visual paradigms that convey the logical structure of illusory inferences from disjunction: (a AND b) OR c, a |- b. Although the logical information was conveyed entirely via non-linguistic means, we found that the visual paradigms induce reasoning fallacies, though less attractive than their linguistic counterparts. The visual paradigms highlight the role of alternative-based reasoning, or question-answer dynamics, as they control for narrowly interpretive processes that confound the study of their linguistic counterparts. To our knowledge, this is the first work to develop visual paradigms that represent reasoning fallacies committed by adults and involve multiple logical operators non-trivially embedded. Previous studies focused on pre-verbal children or non-human animals, and for this reason limited the scope of research to visually representing logically simple, valid inferences.