Causal Inference Lab

Talk by Niels Skovgaard-Olsen (Göttingen)


On Monday 15 March at 10:00, Niels Skovgaard-Olsen will speak at the Causal Inference Lab on conditionals and the hierarchy of causal queries. For more information, please click here.

To join the meeting, please click https://uva-live.zoom.us/j/84280955332

Date: Monday 15 March 2021
Time: 10:00 - 12:00
Location: Online, via Zoom
 

Conditionals and the Hierarchy of Causal Queries

Niels Skovgaard-Olsen, Simon Stephan & Michael R. Waldmann

 

Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queriesconcerning evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions.

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