Rethinking Temporal Contiguity and the Judgement of Causality: Effects of Prior Knowledge, Experience, and Reinforcement Procedure

Abstract

Time plays a pivotal role in causal inference. Nonetheless most contemporary theories of causal induction do not address the implications of temporal contiguity and delay, with the exception of associative learning theory. Shanks, Pearson, and Dickinson (1989) and several replications (Reed, 1992, 1999) have demonstrated that people fail to identify causal relations if cause and effect are separated by more than two seconds. In line with an associationist perspective, these findings have been interpreted to indicate that temporal lags universally impair causal induction. This interpretation clashes with the richness of everyday causal cognition where people apparently can reason about causal relations involving considerable delays. We look at the implications of cause-effect delays from a computational perspective and predict that delays should generally hinder reasoning performance, but that this hindrance should be alleviated if reasoners have knowledge of the delay. Two experiments demonstrated that (1) the impact of delay on causal judgement depends on participants' expectations about the timeframe of the causal relation, and (2) the free-operant procedures used in previous studies are ill-suited to study the direct influences of delay on causal induction, because they confound delay with weaker evidence for the relation in question. Implications for contemporary causal learning theories are discussed.

Structural awareness mitigates the effect of delay in human causal learning

“…The effect of trial length on total responses was also significant, F(1, 32) = 14.172, MSE = 5,532.221, η p 2 = .307, which replicates previous findings (e.g., Buehner & May, 2003). The important comparisons, however, were those involving trial markers-specifically, to elucidate whether the effects of structural information involve an elicited change in response patterns or are due solely to a higher-level understanding of structure.…”

“…Furthermore, participants are free to respond more than once per trial, but typically only the first response is subjected to the reinforcement schedule. As a result, longer trials in an FOP may reduce the actual contingency experienced by the participant (Buehner & May, 2003).…”

Models of covariation-based causal judgment: A review and synthesis

“…This can be seen as a special case of the fundamental problem of associative learning (in a broad sense)-namely, the problem of describing how learned beliefs relate to the environmental contingencies on which they are based. Causal beliefs are influenced by a range of factors such as the temporal (Shanks, Pearson, & Dickinson, 1989; see also Buehner & May, 2003) and spatial (Glautier, 2002) distribution of events, as well as by more top-down factors such as causal expectations (Waldmann & Hagmayer, 2001). Yet within the total space defined by the attributes that influence causal learning, research has tended to occupy a rather restricted region: Specifically, numerous studies have held constant all other factors (e.g., spatial and temporal relationships) and varied only covariation information-that is, information about the frequencies of conjunctions and disjunctions between a target cause and effect.…”

The Influence of Delays in Real-Time Causal Learning

“…An important caveat is that in certain contexts, and with certain types of causal relation, people can tolerate much longer delays. One clear demonstration of this is when people have prior knowledge about the causal mechanism that explains the delays [20,21]. 1 For example, people expect a short delay between the click of a mouse and the appearance of an object on the computer screen, but tolerate a longer delay between the eating of seafood and a subsequent allergic reaction.…”