It is undoubtable that over the last decade, Oaksford & Chater (O&C) have revolutionized the psychology of human reasoning. What were previously viewed as “logical reasoning” tasks, such as Wason's card selection task, were given a probabilistic re-interpretation. At the same time, their work has formed a corner-stone in the wider probabilistic revolution that has taken place over the last 10 to 15 years: Finding evidence for human sensitivity to probabilities in as unlikely a corner as “logical” reasoning tasks, lends support to the wider claim that human cognition is fundamentally about probabilities.

Given the current popularity of Bayesian approaches to cognition (see e.g., Chater et al. Reference Chater, Tenenbaum and Yuille2006; Chater & Oaksford 2008, for overviews), it is worth trying to remind oneself just how much has changed in cognitive science in that period. At the beginning of the 1990s, logic was taught extensively in philosophy and cognitive science courses, but little or no mention was given to probability theory; now core topics such as epistemology are incomprehensible without a basic understanding of probability. Cognitive science as a field was still in the throws of the symbolic versus connectionist debate (e.g., Fodor & Pylyshyn Reference Fodor and Pylyshyn1988; Smolensky Reference Smolensky1990) and both Nick Chater and Mike Oaksford were involved in the connectionist project (e.g., Bullinaria & Chater Reference Bullinaria and Chater1995; Oaksford & Brown Reference Oaksford and Brown1994). Arguably, the rise of connectionism was a major factor in cognitive science's statistical “turn” (e.g., Chater Reference Chater, Levy, Bairaktaris, Bullinaria and Cairns1995), but connectionism's emphasis was firmly on “mechanism” and its (potentially) “brainstyle” processing.

However, since then, the connectionist project has stagnated by comparison to what has been achieved in other areas, such as the psychology of reasoning. Crucial to this latter success, it seems, was the step back, or better, “upwards,” in terms of the degrees of abstraction, and levels of description at which explanation were sought.

Retreating from considerations of implementation, or, by and large, even algorithms, O&C have stuck resolutely to computational level descriptions, and, in so doing, have become key exponents of Anderson's project of rational analysis (Anderson Reference Anderson1990; Chater & Oaksford 2008; Oaksford & Chater Reference Oaksford and Chater1998b). To this day, computational level descriptions provoke suspicion in mainstream experimental psychology. “But what is it that people are actually doing?”, “what is going on in the head?” are standard questions to researchers focused on the computational level, as is exemplified in the dialogue between Sceptic and Advocate in the final chapter of O&C's new book, Bayesian Rationality (Oaksford & Chater Reference Oaksford and Chater2007, henceforth BR).

All are agreed that the project of understanding human behavior is not over until processes and their implementation have also been specified, but the thing that comes across most strikingly in O&C's book is the level of explanatory specificity that has now been achieved in the psychology of reasoning. Before O&C's seminal paper on the selection task (Oaksford & Chater Reference Oaksford and Chater1994), data in the psychology of logical reasoning were a (in many ways somewhat haphazard) collection of qualitative phenomena (“context effects,” “supression effects,” etc.). Reading O&C's summary of the state of affairs 14 years on, the psychology of reasoning has become an arena in which detailed quantitative predictions are evaluated. This is not only true of their own probabilistic approach; O&C have also forced the hand of rival approaches which have since taken on board quantitative model evaluation (Klauer et al. Reference Klauer, Stahl and Erdfelder2007; Oberauer Reference Oberauer2006; Schroyens & Shaeken Reference Schroyens and Schaeken2003).

It is worth pausing to consider how remarkable this is. The reasoning tasks in question are firmly “high-level cognition” of the kind that is characteristic of what Fodor (Reference Fodor1983) considered to be “central processing,” and hence an aspect of human cognition for which we would never have detailed theories and predictions due to the inherent open-endedness of high-level thought. That the field can capture subtle changes in behavior in response to changes in the content of high-level, verbal experimental materials in such detail is truly a success. Moreover, this specificity has been spreading through other aspects of human reasoning, as well (e.g., Tenenbaum et al. Reference Tenenbaum, Kemp, Shafto, Feeney and Heit2007).

That greater predictive power with regard to human behavior might be achieved by taking a step backwards to a higher level of abstraction that disregards processes might seem counterintuitive, but it seems to be exactly what has happened in the psychology of reasoning.

One further aspect of O&C's work deserves mention in this context. While it has, in one way, considered “less” than has other research in the psychology of reasoning, there is also a way in which it has consistently considered “more”: Apparent throughout O&C's book is the multi-disciplinarity of their project which has drawn support from both philosophy and Artificial Intelligence (AI). We disregard developments in adjacent disciplines at our peril: The problems of associating natural language if…then statements with the material conditional were long known in philosophy, but ignored by psychologists of reasoning (see Edgington Reference Edgington1995; Evans & Over Reference Evans and Over2004). Likewise, developments in AI spoke to the feasibility of the “logicist” program. Yet interdisciplinarity continues to be less of an asset and more of a stumbling block for publication in many of the core psychology journals that have housed the psychology of reasoning. At the same time, cognitive science as a discipline seems, if anything, to have lost in appeal over the last decade. Certainly in the United Kingdom, the number of degree courses in cognitive science has gone down – a trend that contrasts with the booming interest in cognitive neuroscience. Cognitive neuroscience, of course, seems first and foremost concerned with processes and their implementation. Although it undoubtedly will lead to results that are new and exciting in their own right, it seems worth pointing out that this trend is a move in the opposite direction to that taken so successfully by O&C; this should give pause for thought to those interested in high-level cognition.