According to Hubert Dreyfus’s famous claim that expertise is fundamentally “mindless,” experts in any domain perform most effectively when their activity is automatic and unmediated by concepts or cognitive processes like attention and memory. While several scholars have recently challenged the plausibility of Dreyfus’s “mindless” account of expertise for explaining a wide range of expert activities, there has been little consideration of the one form of expertise which might be most amenable to Dreyfus’s account – namely, perceptual expertise. Indeed, Dreyfus’s account of expert coping is ultimately an account of perceptual expertise, in that an expert’s intuitive situational responses are thought to rely on a sophisticated repertoire of perceptual skills. In this paper, I examine the feedforward model of sensory processing that Dreyfus uses to illustrate the perceptual underpinnings of expert action, and consider its resonance with psychological research that characterizes perceptual expertise as being automatic, holistic, pre-attentive, and non-cognitive in nature. However, citing competing empirical research, I argue instead that Dreyfus’s model of perceptual expertise cannot adequately explain the integral roles of attention, memory, and conceptual knowledge in expert object recognition. I conclude that the Dreyfusian model of perceptual expertise fails – the perceptual repertoire of skills that grounds expert object recognition is not operative in isolation from the expert’s conceptual repertoire.
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For discussion of how recent developments of chunking theory respond to Dreyfus’s objections, see Gobet and Chassy 2009.
To clarify, the ventral visual pathway is hierarchically structured into low-level and high-level areas according to the level of abstraction and complexity at which visual stimuli are processed. The ventral stream starts in the occipital lobe, branches off from the primary or “striate” visual cortex (V1) and secondary or “prestriate” visual cortex (V2), and then proceeds through to “extrastriate” areas V3 and V4. These four visual regions are considered to be low-level areas because they are responsive to rudimentary sensory features like color and shape. An intermediate state of processing occurs at the lateral occipital complex, where sensory features are integrated into the representation of a coherent three-dimensional object. The ventral stream culminates in the inferior temporal cortex located in the temporal lobe. Here, high-level regions are responsible for identifying objects under categories (e.g., “car,” “face,” “dog”) that abstract away from variations in low-level stimuli. Of course, there are also recurrent feedback signals from high-level areas back down to low-level areas. See Grill-Spector 2010 for a more detailed overview of the high-level and low-level visual regions involved in object processing.
The “Einstellung effect” refers to cases where a given problem automatically triggers certain cognitive states and habitual responses that prevent one from detecting a better solution. Bilalic et al. studied the occurrence of this effect among expert chess players, by presenting them with a board situation where checkmate could be reached through a familiar five-move sequence or an uncommon three-move sequence. The experts easily found the five-move sequence; but even when they reported that they were still looking for another solution, they were observed through eye-tracking technology to still be focusing on the features of the problem that were relevant to the solution they had already given. The conclusion drawn was that the problem activated a memory-schema which directs the experts’ attention to the features relevant to the familiar sequence, thereby distracting them from the features that would be relevant to another, more simple solution.
See Gauthier and Bukach 2007 for discussion of “composite task” tests that measure the interference to expert recognition caused by the holistic processing of incongruous images.
The orbitofrontal cortex has been associated with a wide range of cognitive functions, the most relevant for our purposes being the processing of affective value and reward, decision-making, guessing and hypothesis-testing, and the formation of expectations. See Bar et al. 2006: 453 for discussion of how the rapid detection of coarse-grained gist and the formation of top-down predictions about object-identities may subserve these cognitive functions in a way that would have conferred evolutionary benefits.
Dreyfus (2002: 376) mentions three ways in which, without any conceptual rules, the network could learn to process disparate inputs as being relevantly similar for producing a certain output response: There could be innate, non-cognitive gestalt structures that group inputs together; the temporal order and frequency of inputs could come to signify a shared relevance for a certain output-response, like how nearby objects which afford a reaching response would be detected more early and often than things which do not afford reaching; and inputs could be grouped as similar according to whether they tend to produce a practically satisfactory response.
It is worth noting that the patterns of activation in the early visual cortex (V1) were relatively task-independent – that is to say, experimenters could determine which object was being seen from the pattern of activation in the early visual cortex regardless of which task was being performed. Harel, Kravitz, and Baker hence write that “in all visual regions it was still possible to decode object identity across tasks, suggesting that although representations are perturbed, they are not completely changed” (2014: 968). We might say, then, that the top-down influence of behavioral goals or observer intent do not construct an object representation out of whole cloth – they may penetrate the visual processing of visual object representations, but (at least in non-hallucinatory cases) they do not fully replace the bottom-up object information delivered from the early visual cortex.
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I would like to thank the two anonymous reviewers for generously providing suggestions for correction and clarification.
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Chaturvedi, A. Against a “mindless” account of perceptual expertise. Phenom Cogn Sci 18, 509–531 (2019). https://doi.org/10.1007/s11097-018-9557-z
- Hubert Dreyfus
- Perceptual expertise
- Object recognition
- Perceptual concepts