Although not the main point of his target article, Block defends the view that perception and awareness of perception could be functions of different brain systems. I will argue that the available data do not support this view, and that Block's defense of the view rests on problematic eonstruals of the “executive system” and of the components of information-processing models.

We agree with the author's working model, but we suggest that (a) the classical distinction between fast and slow processes as separable processes can be softened, and (b) human performance might result from an interplay between fast and slow processing and these processes may be mediated by systems that evolve to satisfy the need for operation in a complex environment.

ABSTRACTHumans are cognitive misers because their basic tendency is to default to processing mechanisms of low computational expense. Such a tendency leads to suboptimal outcomes in certain types of hostile environments. The theoretical inferences made from correct and incorrect responding on heuristics and biases tasks have been overly simplified, however. The framework developed here traces the complexities inherent in these tasks by identifying five processing states that are possible in most heuristics and biases tasks. The framework also identifies three possible (...) processing defects: inadequately learned mindware; failure to detect the necessity of overriding the miserly response; and failure to sustain the override process once initiated. An important insight gained from using the framework is that degree of mindware instantiation is strongly related to the probability of successful detection and override. Thus, errors on such tasks cannot be unambiguously attributed to miserly processing – and corre... (shrink)

No doubt older work in the dual-process tradition overemphasized the importance and frequency of the override function, and the working model in this target article provides a useful corrective. The attempt to motivate the model using the so-called exclusivity assumption is unnecessary, because no recent dual-process model in the reasoning literature has rested strongly on this assumption.

Repression has become an empirical fact that is at once obvious and problematic. Fragmented clinical and laboratory traditions and disputed terminology have resulted in a Babel of misunderstandings in which false distinctions are imposed (e.g., between repression and suppression) and necessary distinctions not drawn (e.g., between the mechanism and the use to which it is put, defense being just one). “Repression” was introduced by Herbart to designate the (nondefensive) inhibition of ideas by other ideas in their struggle for consciousness. Freud (...) adapted repression to the defensive inhibition of “unbearable” mental contents. Substantial experimental literatures on attentional biases, thought avoidance, interference, and intentional forgetting exist, the oldest prototype being the work of Ebbinghaus, who showed that intentional avoidance of memories results in their progressive forgetting over time. It has now become clear, as clinicians had claimed, that the inaccessible materials are often available and emerge indirectly (e.g., procedurally, implicitly). It is also now established that the Ebbinghaus retention function can be partly reversed, with resulting increases of conscious memory over time (hypermnesia). Freud's clinical experience revealed early on that exclusion from consciousness was effected not just by simple repression (inhibition) but also by a variety of distorting techniques, some deployed to degrade latent contents (denial), all eventually subsumed under the rubric of defense mechanisms (“repression in the widest sense”). Freudian and Bartlettian distortions are essentially the same, even in name, except for motive (cognitive vs. emotional), and experimentally induced false memories and other “memory illusions” are laboratory analogs of self-induced distortions. Key Words: avoidance; Bartlett; defense; denial; distortion; Ebbinghaus; false-memories; Freud; inhibition; repression; suppression. (shrink)

The commentary argues that we cannot be sure that human consciousness has survival value and that in order to understand the origins and, perhaps, the function of consciousness, we should examine the behavioural and neural precursors to consciousness in nonhumans. An example is given of research on the role of context in decisions regarding fleeing from probable predators in the Mongolian gerbil.

Gray's account is remarkable in its depth and scope but too little attention is paid to poor correspondences with the literature on hippocampal/subicular damage, the theta rhythm, and novelty detection. An alternative account, focusing on hippocampal involvement in organizing memories in a way that makes them accessible to conscious recollection but not in access to consciousness per se, avoids each of these limitations.

Replying to Queen Elizabeth II who in November 2008 asked why so few economists had warned about the emerging financial crisis, a group of eminent economists of the British Academy, claimed that while this failure had many causes, the most important was principally a failure of the collective imagination of many bright people, to understand the risks to the system as a whole. The paper suggests that this failure is due also to the still heavy influence of the paradigm of (...) rational expectations, that did not provide the intellectual tools to grasp the signs of the impending financial crisis. The paper explores the development of Muth’s rational expectations hypothesis and the parallel development of Simon’s idea of bounded rationality—two opposite views about economic behavior that originated in the same context, during the early 1960s at Carnegie Mellon. It is shown that the latter, while marginalized for decades from the core economic ideas, generated a wide development in cognitive psychology, problem solving and experimental economics that grew up in the last decades and now permit a more profound analysis of human behavior in economic and organizational contexts, that can be the seed of a new thinking in economics. The challenge for economists is to use this new toolbox to incorporate in their models real human behaviors, getting out from the economy of wishful thinking. (shrink)

Cognitive scientists routinely distinguish between controlled and automatic mental processes. Through learning, practice, and exposure, controlled processes can become automatic; however, whether automatic processes can become deautomatized – recuperated under the purview of control – remains unclear. Here we show that a suggestion derails a deeply ingrained process involving involuntary audiovisual integration. We compared the performance of highly versus less hypnotically suggestible individuals in a classic McGurk paradigm – a perceptual illusion task demonstrating the influence of visual facial movements on (...) auditory speech percepts. Following a posthypnotic suggestion to prioritize auditory input, HSIs but not LSIs manifested fewer illusory auditory perceptions and correctly identified more auditory percepts. Our findings demonstrate that a suggestion deautomatized a ballistic audiovisual process in HSIs. In addition to guiding our knowledge regarding theories and mechanisms of automaticity, the present findings pave the road to a more scientific understanding of top-down effects and multisensory integration. (shrink)

By reviewing most of the neurobiology of consciousness, this article highlights some major reasons why a successful emulation of the dynamics of human consciousness by artificial intelligence is unlikely. The analysis provided leads to conclude that human consciousness is epigenetically determined and experience and context-dependent at the individual level. It is subject to changes in time that are essentially unpredictable. If cracking the code to human consciousness were possible, the result would most likely have to consist of a temporal pattern (...) code simulating long-distance signal reverberation and de-correlation of all spatial signal contents from temporal signals. In the light of the massive evidence for complex interactions between implicit (non-conscious) and explicit (conscious) contents of representation, the code would have to be capable of making implicit (non-conscious) processes explicit. It would have to be capable of a progressively less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure identical to that of the human brain, from the synaptic level to that of higher cognitive functions. The code’s activation thresholds would depend on specific temporal signal coincidence probabilities, vary considerably with time and across individual experience data, and would therefore require dynamically adaptive computations capable of emulating the properties of individual human experience. No known machine or neural network learning approach has such potential. (shrink)

Propositions as to the nature of consciousness, based on disorders of perception that result from brain damage, and taking insufficient account of the numerous ways in which normal subjects may deviate from that “usual” sequence of events (input → subjective awareness → output) risk increasing rather than diminishing any existing confusion about the function of consciousness.

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

“Implicit bias” is a term of art referring to relatively unconscious and relatively automatic features of prejudiced judgment and social behavior. While psychologists in the field of “implicit social cognition” study “implicit attitudes” toward consumer products, self-esteem, food, alcohol, political values, and more, the most striking and well-known research has focused on implicit attitudes toward members of socially stigmatized groups, such as African-Americans, women, and the LGBTQ community.[1] For example, imagine Frank, who explicitly believes that women and men are equally (...) suited for careers outside the home. Despite his explicitly egalitarian belief, Frank might nevertheless implicitly associate women with the home, and this implicit association might lead him to behave in any number of biased ways, from trusting feedback from female co-workers less to hiring equally qualified men over women. Psychological research on implicit bias is relatively recent (§1), but a host of metaphysical (§2), epistemological (§3), and ethical questions (§4) about implicit bias are pressing.[2]. (shrink)

Explicatures are not cancellable. Theoretical considerations.

Cognitive scientists have revealed systematic errors in human reasoning. There is disagreement about what these errors indicate about human rationality, but one upshot seems clear: human reasoning does not seem to fit traditional views of human rationality. This concern about rationality has made its way through various fields and has recently caught the attention of philosophers. The concern is that if philosophers are prone to systematic errors in reasoning, then the integrity of philosophy would be threatened. In this paper, I (...) present some of the more famous work in cognitive science that has marshaled this concern. Then I present reasons to think that those with training in philosophy will be less prone to certain systematic errors in reasoning. The suggestion is that if philosophers could be shown to be less prone to such errors, then the worries about the integrity of philosophy could be constrained. Then I present evidence that, according to performance on the CRT (Frederick 2005), those who have benefited from training and selection in philosophy are indeed less prone to one kind of systematic error: irrationally arbitrating between intuitive and reflective responses. Nonetheless, philosophers are not entirely immune to this systematic error, and their proclivity for this error is statistically related to their responses to a variety of philosophical questions. So, while the evidence herein puts constraints on the worries about the integrity of philosophy, it by no means eliminates these worries. The conclusion, then, is that the present evidence offers prima facie reasons to ascribe a mitigated privilege to philosophers' ability to rationally arbitrate between intuitive and reflective responses. (shrink)