Rationality, Perception, and the All-Seeing Eye

Exploration of a new integrative intellectual enterprise: the cognitive social sciences. Research in the cognitive sciences has advanced significantly in recent decades. Computational cognitive modeling has profoundly changed the ways in which we understand cognition. Empirical research has progressed as well, offering new insights into many psychological phenomena. This book investigates the possibility of exploiting the successes of the cognitive sciences to establish a better foundation for the social sciences, including the disciplines of sociology, anthropology, economics, and political science. The result may be a new, powerful, integrative intellectual enterprise: the cognitive social sciences. The book treats a range of topics selected to capture issues that arise across the social sciences, covering computational, empirical, and theoretical approaches. The chapters, by leading scholars in both the cognitive and the social sciences, explore the relationship between cognition and society, including such issues as methodologies of studying cultural differences; the psychological basis of politics (for instance, the role of emotion and the psychology of moral choices); cognitive dimensions of religion; cognitive approaches to economics; meta-theoretical questions on the possibility of the unification of social and cognitive sciences. Combining depth and breadth, the book encourages fruitful interdisciplinary interaction across many fields.

Most economists who are familiar with the works of George Shackle probably view him primarily as someone who combined elements from, and contributed to, Austrian and Post Keynesian approaches to economics. In this chapter, however, we cast him in a different role, that of a pioneer in behavioural economics. As is evident from Earl (ed.) (1988), Sent (2004) and Tomer (2007), behavioural economics takes many forms but may be generally thought of as using knowledge of how people actually make decisions, and of actual business practices, as foundations for economic analysis and policy. Economists sometimes gather the knowledge that provides the foundations for behavioural economics themselves, via questionnaires, in-depth case studies and experiments. Some, including Shackle, also engage in intense introspection on the nature of the human condition and how people deal with the challenges of everyday life. But many of the underpinnings of behavioural economics have come from social and cognitive sciences, particular from various branches of psychology. Indeed, though the frequently renamed prize that is popularly known as the Nobel Prize in Economics has been awarded twice for contributions to behavioural economics, in neither case did the recipient hold an academic affiliation as an economist: the 1978 recipient, Herbert Simon, a remarkable polymath, was a professor of computing science and psychology, while Daniel Kahneman, who shared the 2002 Prize with experimental economist Vernon Smith, is a professor of psychology.

In a case study of the growth of cognitive science, we analyzed the activities of the Cognitive Science Society with a particular emphasis on the multidisciplinary nature of the field. Analyses of departmental affiliations, training back‐grounds, research methodology, and paper citations suggest that the journal Cognitive Science and the Annual Meeting of the Cognitive Science Society are dominated by cognitive psychology and computer science, rather than being an equal division among the constituent disciplines of cognitive science. However, at many levels, a growing percentage of work was found to involve a conjunction of multiple disciplines, such that approximately 30–50% of recent work in the Cognitive Science Society is multidisciplinary. In a questionnaire study of cognitive scientists involved in collaborative research, multidisciplinarity was found to shape the research process and affect the factors associated with successful research.

Does the language you speak affect the way you think? According to the Principle of Linguistic Relativity, it does. Whether, however, the principle holds, has for several decades been one of the most controversial issues in cognitive science (for overviews, see Lucy, 1997; Wolff & Holmes, 2011). At the risk of oversimplifying its history, ideas linked to linguistic relativity can be traced back to philosophical writings in the German Romanticism of the 19th century (such as by Wilhelm von Humboldt) and became more widely known when ethno-linguists Edward Sapir and Benjamin Lee Whorf elaborated on them in their scientific work in the first half of the 20th century. While popular in the humanities, the proposition that speakers of different languages might perceive the world differently was untenable in early cognitive science. It was regarded as incommensurate with the assumption of a unified mind operating on a universal language of thought and hence simply inconceivable. When linguistic relativity eventually was put on the agenda in the 1990s (Gumperz & Levinson, 1991; Lucy, 1992), it was still met with substantial dissent (e.g., Pinker, 1994; overview in Gleitman & Papafragou, 2005); and although the antagonism of the early days has since given way to a more constructive exchange in which both opponents and supporters are increasingly seeking the middle ground and are even beginning to collaborate (e.g., Malt & Majid, 2013; Regier & Kay, 2009), the topic remains hotly debated. The current issue of Topics in Cognitive Science aims to make a productive contribution to this debate, both in format and content. In terms of format, this topic is one of only two that the journal has published featuring a target article, followed by a range of commentaries and a response to those commentaries by the author of the target article. This setup, known from Current Anthropology and Behavioral and Brain Sciences, is ideal for assembling multiple perspectives on controversial topics of broad interest across disciplines. The target article around which the current issue is structured (Kemmerer, 2023), is authored by linguist David Kemmerer (Purdue University, US). He develops a theoretical argument in support of linguistic relativity as deriving from the Grounded Cognition Model, a theory on conceptual knowledge that is highly influential within cognitive science. The argument entails a novel prediction that has the potential to inspire new experimental work across a range of academic communities that work on topics as diverse as perception, action, memory, emotion, language, culture, development, and evolution. For bringing together responses across such a wide field, Topics in Cognitive Science is the optimal forum. And, indeed, the eight commentaries accompanying this target article do reflect a wide variety of perspectives, authored by scholars who represent research communities on four continents and from across the social sciences, information sciences, and cognitive sciences, including linguistics, neuroscience, philosophy, and psychology. Credit for this topic goes to Asifa Majid (Oxford University, UK), a member of the Senior Editorial Board of Topics in Cognitive Science, who herself is a pioneer and leading figure in this subfield of cognitive science. She has been a strong voice for taking (linguistic) diversity and its consequences for cognition seriously (Majid, Bowerman, Kita, Haun, & Levinson, 2004), and yet she is also respected across camps for placing empirical evidence higher than theoretical ideology and for remaining open to a middle ground (e.g., Majid, 2021; Malt, Gennari, Imai, Ameel, Tsuda, & Majid, 2008). It was she who recruited the target article from David Kemmerer for Topics in Cognitive Science, suggested the format, handled the reviewing process, invited the commentaries with a clear objective for diversity, and monitored the compilation of the entire topic. topiCS encourages letters and commentaries on all topics, as well as proposals for new topics. Letters are not longer than two published pages (ca. 400–1000 words). Commentaries (between 1000 and 2000 words) are often solicited by Topic Editors prior to the publication of their topic, but they may also be considered after publication. Letters and commentaries typically come without abstract and with few references, if any. The Executive Editor and the Senior Editorial Board (SEB) are constantly searching for new and exciting topics for topiCS. Feel free to open communications with a short note to the Executive Editor ([email protected]) or a member of the SEB (for a list, see the publisher's homepage for topiCS: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1756-8765/homepage/EditorialBoard.html).

This article provides an overview of the main tendencies and ideas in the embodied mind paradigm in the expanding field of modern cognitive science. The focus is not on the biological and neurological aspects of cognitive science, rather the article demonstrates how basic concepts and theories from cognitive science have influenced linguistics, sociology, the understanding of art and creativity, film and film perception, as well as our understanding of historical film narratives and mediated memories. Although these areas of humanities and social science may seem unrelated, this article demonstrates how the embodied mind paradigm has actually forged links between separate scientific disciplines. Cognitive science and the embodied mind theory have created a stronger interdisciplinary connection between cognitive understanding in social science and humanities. Metaphors and image schema, the way our brain relies on narrative structures, the dynamic ability of the brain to blend old and new schemas, and the unparalleled creativity of the brain are all part of the approaches of the cognitive social science and humanities to social interaction, communication and creativity described here. The article also discusses the relationship between the more universal dimensions of the human mind and the question of cultural and social variations. The argument here is that a cognitive and more universal theory of human beings is not the same as determinism. On the contrary, when we understand our universal commonalities and the basic functions of our embodied mind we will also be better placed to understand cultural and social differences and variations.

This chapter outlines an approach to genre as the driving force behind language, cognition, and communication. Genre can and has been studied in the humanities as well as the cognitive and social sciences, but the present chapter presents a theoretical integration of these approaches and offers a model that can be empirically investigated by various methods across the board of these disciplines. The model itself is based in cognitive psychology, and a number of possibilities and implications for text analysis are illustrated. Both the role of language itself as well as the connection with literature are included in the discussion in order to suggest how a complete picture can be achieved of the bi-directional traffic between cognitive science and the humanities.

Theopsych: A Psychological Science Primer for Theologians

When rejecting and accepting hypotheses, it is important to determine the risk of false positive conclusions. Hierarchical Bayesian models are frequently applied in cognitive science, psychology, cognitive neuroscience, and psychiatry to reduce the variability of low-level parameters through partial pooling, and to obtain more robust parameter estimates for complex models using limited data. This may lower the risk of false positive inferences from lower-level estimates. In contrast, higher-level (e.g. group-level) estimates may be more affected by modeling choices (e.g. prior distributions), population-level variances in effects, and inference methods, which may in turn affect false positive rates for group-level effects. Here we used simulation and computational modeling to systematically examine false positive rates and effects of specific modeling choices on inferences in a simple hierarchical Bayesian temporal discounting model. To this end, 600 data sets of a temporal discounting task with two conditions were simulated, drawing individual condition effect parameters from a null distribution with varying standard deviations. For each simulated data set, the group-level mean change in the discount rate was modeled with eight different prior variances of the condition effect. Results were subsequently evaluated using several commonly applied Bayesian inference methods: the Savage-Dickey Bayes factor (BF), the directional Bayes factor (dBF), P(effect > 0), and the highest density interval (HDI) against zero decision rule. Results confirm that inference methods that directly depend on the posterior distribution can be used regardless of prior variances, whereas the Savage-Dickey BF should only be used with sufficiently informative priors. Based on the simulation work, decision thresholds that ensure false positive rates below 5% are provided for each inference method. Results are discussed in the context of computational modeling approaches in cognitive (neuro-)science and psychology.

Cognitive Informatics (CI) is a transdisciplinary enquiry of the internal information processing mechanisms and processes of the brain and natural intelligence shared by almost all science and engineering disciplines. This article presents an intensive review of the new field of CI. The structure of the theoretical framework of CI is described encompassing the Layered Reference Model of the Brain (LRMB), the OAR model of information representation, Natural Intelligence (NI) vs. Artificial Intelligence (AI), Autonomic Computing (AC) vs. imperative computing, CI laws of software, the mechanism of human perception processes, the cognitive processes of formal inferences, and the formal knowledge system. Three types of new structures of mathematics, Concept Algebra (CA), Real-Time Process Algebra (RTPA), and System Algebra (SA), are created to enable rigorous treatment of cognitive processes of the brain as well as knowledge representation and manipulation in a formal and coherent framework. A wide range of applications of CI in cognitive psychology, computing, knowledge engineering, and software engineering has been identified and discussed.

Removing the stigma of medication for opioid use disorder

Surveillance in Barrett's Esophagus: Lessons from Behavioral Economics

Cognitive science is a network of interrelated scientific disciplines engaged in researching human cognition and its brain mechanisms. The birth of cognitive science has been the result of numerous integrated processes. Cognitive science is made up of experimental psychology cognition, philosophy consciousness, neuroscience, cognitive anthropology, linguistics, computer science and artificial intelligence. In recent years, a number of other research areas have been added to the body of cognitive science. Among researchers there have been discussions about whether cognitive science is a separate research area or it consists of a series of specialized areas. In fact, the point at issue is whether cognitive science is still a multidisciplinary project or already an interdisciplinary one. P. Thagard believes that cognitive science has reached the level of interdisciplinarity and explains the advances in this area through the metaphor of “trading zones”. The success elements of cognitive science are: fruitful unification of scientific interests of cognitive science founders; organizational structure of the scientific community – universities, where a special interdisciplinary intellectual environment has been created; a large number of joint research projects supported by governments and business; integrated use of scientific methods and fundamental ideas. D. Sperber and J. Miller prefer to talk not about a unified cognitive science but cognitive sciences, i.e., the commonwealth of sciences working together on the study of a single object - human cognition, however, the extent of their interactive communication is still small. Thus, we should speak about multidisciplinarity rather than genuine interdisciplinarity of the joint research of separate sciences.

INTRODUCTION The research project outlined in Thomas Kuhn's The Structure of Scientific Revolutions seems intrinsically historical, philosophical, and psychological (Kuhn 1970). However, by and large, Kuhn never utilized research in the cognitive sciences that would have furthered his own paradigm in ways I think he would have found agreeable. Until his very last writings, psychology dropped out of Kuhn's post- Structure published articulations of his views just at the time that the cognitive revolution was beginning to provide accounts of representation, problem solving, and learning that I believe are pertinent to his intuitive insights. With hindsight one can construct significant parallels between the views of knowledge, perception, and learning developed in each. In what follows I will discuss in what ways some of Kuhn's insights might be furthered today in light of cognitive science research. Seen through a cognitive lens, Kuhn's little book seems all the more remarkable and insightful. Many of the issues with which he grappled have been the subject of entire areas of research in cognitive science, especially cognitive psychology. In the course of this essay I can only give brief indications of how Kuhn's thinking and research in areas of cognitive science have been running along parallel lines and of how one might, through cognitive-historical analysis, create some intersecting lines. In his Presidential Address to the Philosophy of Science Association, Kuhn expressed his abiding interest as being in “incommensurability and the nature of the conceptual divide between the developmental stages separated by … ‘scientific revolutions’” (Conant and Haugeland 2000, p. 228).

This article addresses itself to the conceptual crisis in present-day Cognitive Science. It argues that, in particular, cognitive psychology and AI suffer from a destructive Cartesian legacy. Moreover, the modern schools of philosophy which have found fault with Descartes may provide a more secure foundation on which to build Cognitive Science. It is certainly over-sanguine to hope that the new techniques afforded by connectionism will on their own found a less problematic discipline. Merleau-Ponty’s work on perception is examined in a philosophical, then a computational context. A line of argument is then developed wherein Merleau-Ponty’s and Piaget’s perspectives are synthesised. From this, a new perspective on the nature of subject/object relations in human cognition is developed, and related to current Cognitive Science. Finally, future directions for research are proposed.KeywordsNatural Language ProcessingMachine TranslationPhilosophical ProblemFrame ProblemEquation MindThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

GENERAL COMMENTARY article Front. Psychol., 21 December 2015Sec. Comparative Psychology Volume 6 - 2015 | https://doi.org/10.3389/fpsyg.2015.01928