Joint perceptual decision-making: a case study in explanatory pluralism.

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches

Building Machines That Learn and Think Like People

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

Perceptual crossing: the simplest online paradigm

Researchers in social cognition increasingly realize that many phenomena cannot be understood by investigating offline situations only, focusing on individual mechanisms and an observer perspective. There are processes of dynamic emergence specific to online situations, when two or more persons are engaged in a real-time interaction that are more than just the sum of the individual capacities or behaviors, and these require the study of online social interaction. Auvray et al.'s (2009) perceptual crossing paradigm offers possibly the simplest paradigm for studying such online interactions: two persons, a one-dimensional space, one bit of information, and a yes/no answer. This study has provoked a lot of resonance in different areas of research, including experimental psychology, computer/robot modeling, philosophy, psychopathology, and even in the field of design. In this article, we review and critically assess this body of literature. We give an overview of both behavioral experimental research and simulated agent modeling done using the perceptual crossing paradigm. We discuss different contexts in which work on perceptual crossing has been cited. This includes the controversy about the possible constitutive role of perceptual crossing for social cognition. We conclude with an outlook on future research possibilities, in particular those that could elucidate the link between online interaction dynamics and individual social cognition

Cognition and the Web

Empirical research related to the Web has typically focused on its impact to social relationships and wider society; however, the cognitive impact of the Web is also an increasing focus of scientific interest and research attention. In this paper, I attempt to provide an overview of what I see as the important issues in the debate regarding the relationship between human cognition and the Web. I argue that the Web is potentially poised to transform our cognitive and epistemic profiles, but that in order to understand the nature of this influence we need to countenance a position that factors in the available scientific evidence, the changing nature of our interaction with the Web, and the possibility that many of our everyday cognitive achievements rely on complex webs of social and technological scaffolding. I review the literature relating to the cognitive effects of current Web technology, and I attempt to anticipate the cognitive impact of next-generation technologies, such as Web-based augmented reality systems and the transition to data-centric modes of information representation. I suggest that additional work is required to more fully understand the cognitive impact of both current and future Web technologies, and I identify some of the issues for future scientific work in this area. Given that recent scientific effort around the Web has coalesced into a new scientific discipline, namely that of Web Science, I suggest that many of the issues related to cognition and the Web could form part of the emerging Web Science research agenda

Outline of a new approach to the nature of mind

I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin’s continuity hypothesis and proposes that the mental gap is within our own species