Wants and desires are central to ordinary experience and to aesthetic, philosophical, and theological thought. Yet despite a burgeoning interest in the history of emotions research, their history as objects of scientific study has received little attention. This historiographical neglect mirrors a real one, with the retreat of introspection in the positivist human sciences of the early 20th century culminating in the relative marginalization of questions of psychic interiority. This article therefore seeks to explain an apparent paradox: the attempt to (...) develop a comprehensive theory of ‘why … we want what we want’ in the 1940s by esteemed American ‘neo-behaviorist’ psychologist Edward Tolman – a proponent of a methodology famous for its prohibition on appeals to unobservable mental phenomena. Though chiefly known today for his theory of ‘cognitive maps’, Tolman also sought to map the contours of desire as such, integrating Freudian and behaviorist models of the ‘drives’ to develop a complex iconography of the universal structures of motivation. Close attention to Tolman's striking maps offers a compelling limit case for what could and could not be captured within an anti-mentalist framework, and illuminates an important precursor to theories of motivational ‘affect’ in the postwar cognitive and neurosciences. His work upsets a standard chronology that centers on the ‘cognitive revolution’ of the 1960s, and points to the significance of psychoanalysis to an earlier turn to cognitivism. Tolman concluded his theory pointed ‘in the direction of more socialism’ – a reminder of the politically labile anti-essentialism of behaviorism's commitment to mental plasticity. (shrink)

ArgumentNeuroscience research has created multiple versions of the human brain. The “social brain” is one version and it is the subject of this paper. Most image-based research in the field of social neuroscience is task-driven: the brain is asked to respond to a cognitive stimulus. The tasks are derived from theories, operational models, and back-stories now circulating in social neuroscience. The social brain comes with a distinctive back-story, an evolutionary history organized around three, interconnected themes: mind-reading, empathy, and the emergence (...) of self-consciousness. This paper focuses on how empathy has been incorporated into the social brain and redefined via parallel research streams, employing a shared, imaging technology. The concluding section describes how these developments can be understood as signaling the emergence of a new version of human nature and the unconscious. My argument is not that empathy in the social brain is a myth, but rather that it is served by a myth consonant with the canons of science. (shrink)

In the current dialogue of “science and religion,” it is widely assumed that the thoughts of Darwinists and that of atheists overlap. However, Jerry Fodor, a full-fledged atheist, recently announced a war against Darwinism with his atheistic campaign. Prima facie, this “civil war” might offer a chance for theists: If Fodor is right, Darwinistic atheism will lose the cover of Darwinism and become less tenable. This paper provides a more pessimistic evaluation of the situation by explaining the following: Fodor’s criticism (...) of adaptationism (as the backbone of Darwinism), viz., his refutation of any counterfactual-supporting laws on the macro-evolutionary level, implies that a law-maker is dispensable on this level. This will either encourage skepticism against the omniscience (at least that concerning the future of macro-evolution) of the Creator, or render the notion of God less appealing. (shrink)

Interdisciplinary research is frequently viewed as an important component of the research landscape through its innovative ability to integrate knowledge from different areas. However, support for interdisciplinary research is often strategic rhetoric, with policy-makers and universities frequently adopting practices that favour disciplinary performance. We argue that disciplinary and interdisciplinary research are complementary, and we develop a simple framework that demonstrates this for a semi-permanent interdisciplinary research field. We argue that the presence of communicating infrastructures fosters communication and integration between disciplines (...) and the interdisciplinary research field to generate innovative knowledge. We apply this to the experience of economic history in Australia in the second half of the twentieth century to demonstrate the life cycle of a semi-permanent interdisciplinary research field. (shrink)

Recent years have seen growing evidence of a fruitful engagement between phenomenology and cognitive science. This paper confronts an in-principle problem that stands in the way of this intellectual coalition, namely the fact that a tension exists between the transcendentalism that characterizes phenomenology and the naturalism that accompanies cognitive science. After articulating the general shape of this tension, I respond as follows. First, I argue that, if we view things through a kind of neo-McDowellian lens, we can open up a (...) conceptual space in which phenomenology and cognitive science may exert productive constraints on each other. Second, I describe some examples of phenomenological cognitive science that illustrate such constraints in action. Third, I use the mutually constraining relationship at work here as the platform from which to bring to light a domesticated version of the transcendental and a minimal form of naturalism that are compatible with each other. (shrink)

Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...) the functional properties of the system, which may not coincide with its mechanistic organization. I describe these techniques and show that despite being non-mechanistic, these cognitive models can satisfy the normative constraints on good explanations. (shrink)

I have argued elsewhere that non-sentential representations that are the close kin of scale models can be, and often are, realized by computational processes. I will attempt here to weaken any resistance to this claim that happens to issue from those who favor an across-the-board computational theory of cognitive activity. I will argue that embracing the idea that certain computers harbor nonsentential models gives proponents of the computational theory of cognition the means to resolve the conspicuous disconnect between the sentential (...) character of the data structures they posit and the nonsentential qualitative character of our perceptual experiences of corporeal (i.e., spatial, kinematic, and dynamic) properties. Along the way, I will question the viability of some externalist remedies for this disconnect, and I will explain why the computational theory put forward here falls quite clearly beyond the useful bounds of the Chinese-Room argument. (shrink)

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...) targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

In this paper, I will focus on the extension theories of technology. I will identify four influential positions that have been put forward: (1) technology as an extension of the human organism, (2) technology as an extension of the lived body and the senses, (3) technology as an extension of our intentions and desires, and (4) technology as an extension of our faculties and capabilities. I will describe and critically assess these positions one by one and highlight their advantages and (...) their shortcomings and limitations. Along the way, I will explicate some of the differences and similarities between the various approaches. I conclude the paper with some suggestions for future research directions that will be beneficial for advancing theory building and that will drive forward the philosophical refinement of extension theory. (shrink)

Cognitive Science is a promising field of research that deals with one of the most fundamental questions ever: how do beings know? However, despite the long and extensive tradition of the field it has not yet become an area of knowledge with scientific identity. This is primarily due to three reasons: the lack of boundaries in defining the object of study, i.e. cognition, the lack of a precise, robust and consistent scientific methodology and results, and the inner problems derived from (...) its interdisciplinary nature. This paper presents a background review, a theoretical frame and a humble reflection on these topics in order to arouse the internal debate among readers once more. (shrink)

To which extent is it justified to adopt Kant as a godfather of cognitive science? To prepare the stage for an answer of this question, we need to set aside Kant’s general transcendental approach to the mind which is radically anti-empiricist and instead turn our attention to his specific topics and claims regarding the mind which are often not focus of Kant’s epistemological investigations. If someone is willing to take this stance, it turns out that there are many bridges connecting (...) Kant with contemporary cognitive science. We investigate possible bridges suggested in the literature between some of Kant’s central claims about consciousness, mental content, and functions of mind, and some specific treatments of these topics in contemporary philosophy of mind and cognitive science. While doing so, we offer additional arguments for some proposed bridges, reconstruct others and completely destroy still other bridges by demonstrating that some suggested links between Kant and cognitive science remain only apparent. (shrink)

Our primary goal in this article is to discuss the cross-talk between biological and cultural factors that become manifested in the individual brain development, neural wiring, neurochemical homeostasis, and behavior. We will show that behavioral propensities are the product of both cultural and biological factors and an understanding of these interactive processes can provide deep insights into why people behave the way they do. This interdisciplinary perspective is offered in an effort to generate dialog and empirical work among scholars interested (...) in merging aspects of anthropology and neuroscience, and anticipates that biological and cultural anthropology converge. We discuss new theoretical developments, hypothesis-testing strategies, and cross-disciplinary methods of observation and data collection. We believe that the exigency of integrating anthropology and the neurosciences is indisputable and anthropology's role in an emerging interdisciplinary science of human behavior will be critical because its focus is, and has always been, on human biological and cultural systems. (shrink)

An intuitive view is that creativity involves bringing together what is already known and familiar in a way that produces something new. In cognitive science, this intuition is typically formalized in terms of computational processes that combine or associate internally represented information. From this computationalist perspective, it is hard to imagine how non-representational approaches in embodied cognitive science could shed light on creativity, especially when it comes to abstract conceptual reasoning of the kind scientists so often engage in. The present (...) article offers an entry point to addressing this challenge. The scientific project of embodied cognitive science is a continuation of work in the functionalist tradition in psychology developed over a century ago by William James and John Dewey, among others. The focus here is on how functionalist views on the nature of mind, thought, and experience offer an alternative starting point for cognitive science in general, and for the cognitive science of scientific creativity in particular. The result may seem paradoxical. On the one hand, the article claims that the functionalist conceptual framework motivates rejecting mainstream cognitive views of creativity as the combination or association of ideas. On the other hand, however, the strategy adopted here—namely, revisiting ideas from functionalist psychology to inform current scientific theorizing—can itself be described as a process of arriving at new, creative ideas from combinations of old ones. As is shown here, a proper understanding of cognition in light of the functionalist tradition resolves the seeming tension between these two claims. (shrink)

A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.

The Lisp programming language is often described as the first functional programming language and also as an important early AI language. In the history of functional programming, however, it occupies a rather anomalous position, as the circumstances of its development do not fit well with the widely accepted view that functional languages have been developed through a theoretically-inspired project of deriving practical programming languages from the lambda calculus. This paper examines the origins of Lisp in the early AI programming work (...) of the mid-to-late 1950s, and in particular in the work of Allen Newell, Cliff Shaw and Herbert Simon. Their 1956 program, the Logic Theory Machine, introduced new ideas about data and program structures that were articulated in response to perceived limitations in existing programming technique. Later writers, notably John Backus, have described these features as constituting a “programming language style” distinct from the traditional style that preceded it. The paper examines the origins of the earlier style in practices of manual computation, analyses the key technical differences between it and the style first manifested in the Logic Theory Machine, and concludes that programming practice and experience play a large and underappreciated role in the development of programming styles and languages. (shrink)

The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to symbol grounding. (...) In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism. (shrink)

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...) and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing. (shrink)

According to the hypotheses of distributed and extended cognition, remembering does not always occur entirely inside the brain but is often distributed across heterogeneous systems combining neural, bodily, social, and technological resources. These ideas have been intensely debated in philosophy, but the philosophical debate has often remained at some distance from relevant empirical research, while empirical memory research, in particular, has been somewhat slow to incorporate distributed/extended ideas. This situation, however, appears to be changing, as we witness an increasing level (...) of interaction between the philosophy and the empirical research. In this editorial, we provide a high-level historical overview of the development of the debates around the hypotheses of distributed and extended cognition, as well as relevant theory and empirical research on memory, considering both the role of memory in theoretical debates around distributed/extended ideas and strands of memory research that resonate with those ideas; we emphasize recent trends towards increased interaction, including new empirical paradigms for investigating distributed memory systems. We then provide an overview of the special issue itself, drawing out a number of general implications from the contributions, and conclude by sketching promising directions for future research on distributed memory. (shrink)

Enactive and ecological approaches to cognitive science both claim a “mutuality” between agents and their environments – that they have a complementary nature and should be addressed as a single whole system. Despite this apparent agreement, each offers criticisms of the other on precisely this point – enactivists claiming that ecological psychologists over-emphasise the environment, while the complementary criticism, of agent-centred constructivism, is levelled by ecological psychologists at enactivists. In this paper I suggest that underlying the confusion between the two (...) approaches is the complexity of agency, which comes in different forms, at different scales or levels of analysis. Cognitive science has not theorised the relationship between these different forms in a sufficiently disciplined manner, and a task therefore remains of finding a way to map the complex territory of agency. (shrink)

The past decade has seen an explosion of work on the history of the human sciences during the Cold War. This work, however, does not engage with one of the leading human sciences of the period: linguistics. This article begins to rectify this knowledge gap by investigating the influence of linguistics and its concept of study, language, on American public, political and intellectual life during the postwar and early Cold War years. I show that language emerged in three frameworks in (...) this period: language as tool, language as weapon, and language as knowledge. As America stepped onto the international stage, language and linguistics were at the forefront: the military poured millions of dollars into machine translation, American diplomats were required to master scores of foreign languages, and schoolchildren were exposed to language-learning on a scale never before seen in the United States. Together, I argue, language and linguistics formed a critical part of the rise of American leadership in the new world order — one that provided communities as dispersed as the military, the diplomatic corps, scientists and language teachers with a powerful way of tackling the problems they faced. To date, linguistics has not been integrated into the broader framework of Cold War human sciences. In this article, I aim to bring both language, as concept, and linguistics, as discipline, into this framework. In doing so, I pave the way for future work on the history of linguistics as a human science. (shrink)

Cultural psychologists often describe the relationship between mind and culture as ‘dynamic.’ In light of this, we provide two desiderata that a theory about encultured minds ought to meet: the theory ought to reflect how cultural psychologists describe their own findings and it ought to be thoroughly naturalistic. We show that a realist theory of causal powers—which holds that powers are causally-efficacious and empirically-discoverable—fits the bill. After an introduction to the major concepts in cultural psychology and describing causal power realism, (...) we use a case study—the effects of pathogen prevalence on culture and cognition—to show the explanatory capacities of the powers framework. (shrink)

Recent progress in artificial intelligence 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 that of 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 build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)

This article outlines the emergence of ABA in the mid-20th century, and the current popularity of ABA in the anglophone world. I draw on the work of earlier historians to highlight the role of Ole Ivar Lovaas, the most influential practitioner of ABA. I argue that reception of his initial work was mainly positive, despite concerns regarding its efficacy and use of physical aversives. Lovaas’ work, however, was only cautiously accepted by medical practitioners until he published results in 1987. Many (...) accepted the results as validation of Lovaas’ research, though both his methods and broader understanding of autism had shifted considerably since his early work in the 1960s. The article analyses the controversies surrounding ABA since the early 1990s, considering in particular criticisms made by autistic people in the ‘neurodiversity movement’. As with earlier critics, some condemn the use of painful aversives, exemplified in the campaign against the use of shock therapy at the Judge Rotenberg Center. Unlike earlier, non-autistic critics, however, many in this movement reject the ideological goals of ABA, considering autism a harmless neurological difference rather than a pathology. They argue that eliminating benign autistic behaviour through ABA is impermissible, owing to the individual psychological harm and the wider societal impact. Finally, I compare the claims made by the neurodiversity movement with those made by similar 20th- and 21st-century social movements. (shrink)

Artificial intelligence (AI) is one of the main drivers of what has been described as the “Fourth Industrial Revolution”, as well as the most innovative technology developed to date. It is a pervasive transformative innovation, which needs a new approach. In 2017, the European Parliament introduced the notion of the “electronic person”, which sparked huge debates in philosophical, legal, technological, and other academic settings. The issues related to AI should be examined from an interdisciplinary perspective. In this paper, we examine (...) this legal innovation—that has been proposed by the European Parliament—from not only legal but also technological points of view. In the first section, we define AI and analyse its main characteristics. We argue that, from a technical perspective, it appears premature and probably inappropriate to introduce AI personhood now. In the second section, justifications for the European Parliament’s proposals are explored in contrast with the opposing arguments that have been presented. As the existing mechanisms of liability could be insufficient in scenarios where AI systems cause harm, especially when algorithms of AI learn and evolve on their own, there is a need to depart from traditional liability theories. (shrink)

This paper criticizes the role of intuition-based ascriptions of cognition that are closely related to the ascription of mind. This practice hinders the explication of a clear and stable target domain for the cognitive sciences. To move forward, the proposal is to cut the notion of cognition free from such ascriptions and the intuition-based judgments that drive them. Instead, cognition is reinterpreted and developed as a scientific concept that is tied to a material domain of research. In this reading, cognition (...) becomes a changeable theoretical concept that can and must be adapted to the findings within this target domain. Taking humans as the best-established existing example of the relevant material target domain, this central case is extended to include all living systems. To clarify what it is about living systems that warrants their role as cognitive target domain, the new concept of cobolism is introduced as a complement to metabolism. Cobolism refers to the systematic ways in which each living system encompasses structures, processes and external events that maintain the fundamental metabolic processes that constitute the core of each living system. Cobolism is perfectly general, applies to bacterial and human cases alike, and provides a general format to describe wildly different cognitive organizations. It provides a clear target for the cognitive sciences to work on, turning them into what we can call the cognitive life sciences. (shrink)

Cultural psychologists often describe the relationship between mind and culture as ‘dynamic.’ In light of this, we provide two desiderata that a theory about encultured minds ought to meet: the theory ought to reflect how cultural psychologists describe their own findings and it ought to be thoroughly naturalistic. We show that a realist theory of causal powers — which holds that powers are causally-efficacious and empirically-discoverable — fits the bill. After an introduction to the major concepts in cultural psychology and (...) describing causal power realism, we use a case study — the effects of pathogen prevalence on culture and cognition — to show the explanatory capacities of the powers framework. (shrink)

The paper takes as its starting point Donna Haraway’s suggestion, “The actors are cyborg, nature is coyote, and the geography is elsewhere”. It discusses first the understanding of the cyborg promoted by Haraway as illustrating an ontological non-humanist disposition, rather than a periodizing claim. The second part of the paper examines some instances of low-tech cyborg identities, which have emerged in developing countries (elsewhere) as a consequence of development initiatives. The paper argues that the quite literal attempts to develop cyborgs (...) in such countries gives rise to developments not foreseen or controllable by the development industries. If cyborg identities are developing and minds and bodies shaped in the frictions between culture, technology, economy, and development projects and activities then what are the implications for cognitive studies. In the final part of the paper this question is considered and it is suggested that cognitive studies would do well to expand their analytical foci to take into account cyborg bodies and minds found “elsewhere”. (shrink)

The article presents an epistemological and partially methodological analysis of cognitive science as a scientific discipline, created as a result of the transformations that took place in the philosophical and psychological concepts of the mind and cognition, which were carried out with the aid of tools and methods of modelling as well as through simulating human cognitive processes and consciousness. In order to describe this interdisciplinary science, and its positions, as well as the stages and directions of its development, it (...) makes use of the epistemological model formulated by Michel Foucault, in which he draws attention to social, ideological and technological conditions of scientific knowledge. The opinions of the leading creators and critics of cognitive science, such as George A. Miller, Howard Gardner, Margaret Boden and José Luis Bermúdez are referenced to and analyzed with the use of this model. The article shows the epistemologically and methodologically divergent status of cognitive science, as well as its cognitive and institutional conditions and challenges, which stand before it after half a century of intensive development. (shrink)

Will robots ever be able to learn like humans? To answer that question, one first needs to ask: what is learning? Hubert and Stuart Dreyfus had a point when they claimed that computers and robots would never be able to learn like humans because human learning, after an initial phase of rule-based learning, is uncertain, context sensitive and intuitive under contract F49620-C-0063 with the University of California) Berkeley, February 1980.. Washington, DC: Storming Media. https://www.stormingmedia.us/15/1554/A155480.html. Accessed 10 Oct 2017, 1980). I (...) would add that learning also builds on prior learning, and that from the outset, human learning is a socio-cultural materially grounded collective epistemology. This posthuman acknowledgement shifts the focus from the individual learner to learning within collective phenomena. Dreyfus and Dreyfus do not seem to emphasise the essentially social and cultural nature of the human condition. Learning theory, new materialism and postphenomenology have emphasised in different ways the materially based socio-cultural nature of human learning. They thereby point towards a ‘posthuman’ learning that is far from the machine-like or enhanced creature envisioned by singularists. Until robots are essentially social and ground their epistemologies in socio-cultural materiality, I suggest that human-like AI is not possible. (shrink)

The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the (...) traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. -/- According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). -/- In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them. (shrink)

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, I first (...) contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did Turing refer to (...) gender imitation in a test for machine intelligence? In this article, I shall address these questions by unveiling social, historical and epistemological roots of the so-called Turing test. I will draw attention to a historical fact that has been only scarcely observed in the secondary literature thus far, namely that Turing’s 1950 test emerged out of a controversy over the cognitive capabilities of digital computers, most notably out of debates with physicist and computer pioneer Douglas Hartree, chemist and philosopher Michael Polanyi, and neurosurgeon Geoffrey Jefferson. Seen in its historical context, Turing’s 1950 paper can be understood as essentially a reply to a series of challenges posed to him by these thinkers arguing against his view that machines can think. Turing did propose gender learning and imitation as one of his various imitation tests for machine intelligence, and I argue here that this was done in response to Jefferson's suggestion that gendered behavior is causally related to the physiology of sex hormones. (shrink)

Virtue ethics seems to be a promising moral theory for understanding and interpreting the development and behavior of artificial moral agents. Virtuous artificial agents would blur traditional distinctions between different sorts of moral machines and could make a claim to membership in the moral community. Accordingly, we investigate the “machine question” by studying whether virtue or vice can be attributed to artificial intelligence; that is, are people willing to judge machines as possessing moral character? An experiment describes situations where either (...) human or AI agents engage in virtuous or vicious behavior and experiment participants then judge their level of virtue or vice. The scenarios represent different virtue ethics domains of truth, justice, fear, wealth, and honor. Quantitative and qualitative analyses show that moral attributions are weakened for AIs compared to humans, and the reasoning and explanations for the attributions are varied and more complex. On “relational” views of membership in the moral community, virtuous machines would indeed be included, even if they are indeed weakened. Hence, while our moral relationships with artificial agents may be of the same types, they may yet remain substantively different than our relationships to human beings. (shrink)

This article explores the proposition that the brain, normally seen as an organ of the human body, should be understood as a biologically based form of artificial intelligence, in the course of which the case is made for a new kind of ‘brain exceptionalism’. After noting that such a view was generally assumed by the founders of AI in the 1950s, the argument proceeds by drawing on the distinction between science—in this case neuroscience—adopting a ‘telescopic’ or a ‘microscopic’ orientation to (...) reality, depending on how it regards its characteristic investigative technologies. The paper concludes by recommending a ‘microscopic’ yet non-reductionist research agenda for neuroscience, in which the brain is seen as an underutilised organ whose energy efficiency is likely to outstrip that of the most powerful supercomputers for the foreseeable future. (shrink)

There is a small but growing community of researchers spanning a spectrum of disciplines which are united in rejecting the still dominant computationalist paradigm in favor of theenactive approach. The framework of this approach is centered on a core set of ideas, such as autonomy, sense-making, emergence, embodiment, and experience. These concepts are finding novel applications in a diverse range of areas. One hot topic has been the establishment of an enactive approach to social interaction. The main purpose of this (...) paper is to serve as an advanced entry point into these recent developments. It accomplishes this task in a twofold manner: it provides a succinct synthesis of the most important core ideas and arguments in the theoretical framework of the enactive approach, and it uses this synthesis to refine the current enactive approach to social interaction. A new operational definition of social interaction is proposed which not only emphasizes the cognitive agency of the individuals and the irreducibility of the interaction process itself, but also the need for jointly co-regulated action. It is suggested that this revised conception of ‘socio-cognitive interaction’ may provide the necessary middle ground from which to understand the confluence of biological and cultural values in personal action. (shrink)

What forms of consciousness can the subject have of her body in action? This is a recurrent issue in contemporary research on skilled movement and expertise, and according to a widespread view, the body makes itself inconspicuous in performance in favour of the object or goal that the activity is directed to. However, this attitude to consciousness in bodily performance seems unsatisfying for an understanding of skilled action, and the work of several researchers can be seen as responding to this (...) view: Montero, Legrand, Ravn and others in the philosophy of expertise and of dance have developed various notions of consciousness and cognition to account for the mindful processes at play in performance. Two related questions can be distinguished here: 1. Is there an inherent conflict between skilled action and at least more than marginal awareness of that action, or is it possible – and even desirable – to reflect on our own performance without considerably impeding on it? 2. What forms of consciousness pertaining to the body in action must we distinguish in order to answer the first question? This paper gives an overview of this discussion, focusing on the second issue, although the first will come into play in so far as it is linked with the latter question. Drawing on Merleau-Ponty’s analyses of bodily reflection and on dancers’ descriptions, I show that there is, in phenomenological terms, a bodily level of reflection: a fully conscious and exploratory activity that is led by the skilled body, and that is explicitly aimed at by many performers. (shrink)

Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...) neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin–Huxley and FitzHugh–Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience. (shrink)

A key failing in contemporary philosophy of mind is the lack of attention paid to evolutionary theory in its research projects. Notably, where evolution is incorporated into the study of mind, the work being done is often described as philosophy of cognitive science rather than philosophy of mind. Even then, whereas possible implications of the evolution of human cognition are taken more seriously within the cognitive sciences and the philosophy of cognitive science, its relevance for cognitive science has only been (...) appreciated relatively recently, and the approach still comes in for some major criticism from prominent theorists within the field. This paper explores some of the reasons for this state of affairs and finds that it might have less to do with due consideration and well-founded scepticism about the relevance of evolutionary theory to these disciplines and more to do with historical accident and faulty assumptions on the part of key theorists in these disciplines. It is also noted that where cognitive scientists are taking evolution into account in their work on the mind, they straying more and more into domains that used to fall exclusively under the purview of philosophy of mind as it is traditionally conceived – qualia, consciousness, perception, intentionality and so forth. The point is made that in ignoring the work being done on the evolution of mind, philosophy of mind runs the risk of becoming obsolete. (shrink)

Se analiza el debate entre Eleonore Stump y Antonio Damasio a propósito de dos posibles estrategias a la hora de superar el “error” neurocientífico del dualismo cartesiano respecto de la correlación entre mente y cerebro, a saber: o bien se corrige el “error” neurocientífico de Descartes desde un modelo híbrido de tipo monista como el de Spinoza que ahora también se utiliza para justificar un materialismo eliminativo aún más radicalizado, a pesar de seguir manteniendo de un modo meramente heurístico las (...) diferencias entre mente y cerebro, al modo propuesto por Antonio Damasio; o bien se recurre a un modelo dualista vitalista de integración jerarquizada interactiva entre la mente y el cerebro, al modo propuesto por Aquinas, y aún antes Aristóteles, con una indudable ventaja. En este segundo caso sería posible justificar la existencia de diversos niveles de autorregulación deliberativa entre mente y cerebro, sin tener que restringir de un modo apriorista los márgenes de libertad y espontaneidad a un único nivel autoinmune básico de tipo determinista, salvo que se hiciera con fines meramente heurísticos, al modo ahora también señalado por Eleonore Stump. Por su parte la comunicación analiza las consecuencias que cada una de estas propuestas pueden llegar a tener para la justificación de los diversos tipos de autorregulación que hoy día se asignan a la neuroética, neuropolítica y neuroeconomía. (shrink)

Service-Robotic—mainly defined as “non-industrial robotics”—is identified as the next economical success story to be expected after robots have been ubiquitously implemented into industrial production lines. Under the heading of service-robotic, we found a widespread area of applications reaching from robotics in agriculture and in the public transportation system to service robots applied in private homes. We propose for our interdisciplinary perspective of technology assessment to take the human user/worker as common focus. In some cases, the user/worker is the effective subject (...) acting by means of and in cooperation with a service robot; in other cases, the user/worker might become a pure object of the respective robotic system, for example, as a patient in a hospital. In this paper, we present a comprehensive interdisciplinary framework, which allows us to scrutinize some of the most relevant applications of service robotics; we propose to combine technical, economical, legal, philosophical/ethical, and psychological perspectives in order to design a thorough and comprehensive expert-based technology assessment. This allows us to understand the potentials as well as the limits and even the threats connected with the ongoing and the planned implementation of service robots into human lifeworld—particularly of those technical systems displaying increasing grades of autonomy. (shrink)

Abstract In this article, we investigate the merits of an enactive view of cognition for the contemporary debate about social cognition. If enactivism is to be a genuine alternative to classic cognitivism, it should be able to bridge the “cognitive gap”, i.e. provide us with a convincing account of those higher forms of cognition that have traditionally been the focus of its cognitivist opponents. We show that, when it comes to social cognition, current articulations of enactivism are—despite their celebrated successes (...) in explaining some cases of social interaction—not yet up to the task. This is because they (1) do not pay sufficient attention to the role of offline processing or “decoupling”, and (2) obscure the cognitive gap by overemphasizing the role of phenomenology. We argue that the main challenge for the enactive view will be to acknowledge the importance of both coupled (online) and decoupled (offline) processes for basic and advanced forms of (social) cognition. To meet this challenge, we articulate a dynamic embodied view of cognition. We illustrate the fruitfulness of this approach by recourse to recent findings on false belief understanding. Content Type Journal Article Pages 1-23 DOI 10.1007/s11097-011-9223-1 Authors Leon C. de Bruin, Department of Philosophy II, Ruhr-University Bochum, Universitätsstr. 150, 44801 Bochum, Germany Lena Kästner, Department of Philosophy II, Ruhr-University Bochum, Universitätsstr. 150, 44801 Bochum, Germany Journal Phenomenology and the Cognitive Sciences Online ISSN 1572-8676 Print ISSN 1568-7759. (shrink)

Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...) human society held a prejudiced attitude toward machinery—seeing machines a priori as mindless objects—machines could not be said to be intelligent, by definition. He also realized, though, that if humans’ a priori, chauvinistic attitude toward machinery changed, the existence of intelligent machines would become logically possible. Turing thought that such a change would eventually occur: He believed that when scientists overcome the technological challenge of constructing sophisticated machines that could imitate human verbal behavior—i.e., do well in the imitation game—humans’ prejudiced attitude toward machinery will have altered in such a way that machines could be said to be intelligent. The imitation game, for Turing, was not an intelligence test, but a technological aspiration whose realization would likely involve a change in society’s attitude toward machines. (shrink)

Though there are many challenges to Ekman’s thesis that there are basic emotions with universal corresponding facial expressions, our main criticism revolves around the extent to which grounding situations alter how people read faces. To that end, we recruit testifying experimental studies that show identical faces expressing varying emotions when contextualized differently. Rather than dismissing these as illusions, we start with the position—generally favored by embodied thinkers—that situations are primary: they are where specifiable and hence knowable properties first show up. (...) We further argue that situationally inflected emotional expressions are informationally meaningful. We reject the idea that reading expressions is primarily about ascertaining internal mental states, arguing instead that people are registering overall situations when looking at faces. However, if mind is understood as a situated phenomenon that extends into active ecological frames, then one can still argue that mindreading is going on. Although we do not claim isolated things like cliffs or cars have agency, we speculate networked systems with cliffs, people, cars, bears, etc., collectively function with intentionality, more so if advancing a robust situated mind thesis, contra figures like Dennett who argue that people over-impute mind to things. Our position has practical implications insofar as it casts doubts on recent attempts to develop AI systems that extract emotional intent out of facial expressions since many of these systems are grounded on Ekman’s basic view. (shrink)

The paper examines Marcello Barbieri’s (2007) Introduction to Biosemiotics. Highlighting debate within the biosemiotic community, it focuses on what the volume offers to those who explain human intellect in relation to what Turing called our ‘physical powers.’ In scrutinising the basis of world-modelling, parallels and contrasts are drawn with other work on embodied-embedded cognition. Models dominate biology. Is this a qualitative fact or does it point to biomechanisms? In evaluating the 18 contributions, it is suggested that the answers will shape (...) the field. First, they will decide if biochemistry and explanatory reduction can be synergised by biosemantics. Second, they will show if our intellectual powers arise from biology. Does thinking use—not a language faculty—but what Markoš and colleagues call semiosis by the living? Resolution of such issues, it is suggested, can change how we view cognition. Above all, if the biomechanists win the day, cultural models can be regarded as extending natural meaning. On such a view, biomechanisms prompt us to act and perceive as we model our own natural models. This fits Craik’s vision: intellect gives us the alphanumerical ‘symbols’ that allow thoughts to have objective validity. For the biomechanist, this is explained—not by brains alone—but, rather, by acting under the constraints of historically extended sensoria. (shrink)

This paper introduces a new, expanded range of relevant cognitive psychological research on collaborative recall and social memory to the philosophical debate on extended and distributed cognition. We start by examining the case for extended cognition based on the complementarity of inner and outer resources, by which neural, bodily, social, and environmental resources with disparate but complementary properties are integrated into hybrid cognitive systems, transforming or augmenting the nature of remembering or decision-making. Adams and Aizawa, noting this distinctive complementarity argument, (...) say that they agree with it completely: but they describe it as “a non-revolutionary approach” which leaves “the cognitive psychology of memory as the study of processes that take place, essentially without exception, within nervous systems.” In response, we carve out, on distinct conceptual and empirical grounds, a rich middle ground between internalist forms of cognitivism and radical anti-cognitivism. Drawing both on extended cognition literature and on Sterelny’s account of the “scaffolded mind” (this issue), we develop a multidimensional framework for understanding varying relations between agents and external resources, both technological and social. On this basis we argue that, independent of any more “revolutionary” metaphysical claims about the partial constitution of cognitive processes by external resources, a thesis of scaffolded or distributed cognition can substantially influence or transform explanatory practice in cognitive science. Critics also cite various empirical results as evidence against the idea that remembering can extend beyond skull and skin. We respond with a more principled, representative survey of the scientific psychology of memory, focussing in particular on robust recent empirical traditions for the study of collaborative recall and transactive social memory. We describe our own empirical research on socially distributed remembering, aimed at identifying conditions for mnemonic emergence in collaborative groups. Philosophical debates about extended, embedded, and distributed cognition can thus make richer, mutually beneficial contact with independently motivated research programs in the cognitive psychology of memory. (shrink)

Gedächtnis-Enhancement oder Memory-Enhancement ist ein Teilbereich der verschiedenen Ansätze zur pharmakologischen und technischen Verbesserung menschlicher Leistungsfähigkeit. Wie Erfahrungsberichte von Menschen mit von Natur aus gesteigertem Erinnerungsvermögen zeigen, ist eine Steigerung der Gedächtnisfähigkeit prinzipiell möglich. Allerdings verweisen diese Erfahrungen auch auf einige Komplikationen und Beschwernisse infolge dieser gesteigerten Leistungsfähigkeit. Es wird argumentiert, dass erstens diejenigen philosophischen Theorien, die die Funktion des Gedächtnisses v. a. in der Speicherung von Informationen lokalisieren, einige dieser Probleme nicht antizipieren und nur unzulänglich erklären können. Zweitens wird (...) argumentiert, dass philosophische Konzepte zur Funktion von Erinnern und Vergessen, die deren Bedeutung bei der Bildung eines normativ geleiteten Selbstverständnisses in den Vordergrund stellen, diese und weitere mögliche Komplikationen deutlicher in den Blick bekommen können. Beispielhaft wird hier auf Ansätze von Ricoeur und Nietzsche eingegangen. (shrink)