If Australasian philosophers constitute the kind of group to which a collective identity or broadly shared self-image can plausibly be ascribed, the celebrated history of Australian materialism rightly lies close to its heart. Jack Smart’s chapter in this volume, along with an outstanding series of briefer essays in A Companion to Philosophy in Australia and New Zealand (Forrest 2010; Gold 2010; Koksvik 2010; Lycan 2010; Matthews 2010; Nagasawa 2010; Opie 2010; Stoljar 2010a), effectively describe the naturalistic realism of Australian philosophy (...) of mind. In occasional semi-serious psychogeographic speculation, this long-standing and strongly-felt intellectual attitude has been traced back to the influences of our light, land, or lifestyle (Devitt 1996, x; compare comments by Chalmers and O’Brien in Mitchell, 2006). Australasian work in philosophy of mind and cognition has become more diverse in the last 40 years, but is almost all still marked, in one way or another, by the history of these debates on materialism. (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)

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)

Anthropology and the other cognitive science (CS) subdisciplines currently maintain a troubled relationship. With a debate in topiCS we aim at exploring the prospects for improving this relationship, and our introduction is intended as a catalyst for this debate. In order to encourage a frank sharing of perspectives, our comments will be deliberately provocative. Several challenges for a successful rapprochement are identified, encompassing the diverging paths that CS and anthropology have taken in the past, the degree of compatibility between (1) (...) CS and (2) anthropology with regard to methodology and (3) research strategies, (4) the importance of anthropology for CS, and (5) the need for disciplinary diversity. Given this set of challenges, a reconciliation seems unlikely to follow on the heels of good intentions alone. (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)

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)

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)

Philosophical Psychology, Volume 0, Issue 0, Page 1-5, Ahead of Print.

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)

Simon’s bounded rationality , the first scientific research program to seriously take the cognitive limitations of decision makers into account, has often been conflated with his more restricted concept of satisficing—choosing an alternative that meets or exceeds specified criteria, but that is not guaranteed to be unique or in any sense “the best.” Proponents of optimization often dismiss bounded rationality out of hand with the following “hallway syllogism” : bounded rationality “boils down to” satisficing; satisficing is “simply” a theory of (...) search for alternatives that takes into account the costs of computation. Hence, bounded rationality is “just a minor tweak” on optimal search theory. (shrink)

This paper extends three decades of work arguing that researchers who discuss consciousness should not restrict themselves only to (adult) human minds, but should study (and attempt to model) many kinds of minds, natural and artificial, thereby contributing to our understanding of the space containing all of them. We need to study what they do or can do, how they can do it, and how the natural ones can be emulated in synthetic minds. That requires: (a) understanding sets of requirements (...) that are met by different sorts of minds, i.e. the niches that they occupy, (b) understanding the space of possible designs, and (c) understanding complex and varied relationships between requirements and designs. Attempts to model or explain any particular phenomenon, such as vision, emotion, learning, language use, or consciousness lead to muddle and confusion unless they are placed in that broader context. A methodology for making progress is summarised and a novel requirement proposed for a theory of how human minds work: the theory should support a single generic design for a learning, developing system that, in addition to meeting familiar requirements, should be capable of developing different and opposed philosophical viewpoints about consciousness, and the so-called hard problem. In other words, we need a common explanation for the mental machinations of mysterians, materialists, functionalists, identity theorists, and those who regard all such theories as attempting to answer incoherent questions. No designs proposed so far come close. (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)

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)

Cognitive science is the interdisciplinary investigation of mind and intelligence, embracing psychology, neuroscience, anthropology, artificial intelligence, and philosophy. There are many important philosophical questions related to this investigation, but this short chapter will focus on the following three. What is the nature of the explanations and theories developed in cognitive science? What are the relations among the five disciplines that comprise cognitive science? What are the implications of cognitive science research for general issues in the philosophy of science? I will (...) argue that cognitive theories and explanations depend on representations of mechanisms and that the relations among the five disciplines, especially psychology and neuroscience, depend on relations between kinds of mechanisms. These conclusions have implications for central problems in general philosophy of science such as the nature of theories, explanations, and reduction between theories at different levels. (shrink)

The foundations of biology have been a topic of debate for the past few decades. The traditional perspective of the Modern Synthesis, which portrays organisms as passive entities with limited role in evolutionary theory, is giving way to a new paradigm where organisms are recognized as active agents, actively shaping their own phenotypic traits for adaptive purposes. Within this context, this article raises the question of whether contemporary biological theory is undergoing a cognitive revolution. This inquiry can be approached in (...) two ways: from a theoretical standpoint, exploring the centrality of the cognitive sciences in current theoretical biology; and from a historical perspective, examining the resemblance between the current state of theoretical biology and the Cognitive Revolution of the mid-20th century. Both inquiries yield affirmative answers, though important nuances will be emphasized. The cognitive sciences' explanatory framework is employed to elucidate the agentic characteristics of organisms, establishing a clear parallelism between the Cognitive Revolution and the present state of theoretical biology. (shrink)

Some philosophers search for the mark of the cognitive: a set of individually necessary and jointly sufficient conditions identifying all instances of cognition. They claim that the mark of the cognitive is needed to steer the development of cognitive science on the right path. Here, I argue that, at least at present, it cannot be provided. First (§2), I identify some of the factors motivating the search for a mark of the cognitive, each yielding a desideratum the mark is supposed (...) to satisfy (§2.1). I then (§2.2) highlight a number of tensions in the literature on the mark of the cognitive, suggesting they’re best resolved by distinguishing two distinct programs. The first program (§3) is that of identifying a mark of the cognitive capturing our everyday notion of cognition. I argue that such a program is bound to fail for a number of reasons: it is not clear whether such an everyday notion exists; and even if it existed, it would not be able to spell out individually necessary and jointly sufficient conditions for cognition; and even if it were able to spell them out, these conditions won’t satisfy the desiderata a mark of the cognitive should satisfy. The second program is that of identifying a mark of the cognitive spelling out a genuine scientific kind. But the current state of fragmentation of cognitive science, and the fact that it is splintered in a myriad of different research traditions, prevent us from identifying such a kind. And we have no reason to think that these various research traditions will converge, allowing us to identify a single mark. Or so, at least, I will argue in (§4). I then conclude the paper (§5) deflecting an intuitive objection, and exploring some of the consequences of the thesis I have defended. (shrink)

his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor is the (...) main goal of this article. The statement is substantiated that the invention of mechanical computing devices, having a long history in the European engineering tradition, formed the prerequisites for the emergence of machine functionalism in the modern philosophy of mind. The idea of multiple implementation stems from the principle that a formal symbol system prescribes rules for the use of rational abstractions through the physical architecture of a computational engine. The article considers the reasons for the conceptual shift and reveals the semantic foundations for the metaphorical transfer of the properties of abstract objects from the theory of automata to the field of modern philosophy of mind. The criticism and ways of protecting the philosophical program of machine functionalism are analyzed by changing the content of the metaphor “Mind as machine”. The reasons for the stability of the information-computer approach in cognitive sciences are also disclosed and explained. (shrink)

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)

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)

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)

Keskustelu tekoälyn soveltamiseen liittyvistä eettisistä ja poliittisista kysymyksistä käy juuri nyt kuumana. Emme halua tässä puheenvuorossa osallistua keskusteluun tarttumalla johonkin tiettyyn eettiseen ongelmaan. Sen sijaan pyrimme sanomaan jotain itsekeskustelusta ja sen vaikeudesta. Haluamme kiinnittää huomiota siihen, kuinka erilaiset ihmismielen ajattelutaipumukset ja virhepäätelmät voivat huomaamattamme vaikuttaa tapaamme hahmottaa ja ymmärtää tekoälyä ja siihen liittyviä eettisiä kysymyksiä. Kun ymmärrämme paremmin sen, kuinka hankalaa näiden kysymysten hahmottaminen arkisen mielemme kategorioilla oikein on, ja kun tunnistamme tästä syntyvät virhepäätelmät ja ajattelun vääristymät, kykenemme entistä korkeatasoisempaan (...) eettiseen arviointiin tekoälyyn liittyvissä kysymyksissä. Tarkoituksemme ei ole tarkastella loogisiavirhepäätelmiä, jotka rikkovat formaalin modus tollensin tai modus ponensin sääntöjä. Sen sijaan esittelemme empiirisiä tutkimustuloksia, jotka havainnollistavat ihmismielen taipumustatehdä systemaattisia virhearviointeja erilaisissa tilanteissa. (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)

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)

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)

What does it take to see how autistic people participate in social interactions? And what does it take to support and invite more participation? Western medicine and cognitive science tend to think of autism mainly in terms of social and communicative deficits. But research shows that autistic people can interact with a skill and sophistication that are hard to see when starting from a deficit idea. Research also shows that not only autistic people, but also their non-autistic interaction partners can (...) have difficulties interacting with each other. To do justice to these findings, we need a different approach to autistic interactions—one that helps everyone see, invite, and support better participation. I introduce such an approach, based on the enactive theory of participatory sense-making and supported by insights from indigenous epistemologies. This approach helps counteract the homogenising tendencies of the “global mental health” movement, which attempts to erase rather than recognise difference, and often precludes respectful engagements. Based in the lived experiences of people in their socio-cultural-material and interactive contexts, I put forward an engaged—even engaging—epistemology for understanding how we interact across difference. From this perspective, we see participatory sense-making at work across the scientific, diagnostic, therapeutic, and everyday interactions of autistic and non-autistic people, and how everyone can invite and support more of it. (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)

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)

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)

The pragmatist tradition in philosophy has left a sound legacy in many contemporary research fields. John Dewey’s continuist and emergentist approach to the nature-or-nurture problem in relation to the individual human mind has been regained lately in evolutionist psychology and related disciplines. For Dewey, language plays a fundamental role in creating and maintaining this continuity between the individual mind and the social and physical environment humans inhabit. The present article will focus on a few contemporary lines of research that identify (...) language as the ‘glue’ that bonds each individual to one another and to society, with a decisive impact on the development of one’s own mind. (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)

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 ethical concerns regarding the successful development of an Artificial Intelligence have received a lot of attention lately. The idea is that even if we have good reason to believe that it is very unlikely, the mere possibility of an AI causing extreme human suffering is important enough to warrant serious consideration. Others look at this problem from the opposite perspective, namely that of the AI itself. Here the idea is that even if we have good reason to believe that (...) it is very unlikely, the mere possibility of humanity causing extreme suffering to an AI is important enough to warrant serious consideration. This paper starts from the observation that both concerns rely on problematic philosophical assumptions. Rather than tackling these assumptions directly, it proceeds to present an argument that if one takes these assumptions seriously, then one has a moral obligation to advocate for a ban on the development of a conscious AI. (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)

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)

Given the personal acquaintance between Alan M. Turing and W. Ross Ashby and the partial proximity of their research fields, a comparative view of Turing’s and Ashby’s work on modelling “the action of the brain” (letter from Turing to Ashby, 1946) will help to shed light on the seemingly strict symbolic/embodied dichotomy: While it is clear that Turing was committed to formal, computational and Ashby to material, analogue methods of modelling, there is no straightforward mapping of these approaches onto symbol-based (...) AI and embodiment-centered views respectively. Instead, it will be demonstrated that both approaches, starting from a formal core, were at least partly concerned with biological and embodied phenomena, albeit in revealingly distinct ways. (shrink)

A solution to the “hard problem” requires taking the point of view of the organism and its sub- agents. The organism constructs phenomenality through acts of fiat, much as we create meaning in language, through the use of symbols that are assigned meaning in the context of an embodied evolutionary history. Phenomenality is a virtual representation, made to itself by an executive agent (the conscious self), which is tasked with monitoring the state of the organism and its environment, planning future (...) action, and coordinating various sub-agencies. Consciousness is not epiphenomenal and serves a function for higher organisms that is distinct from unconscious processing. While a strictly scientific solution to the hard problem is not possible for a science that excludes the subjectivity it seeks to explain, there is hope to at least informally bridge the explanatory gulf between mind and matter. (shrink)

This paper explores early Australasian philosophy in some detail. Two approaches have dominated Western philosophy in Australia: idealism and materialism. Idealism was prevalent between the 1880s and the 1930s, but dissipated thereafter. Idealism in Australia often reflected Kantian themes, but it also reflected the revival of interest in Hegel through the work of ‘absolute idealists’ such as T. H. Green, F. H. Bradley, and Henry Jones. A number of the early New Zealand philosophers were also educated in the idealist tradition (...) and were influential in their communities, but produced relatively little. In Australia, materialism gained prominence through the work of John Anderson, who arrived in Australia in 1927, and continues to be influential. John Anderson had been a student of Henry Jones, who might therefore be said to have influenced both main strands of Australian philosophical thought. (shrink)

What is the role of the environment, and of the information it provides, in cognition? More specifically, may there be a role for certain artefacts to play in this context? These are questions that motivate "4E" theories of cognition (as being embodied, embedded, extended, enactive). In his take on that family of views, Hajo Greif first defends and refines a concept of information as primarily natural, environmentally embedded in character, which had been eclipsed by information-processing views of cognition. He continues (...) with an inquiry into the cognitive bearing of some artefacts that are sometimes referred to as 'intelligent environments'. Without necessarily having much to do with Artificial Intelligence, such artefacts may ultimately modify our informational environments. -/- With respect to human cognition, the most notable effect of digital computers is not that they might be able, or become able, to think but that they alter the way we perceive, think and act. (shrink)

Intersemiotic translation (IT) was defined by Roman Jakobson (The Translation Studies Reader, Routledge, London, p. 114, 2000) as “transmutation of signs”—“an interpretation of verbal signs by means of signs of nonverbal sign systems.” Despite its theoretical relevance, and in spite of the frequency in which it is practiced, the phenomenon remains virtually unexplored in terms of conceptual modeling, especially from a semiotic perspective. Our approach is based on two premises: (i) IT is fundamentally a semiotic operation process (semiosis) and (ii) (...) IT is a deeply iconic-dependent process. We exemplify our approach by means of literature to dance IT and we explore some implications for the development of a general model of IT. (shrink)

The machine-organism analogy has played a pivotal role in the history of Western philosophy and science. Notwithstanding its apparent simplicity, it hides complex epistemological issues about the status of both organism and machine and the nature of their interaction. What is the real object of this analogy: organisms as a whole, their parts or, rather, bodily functions? How can the machine serve as a model for interpreting biological phenomena, cognitive processes, or more broadly the social and cultural transformations of the (...) relations between individuals, and between individuals and the environments in which they live? Wired Bodies. New Perspectives on the Machine-Organism Analogy provides the reader with some of the latest perspectives on this vast debate, addressing three major topics:1) the development of a ‘mechanistic’ framework in medicine and biology; 2) the methodological issues underlying the use of ‘simulation’ in cognitive science; 3) the interaction between humans and machines according to 20th-century epistemology. (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)