Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...) the ‘symbol grounding problem'. When behaviour is viewed as a control process, it is natural to explain how internal representations, even symbols, can have meaning for an organism, and how actions can be motivated by organic needs. (shrink)

Proceedings of the Workshop on AI and Cognition.

This essay shows the presence of transcendence in the on-going attempt to come up with a purely scientific account of the workings of the human mind. At the center of the developmental stages of this attempt is the computational theory of mind, which regards the human mind as some kind of computer. With Wittgenstein’s analysis of the limits of linguistic representation in the Tractatus as a framework, it is argued that the various difficulties encountered by this attempt are primarily due (...) to the transcendental nature of the human mind, which eludes scientific explanation. (shrink)

In this paper, we try to show why a formal definition of truth is not satisfactory (first point). Later, we expound (second point) the polemic between Austin and Strawson about truth with the intention to show that both refer to different problems concerning truth and to prove that Austin did not lose this confrontation and that we can recover some elements of his investigation for making an adequate approach to this notion. We will complete our definition of truth using the (...) latest thesis of Charles Travis and that will permit us to conclude with a semantic definition of truth for natural languages. (shrink)

Can animals think? In this paper I address the proposal that many animals, including insects such as honeybees, have genuine thoughts. I consider one prominent version of this view that claims that honeybees can represent and process information about their environments in a way that satisfies the main hallmarks of human conceptual thought. I shall argue, however, that this view fails to provide convincing grounds for accepting that animals possess concepts. More precisely, I suggest that two important aspects of conceptual (...) thought, viz., concept individuation and the generality constraint, are not satisfied. (shrink)

Interdisciplinary investigations marry the methods and concerns of different fields. Computer science is the study of precise descriptions of finite processes; semantics is the study of meaning in language. Thus, computational semantics embraces any project that approaches the phenomenon of meaning by way of tasks that can be performed by following definite sets of mechanical instructions. So understood, computational semantics revels in applying semantics, by creating intelligent devices whose broader behavior fits the meanings of utterances, and not just their form. (...) IBM’s Watson (Ferrucci, Brown, Chu-Carroll, Fan, Gondek, Kalyanpur, Lally, Murdock, Nyberg, Prager, Schlaefer & Welty 2010) is a harbinger of the excitement and potential of this technology. (shrink)

Can computer systems ever be considered moral agents? This paper considers two factors that are explored in the recent philosophical literature. First, there are the important domains in which computers are allowed to act, made possible by their greater functional capacities. Second, there is the claim that these functional capacities appear to embody relevant human abilities, such as autonomy and responsibility. I argue that neither the first (Domain-Function) factor nor the second (Simulacrum) factor gets at the central issue in the (...) case for computer moral agency: whether they can have the kinds of intentional states that cause their decisions and actions. I give an account that builds on traditional action theory and allows us to conceive of computers as genuine moral agents in virtue of their own causally efficacious intentional states. These states can cause harm or benefit to moral patients, but do not depend on computer consciousness or intelligence. (shrink)

Employing Searle’s views, I begin by arguing that students of Mathematics behave similarly to machines that manage symbols using a set of rules. I then consider two types of Mathematics, which I call Cognitive Mathematics and Technical Mathematics respectively. The former type relates to concepts and meanings, logic and sense, whilst the latter relates to algorithms, heuristics, rules and application of various techniques. I claim that an upgrade in the school teaching of Cognitive Mathematics is necessary. The aim is to (...) change the current mentality of the stakeholders so as to compensate for the undue value presently attached to Technical Mathematics, due to advances in technology and its applications, and thus render the two sides of Mathematics equal. Furthermore, I suggest a reorganization/systematization of School Mathematics into a cognitive network to facilitate students’ understanding of the subject. The final goal is the transition from mechanical execution of rules to better understanding and in-depth knowledge of Mathematics. (shrink)

Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...) dynamicist answer: computation is not required for explaining cognition. The first four answers are only accurate to a first approximation. But the “devil” is in the details. The last answer cashes in on the parenthetical “if any” in the question above. The classicist argues that cognition is symbolic computation. But digital computationalism need not be equated with classicism. Indeed, computationalism can, in principle, range from digital (and analogue) computationalism through (the weaker thesis of) generic computationalism to (the even weaker thesis of) digital (or analogue) pancomputationalism. Connectionism, which has traditionally been criticised by classicists for being non-computational, can be plausibly construed as being either analogue or digital computationalism (depending on the type of connectionist networks used). Computational neuroscience invokes the notion of neural computation that may (possibly) be interpreted as a sui generis type of computation. The extreme dynamicist argues that the time has come for a post-computational cognitive science. This paper is an attempt to shed some light on this debate by examining various conceptions and misconceptions of (particularly digital) computation. (shrink)

The article presents a critical survey of the philosophical discussion of the mind-body-problem since the collapse of Rylean behaviourism. The major theories (identity theories, supervenience, emergentist materialism, dualist interactionism and functionalism) are sketched and briefly evaluated with regard to their advantages and disadvantages. The conclusion is that no satisfactory theory about the relation between mental and neurophysiological states exists today, but considerable progress has been made regarding the contours of this cluster of problems. A catalogue of criteria which every future (...) theory concerning the mind-body problem must fulfill is given at the end. (shrink)

Roy Sorensen advances an evolutionary explanation of our capacity for thought experiments which doubles as a naturalized epistemological justification. I argue Sorensens explanation fails to satisfy key elements of environmental-selectionist explanations and so fails to carry epistemic force. I then argue that even if Sorensen succeeds in showing the adaptive utility of our capacity, he still fails to establish its reliability and hence epistemic utility. I conclude Sorensens account comes to little more than a just-so story.

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

The dominant scientific and philosophical view of the mind – according to which, put starkly, cognition is computation – is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine.

Considerations of personal identity bear on John Searle's Chinese Room argument, and on the opposed position that a computer itself could really understand a natural language. In this paper I develop the notion of a virtual person, modelled on the concept of virtual machines familiar in computer science. I show how Searle's argument, and J. Maloney's attempt to defend it, fail. I conclude that Searle is correct in holding that no digital machine could understand language, but wrong in holding that (...) artificial minds are impossible: minds and persons are not the same as the machines, biological or electronic, that realize them. (shrink)

This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation.

Computationalism provides a framework for understanding how a mathematically describable physical world could give rise to conscious observations without the need for dualism. A criterion is proposed for the implementation of computations by physical systems, which has been a problem for computationalism. Together with an independence criterion for implementations this would allow, in principle, prediction of probabilities for various observations based on counting implementations. Applied to quantum mechanics, this results in a Many Computations Interpretation (MCI), which is an explicit form (...) of the Everett style Many Worlds Interpretation (MWI). Derivation of the Born Rule emerges as the central problem for most realist interpretations of quantum mechanics. If the Born Rule is derived based on computationalism and the wavefunction it would provide strong support for the MWI; but if the Born Rule is shown not to follow from these to an experimentally falsified extent, it would indicate the necessity for either new physics or (more radically) new philosophy of mind. (shrink)

I review three problems that have historically motivated pessimism about artificial intelligence: (1) the Problem of Consciousness, according to which artificial systems function without the right sort of conscious oversight; (2) The Problem of Global Relevance, according to which artificial systems cannot solve fully general theoretical and practical problems; (3) The Problem of Semantic Irrelevance, according to which artificial systems cannot be guided by semantic comprehension. I connect the dots between all three problems by drawing attention to non-syntactic inferences—inferences that (...) are made on the basis of insight into the rational relationships among thought-contents. Consciousness alone affords such insight, I argue, and such insight alone confers positive epistemic status on the execution of the inferences. Only when artificial systems can execute inferences that are rationally guided by phenomenally conscious states will such systems count as intelligent in a literal sense. (shrink)

In a brief overview this article discusses that, in the multifaceted field of cognitive sciences, the problem of consciousness and mind is far from being resolved. The article then argues that this problem is worked out in careful detail in Peirce’s work. Intelligence, hence mind, for Peirce, is distinct from consciousness. Without being dissociable, they are, in fact, distinct but complementary. Hence, Peirce’s ideas should be recovered not only for the sake of their relevance, but also because cognitivists have a (...) lot to learn from Peirce. (shrink)

When experimental philosophers carry out studies on thought experiments, some participants are excluded based on certain exclusion criteria, mirroring standard social science vignette methodology. This involves excluding people that do not pay attention or who miscomprehend the scenario presented in thought experiments. However, experimental philosophy studies sometimes exclude an alarmingly high number of participants. We argue that this threatens the external and internal validity of the conclusions being drawn and we show how a simple visualization of thought experiments can reduce (...) exclusion rates significantly. Furthermore, we argue that focus should not merely be on how many are excluded, but also why they are excluded, and we highlight the role of comprehension questions in this regard. Philosophical thought experiments often rely on the acceptance of certain key premises that may be regarded contestable, and asking comprehension questions involving such key assumptions could be problematic as that may result in some participants being inadvertently excluded from the study, potentially creating a selection bias. (shrink)

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

When does a human being cease to exist? For millennia, the answer to this question had remained largely unchanged: death had been diagnosed when heartbeat and breathing were permanently absent. Only comparatively recently, in the 1950s, rapid developments in intensive-care medicine called into question this widely accepted criterion. What had previously been deemed a permanent cessation of vital functions suddenly became reversible. -/- A new criterion of death was needed. It was suggested that the destruction of the brain could indicate (...) the death of the organism in the presence of external life support. Soon the so-called brain death became the new worldwide standard. In recent years, however, doubts about this neurological criterion have been growing. Is brain death really our death? -/- This is the question that this thesis seeks to answer. To this end, we shall connect the medical debate about the definition of death to the philosophical debate about personal identity. While we will find that the destruction of its brain does in fact not correspond to an organism’s death, we shall also ask whether the assumption that we are essentially organisms is correct. May brain death be the ceasing to exist of a different entity? -/- Substituting clinical case reports and considerations about human physiology for the use of thought experiments, the thesis takes a novel and philosophically unconventional approach to the problem of what we essentially are. We shall analyse various pathological conditions and their respective effects on the bodily and mental characteristics of our existence. We will conclude that brain death is indeed our death – but for reasons entirely different from those cited in the original justification of this criterion. (shrink)

With recent advancements in technology and computer science, we have reached a point where we can clearly state that thinking is no longer the exclusive privilege of living minds. Artificial intelligence can gather and process information in a manner fairly similar or even superior to our thinking process. AI can use this processed information in a reasoning process to make decisions and execute them. However, what makes our mind distinct from AI is the addition of “I,” that is, an entity (...) composed of two mental processes of awareness-based choice selection and discretionary selection of information for attention that are the fundamental core function of decision making and awareness processes, respectively. ABCS allows the coexistence of free will alongside—but unrestrained by—the chain of causality in the decision-making process with the help of awareness. “I” also allows for DSIA, which is a key step in the awareness process. This intertwined process is crucial for our consciousness. Similar to AI, the mind is devoid of any form of self-recognition without awareness. Self-awareness is a collaborative function of “I” and the mind. “I” is instrumental in the sense of self-awareness, but on its own, it is selfless. Additionally, “I” is the heart of the decision-making process. Therefore, AI is missing “I,” a selfless master of the mind. (shrink)

Artificial Intelligence in the form of different machine learning models is applied to Big Data as a way to turn data into valuable knowledge. The rhetoric is that ensuing predictions work well—with a high degree of autonomy and automation. We argue that we need to analyze the process of applying machine learning in depth and highlight at what point human knowledge production takes place in seemingly autonomous work. This article reintroduces classification theory as an important framework for understanding such seemingly (...) invisible knowledge production in the machine learning development and design processes. We suggest a framework for studying such classification closely tied to different steps in the work process and exemplify the framework on two experiments with machine learning applied to Facebook data from one of our labs. By doing so we demonstrate ways in which classification and potential discrimination take place in even seemingly unsupervised and autonomous models. Moving away from concepts of non-supervision and autonomy enable us to understand the underlying classificatory dispositifs in the work process and that this form of analysis constitutes a first step towards governance of artificial intelligence. (shrink)

Integrated Information Theory posits a new kind of information, which, given certain constraints, constitutes consciousness. Searle objects to IIT because its appeal to information relies on observer-relative features. This misses the point that IIT’s notion of integrated information is intrinsic, the opposite of observer-relative. Moreover, Searle overlooks the possibility that IIT could be embraced as an extension of his theory. While he insists that causal powers of the brain account for consciousness, he maintains that these causal powers aren’t tied to (...) protoplasmic material. Whatever these causal powers are, they don’t consist in mere information-processing or computation. IIT agrees, and also positively characterizes the relevant causal powers as those involved in generating integrated information. Examining the further commitments of each theory reveals that IIT renews a fundamentally ontological challenge to information-processing and computational theories of mind. (shrink)

This paper critically assesses John Danaher’s ‘ethical behaviourism’, a theory on how the moral status of robots should be determined. The basic idea of this theory is that a robot’s moral status is determined decisively on the basis of its observable behaviour. If it behaves sufficiently similar to some entity that has moral status, such as a human or an animal, then we should ascribe the same moral status to the robot as we do to this human or animal. The (...) paper argues against ethical behaviourism by making four main points. First, it is argued that the strongest version of ethical behaviourism understands the theory as relying on inferences to the best explanation when inferring moral status. Second, as a consequence, ethical behaviourism cannot stick with merely looking at the robot’s behaviour, while remaining neutral with regard to the difficult question of which property grounds moral status. Third, not only behavioural evidence ought to play a role in inferring a robot’s moral status, but knowledge of the design process of the robot and of its designer’s intention ought to be taken into account as well. Fourth, knowledge of a robot’s ontology and how that relates to human biology often is epistemically relevant for inferring moral status as well. The paper closes with some concluding observations. (shrink)

We need an account of corporate agency that is temporally robust – one that will help future people to cope with challenges posed by corporate groups in a range of credible futures. In particular, we need to bequeath moral resources that enable future people to avoid futures dominated by corporate groups that have no regard for human beings. This paper asks how future philosophers living in broken or digital futures might re-imagine contemporary debates about corporate agency. It argues that the (...) only temporally robust account is moralised extreme collectivism, where full moral personhood is accorded to those corporate groups that are reliably disposed to respond appropriately to moral reasons. (shrink)

Philosophers have traditionally held that propositions mark the domain of rational thought and inference. Many philosophers have held that only conceptually sophisticated creatures like us could have propositional attitudes. But in recent decades, philosophers have adopted increasingly liberal views of propositional attitudes that encompass the mental states of various non-human animals. These views now sit alongside more traditional views within the philosophical mainstream. In this paper I argue that liberalized views of propositional attitudes are so liberal that they encompass states (...) of all sorts of apparently mindless systems like circadian clocks in plants. I begin by arguing that on the most well-developed and widely endorsed theories of underived representation in philosophy, circadian clocks qualify as representations. I then argue that standard reasons for thinking that perceptual states and pictures have propositional content carry over to circadian clocks. Finally, I argue that circadian representations in plants play the kind of functional role that is widely taken to be partly constitutive of belief-like attitudes. So according to mainstream theories of representation, propositions, and attitudes, plants have propositional attitudes. Yet on other more traditional views, this conclusion would seem absurd. So, contrary to appearances, there is no shared, stable understanding of what propositional attitudes are in contemporary philosophy. (shrink)

The aim of this paper is to offer an analysis of the notion of artificial moral agent (AMA) and of its impact on human beings’ self-understanding as moral agents. Firstly, I introduce the topic by presenting what I call the Continuity Approach. Its main claim holds that AMAs and human moral agents exhibit no significant qualitative difference and, therefore, should be considered homogeneous entities. Secondly, I focus on the consequences this approach leads to. In order to do this I take (...) into consideration the work of Bostrom and Dietrich, who have radically assumed this viewpoint and thoroughly explored its implications. Thirdly, I present an alternative approach to AMAs—the Discontinuity Approach—which underscores an essential difference between human moral agents and AMAs by tackling the matter from another angle. In this section I concentrate on the work of Johnson and Bryson and I highlight the link between their claims and Heidegger’s and Jonas’s sug-gestions concerning the relationship between human beings and technological products. In conclusion I argue that, although the Continuity Approach turns out to be a necessary postulate to the machine ethics project, the Discontinuity Approach highlights a relevant distinction between AMAs and human moral agents. On this account, the Discontinuity Approach generates a clearer understanding of what AMAs are, of how we should face the moral issues they pose, and, finally, of the difference that separates machine ethics from moral philosophy. (shrink)

The contribution by Hubert L. Dreyfus to the debate on the feasibility of AI projects has been surely of great relevance because of his pointing out specific limits of the machine as compared to the human mind. His critics, along with the actual difficulties encountered in the advance of a pure symbolic AI, induced a wide discussion that in some measure stimulated other ways to follow for reproducing human abilities. Nevertheless, a curious fact characterizes the history of AI regarding the (...) problems raised, among the many, by Dreyfus. While in the first era the main concern by the opponents was to certify the limited power of computers as compared to humans, it seems that today the main concern is exactly the opposite, namely the growing and threatening power of AI devices, both software and hardware based, such as robots. Maybe the reason of that has been, and is today too, the imbalance assigned to the discussion, on the one side, of what human faculties are and work, and, on the other, on what the artificial is and can work. Designing the artificial, in every field, means to give birth to devices that consist of a sort of overlapping of nature and technology, and, therefore, they deserve to be named naturoids. This implies that, to understand them, we need to study their genuine ‘artificial nature’ in general terms, bringing further what H. A. Simon called the ‘science of the artificial’. (shrink)

We argue that one important aspect of the “cognitive neuroscience revolution” identified by Boone and Piccinini :1509–1534. doi: 10.1007/s11229-015-0783-4, 2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both “from below” and “from above”—that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves, and from a greater appreciation of the problems (...) solved by bio-cognitive systems, chiefly regulation and prediction. We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of dynamical models as a central postulate in neurocognitive research. (shrink)

Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or "shortcut" mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which "heuristic" is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This dissertation seeks to (...) remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data. (shrink)

The mental realm seems different to the physical realm; the mental is thought to be dependent on, yet distinct from the physical. But how, exactly, are the two realms supposed to be different, and what, exactly, creates the seemingly insurmountable juxtaposition between the mental and the physical? This review identifies and discusses five marks of the mental, features that set characteristically mental phenomena apart from the characteristically physical phenomena. These five marks (intentionality, consciousness, free will, teleology, and normativity) are not (...) presented as a set of features that define mentality. Rather, each of them is something we seem to associate with phenomena we consider mental, and each of them seems to be in tension with the physical view of reality in its own particular way. It is thus suggested how there is no single mind-body problem, but a set of distinct but interconnected problems. Each of these separate problems is analyzed, and their differences, similarities and connections are identified. This provides a useful basis for future theoretical work on psychology and philosophy of mind, that until now has too often suffered from unclarities, inadequacies, and conflations. (shrink)

Dramatic changes or revolutions in a field of science are often made by outsiders or 'trespassers,' who are not limited by the established, 'expert' approaches. Each essay in this diverse collection shows the fruits of intellectual trespassing and poaching among fields such as economics, Kantian ethics, Platonic philosophy, category theory, double-entry accounting, arbitrage, algebraic logic, series-parallel duality, and financial arithmetic.

O debate entre J. Searle e D. Dennett acerca da possibilidade técnica de uma Inteligência artificial gira em torno de uma única questão: estados mentais expressam algo intrínseco, privado e subjetivo, experimentado em primeira-pessoa ou não passam de entidades obscurantistas, frutos da ignorância e, em princípio, reduzíveis à objetividade científica da neurociência? Searle defende a primeira tese, enquanto Dennett argumenta pela segunda. O texto expõe a posição de Dennett, a crítica de Searle e se direciona para uma nova solução, que (...) defende um monismo integral, no qual mente e cérebro podem ser vistos como duas dimensões de uma mesma realidade. Nesse sentido, o projeto de Inteligência artifical precisará revisar o conceito de “físico” se quiser avançar em suas pretenções, incluindo nele conceitos hoje antagônicos como intencionalidade, liberdade e subjetividade.The debate between J. Searle and D. Dennett about the technical possibility of an artificial intelligence revolves around a single issue: mental states express something intrinsic, private and subjective, experienced in first-person or are merely obscurantist entities, results from ignorance and, in principle, reducible to scientific objectivity of neuroscience? Searle argues for the first position, while Dennett argues for the second. The text exposes the position of Dennett, the criticism of Searle and is directed to a new solution, which advocates an integral monism, in which mind and brain can be seen as two dimensions of the same reality. In this sense, the project of artificial intelligence need to review the concept of "physical" if it wants to advance its claims, including today antagonistic concepts such as intentionality, freedom and subjectivity. (shrink)

Most people find it obvious that concepts like APPLE, DOG, WATER, CACTUS, SWIM, CHIRP, FURRY, and SMOOTH are acquired from perceptual experiences along with some kind of inferential procedure. Models of how these concepts are inferentially acquired, however, force the acquired concepts to be representationally complex, built from, and composed by, the more primitive representations. Since at least the time of Plato, philosophers and psychologists have struggled to find complex sets of representations that have the same meanings, definitionally or probabilistically, (...) as these concepts. For example, to think about the property-kind being gold is not the same as to think about the complex property-kind being yellowish & shiny & malleable.... I call this Fodor's Challenge: Find an acquisition process that is genuinely inferential and yields a concept that genuinely is one of these lexical concepts. Rather than continue the pursuit of a complex representation that has the same meaning as our concept GOLD. I offer a model on which many lexical concepts are acquired from perception and inference, without being built up from, and composed by, the representations involved. The model, Baptizing Meanings for Concepts, is inspired in part by Saul Kripke's baptism process for assigning meanings to linguistic terms. Many lexical concepts, according to the BMC, are acquired by inferring the presence a new property-kind, picking out the property-kind in terms of those perceptible features, and then assigning a simple mental term, a concept, for that property-kind. (shrink)

Over the past 15 years, there have been two increasingly popular approaches to the study of meaning in cognitive science. One, based on theories of embodied cognition, treats meaning as a simulation of perceptual and motor states. An alternative approach treats meaning as a consequence of the statistical distribution of words across spoken and written language. On the surface, these appear to be opposing scientific paradigms. In this review, we aim to show how recent cross-disciplinary developments have done much to (...) reconcile these two approaches. The foundation to these developments has been the recognition that intralinguistic distributional and sensory-motor data are interdependent. We describe recent work in philosophy, psychology, cognitive neuroscience, and computational modeling that are all based on or consistent with this conclusion. We conclude by considering some possible directions for future research that arise as a consequence of these developments. (shrink)

The paper aims to assess whether the ideas developed by Don Ross in his recent book Economic theory and cognitive science: microexplanation, which relates neoclassical economics to recent developments in cognitive science, might revolutionize the methodology of economics. Since Ross challenges a conception of economics associated with what is pejoratively called 'Folk psychology', the paper discusses ideas of the philosopher Daniel Dennett on which this challenge is largely based. This discussion could not avoid bearing on questions such as the nature (...) of consciousness, the interpretation of ontological realism, the relations between agency and selfhood, and the nature and scope of economics. The paper attempts to rehabilitate the two pieces of the traditional conception of economics that were most radically contested by Ross, namely methodological individualism and the foundational role of rationality in economics. A relatively nuanced judgment on Ross's bold enterprise is proposed in conclusion. (shrink)

Emotional experiences are often described in metaphoric language. A major question in linguistics and cognitive science is whether such metaphoric linguistic expressions reflect a deeper principle of cognition. Are abstract concepts structured by the embodied, sensorimotor domains that we use to describe them? This review presents the argument for conceptual metaphors of affect and summarizes recent findings from empirical studies. These findings show that, consistent with the conceptual metaphor account, the associations between affect and physical domains such as spatial position, (...) musical pitch, brightness, and size which are captured in linguistic metaphors also influence performance on attention, memory and judgment tasks. Despite this evidence, a number of concerns with metaphor as an account of affect representation are considered. (shrink)

In this article I present some characteristics of logics and semantics of an uncertain world. I confront two-valued and fuzzy logic. I use Kafka’s novel Process as an example, which is designed as an uncertain context with words which are rigid designators without rigid meaning. That produces an uncertain world of logical and semantical relations. In presentation of problems I introduce basic concepts of Frege’s, Wittgenstein’s, Tarsky’s, Searle’s, Quine’s and Davidson’s philosophy of language. I differ the logical and semantical identification (...) of identity. I differ reference and inference, or representation and identification as two components which are fundamental for the identification of identity. I found this difference on the role of logical unification and granulation of predicates in the structure of thought and semantical unification and granulation of attributes in the structure of statements and their relation to ontology of context. Through the confrontation of the logical and semantical unification and granulation I find that the limits of logic are not also the limits of language. The semantical unification goes over the highest genre and below the lowest species. That enables the extra-logical, non-scientifical, con-fessional, pro-phetical, artistic, and ordinary use of language. (shrink)

Modern biology has not yet come to terms with the presence of many organic codes in Nature, despite the fact that we can prove their existence. As a result, it has not yet accepted the idea that the great events of macroevolution were associated with the origin of new organic codes, despite the fact that this is the most parsimonious and logical explanation of those events. This is probably due to the fact that the existence of organic codes in all (...) fundamental processes of life, and in all major transitions in the history of life, has enormous theoretical implications. It requires nothing less than a new theoretical framework, and that kind of change is inevitably slow. There are too many facts to reconsider, too many bits of history to weave together in a new mosaic. But this is what science is about, and the purpose of the present paper is to show that it can be done. More precisely, it is shown that the whole natural history of the brain can be revisited in the light of the organic codes. What is described here is only a bird’s-eye view of brain macroevolution, but it is hoped that the extraordinary potential of the organic codes can nevertheless come through. The paper contains also another message. The organic codes prove that life is based on semiosis, and are in fact the components of organic semiosis, the first and the most diffused form of semiosis on Earth, but not the only one. It will be shown that the evolution of the brain was accompanied by the development of two new types of sign processes. More precisely, it gave origin first to interpretive semiosis, mostly in vertebrates, and then to cultural semiosis, in our species. (shrink)

In their enthusiasm for programming, computational linguists have tended to lose sight of what humansdo. They have conceived of conversations as independent of sound and the bodies that produce it. Thus, implicit in their simulations is the assumption that the text is the essence of talk. In fact, unlike electronic mail, conversations are acoustic events. During everyday talk, human understanding depends both on the words spoken and on fine interpersonal vocal coordination. When utterances are analysed into sequences of word-based forms, (...) however, these prosodic aspects of language disappear. Therefore, to investigate the possibility that machines might talk, we propose acommunion game that includes this interpersonal patterning. Humans and machines would talk together and, based on recordings of them, a panel would appraise the relevant merit of each machine's simulation by how true to life it sounded. Unlike Turing's imitation game, the communion game overtly focuses attention, not on intelligence, but on language. It is designed to facilitate the development of social groups of adaptive robots that exploit complex acoustic signals in real time. We consider how the development of such machines might be approached. (shrink)