Intelligent algorithms together with various machine learning techniques hold a dominant position among major challenges for contemporary value sensitive design. Self-learning capabilities of current AI applications blur the causal link between programmer and computer behavior. This creates a vital challenge for the design, development and implementation of digital technologies nowadays. This paper seeks to provide an account of this challenge. The main question that shapes the current analysis is the following: What conceptual tools can be developed within the value (...) sensitive design school of thought for evaluating machine learning algorithms where the causal relation between designers and the behavior of their computer systems has been eroded? The answer to this question will be provided through two levels of investigation within the value sensitive design methodology. The first level is conceptual. Within the conceptual level, we will introduce the notion of computer intentionality and will show how this term may be used for solving an issue of non-causal relation between designer and computer system. The second level of investigation is technical. At this level the emphasis will be given to machine learning algorithms. (shrink)

In this carefully argued critique, Steven Horst pronounces the theory deficient.

Can computers think? This book is intended to demonstrate that thinking, understanding, and intelligence are more than simply the execution of algorithms--that is, that machines cannot think. Written and edited by leaders in the fields of artificial intelligence and the philosophy of computing.

Searle’s celebrated Chinese room thought experiment was devised as an attempted refutation of the view that appropriately programmed digital computers literally are the possessors of genuine mental states. A standard reply to Searle, known as the “robot reply” (which, I argue, reflects the dominant approach to the problem of content in contemporary philosophy of mind), consists of the claim that the problem he raises can be solved by supplementing the computational device with some “appropriate” environmental hookups. I argue that not (...) only does Searle himself casts doubt on the adequacy of this idea by applying to it a slightly revised version of his original argument, but that the weakness of this encoding-based approach to the problem of intentionality can also be exposed from a somewhat different angle. Capitalizing on the work of several authors and, in particular, on that of psychologist Mark Bickhard, I argue that the existence of symbol-world correspondence is not a property that the cognitive system itself can appreciate, from its own perspective, by interacting with the symbol and therefore, not a property that can constitute intrinsic content. The foundational crisis to which Searle alluded is, I conclude, very much alive. (shrink)

This book offers a sustained critique of the computational theory of mind that deserves the attention of those interested in the presuppositions and implications of computational psychology. Horst begins by laying out the theory, reconstructing its perceived role in vindicating intentional psychology, and recounting earlier critiques on which he builds. Part 2, the heart of the book, analyzes a notion central to CTM—that of a symbol—arguing that symbols are conventional. In Part 3 Horst applies the results of this analysis to (...) CTM to diagnose a serious confusion in its account of semantic properties and the corresponding notion of mental representation. Part 4 offers an alternative perspective on computational psychology, suggesting a separation of the practice of computational psychology from the philosophical claims made by CTM. (shrink)

One cannot summarize the intent of this insightful and engaging book better than the author himself: “The thesis... is that CTM [the Computational Theory of Mind] does not provide a solution to the philosophical problems that it is heralded as solving—indeed, it involves some deep confusions about computers, symbols, and meaning—but that this does not undercut the possibility that the computer paradigm may provide an important resource... for the development of a mature science of cognition”.

(1) Van Gelder's concession that the dynamical hypothesis is not in opposition to computation in general does not agree well with his anticomputational stance. (2) There are problems with the claim that dynamic systems allow for nonrepresentational aspects of computation in a way in which digital computation cannot. (3) There are two senses of the “cognition is computation” claim and van Gelder argues against only one of them. (4) Dynamical systems as characterized in the target article share problems of universal (...) realizability with formal notions of computation, but differ in that there is no solution available for them. (5) The dynamical hypothesis cannot tell us what cognition is, because instantiating a particular dynamical system is neither necessary nor sufficient for being a cognitive agent. (shrink)

This article responds to two unresolved and crucial problems of cognitive science: (1) What is actually accomplished by functions of the nervous system that we ordinarily describe in the intentional idiom? and (2) What makes the information processing involved in these functions semantic? It is argued that, contrary to the assumptions of many cognitive theorists, the computational approach does not provide coherent answers to these problems, and that a more promising start would be to fall back on mathematical communication theory (...) and, with the help of evolutionary biology and neurophysiology, to attempt a characterization of the adaptive processes involved in visual perception. Visual representations are explained as patterns of cortical activity that are enabled to focus on objects in the changing visual environment by constantly adjusting to maintain levels of mutual information between pattern and object that are adequate for continuing perceptual control. In these terms, the answer proposed to (1) is that the intentional functions of vision are those involved in the establishment and maintenance of such representations, and to (2) that semantic features are added to the information processes of vision with the focus on objects that these representations accomplish. The article concludes with proposals for extending this account of intentionality to the higher domains of conceptualization and reason, and with speculation about how semantic information-processing might be achieved in mechanical systems. (shrink)

What is the relation between computation and intennonality? Cognition presup- poses intentionality (or semantics). This much is certain. So, if, according to com- putationalism, cognition is computation, then computation, mo, presupposes..

The paper examines the status of conscious presentation with regard to mental content and intentional states. I argue that conscious presentation of mental content should be viewed on the model of a secondary quality, as a subjectiveeffect of the microstructure of an underlying brain state. The brain state is in turn viewed as the instantiation of an abstract computational state, with the result that introspectively accessible content is interpreted as a presentation of the associated computational state realized by the brain. (...) However, if the relation between consciousness and representational content is construed in this manner, then conscious presentation does not provide an adequate foundation for the claim that human mental states areintrinsically intentional. On this model, I argue that functionalism is able to account for (non-intrinsic) intentionality, but not for consciousness, which has implications for the computational paradigm, as well as for Searle's Chinese room thought experiment. (shrink)

I suggest that most discussions of intentional systems have overlooked an important aspect of living organisms: the intrinsic goal-directedness inherent in the behaviour of living eukaryotic cells. This goal directedness is nicely displayed by a normal cell’s ability to rearrange its own local material structure in response to damage, nutrient distribution or other aspects of its individual experience. While at a vastly simpler level than intentionality at the human cognitive level, I propose that this basic capacity of living things (...) provides a necessary building block for cognition and high-order intentionality, because the neurons that make up vertebrate brains, like most cells in our body, embody such capacities. I provisionally dub the capacities in question “nano-intentionality”: a microscopic form of “aboutness”. The form of intrinsic intentionality I propose is thoroughly materialistic, fully compatible with known biological facts, and derived non-mysteriously through evolution. Crucially, these capacities are not shared by any existing computers or computer components, and thus provide a clear, empirically-based distinction between brains and currently existing artificial information processing systems. I suggest that an appreciation of this aspect of living matter provides a potential route out of what may otherwise appear to be a hopeless philosophical quagmire confronting information-processing models of the mind. (shrink)

One of the most influential arguments against the claim that computers can think is that while our intentionality is intrinsic, that of computers is derived: it is parasitic on the intentionality of the programmer who designed the computer-program. Daniel Dennett chose a surprising strategy for arguing against this asymmetry: instead of denying that the intentionality of computers is derived, he endeavours to argue that human intentionality is derived too. I intend to examine that biological plausibility (...) of Dennett’s suggestion and show that Dennett’s argument for the claim that human intentionality is derived because it was designed by natural selection is based on the misunderstanding of how natural selection works. (shrink)

1. Introduction. The problems of other minds ; Body, mind and other minds ; The analogical theory ; The critical theory ; Functionalism and mental states as theoretical entities ; A brief outline of things to come -- 2. Functionalism and the nature of mental representations. Functionalism and cognitive psychology ; Folk psychology and the representational theory of mind -- 3. Theory theory and simulation theory. A very short introduction to the world of theory theory and simulation theory ; A (...) look at simulation theory ; A look at theory theory -- 4. Intentionality and the theory theory. The generic theory theory ; Cognitive and primordial intentionality ; Theory theorists and primordial intentionality ; Fodor's computational theory of primordial intentionality -- 5. The body schema. Historical notes on the notion of body schema ; An outline of a notion of body schema -- 6. On the notion of primordial intentionality. Concrete and abstracts movements ; Why primordial intentionality is not reducible to cognitive intentionality ; The intentionality of primordial intentionality -- 7. The irreducibility of primordial intentionality. The first argument against homuncular functionalism ; The second argument against homuncular functionalism -- 8. Transferring the body schema. Husserl's phenomenology of intersubjectivity ; Towards a primordial intentionality of intersubjectivity ; Some implications and a comparison to Husserl -- 9. Theory theory and simulation theory revisited. Attribution of primordial intentionality as cognitive simulation ; If homuncular functionalism were true ... ; Primordial intentionality and belief-desire psychology ; The theory of body schematic transfer and the simulation theory -- 10. Body schematic transfer and the conceptual problem of other minds. Strawson on the problem of other minds ; Disarming Strawson's objections ; Solving the conceptual problem -- 11. Concluding remarks -- Summary in Swedish -- References. (shrink)

In his book The Conscious Mind David Chalmers introduced a by now familiar distinction between the hard problem and the easy problems of consciousness. The easy problems are those concerned with the question of how the mind can process information, react to environmental stimuli, and exhibit such capacities as discrimination, categorization, and introspection (Chalmers, 1996, 4, 1995, 200). All of these abilities are impressive, but they are, according to Chalmers, not metaphysically baffling, since they can all be tackled by means (...) of the standard repertoire of cognitive science and explained in terms of computational or neural mechanisms. This task might still be difficult, but it is within reach. In contrast, the hard problem—also known as the problem of consciousness (Chalmers, 1995, 201)—is the problem of explaining why mental states have phenomenal or experiential qualities. Why is it like something to ‘taste coffee’, to ‘touch an ice cube’, to ‘look at a sunset’ etc.? Why does it feel the way it does? Why does it at all feel like anything? Chalmers’s distinction confronts us with a version of the so-called ‘explanatory gap’. On the one hand, we have certain cognitive functions, which can apparently be explained reductively, and on the other hand, we have a number of experiential qualities, which seem to resist this reductive explanation. We can establish that a certain function is accompanied by a certain experience, but we have no idea why that happens, and regardless of how closely we scrutinize the neural mechanisms we don’t seem to be getting any closer at an answer. In his book, Chalmers also distinguished two concepts of mind: a phenomenal concept and a psychological concept. The first captures the conscious aspect of mind: Mind is understood in terms of conscious experience. The second concept understands mind in functional terms as the causal or explanatory basis for behavior.. (shrink)

In his bookThe Conscious MindDavid Chalmers introduced a now-familiar distinction between the hard problem and the easy problems of consciousness. The easy problems are those concerned with the question of how the mind can process information, react to environmental stimuli, and exhibit such capacities as discrimination, categorization, and introspection. All of these abilities are impressive, but they are, according to Chalmers, not metaphysically baffling, since they can all be tackled by means of the standard repertoire of cognitive science and explained (...) in terms of computational or neural mechanisms. This task might still be difficult, but it is within reach. In contrast, the hard problem — also known astheproblem of consciousness — is the problem of explaining why mental states have phenomenal or experiential qualities. Why is it like something to ‘taste coffee,’ to ‘touch an ice cube,’ to ‘look at a sunset,’ etc.? Why does it feel the way it does? Why does it feel like anything at all? (shrink)

Phenomenologists such as Merleau?Ponty have argued that the ordinary teleological relation between an embodied agent and the world is neither ?subjective? nor ?cognitive?, i.e. that it is not normally mediated by a chain of explicit cognition occurring within a distinct mental subject. Yet, while this seems true from a first?person, phenomenological perspective, I argue that teleological forms of explanation require the ascription of Intentional states. Intentional states, however, are usually regarded as subjective, cognitive states. In order to reconcile the phenomenology (...) with the logic of teleology, I introduce the notion of ?body?intentionality?. I maintain that we can use a modified version of Jonathan Bennett's concept of a teleological law to specify third?person empirical criteria for a pre?cognitive, pre?subjective kind of Intentionality. I also argue that this notion of body?intentionality provides us with at least a partial solution to the mind?body problem that avoids the inadequacies of the computational theory of mind. (shrink)

The present article articulates the strategy of much of my work to date, which has been concerned to understand how we can possibly come to have any objective understanding of the mind. Generally, I align myself with those who think the best prospect of such an understanding lies in a causal/computational/representational theory of thought (CRTT). However, there is a tendency in recent developments of this and related philosophical views to burden the crucial property of intentionality with what I call (...) Strong Externalism, a state’s intentional content being determined by some real external phenomenon to which the state is causally related. I argue against this tendency, drawing attention to the crucial role in cognitive scientific explanations of empty concepts, such as [angel], and the “intentional inexistents” that such concepts “represent.” This obliges me to take a brief excursion into what I hope is a minimal metaphysics, defending a methodology I call the “LEXX” strategy that treats phenomena as real only insofar as they are needed in genuine explanations. After a brief discussion of the need for greater patience generally regarding a theory of intentionality, I deploy this strategy with regard to many phenomena that are the purported objects of mental states, e.g. triangles, cones, words, sentences, colors, mental images and qualia. I argue that these phenomena do not actually exist: they are mere intentional inexistents, unreal projections of the intentional content of various mental states, and not themselves needed in any genuine explanations. In a concluding section, I summarize my suggestions about how a CRTT can explain the various illusions we have in this regard, particularly those concerning consciousness and qualia. (shrink)

Scholars refute the dichotomy of subject and object in the study of technology. Basing on relational ontology and revised empirical study, namely the social historical phenomenology of technology, inspired by post-phenomenology and actor-network theory, this study adopts an approach informed by the genetic phenomenological sociology (Zhang 2017; 2020) of technology, and examines the formation of Apple’s technology in the process of its emergence and diffusion. Unlike post-phenomenology and actor-network theory, which mainly examine the role of technology in the relation of (...) human-technology-world after technology was formed, this study examines technology in the process of its formation. The relationship between the intentionality of humanity and the potentiality of technology is explored empirically and ontologically, thus transcending the dichotomy of subject and object in the examination of technology through the relational ontology indicated in potentiality, intentionality, embodiment, and genealogy, and simultaneously building a foundation for the critique, ethics, and normative theory of media and technology. (shrink)

This paper presents an emerging aspect of intentionality through recent Artificial Intelligence (AI) developments in art and design. Our main thesis is that, if we focus just on the outcome of the artistic process, the intentionality of the artist does not have any relevance. Intention is measured as a result of actions regardless of whether they are human-based or not as long as there is an esthetical value intersubjectively acknowledged. In other words, what matters is the ‘intentio’ embedded (...) in the work of art (the output) rather than the ‘intendere’ (the process). By considering the former aspect, intentionality becomes free of human intervention, therefore 'unintentional'. This thesis is supported through a range of examples related to AI in general and AI art in particular. However, in the case of a self-driving vehicle, the macro-goal of the system is fixed by humans, even though the AI system itself will take care of decomposing the macro-goal into a set of micro-goals and take the corresponding decisions. In the case of art, the system does not need to have any exterior goal to the extent that art is pure freedom of expression, as many philosophers have acknowledged. In this sense, the decisions of any AI system generating art or design are independent of humans and must be judged only on the ground of the final outcome. A work of art will be judged ‘artistic’ to the extent that humans will recognize an artistic intent in the work itself. In particular, the introduction of random processes makes an AI-generated artwork fully independent of human creativity. (shrink)

Computationalism is the claim that all possible thoughts are computations, i.e. executions of algorithms. The aim of the paper is to show that if intentionality is semantically clear, in a way defined in the paper, then computationalism must be false. Using a convenient version of the phenomenological relation of intentionality and a diagonalization device inspired by Thomson's theorem of 1962, we show there exists a thought that canno be a computation.

The present study aims at supporting the argument that emotions, unlike a physicalistic interpretation, cannot be reduced to the conceptual elements used in the communication or exteriorization process. The subject is based on two hypotheses: the first is that the relation between the issuance of an emotive content (emotion) and a possible mental representation presents a linguistic nature. In general terms, this means that an emotion, or the psychological content associated with it is based on the plot of other concepts. (...) The second hypothesis is that it is not possible to refer to emotions without considering cognition from a semantic problem and, consequently, in the refusal of a realistic or anti-realistic posture in relation to the way the phenomena - internal and/or external to our consciousness - are referred. Thus, a conceptual model to understand emotions would be essential to settle the problem associated with ordinary language, realism, and the computational tendencies that comprehend the mental content in strictly syntactic terms. (shrink)

Computationalism is the claim that all possible thoughts are computations, i.e. executions of algorithms. The aim of the paper is to show that if intentionality is semantically clear, in a way defined in the paper, then computationalism must be false. Using a convenient version of the phenomenological relation of intentionality and a diagonalization device inspired by Thomson's theorem of 1962, we show there exists a thought that cannot be a computation.

In this paper I will discuss a certain philosophical and conceptual program -- that I have called philosophy of social action writ large -- and also show in detail how parts of the program have been, and is currently being carried out. In current philosophical research the philosophy of social action can be understood in a broad sense to encompass such central research topics as action occurring in a social context (this includes multi-agent action); shared we-attitudes (such as we-intention, mutual (...) belief) and other social attitudes expressing collective intentionality and needed for the explication and explanation of social action; social macro-notions, such as actions performed by social groups and properties of social groups such as their goals and beliefs; social practices, and institutions (see e.g. Tuomela, 1995, 2000a, 2001). The theory of social action understood analogously in a broad sense would then involve not only philosophical but all other relevant theorizing about social action. Thus, in this sense, such fields of Artificial Intelligence (AI) as Distributed AI (DAI) and the theory of Multi-Agent Systems (MAS) fall within the scope of the theory of social action. DAI studies the social side of computer systems and includes various well-known areas ranging from human-computer interaction, computer-supported cooperative work, organizational processing, and distributed problem solving to the simulation of social systems. (shrink)

This paper aims to highlight the life of computer technologies to understand what kind of ‘technological intentionality’ is present in computers based upon the phenomenological elements constituting the objects in general. Such a study can better explain the effects of new digital technologies on our society and highlight the role of digital technologies by focusing on their activities. Even if Husserlian phenomenology rarely talks about technologies, some of its aspects can be used to address the actions performed by (...) the digital technologies by focusing on the objects’ inner ‘life’ thanks to the analysis of passive synthesis and phenomenological horizons in the objects. These elements can be used in computer technologies to show how digital objects are ‘alive.’ This paper focuses on programs developed through high-order languages like C++ and unsupervised learning techniques like ‘Generative Adversarial Model.’ The phenomenological analysis reveals the computer’s autonomy within the programming stages. At the same time, the conceptual inquiry into the digital system’s learning ability shows the alive and changeable nature of the technological object itself. (shrink)

More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important (...) aspects of human cognition may in principle be captured in a computational model. This assumption stems from the belief that beyond a certain level, implementational details are irrelevant to cognition. According to this belief, neurons, and biological wetware in general, have no preferred status as the substrate for a mind. As it happens, the best examples of minds we have at present have arisen from a carbon-based substrate, but this is due to constraints of evolution and possibly historical accidents, rather than to an absolute metaphysical necessity. As a result of this belief, many cognitive scientists have chosen to focus not on the biological substrate of the mind, but instead on the abstract causal structure_ _that the mind embodies (at an appropriate level of abstraction). The view that it is abstract causal structure that is essential to mentality has been an implicit assumption of the AI research program since Turing (1950), but was first articulated explicitly, in various forms, by Putnam (1960), Armstrong (1970) and Lewis (1970), and has become known as _functionalism_. From here, it is a very short step to _computationalism_, the view that computational structure is what is important in capturing the essence of mentality. This step follows from a belief that any abstract causal structure can be captured computationally: a belief made plausible by the Church–Turing Thesis, which articulates the power. (shrink)

Three examples of theoretical analysis of evolutionary processes are presented. It is shown that the mechanisms involved have little to do with cognitive processes except for superficial and formal analogies. That is the case not only for classical models of adaptive evolution , but also for more recent ones making use of neural network computation and self-organization theories.Recent works on functional self-organization exhibiting some features of intentionality are discussed in this context. It is argued that Dennett's intentional stance cannot (...) be used as a theoretical framework common to human prepositional attitudes, animal behaviour and adaptive evolution. Indeed, a physical theory of intentionality could account, at least in principle, for the production of intentional self-organizing systems. However, except for a renewed theological “argument from design”, there is no justification to attribute intentionality to evolutionary processes and “Mother Nature”, for the reason that they have produced organisms endowed with intentional psycholinguistic capabilities. (shrink)

The formal conception of computation (FCC) holds that computational processes are not sensitive to semantic properties. FCC is popular, but it faces well-known difficulties. Accordingly, authors such as Block and Peacocke pursue a ?semantically-laden? alternative, according to which computation can be sensitive to semantics. I argue that computation is insensitive to semantics within a wide range of computational systems, including any system with ?derived? rather than ?original? intentionality. FCC yields the correct verdict for these systems. I conclude that there (...) is only one promising strategy for semantically-laden theorists: identify special computational systems that help generate their own semantic properties, and then show that computation within those systems is semantically-laden. Unfortunately, the few existing discussions that pursue this strategy are problematic. (shrink)

On the Origin of Objects is, at heart, an extended search for a non-circular and nonreductive characterization of two key notions: intentionality and computation. Only a non-circular and non-reductive account of these key notions can, Smith believes, provide a secure platform for a proper understanding of the mind. The project has both a negative and a positive aspect. Negatively, Smith rejects views that attempt to identify the key notions with lower-level physical properties, arguing instead for a more abstract and (...) systemic understanding. This negative effort occupies Part I of the book. In Part II, we encounter the positive side of Smith's proposal: an attempt to develop a non-reductive analysis of computation and meaning able to meet the requirements laid out in Part I. One purpose of this critical review is to lay out this project in fairly simple terms. This is necessary since Smith's own treatment and prose sometimes obscures the flow of the argument. I suggest that, properly understood, Smith's proposal bears a clear affinity to ideas emerging from the dynamical systems movement within Cognitive Science, and that this tie-in can help put flesh on several of the more metaphorical characterizations in the book. My main criticism is that the book ultimately fails to provide an account able to meet Smith's own requirements for a truly non-reductive account of intentionality. This is especially the case regarding Smith's commitment to licensing a partition of the world based on no a priori assumptions whatsoever. The exercise is a valuable one, however, since it forces us to look harder at some foundational assumptions and at least hints at a new and refreshing perspective: one in which the key explanatory relations are grounded in facts about human practice and pragmatically established social norms. (shrink)

Pietraszewski provides a compelling case that representations of certain interaction-types are the “cognitive primitives” that allow all tokens of group-in-conflict to be represented within the mind. Here, I argue that the folk concept GROUP encodes shared intentions and goals as more central than these interaction-types, and that providing a computational theory of social groups will be more difficult than Pietraszewski envisages.

After discussing the distinction between artifacts and natural entities, and the distinction between artifacts and technology, the conditions of the traditional account of moral agency are identified. While computer system behavior meets four of the five conditions, it does not and cannot meet a key condition. Computer systems do not have mental states, and even if they could be construed as having mental states, they do not have intendings to act, which arise from an agent’s freedom. On the (...) other hand, computer systems have intentionality, and because of this, they should not be dismissed from the realm of morality in the same way that natural objects are dismissed. Natural objects behave from necessity; computer systems and other artifacts behave from necessity after they are created and deployed, but, unlike natural objects, they are intentionally created and deployed. Failure to recognize the intentionality of computer systems and their connection to human intentionality and action hides the moral character of computer systems. Computer systems are components in human moral action. When humans act with artifacts, their actions are constituted by the intentionality and efficacy of the artifact which, in turn, has been constituted by the intentionality and efficacy of the artifact designer. All three components – artifact designer, artifact, and artifact user – are at work when there is an action and all three should be the focus of moral evaluation. (shrink)

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing away with semantics (...) entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators. (shrink)

Social Facts and Collective Intentionality is a combination of terms that refers to a new field of basic research. Written mainly in the mood and by means of analytical philosophy, at the very heart of this new approach is conceptual explication of all the various versions of social facts and collective intentionality and its ramifications. This approach tackles the topics of traditional social philosophy using new conceptual methods, including techniques of formal logic, computer simulations, and artificial intelligence. (...) Such research also addresses careful research relating to ontological, epistemological, normative and--last but not least-- methodological questions. This volume represents the state of the art in this new field. The volume and its contributors tackle a series of vexing issues in the social sciences: (1) the sense of affiliation to large in contrast to small groups, (2) whether collective membership is the same as common knowledge, (3) the worth of information exchange based on faulty data, (4) the difference between standards of information and transfer of information, and (5) whether reliability is grounded in personal experience or as members in epistemic communities or networks. Contributors to this volume have a strong commitment to the social or collective character and mutual interplay of scientific information. "Collective Intentionality" is the term chosen by researchers working in this cross-disciplinary field. The group is currently conducting research in areas such as artificial intelligence, linguistics, logic, and the philosophy of the social sciences. Its work is distinguished by issues of collective behavior such as jointness, groupness, we and us. The present volume covers the state of the art of collective analysis, while fully appreciating that it is a stepping stone, albeit an important one, in redirecting the attention of basic philosophy away from the individual to the collective mode of exact analysis. Georg Meggle is professor for philosophical foundations of anthropology and of cognitive sciences at the University of Leipzig, Germany. He is a key contributor to Realism in Action with a study of Common Belief and Common Knowledge, and author of an earlier study of theoretical foundations of semantics. (shrink)

Cognition has traditionally been understood in terms of internal mental representations, and computational operations carried out on internal mental representations. Radical approaches propose to reconceive cognition in terms of agent-environment dynamics. An outstanding challenge for such a philosophical project is how to scale-up from perception and action to cases of what is typically called ‘higher-order’ cognition such as linguistic thought, the case we focus on in this paper. Perception and action are naturally described in terms of agent-environment dynamics, but can (...) a person’s thoughts about absent, abstract or counterfactual states of affairs also be accounted for in such terms? We argue such a question will seem pressing so long as one fails to appreciate how richly resourceful the human ecological niche is in terms of the affordances it provides. The explanatory work that is supposedly done by mental representations in a philosophical analysis of cognition, can instead be done by looking outside of the head to the environment structured by sociomaterial practices, and the affordances it makes available. Once one recognizes how much of the human ecological niche has become structured by activities of talking and writing, this should take away at least some of the motivation for understanding linguistic thinking in terms of content-bearing internal representations. We’ll argue that people can think about absent, abstract or counterfactual because of their skills for engaging with what we will call “enlanguaged affordances”. We make use of the phenomenological analysis of speech in Merleau-Ponty to show how the multiple affordances an individual is ready to engage with in a particular situation will typically include enlanguaged affordances. (shrink)

A weak version of the life-mind continuity thesis entails that every living system also has a basic mind (with a non-representational form of intentionality). The strong version entails that the same concepts that are sufficient to explain basic minds (with non-representational states) are also central to understanding non-basic minds (with representational states). We argue that recent work on the free energy principle supports the following claims with respect to the life-mind continuity thesis: (i) there is a strong continuity between (...) life and mind; (ii) all living systems can be described as if they had representational states; (iii) the ’as-if representationality’ entailed by the free energy principle is central to understanding both basic forms of intentionality and intentionality in non-basic minds. In addition to this, we argue that the free energy principle also renders realism about computation and representation compatible with a strong life-mind continuity thesis (although the free energy principle does not entail computational and representational realism). In particular, we show how representationality proper can be grounded in ’as-if representationality’. (shrink)

While the notion of the mind as information-processor--a kind of computational system--is widely accepted, many scientists and philosophers have assumed that this account of cognition shows that the mind's operations are characterizable independent of their relationship to the external world. Existential Cognition challenges the internalist view of mind, arguing that intelligence, thought, and action cannot be understood in isolation, but only in interaction with the outside world. Arguing that the mind is essentially embedded in the external world, Ron McClamrock provides (...) a schema that allows cognitive scientists to address such long-standing problems in artificial intelligence as the "frame" problem and the issue of "bounded" rationality. Extending this schema to cover progress in other studies of behavior, including language, vision, and action, McClamrock reinterprets the importance of the organism/environment distinction. McClamrock also considers the broader philosophical question of the place of mind in the world, particularly with regard to questions of intentionality, subjectivity, and phenomenology. With implications for philosophy, cognitive and computer science, AI, and psychology, this book synthesizes state-of-the-art work in philosophy and cognitive science on how the mind interacts with the world to produce thoughts, ideas, and actions. (shrink)

In Context and Content Robert Stalnaker develops a philosophical picture of the nature of speech and thought and the relations between them. Two themes in particular run through these collected essays: the role that the context in which speech takes place plays in accounting for the way language is used to express thought, and the role of the external environment in determining the contents of our thoughts. Stalnaker argues against the widespread assumption of the priority of linguistic over mental representation, (...) which he suggests has had a distorting influence on our understanding. The first part of the book develops a framework for representing contexts and the way they interact with the interpretation of what is said in them. This framework is used to help to explain a range of linguistic phenomena concerning presupposition and assertion, conditional statements, the attribution of beliefs, and the use of names, descriptions, and pronouns to refer. Stalnaker then draws out the conception of thought and its content that is implicit in this framework. He defends externalism about thought--the assumption that our thoughts have the contents they have in virtue of the way we are situated in the world--and explores the role of linguistic action and linguistic structure in determining the contents of our thoughts. Context and Content offers philosophers and cognitive scientists a summation of Stalnaker's important and influential work in this area. His new introduction to the volume gives an overview of this work and offers a convenient way in for those who are new to it. The Oxford Cognitive Science series is a new forum for the best contemporary work in this flourishing field, where various disciplines--cognitive psychology, philosophy, linguistics, cognitive neuroscience, and computational theory--join forces in the investigation of thought, awareness, understanding, and associated workings of the mind. Each book constitutes an original contribution to its subject, but will be accessible beyond the ranks of specialists, so as to reach a broad interdisciplinary readership. The series will be carefully shaped and steered with the aim of representing the most important developments in the field and bringing together its constituent disciplines. (shrink)

The “problem of emotions,” that is, that many of them are both meaningful and corporeal, has yet to be resolved. Western thinkers, from Augustine to Descartes to Zajonc, have handled this problem by employing various forms of mind–body dualism. Some psychologists and neuroscientists since the 1970s have avoided it by talking about cognitive and emotional “processing,” using a terminology borrowed from computer science that nullifies the meaningful or intentional character of both thought and emotion. Outside the Western-influenced contexts, emotion (...) and thought are not seen as distinct kinds of things. Here a solution of sorts is proposed by thinking of emotional expression as a dynamic activity that declares and stirs emotions at the same time. As such, its dynamism may help historians to understand the dramatic changes and trends they investigate. (shrink)

According to John Haugeland, the capacity for “authentic intentionality” depends on a commitment to constitutive standards of objectivity. One of the consequences of Haugeland’s view is that a neurocomputational explanation cannot be adequate to understand “authentic intentionality”. This paper gives grounds to resist such a consequence. It provides the beginning of an account of authentic intentionality in terms of neurocomputational enabling conditions. It argues that the standards, which constitute the domain of objects that can be represented, reflect (...) the statistical structure of the environments where brain sensory systems evolved and develop. The objection that I equivocate on what Haugeland means by “commitment to standards” is rebutted by introducing the notion of “florid, self-conscious representing”. Were the hypothesis presented plausible, computational neuroscience would offer a promising framework for a better understanding of the conditions for meaningful representation. (shrink)

The award of the 2003 Barwise Prize to Daniel Dennett by the American Philosophical Association signifies Dennett’s importance in the developing area of philosophical inquiry into computing and information. One source of Dennett’s intellectual stature is his command of scientific and engineering ideas, which he effectively applies to philosophical debates over machine intelligence, consciousness, and intentionality. Dennett regards the computer as both a model and a tool that will transform the ways that philosophy is pursued in the 21st (...) century. In order to understand Dennett’s conception of how philosophy changes and fares, if his mechanistic and reductionist conception of the life of the mind succeeds, we turn to an examination of a central idea in Dennett’s thought: the intuition pump. (shrink)

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of (...) information and biological function. We echo several other philosophers by arguing that these theories over-generalize unless they are constrained by a theory of the functional role of representational vehicles. This leads to a discussion of the functional roles of representations, and how representations might be realized in the brain. We argue that there’s work to be done to identify a distinctively mental kind of representation. We close by sketching a way forward for the project of naturalizing intentionality. This will not be achieved simply by ascribing the content of mental states to generic neural representations, but by identifying specific neural representations that explain the puzzling intentional properties of mental states. (shrink)

Over the past several decades, the philosophical community has witnessed the emergence of an important new paradigm for understanding the mind.1 The paradigm is that of machine computation, and its influence has been felt not only in philosophy, but also in all of the empirical disciplines devoted to the study of cognition. Of the several strategies for applying the resources provided by computer and cognitive science to the philosophy of mind, the one that has gained the most attention from (...) philosophers has been the Computational Theory of Mind (CTM). CTM was first articulated by Hilary Putnam (1960, 1961), but finds perhaps its most consistent and enduring advocate in Jerry Fodor (1975, 1980, 1981, 1987, 1990, 1994). It is this theory, and not any broader interpretations of what it would be for the mind to be a computer, that I wish to address in this paper. What I shall argue here is that the notion of symbolic representation employed by CTM is fundamentally unsuited to providing an explanation of the intentionality of mental states (a major goal of CTM), and that this result undercuts a second major goal of CTM, sometimes refered to as the vindication of intentional psychology. This line of argument is related to the discussions of derived intentionality by Searle (1980, 1983, 1984) and Sayre (1986, 1987). But whereas those discussions seem to be concerned with the causal dependence of familiar sorts of symbolic representation upon meaning-bestowing acts, my claim is rather that there is not one but several notions of meaning to be had, and that the notions that are applicable to symbols are conceptually dependent upon the notion that is applicable to mental states in the fashion that Aristotle refered to as paronymy. That is, an analysis of the notions of meaning applicable to symbols reveals that they contain presuppositions about meaningful mental states, much as Aristotle's analysis of the sense of healthy that is applied to foods reveals that it means conducive to having a healthy body, and hence any attempt to explain mental semantics in terms of the semantics of symbols is doomed to circularity and regress. I shall argue, however, that this does not have the consequence that computationalism is bankrupt as a paradigm for cognitive science, as it is possible to reconstruct CTM in a fashion that avoids these difficulties and makes it a viable research framework for psychology, albeit at the cost of losing its claims to explain intentionality and to vindicate intentional psychology. I have argued elsewhere (Horst, 1996) that local special sciences such as psychology do not require vindication in the form of demonstrating their reducibility to more fundamental theories, and hence failure to make good on these philosophical promises need not compromise the broad range of work in empirical cognitive science motivated by the computer paradigm in ways that do not depend on these problematic treatments of symbols. (shrink)

A co-actor’s intentionality has been suggested to be a key modulating factor for joint action effects like the joint Simon effect (JSE). However, in previous studies intentionality has often been confounded with agency defined as perceiving the initiator of an action as being the causal source of the action. The aim of the present study was to disentangle the role of agency and intentionality as modulating factors of the JSE. In Experiment 1, participants performed a joint go/nogo (...) Simon task next to a co-actor who either intentionally controlled a response button with own finger movements (agency+/intentionality+) or who passively placed the hand on a response button that moved up and down on its own as triggered by computer signals (agency-/intentionality-). In Experiment 2, we included a condition in which participants believed that the co-actor intentionally controlled the response button with a Brain-Computer Interface while placing the response finger clearly besides the response button, so that the causal relationship between agent and action effect was perceptually disrupted (agency-/intentionality+). As a control condition, the response button was computer controlled while the co-actor placed the response finger besides the response button (agency-/intentionality-). We observed a JSE when the co-actor responded intentionally and the causal relationship between co-actor and action effect could be perceived, but not when the co-actor did not respond intentionally and the causal relationship was disrupted (Experiment 1). When the intentionality of the co-actor was maintained but the perception of the causal relationship between co-actor and action effect destroyed, the JSE was absent (Experiment 2). Our findings clearly indicate a vital role of a co-actor’s agency for the JSE and suggest that the ascription of agency is strongly perceptually grounded. (shrink)