Showing papers in "Minds and Machines in 2010"
TL;DR: This paper suggests that “creative autonomy,” which exists when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary condition for making this argument.
Abstract: The greatest rhetorical challenge to developers of creative artificial intelligence systems is convincingly arguing that their software is more than just an extension of their own creativity. This paper suggests that "creative autonomy," which exists when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary condition for making this argument. Rather than requiring that the system be hermetically sealed to avoid perceptions of human influence, developing creative autonomy is argued to be more plausible if the system is intimately embedded in a broader society of other creators and critics. Ideas are presented for constructing systems that might be able to achieve creative autonomy.
93 citations
TL;DR: It is shown that the second-order-property of e-trust has the effect of minimising an agent’s effort and commitment in the achievement of a given goal.
Abstract: This paper provides a new analysis of e-trust, trust occurring in digital contexts, among the artificial agents of a distributed artificial system. The analysis endorses a non-psychological approach and rests on a Kantian regulative ideal of a rational agent, able to choose the best option for itself, given a specific scenario and a goal to achieve. The paper first introduces e-trust describing its relevance for the contemporary society and then presents a new theoretical analysis of this phenomenon. The analysis first focuses on an agent's trustworthiness, this one is presented as the necessary requirement for e-trust to occur. Then, a new definition of e-trust as a second-order-property of first-order relations is presented. It is shown that the second-order-property of e-trust has the effect of minimising an agent's effort and commitment in the achievement of a given goal. On this basis, a method is provided for the objective assessment of the levels of e-trust occurring among the artificial agents of a distributed artificial system.
80 citations
TL;DR: This paper conducts a very large corpus analysis of web-harvested similes to identify the most interesting characteristics of ironic comparisons, and provides an empirical evaluation of a new algorithm for separating ironic from non-ironic similes.
Abstract: Irony is an effective but challenging mode of communication that allows a speaker to express viewpoints rich in sentiment with concision, sharpness and humour. Creative irony is especially common in online documents that express subjective and deeply-felt opinions, and thus represents a significant obstacle to the accurate analysis of sentiment in web texts. In this paper we look at one commonly used framing device for linguistic irony--the simile--to show how even the most creative uses of irony are often marked in ways that make them computationally feasible to detect. We conduct a very large corpus analysis of web-harvested similes to identify the most interesting characteristics of ironic comparisons, and provide an empirical evaluation of a new algorithm for separating ironic from non-ironic similes.
69 citations
TL;DR: Based on insufficient evidence, and inadequate research, Floridi and his students report inaccuracies and draw false conclusions in their Minds and Machines evaluation, which this paper aims to clarify.
Abstract: Based on insufficient evidence, and inadequate research, Floridi and his students report inaccuracies and draw false conclusions in their Minds and Machines evaluation, which this paper aims to clarify Acting as invited judges, Floridi et al participated in nine, of the ninety-six, Turing tests staged in the finals of the 18th Loebner Prize for Artificial Intelligence in October 2008 From the transcripts it appears that they used power over solidarity as an interrogation technique As a result, they were fooled on several occasions into believing that a machine was a human and that a human was a machine Worse still, they did not realise their mistake This resulted in a combined correct identification rate of less than 56% In their paper they assumed that they had made correct identifications when they in fact had been incorrect
28 citations
TL;DR: Gärdenfors’ theory of conceptual spaces offers a way of bridging the traditional divide between symbolic and sub-symbolic representations, as well as the gap between representational formalism and meaning as perceived by human minds.
Abstract: We examine Gardenfors' theory of conceptual spaces, a geometrical form of knowledge representation (Conceptual spaces: The geometry of thought, MIT Press, Cambridge, 2000), in the context of the general Creative Systems Framework introduced by Wiggins (J Knowl Based Syst 19(7):449---458, 2006a; New Generation Comput 24(3):209---222, 2006b). Gardenfors' theory offers a way of bridging the traditional divide between symbolic and sub-symbolic representations, as well as the gap between representational formalism and meaning as perceived by human minds. We discuss how both these qualities may be advantageous from the point of view of artificial creative systems. We take music as our example domain, and discuss how a range of musical qualities may be instantiated as conceptual spaces, and present a detailed conceptual space formalisation of musical metre.
26 citations
TL;DR: It is argued that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicitintrinsic representations.
Abstract: This paper deals with the question: how is computation best individuated?
1. The semantic view of computation: computation is best individuated by its semantic properties.
The causal view of computation: computation is best individuated by its causal properties.
The functional view of computation: computation is best individuated by its functional properties.
Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated semantically. I criticize the reasons in support of this view and its presupposition of representation and semantics. Furthermore, I argue that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicit intrinsic representations.
25 citations
TL;DR: An approach to story generation that utilize exploration, combination, and transformation, implemented in the Vignette Based Partial Order Causal Link story planner, is an algorithm that searches through a space of possible story solutions, guided by combinations of existing story fragments called vignettes.
Abstract: Storytelling is a pervasive part of our daily lives and culture. The task of creating stories for the purposes of entertaining, educating, and training has traditionally been the purview of humans. This sets up the conditions for a creative authoring bottleneck where the consumption of stories outpaces the production of stories by human professional creators. The automation of story creation may scale up the ability to produce and deliver novel, meaningful story artifacts. From this practical perspective, story generation systems replicate the creative abilities of humans and can thus be considered instances of computational creativity. Computational systems that are purported to be creative typically utilize one of three general approaches: exploration of a space of concepts, combination of concepts, and transformation of concepts. In this article we present an approach to story generation that utilize exploration, combination, and transformation. Our approach, implemented in the Vignette Based Partial Order Causal Link story planner, is an algorithm that searches through a space of possible story solutions, guided by combinations of existing story fragments called vignettes. The vignettes are made relevant to novel story generation contexts through an automated transformation pre-process. Through these processes, we show that story generation can incorporate multiple perspectives on computational creativity. Our approach is presented at both the theoretical and technical levels.
21 citations
TL;DR: A study on relevant elements for the assessment of novelty in computer-generated narratives of folk-tales, working with simple plots and basic narrative elements: events, characters, props and scenarios is presented.
Abstract: Novelty is a key concept to understand creativity. Evaluating a piece of artwork or other creation in terms of novelty requires comparisons to other works and considerations about the elements that have been reused in the creative process. Human beings perform this analysis intuitively, but in order to simulate it using computers, the objects to be compared and the similarity metrics to be used should be formalized and explicitly implemented. In this paper we present a study on relevant elements for the assessment of novelty in computer-generated narratives. We focus on the domain of folk-tales, working with simple plots and basic narrative elements: events, characters, props and scenarios. Based on the empirical results of this study we propose a set of computational metrics for the automatic assessment of novelty. Although oriented to the implementation of our own story generation system, the measurement methodology we propose can be easily generalized to other creative systems.
19 citations
TL;DR: It is argued that the more a pattern of features is general and shared, the more it qualifies as a concept, and how conceptual structure organized around such a stable core can produce contextually appropriate representations on demand.
Abstract: Are concepts stable entities, unchanged from context to context? Or rather are they context-dependent structures, created on the fly? We argue that this does not constitute a genuine dilemma. Our main thesis is that the more a pattern of features is general and shared, the more it qualifies as a concept. Contextualists have not shown that conceptual structures lack a stable, general core, acting as an attractor on idiosyncratic information. What they have done instead is to give a contribution to the comprehension of how conceptual structure organized around such a stable core can produce contextually appropriate representations on demand.
19 citations
TL;DR: The utility of the distinction between conceptual and nonconceptual content in cognitive science, and in particular, in the empirical study of visual perception, is questioned.
Abstract: In this article we question the utility of the distinction between conceptual and nonconceptual content in cognitive science, and in particular, in the empirical study of visual perception. First, we individuate some difficulties in characterizing the notion of "concept" itself both in the philosophy of mind and cognitive science. Then we stress the heterogeneous nature of the notion of nonconceptual content and outline the complex and ambiguous relations that exist between the conceptual/nonconceptual duality and other pairs of notions, such as top---down/bottom-up and modular/nonmodular. Finally we look in greater detail at the proposal developed by Jacob and Jeannerod (Ways of seeing. The scopes and limits of visual cognition. Oxford, UK: Oxford University Press, 2003), who apply the notion of nonconceptual content to empirical research on visual perception. After reconstructing their point of view on concepts, we try to reject their major arguments in support of the conceptual/nonconceptual distinction, i.e. the compositionality of thought and the fineness of grain of percepts.
18 citations
TL;DR: Doubts are raised over whether Dancy’s brand of particularism can adequately explain the graded nature of similarity assessments in analogical arguments, and simple recurrent neural network models of moral case classification are presented and discussed.
Abstract: `Particularism' and `generalism' refer to families of positions in the philosophy of moral reasoning, with the former playing down the importance of principles, rules or standards, and the latter stressing their importance. Part of the debate has taken an empirical turn, and this turn has implications for AI research and the philosophy of cognitive modeling. In this paper, Jonathan Dancy's approach to particularism (arguably one of the best known and most radical approaches) is questioned both on logical and empirical grounds. Doubts are raised over whether Dancy's brand of particularism can adequately explain the graded nature of similarity assessments in analogical arguments. Also, simple recurrent neural network models of moral case classification are presented and discussed. This is done to raise concerns about Dancy's suggestion that neural networks can help us to understand how we could classify situations in a way that is compatible with his particularism. Throughout, the idea of a surveyable standard--one with restricted length and complexity--plays a key role. Analogical arguments are taken to involve multidimensional similarity assessments, and surveyable contributory standards are taken to be attempts to articulate the dimensions of similarity that may exist between cases. This work will be of relevance both to those who have interests in computationally modeling human moral cognition and to those who are interested in how such models may or may not improve our philosophical understanding of such cognition.
TL;DR: A computer program to generate novel designs for the arrangement of furniture within a simulated room based on the engagement-reflection computer model of the creative processes is reported, arguing that this kind of model opens new possibilities for the simulation of the design processes as well as the development of tools.
Abstract: This paper reports a computer program to generate novel designs for the arrangement of furniture within a simulated room. It is based on the engagement-reflection computer model of the creative processes. During engagement the system generates material in the form of sequences of actions (e.g. change the colours of the walls, include some furniture in the room, modify their colour, and so on) guided by content and knowledge constraints. During reflection, the system evaluates the composition produced so far and, if it is necessary, modifies it. We discuss the implementation of the system and some of its most salient features, especially the use of a computational model for creativity in the terrain of design. We argue that this kind of model opens new possibilities for the simulation of the design processes as well as the development of tools.
TL;DR: There are identified the main problems, which occur when attempting to implement emotions into machines, and a consideration of the bodily aspects of emotions is of crucial importance, especially when a system shall be able to learn correlations between environmental objects and events and their “emotional meaning”.
Abstract: For a long time, emotions have been ignored in the attempt to model intelligent behavior. However, within the last years, evidence has come from neuroscience that emotions are an important facet of intelligent behavior being involved into cognitive problem solving, decision making, the establishment of social behavior, and even conscious experience. Also in research communities like software agents and robotics, an increasing number of researchers start to believe that computational models of emotions will be needed to design intelligent systems. Nevertheless, modeling emotions in technical terms poses many difficulties and has often been accounted as just not feasible. In this article, there are identified the main problems, which occur when attempting to implement emotions into machines. By pointing out these problems, it is aimed to avoid repeating mistakes committed when modeling computational models of emotions in order to speed up future development in this area. The identified issues are not derived from abstract reflections about this topic but from the actual attempt to implement emotions into a technical system based on neuroscientific research findings. It is argued that besides focusing on the cognitive aspects of emotions, a consideration of the bodily aspects of emotions--their grounding into a visceral body--is of crucial importance, especially when a system shall be able to learn correlations between environmental objects and events and their "emotional meaning".
TL;DR: It is proposed that there is only one supramodal computational system with recursion in the human mind and that the recursion thesis constitutes a plausible research program for cognitive science.
Abstract: Humans grasp discrete infinities within several cognitive domains, such as in language, thought, social cognition and tool-making. It is sometimes suggested that any such generative ability is based on a computational system processing hierarchical and recursive mental representations. One view concerning such generativity has been that each of the mind's modules defining a cognitive domain implements its own recursive computational system. In this paper recent evidence to the contrary is reviewed and it is proposed that there is only one supramodal computational system with recursion in the human mind. A recursion thesis is defined, according to which the hominin cognitive evolution is constituted by a recent punctuated genetic mutation that installed the general, supramodal capacity for recursion into the human nervous system on top of the existing, evolutionarily older cognitive structures, and it is argued on the basis of empirical evidence and theoretical considerations that the recursion thesis constitutes a plausible research program for cognitive science.
TL;DR: A model of how quality in stories is evaluated is presented, and two possible implementations of the generation guided by this evaluation are shown: exhaustive space exploration and constrained exploration.
Abstract: Evaluation processes are a basic component of creativity. They guide not only the pure judgement about a new artefact but also the generation itself, as creators constantly evaluate their own work. This paper proposes a model for automatic story generation based on the evaluation of stories. A model of how quality in stories is evaluated is presented, and two possible implementations of the generation guided by this evaluation are shown: exhaustive space exploration and constrained exploration. A theoretical model and its implementation are explained and validation of the evaluation function through comparison with human criteria is described.
TL;DR: In this article, forms of justification for inductive machine learning techniques are discussed and classified into four types, with a view to introduce some of these techniques and their justificatory guarantees to the attention of philosophers, and initiate a discussion as to whether they must be treated separately or rather can be viewed consistently from within a single framework.
Abstract: Forms of justification for inductive machine learning techniques are discussed and classified into four types. This is done with a view to introduce some of these techniques and their justificatory guarantees to the attention of philosophers, and to initiate a discussion as to whether they must be treated separately or rather can be viewed consistently from within a single framework.
TL;DR: The thought experiment shows that universal computation can be constructed from natural language structure and skills, and shows why intentional capabilities needed for language use play a role in computation across all media.
Abstract: This paper explains how mathematical computation can be constructed from weaker recursive patterns typical of natural languages. A thought experiment is used to describe the formalization of computational rules, or arithmetical axioms, using only orally-based natural language capabilities, and motivated by two accomplishments of ancient Indian mathematics and linguistics. One accomplishment is the expression of positional value using versified Sanskrit number words in addition to orthodox inscribed numerals. The second is P??ini's invention, around the fifth century BCE, of a formal grammar for spoken Sanskrit, expressed in oral verse extending ordinary Sanskrit, and using recursive methods rediscovered in the twentieth century. The Sanskrit positional number compounds and P??ini's formal system are construed as linguistic grammaticalizations relying on tacit cognitive models of symbolic form. The thought experiment shows that universal computation can be constructed from natural language structure and skills, and shows why intentional capabilities needed for language use play a role in computation across all media. The evolution of writing and positional number systems in Mesopotamia is used to transfer the thought experiment of "oral arithmetic" to inscribed computation. The thought experiment and historical evidence combine to show how and why mathematical computation is a cognitive technology extending generic symbolic skills associated with language structure, usage, and change.
TL;DR: It is argued that although some AI programs appear creative, to call these programmed acts creative in the authors' terms is to misunderstand the use of this word in language.
Abstract: Creativity has a special role in enabling humans to develop beyond the fulfilment of simple primary functions. This factor is significant for Artificial Intelligence (AI) developers who take replication to be the primary goal, since moves toward creating autonomous artificial-beings beg questions about their potential for creativity. Using Wittgenstein's remarks on rule-following and language-games, I argue that although some AI programs appear creative, to call these programmed acts creative in our terms is to misunderstand the use of this word in language. I conclude that replication is not the best way forward for AI development in matters of creativity.
TL;DR: This work proposes a rational framework built on a set of logically inter-connected conjectures to specifically recognize this neglected phase in the overall design process of intelligent systems for practical problem-solving applications.
Abstract: Goal-directed problem solving as originally advocated by Herbert Simon's means-ends analysis model has primarily shaped the course of design research on artificially intelligent systems for problem-solving. We contend that there is a definite disregard of a key phase within the overall design process that in fact logically precedes the actual problem solving phase. While systems designers have traditionally been obsessed with goal-directed problem solving, the basic determinants of the ultimate desired goal state still remain to be fully understood or categorically defined. We propose a rational framework built on a set of logically inter-connected conjectures to specifically recognize this neglected phase in the overall design process of intelligent systems for practical problem-solving applications.
TL;DR: This article offers a defense of the idea that several explanation-types are legitimate in software engineering, and that the appropriateness of an explanation-type depends on the engineer's interests and the format of the explanation-seeking question he asks, with this format depending on his interests.
Abstract: This article reveals that explanatory practice in software engineering is in accordance with pragmatic explanatory pluralism, which states that explanations should at least partially be evaluated by their practical use. More specifically, I offer a defense of the idea that several explanation-types are legitimate in software engineering, and that the appropriateness of an explanation-type depends on (a) the engineer's interests, and (b) the format of the explanation-seeking question he asks, with this format depending on his interests. This idea is defended by considering examples that are representative for explanatory practice in software engineering. Different kinds of technological explanation are spelled out, and the dependence of their appropriateness on interests and question-formats is extensively illustrated.
TL;DR: This paper will further propose a modification of the above mentioned explication of the notion of machines by quantifying the length of an algorithm, which appears possible to reconcile the opposing views on the topic.
Abstract: This paper revisits the often debated question Can machines think? It is argued that the usual identification of machines with the notion of algorithm has been both counter-intuitive and counter-productive. This is based on the fact that the notion of algorithm just requires an algorithm to contain a finite but arbitrary number of rules. It is argued that intuitively people tend to think of an algorithm to have a rather limited number of rules. The paper will further propose a modification of the above mentioned explication of the notion of machines by quantifying the length of an algorithm. Based on that it appears possible to reconcile the opposing views on the topic, which people have been arguing about for more than half a century.
TL;DR: Nikola Grahek’s book lies on the border between philosophical speculation about the nature of pain and empirical results on dissociative pain syndromes, and proposes a thesis that pain is a complex phenomenon that combines both sensory/discriminative and cognitive/emotional elements.
Abstract: Our relationship with pain is certainly paradoxical. It is normal to hate it, avoid it, shun it, and be horrified by those who enjoy producing it. But also, pain is a feature of our biological equipment that is very important to our survival. It is a precious gift that nobody wants. Nikola Grahek’s book lies on the border between philosophical speculation about the nature of pain and empirical results on dissociative pain syndromes. Grahek is proposes a thesis: pain is a complex phenomenon that combines both sensory/discriminative (feeling pain: the quality of pain, time and spatial ubication, intensity) and cognitive/emotional (being in pain: discomfort, motor reactions, anticipation) elements. Therefore, pain cannot be reduced to either in the absence of the other. Imagine the case of Josh. Josh undergoes some tests with painful stimuli; he locates the exact spot where these were produced and recognizes their quality and intensity. Curiously, none of these stimuli is uncomfortable or inconvenient for Josh. Sometimes Josh even smiles when these stimuli occur. Josh has never reacted negatively against the researchers. Moreover, he is always very cooperative with the tests. Josh is not a character of a bizarre mental experiment; he is a patient suffering the rare syndrome called Pain Asymbolia, where the two faces of pain are decoupled: Josh is feeling pain, but he is not in pain. Pain Asymbolia is the syndrome used by Grahek to establish that the dissociation of the sensitive component and the cognitive component is not only a logical possibility but a real fact in nature. As follows, the eight chapters of the book will be summarized to conclude with a commentary on the philosophical conclusion proposed by Grahek in chapter six. In the first and second chapters, Grahek explains the biological function of pain. Pain has two main functions working as an avoiding system and a repair system.
TL;DR: This work lays out some constraints that a theoretically useful notion of domain specificity, in the context of the highly modular mind, would need to meet, and surveys a host of accounts of what domain specificity is, based on the intuitive idea that a domain specific mechanism is restricted in the kind of information that it processes.
Abstract: Is there a notion of domain specificity which affords genuine insight in the context of the highly modular mind, i.e. a mind which has not only input modules, but also central `conceptual' modules? Our answer to this question is no. The main argument is simple enough: we lay out some constraints that a theoretically useful notion of domain specificity, in the context of the highly modular mind, would need to meet. We then survey a host of accounts of what domain specificity is, based on the intuitive idea that a domain specific mechanism is restricted in the kind of information that it processes, and show that each fails at least one of those constraints.
TL;DR: This paper provides the beginning of an account of authentic intentionality in terms of neurocomputational enabling conditions and argues that the standards reflect the statistical structure of the environments where brain sensory systems evolved and develop.
Abstract: 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.
TL;DR: As the final touches are being put to this very special issue of Minds and Machines, which showcases a selection of the finest contributions to the 2008 International Joint Workshop on Computational Creativity, Tony Blair has just unveiled his memoirs to a sharply divided public.
Abstract: As the final touches are being put to this very special issue of Minds and Machines, which showcases a selection of the finest contributions to the 2008 International Joint Workshop on Computational Creativity, Tony Blair has just unveiled his memoirs to a sharply divided public. As befitting this controversial figure’s polarizing legacy, reactions to his autobiography—entitled A Journey—have ranged from the painfully predictable to the creatively original. The jeering crowds that awaited Mr. Blair outside book signings and other public events were entirely predictable, as were the cries of ‘‘war criminal’’ and other lazy categorizations that have long since lost their creative bite. Slightly less predictable was the hurling of shoes at Mr. Blair, an analogical echo of another time when footwear was used as a cultural missile against George W. Bush. At a Dublin book signing, this minor act of analogical creativity was both enhanced and undermined by the cost-effective and very ironic choice of shoes—flip-flops!—since Mr. Blair is most often criticized for being unwilling to recant (or ‘‘flip-flop’’, in political parlance) for his involvement in the Iraq war. However, the most creative protest to greet the publication of A Journey was also the least noisome. Through a campaign launched via Facebook, protesters were encouraged to quietly and mischievously re-categorize Mr. Blair’s book in whatever bookshop they happened to find it. As reported in the British newspaper The Telegraph, employees in bookstores across the country were puzzled to find copies of the book migrating from its ‘‘official’’ home on the Biography shelves to sections such as Fiction and even True Crime. Euan Booth, the student who originated the Facebook campaign, explained himself thus to The Telegraph:
TL;DR: The weak intentional realism of the II theory—which makes intentional descriptions of the world dispensable—is related to Dennett’s ‘intentional stance’ view, and distinguished from strong (indispensable) intentional realist views.
Abstract: This article further explains and develops a recent, comprehensive semantic naturalization theory, namely the interactive indexing (II) theory as described in my 2008 Minds and Machines article "Semantic Naturalization via Interactive Perceptual Causality" (Vol. 18, pp. 527---546). Folk views postulate a concrete intentional relation between cognitive states and the worldly states they are about. The II theory eliminates any such concrete intentionality, replacing it with purely causal relations based on the interactive theory of perception. But intentionality is preserved via purely abstract propositions about the world that index, or correlate with, appropriate cognitive states. Further reasons as to why intentionality must be abstract are provided, along with more details of an II-style account of representation, language use and propositional attitudes. All cognitive representation is explained in terms of classification or sorting dispositions indexed by appropriate propositions. The theory is also related to Fodor's representational theory of mind, with some surprisingly close parallels being found in spite of the purely dispositional basis of the II theory. In particular, Fodor's insistence that thinking about an item cannot be reduced to sorting dispositions is supported via a novel two-level account of cognition--upper level propositional attitudes involve significant intermediate processing of a broadly normative epistemic kind prior to the formation of sorting dispositions. To conclude, the weak intentional realism of the II theory--which makes intentional descriptions of the world dispensable--is related to Dennett's `intentional stance' view, and distinguished from strong (indispensable) intentional realist views. II-style dispositions are also defended.
TL;DR: It is shown that inferentialism entails the falsity of Church’s Thesis and, as a consequence, the Computational Theory of Mind, and this amounts to an entirely novel critique of mechanism in the philosophy of mind.
Abstract: We first discuss Michael Dummett's philosophy of mathematics and Robert Brandom's philosophy of language to demonstrate that inferentialism entails the falsity of Church's Thesis and, as a consequence, the Computational Theory of Mind. This amounts to an entirely novel critique of mechanism in the philosophy of mind, one we show to have tremendous advantages over the traditional Lucas-Penrose argument.
TL;DR: It is suggested that the classes (that implicitly underlie most models of artificial intelligence) are insufficient to explain human goal-directed activity and suggests that humans are goal- directed systems that jointly synthesize arbitrary goals and means.
Abstract: Although activity aimed at the construction of artificial intelligence started about 60 years ago however, contemporary intelligent systems are effective in very narrow domains only. One of the reasons for this situation appears to be serious problems in the theory of intelligence. Intelligence is a characteristic of goal-directed systems and two classes of goal-directed systems can be derived from observations on animals and humans, one class is systems with innately and jointly determined goals and means. The other class contains systems that are able to construct arbitrary goals and means. It is suggested that the classes (that implicitly underlie most models of artificial intelligence) are insufficient to explain human goal-directed activity. A broader approach to goal-directed systems is considered. This approach suggests that humans are goal-directed systems that jointly synthesize arbitrary goals and means. Neural and psychological data favoring this hypothesis and its experimental validation are considered. A simple computer model based on the idea of joint synthesis to simulate goal-directed activity is presented. The usage of the idea of joint synthesis for the construction of artificial intelligence is discussed.
Journal Article•
TL;DR: An effective but challenging mode of communication that allows a speaker to express viewpoints rich in sentiment with concision, sharpness and humour.
Abstract: Irony is an effective but challenging mode of communication that allows a speaker to express viewpoints rich in sentiment with concision, sharpness and humour. Creative irony is especially common i...
TL;DR: There is more to human experience than neural activity, or as Noe puts it, 'the authors are out of their heads' and 'already home in the environment' and the contention that neural activity is sufficient for consciousness must be abandoned, and the search for neural correlates must be rethought.
Abstract: 1. Alva Noe ¨'s Out of Our Heads is a fascinating and stimulating book. The clarity of writing is unparalleled and the breadth of considerations is nothing short of impressive. Although an engagement with the empirical literature has now become common practice for philosophers interested in the nature of the mind, Noe ¨'s ability to juxtapose masterfully the empirical with the conceptual sets him apart from the rest. Out of Our Heads is a well-crafted interlacing of scientific and philosophical considerations that ultimately gives rise to a provocative picture of the human mind. In the eight chapters, preface, and epilogue that comprise the book, Noeadvances a plethora of interconnected theses. He calls for the adoption of a 'biological perspective,' provides empirical evidence in support of an enactive and externalist account of consciousness, and comments on the ways that language, technology, and tools extend our body schema (39). Furthermore, Noestresses the significance of habits and rejects an intellectualist picture of human existence. He also provides evidence against the conviction that our visual experience of the world is a grand illusion, and argues that the groundbreaking research conducted by Hubel and Wisel was governed by the idea that the 'brain is an information-processing device' (161). Finally, Noeinsists that the brain is necessary but not sufficient for experience. Although by no means exhaustive, the above list conveys the book's guiding theme: there is more to human experience than neural activity, or as Noeputs it, 'we are out of our heads' and 'already home in the environment' (xiii). To construe human nature in such a fashion is to call for drastic changes. Most importantly, the contention that neural activity is sufficient for consciousness must be abandoned, and the search for neural correlates must be rethought. Noe ¨, in fact, announces that 'Cartesian neuroscience has no empirical support for its basic assumption that conscious experience is an exhaustively neural phenomenon,' and