According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the 'other minds' problem, and similar topics in philosophy of mind are discussed. We (...) also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic. -/- (This paper was reprinted in: The Turing Test: The Elusive Standard of Artificial Intelligence, J. H. Moor, ed., Kluwer Academic, pp. 23-78, 2003.). (shrink)

This book contains a representationalist theory of self-consciousness and of the phenomenal first-person perspective. It draws on empirical data from the cognitive and neurosciences.

Social machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behavior. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous social machines (...) provide a new paradigm for the design of intelligent systems, marking a new phase in AI. After describing the characteristics of goal-driven social machines, we discuss the consequences of their adoption, for the practice of artificial intelligence as well as for its regulation. (shrink)

There is a longstanding debate among Husserl scholars about whether Husserl thinks perception involves mental representation. The debate, I believe, has not been settled. I deny that the existentialist-inspired charge of representationalism about perception in Husserl is precise enough to stick. Given a clearer understanding of just what mental representation amounts to, I contend that those who defend Husserl against the accusation of representationalism fare little better than Husserl's existentialist-leaning critics. I argue that he is in fact a representationalist about (...) perception insofar as it involves a noematic sense. Nevertheless, Husserl opens up the possibility for a representation-free form of perceiving in certain later discussions of the matter in which he suggests that some perceptual states lack noematic sense. What they lack in noematic sense is compensated for by other means, namely, by two sorts of affect and their functional interrelation with abilities for bodily movement. The texts that entertain this possibility, though, severely limit the scope of its actual occurrence. Husserl never commits to a generally or substantially nonrepresentational view of perception. I attempt to sketch out, however, what this nonrepresentationalism about perception that Husserl nearly landed on might look like, rearranging various more or less familiar elements already present in his theory of perception to that end. (shrink)

Does Nature permit the implementation of behaviours that cannot be simulated computationally? We consider the meaning of physical computation in some detail, and present arguments in favour of physical hypercomputation: for example, modern scientific method does not allow the specification of any experiment capable of refuting hypercomputation. We consider the implications of relativistic algorithms capable of solving the (Turing) Halting Problem. We also reject as a fallacy the argument that hypercomputation has no relevance because non-computable values are indistinguishable from sufficiently (...) close computable approximations. In addition to considering the nature of computability relative to any given physical theory, we can consider the relationship between versions of computability corresponding to different models of physics. Deutsch and Penrose have argued on mathematical grounds that quantum computation and Turing computation have equivalent formal power. We suggest this equivalence is invalid when considered from the physical point of view, by highlighting a quantum computational behaviour that cannot meaningfully be considered feasible in the classical universe. (shrink)

John Searle's Chinese room argument is perhaps the most influential andwidely cited argument against artificial intelligence (AI). Understood astargeting AI proper – claims that computers can think or do think– Searle's argument, despite its rhetorical flash, is logically andscientifically a dud. Advertised as effective against AI proper, theargument, in its main outlines, is an ignoratio elenchi. It musterspersuasive force fallaciously by indirection fostered by equivocaldeployment of the phrase "strong AI" and reinforced by equivocation on thephrase "causal powers" (at least) equal (...) to those of brains." On a morecarefully crafted understanding – understood just to targetmetaphysical identification of thought with computation ("Functionalism"or "Computationalism") and not AI proper the argument is still unsound,though more interestingly so. It's unsound in ways difficult for high church– "someday my prince of an AI program will come" – believersin AI to acknowledge without undermining their high church beliefs. The adhominem bite of Searle's argument against the high church persuasions of somany cognitive scientists, I suggest, largely explains the undeserved reputethis really quite disreputable argument enjoys among them. (shrink)

The Church–Turing Thesis (CTT) is often employed in arguments for computationalism. I scrutinize the most prominent of such arguments in light of recent work on CTT and argue that they are unsound. Although CTT does nothing to support computationalism, it is not irrelevant to it. By eliminating misunderstandings about the relationship between CTT and computationalism, we deepen our appreciation of computationalism as an empirical hypothesis.

Work on analogy has been done from a number of disciplinary perspectives throughout the history of Western thought. This work is a multidisciplinary guide to theorizing about analogy. It contains 1,406 references, primarily to journal articles and monographs, and primarily to English language material. classical through to contemporary sources are included. The work is classified into eight different sections (with a number of subsections). A brief introduction to each section is provided. Keywords and key expressions of importance to research on (...) analogy are discussed in the introductory material. Electronic resources for conducting research on analogy are listed as well. (shrink)

Two Experiments demonstrate the existence of a “collapse illusion”, in which reasoners evaluate Truthteller-type propositions (“I am telling the truth”) as if they were simply true, whereas Liar-type propositions (“I am lying”) tend to be evaluated as neither true nor false. The second Experiment also demonstrates an individual differences pattern, in which shallow reasoners are more susceptible to the illusion. The collapse illusion is congruent with philosophical semantic truth theories such as Kripke's (1975), and with hypothetical thinking theory's principle of (...) satisficing, but can only be partially accounted for by the model theory principle of truth. Pragmatic effects related to sentence cohesion further reinforce hypothetical thinking theory interpretation of the data, although the illusion and cohesion data could also be accounted for within a modified mental model theory. (shrink)

How do we perceive the agency of others? Do the same rules apply when interacting with others who are radically different from ourselves, like other species or robots? We typically perceive other people and animals through their embodied behavior, as they dynamically engage various aspects of their affordance field. In second personal perception we also perceive social or interactional affordances of others. I discuss various aspects of perceptible agency, which might begin to give us some tools to understand interactions also (...) with agents truly other than ourselves or “perhaps agents” like present and future social robots. Robots have various kinds of physical and behavioral presence and thus make their agency—if we want to call it that—perceptible in ways that computers and other forms of AI do not. The largely dualist assumptions pertaining to the hidden bodies of traditional Turing tests are discussed, as well as the social affordance effects of such indirect interactions as opposed to interactions in physically shared space. The question is what role various abilities to reveal, hide and dynamically control the body and broader behavior plays in heterogeneous tech or machine mediated interactions. I argue that the specifics and richness of perceptible agency matters to the kind of reciprocity we can obtain. (shrink)

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)

This paper revisits the conception of intelligence and understanding as embodied in the Turing Test. It argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic inferences in a manner that can be taken to be 'understanding' in a mechanized system. Understanding in this case is a matter of running through the relevant inferences meaning relations allow for, and some of (...) these inferences are plain deductions and some can serve to act as abductions. Understanding in terms of meaning relations also supervenes on linguistic syntax because such understanding cannot be simply reduced to syntactic relations. The current approach to meaning and understanding thus shows that this is one way, if not the only way, of framing Alan Turing's original insight into the nature of thinking in computing systems. (shrink)

Correspondences and similarities between ideas in shamanism and ideas in contemporary cognitive science are considered. The importance of interconnectedness in the web of life worldview characteristic of shamanism and in connectionist models of semantic memory in cognitive science, and the extension of meaning to elements of the natural world in shamanism and indistributed cognition, are considered. Cognitive consequences of such an extension (e.g., use of representativeness and intentional stance heuristics, magical thinking, social attribution errors, and social in‐group/out‐group differences) are discussed. (...) It is suggested that attributions of mental states, beliefs, and desires to a computer on the basis of behavioral measures (e.g., the Turing test) is consistent with the extension of meaning and intentionality to nonhuman elements of the natural world in shamanism. In general, the existence of such correspondencesand similarities suggests that elements of shamanism may reflect cognitive structures and processes that are also used by nonshamans and in nonshamanic settings. (shrink)