Very plausibly, nothing can be a genuine computing system unless it meets an input-sensitivity requirement. Otherwise all sorts of objects, such as rocks or pails of water, can count as performing computations, even such as might suffice for mentality—thus threatening computationalism about the mind with panpsychism. Maudlin in J Philos 86:407–432, ( 1989 ) and Bishop ( 2002a , b ) have argued, however, that such a requirement creates difficulties for computationalism about conscious experience, putting it in conflict with the (...) very intuitive thesis that conscious experience supervenes on physical activity. Klein in Synthese 165:141–153, ( 2008 ) proposes a way for computationalists about experience to avoid panpsychism while still respecting the supervenience of experience on activity. I argue that his attempt to save computational theories of experience from Maudlin’s and Bishop’s critique fails. (shrink)

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive (...) science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience . From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001. (shrink)

Computationalism, a specie of functionalism, posits that a mental state like pain is realized by a ‘core’ computational state within a particular causal network of such states. This entails that what is realized by the core state is contingent on events remote in space and time, which puts computationalism at odds with the locality principle of physics. If computationalism is amended to respect locality, then it posits that a type of phenomenal experience is determined by a single type of computational (...) state. But a computational state, considered by itself, is of no determinate type—it has no particular symbolic content, since it could be embedded in any of an infinite number of algorithms. Hence, if locality is respected, then the type of experience that is realized by a computational state, or whether any experience at all is realized, is under-determined by the computational nature of the state. Accordingly, Block’s absent and inverted qualia arguments against functionalism find support in the locality principle of physics. If computationalism denies locality to avoid this problem, then it cannot be considered a physicalist theory since it would entail a commitment to phenomena, like teleological causation and action-at-a-distance, that have long been rejected by modern science. The remaining theoretical alternative is to accept the locality principle for macro events and deny that formal, computational operations are sufficient to realize a phenomenal mental state. (shrink)

Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I argue that Putnam's argument fails, but that it points out the need for a better understanding of the bridge between the theory of computation and the theory of physical systems: the relation of implementation. It also raises questions about the class of automata that can serve as a basis for understanding the (...) mind. I develop an account of implementation, linked to an appropriate class of automata, such that the requirement that a system implement a given automaton places a very strong constraint on the system. This clears the way for computation to play a central role in the analysis of mind. (shrink)

When certain formal symbol systems (e.g., computer programs) are implemented as dynamic physical symbol systems (e.g., when they are run on a computer) their activity can be interpreted at higher levels (e.g., binary code can be interpreted as LISP, LISP code can be interpreted as English, and English can be interpreted as a meaningful conversation). These higher levels of interpretability are called "virtual" systems. If such a virtual system is interpretable as if it had a mind, is such a "virtual (...) mind" real? This is the question addressed in this "virtual" symposium, originally conducted electronically among four cognitive scientists: Donald Perlis, a computer scientist, argues that according to the computationalist thesis, virtual minds are real and hence Searle's Chinese Room Argument fails, because if Searle memorized and executed a program that could pass the Turing Test in Chinese he would have a second, virtual, Chinese-understanding mind of which he was unaware (as in multiple personality). Stevan Harnad, a psychologist, argues that Searle's Argument is valid, virtual minds are just hermeneutic overinterpretations, and symbols must be grounded in the real world of objects, not just the virtual world of interpretations. Computer scientist Patrick Hayes argues that Searle's Argument fails, but because Searle does not really implement the program: A real implementation must not be homuncular but mindless and mechanical, like a computer. Only then can it give rise to a mind at the virtual level. Philosopher Ned Block suggests that there is no reason a mindful implementation would not be a real one. (shrink)

The paper contains an argument against functionalist theories of consciousness. The argument exploits an intuition to the effect that parts of an individual's brain that are not in use at a time t, can have no bearing on whether that individual is conscious at t. After presenting the argument, I defend it against two possible objections, and then distinguish it from two arguments to which it appears, on the surface to be similar.

As I assume to begin with, animals with a high level of consciousness, are those beings which are more dependent on their materialistic ecological circumstances than those with less cognition. The most obvious support for this factual claim is the yet still unofficial unit of geological time named the Anthropocene Epoch demarcating human devastation of earthly resources, whereby there is no doubt which species on earth is the most materially dependent. Notwithstanding, we need to keep things quantitively in perspective. Of (...) the 545.8 gigatons of biomass on Earth of which most is plants, animals make up 0.47% while humans only 0.01%, bacteria reigns supreme with 12.8% of total. (shrink)

Artificial Neural Networks have reached “grandmaster” and even “super-human” performance across a variety of games, from those involving perfect information, such as Go, to those involving imperfect information, such as “Starcraft”. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong—an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, automated credit-scoring processes (...) “discriminate” on gender, etc.—there are often significant financial, legal, and brand consequences, and the incident becomes major news. As Judea Pearl sees it, the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” —the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for theNew York Times: “we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets—often using an approach known as ‘Deep Learning’—and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space, and causality.” In this paper, foregrounding what in 1949 Gilbert Ryle termed “a category mistake”, I will offer an alternative explanation for AI errors; it is not so much that AI machinery cannot “grasp” causality, but that AI machinery (qua computation) cannot understand anything at all. (shrink)

In this paper, I argue that absences pose a challenge to our understanding of physicalism that has not been properly appreciated. I do this by setting out a thought experiment involving a being in whom absence properties occupy the causal roles that functionalists take to define mental properties, in which case these absence properties realize the being’s mental properties. Such a being should be compatible with the truth of physicalism, I argue, even though its mental properties are neither themselves physical (...) properties nor are they realized/grounded in physical properties—instead, they are realized/grounded in (nonphysical) absence properties. I argue that the case serves as a counterexample to leading formulations of physicalism that appeal to realization or grounding, but not to standard supervenience-based formulations of physicalism, because the latter typically include negative truths in their supervenience base in addition to physical truths. I show how realization- and grounding-based formulations of physicalism might be revised to handle the problem, but also recommend that we rethink how we understand physicalism and the role that negative entities can play for physicalists. (shrink)

Opponents of the computational theory of mind have held that the theory is devoid of explanatory content, since whatever computational procedures are said to account for our cognitive attributes will also be realized by a host of other ‘deviant’ physical systems, such as buckets of water and possibly even stones. Such ‘triviality’ claims rely on a simple mapping account of physical implementation. Hence defenders of CTM traditionally attempt to block the trivialization critique by advocating additional constraints on the implementation relation. (...) However, instead of attempting to ‘save’ CTM by constraining the account of physical implementation, I argue that the general form of the triviality argument is invalid. I provide a counterexample scenario, and show that SMA is in fact consistent with empirically rich and theoretically plausible versions of CTM. This move requires rejection of the computational sufficiency thesis, which I argue is scientifically unjustified in any case. By shifting the ‘burden of explanatory force’ away from the concept of physical implementation, and instead placing it on salient aspects of the target phenomenon to be explained, it’s possible to retain a maximally liberal and unfettered view of physical implementation, and at the same time defuse the triviality arguments that have motivated defenders of CTM to impose various theory-laden constraints on SMA. (shrink)

The relationship between abstract formal procedures and the activities of actual physical systems has proved to be surprisingly subtle and controversial, and there are a number of competing accounts of when a physical system can be properly said to implement a mathematical formalism and hence perform a computation. I defend an account wherein computational descriptions of physical systems are high-level normative interpretations motivated by our pragmatic concerns. Furthermore, the criteria of utility and success vary according to our diverse purposes and (...) pragmatic goals. Hence there is no independent or uniform fact to the matter, and I advance the ‘anti-realist’ conclusion that computational descriptions of physical systems are not founded upon deep ontological distinctions, but rather upon interest-relative human conventions. Hence physical computation is a ‘conventional’ rather than a ‘natural’ kind. (shrink)

How has multiplicity superseded impossibility in philosophical challenges to artificial consciousness? I assess a trajectory in recent debates on artificial consciousness, in which metaphysical and explanatory challenges to the possibility of building conscious machines lead to epistemological concerns about the multiplicity underlying ‘what it is like’ to be a conscious creature or be in a conscious state. First, I analyse earlier challenges which claim that phenomenal consciousness cannot arise, or cannot be built, in machines. These are based on Block’s Chinese (...) Nation and Chalmers’ Hard Problem. To defuse such challenges, theorists of artificial consciousness can appeal to empirical methods and models of explanation. Second, I explain why this naturalistic approach produces an epistemological puzzle on the role of biological properties in phenomenal consciousness. Neither behavioural tests nor theoretical inferences seem to settle whether our machines are conscious. Third, I evaluate whether the new challenge can be managed through a more fine-grained taxonomy of conscious states. This strategy is supported by the development of similar taxonomies for biological species and animal consciousness. Although it makes sense of some current models of artificial consciousness, it raises questions about their subjective and moral significance. (shrink)

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...) and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of (...) cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a manmade system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction. (shrink)

In this paper I discuss three problems of consciousness. The first two have been dubbed the “Hard Problem” and the “Harder Problem”. The third problem has received less attention and I will call it the “Hardest Problem”. The Hard Problem is a metaphysical and explanatory problem concerning the nature of conscious states. The Harder Problem is epistemological, and it concerns whether we can know, given physicalism, whether some creature physically different from us is conscious. The Hardest Problem is a problem (...) about reference. Recently some philosophers – among them David Papineau – who advocate a physicalist approach to both the Hard and the Harder problem have called into question the common sense assumption that phenomenal concepts – subjective concepts that we apply directly to experience – refer determinately (modulo vagueness) to real properties that can be instantiated in minds other than my own. The Hardest Problem is the problem of explaining how, given physicalism, this assumption could be true. In this paper I explore how these three problems appear from the perspective of a physicalist approach to consciousness based on Brian Loar’s account of phenomenal concepts, recently dubbed the “phenomenal concept strategy”. My contention is that this approach can go quite far in handling not just the first two problems but the Hardest Problem as well. (shrink)

Representationalism is widely thought to grease the skids of ontological reduction. If phenomenal character is just a certain sort of intentional content, representationalists argue, the hard problem of accommodating consciousness within a broadly naturalistic view of the world reduces to the much easier problem of accommodating intentionality. I argue, however, that there’s a fatal flaw in this reasoning, for if phenomenal character really is just a certain sort of intentional content, it’s not anything like the sort of intentional content described (...) by our best naturalistic theories. These theories make intentional content a mere Cambridge property of intentional states, a property that can be gained or lost through changes to distinct and causally disconnected objects. But consciousness is manifestly not like this; consciousness cannot suffer a mere Cambridge change. Thus, whatever ground is gained by explaining the phenomenal in terms of the intentional is lost again by undermining our best attempts to explain the intentional in terms of the natural. A Pyrrhic victory at best. (shrink)

Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.

The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s (Representation & Reality, Bradford Books, Cambridge in 1988 ) monograph, “Representation & Reality”, which if correct, has (...) important implications for turing machine functionalism and the prospect of ‘conscious’ machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that, “everything implements the specific machine Q on a particular input set ( x )”. Then, equating Q ( x ) to any putative AI program, I will show that conceding the ‘strong AI’ thesis for Q (crediting it with mental states and consciousness) opens the door to a vicious form of panpsychism whereby all open systems, (e.g. grass, rocks etc.), must instantiate conscious experience and hence that disembodied minds lurk everywhere. (shrink)

A popular argument supporting functionalism has been what is commonly called the “multiple realizability” argument. One version of this argument uses thought experiments designed to show that minds could be composed of different types of material. This article offers a metaphilosophical analysis of this argument and shows that it fails to provide a strong case for functionalism. The multiple realizability argument is best understood as an inference‐to‐the‐best‐explanation argument, whereby a functionalist account of our mental concepts serves to explain our multiple (...) realizability intuitions. I show that the argument is inadequate because alternative accounts of our mental concepts exist that provide equally plausible explanations for these intuitions. Moreover, in the case of our qualia concepts, a nonfunctionalist account explains several other intuitions that functionalism cannot explain. Thus, despite its popularity, the intuition‐based version of the multiple realizability argument is a poor reason for accepting functionalism. (shrink)

The aim of this paper is to determine the plausibility of Robert Kirk’s strict implication thesis as an explication of physicalism and its relation to Jackson and Chalmer’s notion of application conditionals, to the notion of global supervenience and to a posteriori identities. It is argued that the strict implication thesis is subject to the same objection that affects the notion of global supervenience. Furthermore, reference to an idealised physics in the formulation of strict implication threatens to make the thesis (...) vacuous. Third, Kirk’s claim that the strict implication thesis does not entail reduction of the mental to the physical (excluding phenomenal properties) is untenable if a functional model of reduction is preferred over Nagel’s classical model. Finally, Kirk’s claim that the physical facts entail in an a priori way the fact that certain brain states feel somehow seems to be unfounded. (shrink)

I argue for the epiphenomenality of functional properties by means of thought experiments and general principles. General principles suggest that an object’s causal powers nomologically supervene on its intrinsic properties and that its functional role does not. This implies that it is possible for an object to lose its functional role without undergoing any change to its intrinsic properties or causal powers. Nor is it difficult to conceive of such scenarios. Various thought experiments are introduced for just this purpose. But (...) properties that can vary independently of an object’s causal powers in this way are epiphenomenal, for their instantiation by an object at a time makes no difference to the causal processes the object is involved in at that time. The same processes would have occurred even if such properties hadn’t been instantiated. The intrinsicness thesis is controversial, but it is not controversial that it is true of productive causation, and many believe that productive causation is the only form of mental causation worth having. Nevertheless, in the paper’s final section I consider dependence-based accounts of causation, which do not presuppose the intrinsicness of causal powers, and show that they too have difficulties accounting for the efficacy of functional properties. (shrink)

Adopting the notion of “pragmatic information” as interpreted by Roederer and granted that understanding arises from genuine information processing, I show that Searle’s “Chinese Room Argument” in rejecting the thesis of Strong Artificial Intelligence and his responses to critics are sound and acceptable. The paper is a safe and secure translation of Searle’s argument into a language of information. According to the notion of information that I adopt, information and information processing are exclusive attributes of biological and artificial systems. However, (...) I will show that information-theoretically, biological brains are fundamentally different from their artificial simulations. I will argue that only biological systems, or their duplicates, are genuine information processing systems and thus capable of understanding Chinese. “Understanding”, in my proposal, denotes “phenomenal consciousness” in the context of Chalmers’ thesis of naturalistic dualism. (shrink)

In this paper, I address one recent objection to Andy Clark and David Chalmers’s functionalist argument for the extended mind thesis. This objection is posed by Kengo Miyazono, who claims that they unjustifiably identify the original cognitive subject with the hybrid one in order to reach their conclusion about the mind extension. His attack consists of three steps: distinguishing hybrid from traditional cognitive subjects based on the systems reply originally directed at Searle’s Chinese room argument; pointing out that the conclusion (...) of the functionalist argument for EM must be rephrased to state that there are hybrid, and not extended, systems with widely realized mental states; and arguing that functionalist EM cannot justify the assumption about the identity of these two kinds of subjects without circularity. I argue that Miyazono’s main argument is ill-founded but that it, nevertheless, points out one important issue, namely, that we need further justification of the identity assumption, without which EM loses much of its flavor. Thus, I am going to challenge Miyazono’s argument, provide a reinterpretation of the argumentation in the EM debate, defend the possibility of wide and extended selves, and offer a justification of the identity assumption, which I find crucial not only for vindicating EM but also for differentiating EM from other similar theses, such as the thesis about group minds. (shrink)

Consciousness supervenes on activity; computation supervenes on structure. Because of this, some argue, conscious states cannot supervene on computational ones. If true, this would present serious difficulties for computationalist analyses of consciousness (or, indeed, of any domain with properties that supervene on actual activity). I argue that the computationalist can avoid the Superfluous Structure Problem (SSP) by moving to a dispositional theory of implementation. On a dispositional theory, the activity of computation depends entirely on changes in the intrinsic properties of (...) implementing material. As extraneous structure is not required for computation, a system can implement a program running on some but not all possible inputs. Dispositional computationalism thus permits episodes of computational activity that correspond to potential episodes of conscious awareness. The SSP cannot be motivated against this account, and so computationalism may be preserved. (shrink)

"The Emperor's New Mind" by Roger Penrose has received a great deal of both praise and criticism. This review discusses philosophical aspects of the book that form an attack on the "strong" AI thesis. Eight different versions of this thesis are distinguished, and sources of ambiguity diagnosed, including different requirements for relationships between program and behaviour. Excessively strong versions attacked by Penrose (and Searle) are not worth defending or attacking, whereas weaker versions remain problematic. Penrose (like Searle) regards the notion (...) of an algorithm as central to AI, whereas it is argued here that for the purpose of explaining mental capabilities the architecture of an intelligent system is more important than the concept of an algorithm, using the premise that what makes something intelligent is not what it does but how it does it. What needs to be explained is also unclear: Penrose thinks we all know what consciousness is and claims that the ability to judge Go "del's formula to be true depends on it. He also suggests that quantum phenomena underly consciousness. This is rebutted by arguing that our existing concept of "consciousness" is too vague and muddled to be of use in science. This and related concepts will gradually be replaced by a more powerful theory-based taxonomy of types of mental states and processes. The central argument offered by Penrose against the strong AI thesis depends on a tempting but unjustified interpretation of Goedel's incompleteness theorem. Some critics are shown to have missed the point of his argument. A stronger criticism is mounted, and the relevance of mathematical Platonism analysed. Architectural requirements for intelligence are discussed and differences between serial and parallel implementations analysed. (shrink)

What does it take to implement a computer? Answers to this question have often focused on what it takes for a physical system to implement an abstract machine. As Joslin observes, this approach neglects cases of software implementation—cases where one machine implements another by running a program. These cases, Joslin argues, highlight serious problems for mapping accounts of computer implementation—accounts that require a mapping between elements of a physical system and elements of an abstract machine. The source of these problems (...) is the complexity introduced by common design features of ordinary computers, features that would be relevant to any real-world software implementation. While Joslin is focused on contemporary views, his discussion also suggests a counterexample to recent mapping accounts which hold that genuine implementation requires simple mappings. In this paper, I begin by clarifying the nature of software implementation and disentangling it from closely related phenomena like emulation and simulation. Next, I argue that Joslin overstates the degree of complexity involved in his target cases and that these cases may actually give us reasons to favor simplicity-based criteria over relevant alternatives. Finally, I propose a novel problem for simplicity-based criteria and suggest a tentative solution. (shrink)

Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.

In addition to his famous Chinese Room argument, John Searle has posed a more radical problem for views on which minds can be understood as programs. Even his wall, he claims, implements the WordStar program according to the standard definition of implementation because there is some ‘‘pattern of molecule movements’’ that is isomorphic to the formal structure of WordStar. Program implementation, Searle charges, is merely observer-relative and thus not an intrinsic feature of the world. I argue, first, that analogous charges (...) involving other concepts (motion and meaning) lead to consequences no one accepts. Second, I show that Searle’s treatment of computation is incoherent, yielding the consequence that nothing computes anything: even our standard personal computers fail to run any programs on this account. I propose an alternative account, one that accords with the way engineers, programmers, and cognitive scientists use the concept of computation in their empirical work. This alternative interpretation provides the basis of a philosophical analysis of program implementation, one that may yet be suitable for a computational theory of the mind. (shrink)

Recently, Horsman et al. have proposed a new framework, Abstraction/Representation theory, for understanding and evaluating claims about unconventional or non-standard computation. Among its attractive features, the theory in particular implies a novel account of what is means to be a computer. After expounding on this account, I compare it with other accounts of concrete computation, finding that it does not quite fit in the standard categorization: while it is most similar to some semantic accounts, it is not itself a semantic (...) account. Then I evaluate it according to the six desiderata for accounts of concrete computation proposed by Piccinini. Finding that it does not clearly satisfy some of them, I propose a modification, which I call Agential AR theory, that does, yielding an account that could be a serious competitor to other leading account of concrete computation. (shrink)

Against Maudlin, I argue that machines which merely reproduce a pre-programmed series of changes ought to be classed with Turing’s O-Machines even if they would counterfactually show Turing Machine-like activity. This can be seen on an interventionist picture of computational architectures, on which basic operations are the primitive loci for interventions. While constructions like Maudlin’s Olympia still compute, then, claims about them do not threaten philosophical arguments that depend on Turing Machine architectures and their computational equivalents.

When Ken Malone investigates a case of something causing mental static across the United States, he is teleported to a world that doesn't exist.

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

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

If a brain is duplicated so that there are two brains in identical states, are there then two numerically distinct phenomenal experiences or only one? There are two, I argue, and given computationalism, this has implications for what it is to implement a computation. I then consider what happens when a computation is implemented in a system that either uses unreliable components or possesses varying degrees of parallelism. I show that in some of these cases there can be, in a (...) deep and intriguing sense, a fractional (non-integer) number of qualitatively identical phenomenal experiences. This, in turn, has implications for what lessons one should draw from neural replacement scenarios such as Chalmers. (shrink)

and apply it to various examples of neural plasticity in which input is rerouted intermodally or intramodally to nonstandard cortical targets. In some cases but not others, cortical activity ‘defers’ to the nonstandard sources of input. We ask why, consider some possible explanations, and propose a dynamic sensorimotor hypothesis. We believe that this distinction is important and worthy of further study, both philosophical and empirical, whether or not our hypothesis turns out to be correct. In particular, the question of how (...) the distinction should be explained is linked to explanatory gap issues for consciousness. Comparative and absolute explanatory gaps should be distinguished: why does neural activity in a particular area of cortex have this qualitative expression rather than that, and why does it have any qualitative expression at all? We use the dominance/deference distinction to address the comparative gaps, both intermodal and intramodal. We do so not by inward scrutiny but rather by expanding our gaze to include relations between brain, body and environment. (shrink)

The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s monograph, “Representation & Reality”, which if correct, has important implications for turing machine functionalism and the prospect (...) of ‘conscious’ machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that, “everything implements the specific machine Q on a particular input set ”. Then, equating Q to any putative AI program, I will show that conceding the ‘strong AI’ thesis for Q opens the door to a vicious form of panpsychism whereby all open systems,, must instantiate conscious experience and hence that disembodied minds lurk everywhere. (shrink)

Functionalism, which views consciousness as the product of the processing of stimuli by the brain, is perhaps the dominant view among researchers in the cognitive sciences and associated fields. However, as a workable scientific model of consciousness, it has been marred by a singular lack of tangible success, except at the broadest levels of explanation. This paper argues that this is not an accident, and that in its standard construal it is simply too unwieldy to assume the burden of full-fledged (...) theory. In its place, a reduced functionalism is introduced by applying the principle of parsimony successively to the elements of standard functionalism until only a minimal framework remains. This simpler account states that consciousness is a function of instantaneous causal relations between processing elements rather the putative algorithm such relations are instantiating. It is then argued as a corollary that the only such relations that matter are those in which reciprocal influences are at play. Thus, purely afferent and efferent causal relations are pruned from consideration. The theory resulting from the addition of this corollary is shown to have good correspondence with a number of recent neurophysiologically-motivated approaches to consciousness, including those that stress the importance of reentry, those that view synchrony as a key independent variable, and those that highlight the importance of the accessibility of conscious contents to multiple processing modules. In addition, the theory is shown to be consistent with recent results in the literature on masking, and those in the literature on binocular rivalry. The paper concludes by arguing that the theoretical and empirical difficulties inherent in consciousness research imply that the principle of parsimony must occupy a more central role in consciousness research than it would in ordinary scientific discourse. (shrink)

Oscar is going to be the first artificial person — at any rate, he is going to be the first artificial person to be built in Tucson's Philosophy Department. Oscar's creator, John Pollock, maintains that once Oscar is complete he will experience qualia, will be self-conscious, will have desires, fears, intentions, and a full range of mental states (Pollock 1989, pp. ix–x). In this paper I focus on what seems to me to be the most problematical of these claims, viz., (...) that Oscar will experience qualia. I argue that we have not been given sufficient reasons to believe this bold claim. I doubt that Oscar will enjoy qualitative conscious phenomena and I maintain that it will be like nothing to be Oscar. (shrink)