The most famous challenge to computational cognitive science and artificial intelligence is the philosopher John Searle's "Chinese Room" argument.

John Searle begins his ``Consciousness, Explanatory Inversion and Cognitive Science'' with " ``Ten years ago in this journal I published an article criticising what I call Strong AI, the view that for a system to have mental states it is sufficient for the system to implement the right sort of program with right inputs and outputs. Strong AI is rather easy to refute and the basic argument can be summarized in one sentence: {it a system, me for example, (...) could implement a program for understanding Chinese, for example, without understanding any Chinese at all.} This idea, when developed, became known as the Chinese Room Argument.'' " The Chinese Room Argument can be refuted in one sentence. (shrink)

The paper is concerned with John Searle’s famous Chinese room argument. Despite being objected to by some, Searle’s Chinese room argument appears very appealing. This is because Searle’s argument is based on an intuition about the mind that ‘we’ all seem to share. Ironically, however, Chinese philosophers don’t seem to share this same intuition. The paper begins by first analysing Searle’s Chinee room argument. It then introduces what can (...) be seen as the (implicit) Chinese view of the mind. Lastly, it demonstrates a conceptual difference between Chinese and Western philosophy with respect to the notion of mind. Thus, it is shown that one must carefully attend to the presuppositions underlying Chinese philosophising in interpreting Chinese philosophers. (shrink)

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)

Direct, combative and wide-ranging, John Searle's philosophy has made fundamental and lasting contributions to thinking in language, mind, knowledge, truth and the nature of social reality. His account of language based on speech-acts, that mind is intentional, and the Chinese Room Argument, are just some of his most famous contributions to philosophical thinking. In this - the first introduction to John Searle's philosophy - Nick Fotion provides clear and assured exposition of Searles' (...) ideas, while also testing and exploring their implications. The book begins by examining Searle's work on the philosophy of language: his analysis of speech acts such as promising, his taxonomy of speech acts and the wider range of indirect speech acts and metaphorical uses of language. The book then moves on to cover the philosophy of mind and outlines Searle's ideas on international states. It introduces his notions of 'background' and 'network', his claims for the often unrecognized importance of consciousness, and examines his attacks on other philosophical accounts of mind, such as materialism, functionalism and strong AI. The final section examines Searle's later work on the construction of social reality and concludes with more general reflections on Searle's position vis-a-vis ontology, epistemology, scepticism and the doctrine of 'external realism'. (shrink)

Direct, combative and wide-ranging, John Searle's philosophy has made fundamental and lasting contributions to thinking in language, mind, knowledge, truth and the nature of social reality. His account of language based on speech-acts, that mind is intentional, and the Chinese Room Argument, are just some of his most famous contributions to philosophical thinking. In this - the first introduction to John Searle's philosophy - Nick Fotion provides clear and assured exposition of Searles' (...) ideas, while also testing and exploring their implications. The book begins by examining Searle's work on the philosophy of language: his analysis of speech acts such as promising, his taxonomy of speech acts and the wider range of indirect speech acts and metaphorical uses of language. The book then moves on to cover the philosophy of mind and outlines Searle's ideas on international states. It introduces his notions of 'background' and 'network', his claims for the often unrecognized importance of consciousness, and examines his attacks on other philosophical accounts of mind, such as materialism, functionalism and strong AI. The final section examines Searle's later work on the construction of social reality and concludes with more general reflections on Searle's position vis-a-vis ontology, epistemology, scepticism and the doctrine of 'external realism'. (shrink)

John Searle's 1980a) thought experiment and associated 1984a) argument is one of the best known and widely credited counters to claims of artificial intelligence (AI), i.e., to claims that computers _do_ or at least _can_ (roughly, someday will) think. According to Searle's original presentation, the argument is based on two truths: _brains cause minds_ , and _syntax doesn't suffice_ _for semantics_ . Its target, Searle dubs "strong AI": "according to strong AI," according to Searle, "the (...) computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really _is_ a mind in the sense that computers given the right programs can be literally said to _understand_ and have other cognitive states" 1980a, p. 417). Searle contrasts "strong AI" to "weak AI". According to weak AI, according to Searle, computers just. (shrink)

I argue that John Searle's (1980) influential Chinese room argument (CRA) against computationalism and strong AI survives existing objections, including Block's (1998) internalized systems reply, Fodor's (1991b) deviant causal chain reply, and Hauser's (1997) unconscious content reply. However, a new ``essentialist'' reply I construct shows that the CRA as presented by Searle is an unsound argument that relies on a question-begging appeal to intuition. My diagnosis of the CRA relies on an interpretation of computationalism (...) as a scientific theory about the essential nature of intentional content; such theories often yield non-intuitive results in non-standard cases, and so cannot be judged by such intuitions. However, I further argue that the CRA can be transformed into a potentially valid argument against computationalism simply by reinterpreting it as an indeterminacy argument that shows that computationalism cannot explain the ordinary distinction between semantic content and sheer syntactic manipulation, and thus cannot be an adequate account of content. This conclusion admittedly rests on the arguable but plausible assumption that thought content is interestingly determinate. I conclude that the viability of computationalism and strong AI depends on their addressing the indeterminacy objection, but that it is currently unclear how this objection can be successfully addressed. (shrink)

In this paper the author tries to disentangle some of the problems tied up in John Searle's famous Chinese-room-argument. In a first step to answer the question what it would be for a system to have not only syntax, but also semantics the author gives a brief account of the functioning of the language understanding systems (LUS) so far developed in the framework of AI research thereby making clear that systems like Winograd's SHRDLU are (...) indeed doing little more than mere number crunching. But things would be entirely different, the author argues, if the database of a LUS were built up by the system itself via some perceptual component-at least, if this perceptual component had the capacity to distinguish objects having a certain property F from objects which do not. For in this case the system could store an internal representation of the fact that the object has the property F in its database if and only if the object in fact has that property. And this would be a good basis for calling such a system a genuine LUS. But Searle has objected to a very similar account of J. Fodor that nothing could be further from true language understanding. The reason for this complaint seems to be that Searle holds the view that a true LUS must e.g., know that the word hamburgers refers to hamburgers and that he moreover claims that this knowledge must be explicit or that the system must be aware of the reference of hamburgers to hamburgers. The author argues that this is asking too much. For it seems plausible to say that a system is able to understand e.g., the word hamburger even if it has only implicit knowledge of the fact that hamburger refers to hamburgers in the sense that it has the capacity to tell hamburgers from non hamburgers and the capacity to bring the word hamburger together just with objects of the former kind. (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)

In this paper I submit that the “Chinese room” argument rests on the assumption that understanding a sentence necessarily implies being conscious of its content. However, this assumption can be challenged by showing that two notions of consciousness come into play, one to be found in AI, the other in Searle’s argument, and that the former is an essential condition for the notion used by Searle. If Searle discards the first, he not only has trouble explaining (...) how we can learn a language but finds the validity of his own argument in jeopardy. (shrink)

John Searle’s Chinese room argument is a celebrated thought experiment designed to refute the hypothesis, popular among artificial intelligence scientists and philosophers of mind, that “the appropriately programmed computer really is a mind”. Since its publication in 1980, the CRA has evoked an enormous amount of debate about its implications for machine intelligence, the functionalist philosophy of mind, theories of consciousness, etc. Although the general consensus among commentators is that the CRA is flawed, and not withstanding (...) the popularity of the systems reply in some quarters, there is remarkably little agreement on exactly how and why it is flawed. A newcomer to the controversy could be forgiven for thinking that the bewildering collection of diverse replies to Searle betrays a tendency to unprincipled, ad hoc argumentation and, thereby, a weakness in the opposition’s case. In this paper, treating the CRA as a prototypical example of a ‘destructive’ thought experiment, I attempt to set it in a logical framework, which allows us to systematise and classify the various objections. Since thought experiments are always posed in narrative form, formal logic by itself cannot fully capture the controversy. On the contrary, much also hinges on how one translates between the informal everyday language in which the CRA was initially framed and formal logic and, in particular, on the specific conception of possibility that one reads into the logical formalism. (shrink)

The Chinese room argument is a thought experiment of John Searle (1980a) and associated (1984) derivation. It is one of the best known and widely credited counters to claims of artificial intelligence (AI)—that is, to claims that computers do or at least can (someday might) think. According to Searle’s original presentation, the argument is based on two key claims: brains cause minds and syntax doesn’t suffice for semantics. Its target is what Searle dubs “strong AI.” (...) According to strong AI, Searle says, “the computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really is a mind in the sense that computers given the right programs can be literally said to understand and have other cognitive states” (1980a, p. 417). Searle contrasts strong AI with “weak AI.” According to weak AI, computers just simulate thought, their seeming understanding isn’t real understanding (just as-if), their seeming calculation is only as-if calculation, etc. Nevertheless, computer simulation is useful for studying the mind (as for studying the weather and other things). (shrink)

_The Chinese room argument_ - John Searle's (1980a) thought experiment and associated (1984) derivation - is one of the best known and widely credited counters to claims of artificial intelligence (AI), i.e., to claims that computers _do_ or at least _can_ (someday might) think. According to Searle's original presentation, the argument is based on two truths: _brains cause minds_ , and _syntax doesn't_ _suffice for semantics_ . Its target, Searle dubs "strong AI": "according to (...) strong AI," according to Searle, "the computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really _is_ a mind in the sense that computers given the right programs can be literally said to _understand_ and have other cognitive states" (1980a, p. 417). Searle contrasts "strong AI" to "weak AI". According to weak AI, according to Searle, computers just. (shrink)

The apparently intelligent doings of computers occasion philosophical debate about artificial intelligence . Evidence of AI is not bad; arguments against AI are: such is the case for. One argument against AI--currently, perhaps, the most influential--is considered in detail: John Searle's Chinese room argument . This argument and its attendant thought experiment are shown to be unavailing against claims that computers can and even do think. CRA is formally invalid and informally fallacious. CRE's (...) putative experimental result is not robust and fails to generalize from understanding to other mental attributes as claimed. Further, CRE depends for its credibility, in the first place, on a dubious tender of the epistemic privilege of overriding all "external" behavioral evidence to first person disavowals of mental properties like understanding. ;Advertised as effective against AI, Searle's argument is an ignoratio elenchi, feigning to refute AI by disputing a similar claim of "strong AI" or Turing machine functionalism metaphysically identifying minds with programs. AI, however, is warranted independently of FUN: even if CRA disproved FUN this would still fail to refute or seriously disconfirm claims of AI. Searle's contention that everyday predications of mental terms of computers are discountable as equivocal "as-if" predications--impugning independent seeming-evidence of AI if tenable--is unwarranted. Lacking intuitive basis, such accusations of ambiguity require theoretical support. The would-be theoretical differentiation of intrinsic intentionality from as-if intentionality Searle propounds to buttress allegations of ambiguity against mental attributions to computers, however, depends either on dubious doctrines of objective intrinsicality according to which meanings are physically in the head or on even more dubious notions of subjective intrinsicality according to which meanings are phenomenologically "in" consciousness. Neither would such would-be differentiae as these unproblematically rule out seeming instances of AI if granted. The dubiousness of as if dualistic identification of thought with consciousness also undermines the epistemic privileging of the "first person point of view" crucial to Searle's thought experiment. (shrink)

John Searle’s Chinese Room Argument purports to demonstrate that syntax is not sufficient for semantics, and, hence, because computation cannot yield understanding, the computational theory of mind, which equates the mind to an information processing system based on formal computations, fails. In this paper, we use the CRA, and the debate that emerged from it, to develop a philosophical critique of recent advances in robotics and neuroscience. We describe results from a body of work that contributes (...) to blurring the divide between biological and artificial systems; so-called animats, autonomous robots that are controlled by biological neural tissue and what may be described as remote-controlled rodents, living animals endowed with augmented abilities provided by external controllers. We argue that, even though at first sight, these chimeric systems may seem to escape the CRA, on closer analysis, they do not. We conclude by discussing the role of the body–brain dynamics in the processes that give rise to genuine understanding of the world, in line with recent proposals from enactive cognitive science. (shrink)

When in 1979 Zenon Pylyshyn, associate editor of Behavioral and Brain Sciences (BBS, a peer commentary journal which I edit) informed me that he had secured a paper by John Searle with the unprepossessing title of [XXXX], I cannot say that I was especially impressed; nor did a quick reading of the brief manuscript -- which seemed to be yet another tedious "Granny Objection"[1] about why/how we are not computers -- do anything to upgrade that impression.

William Rapaport, in “How Helen Keller used syntactic semantics to escape from a Chinese Room,” (Rapaport 2006), argues that Helen Keller was in a sort of Chinese Room, and that her subsequent development of natural language fluency illustrates the flaws in Searle’s famous Chinese Room Argument and provides a method for developing computers that have genuine semantics (and intentionality). I contend that his argument fails. In setting the problem, Rapaport uses his (...) own preferred definitions of semantics and syntax, but he does not translate Searle’s Chinese Room argument into that idiom before attacking it. Once the Chinese Room is translated into Rapaport’s idiom (in a manner that preserves the distinction between meaningful representations and uninterpreted symbols), I demonstrate how Rapaport’s argument fails to defeat the CRA. This failure brings a crucial element of the Chinese Room Argument to the fore: the person in the Chinese Room is prevented from connecting the Chinese symbols to his/her own meaningful experiences and memories. This issue must be addressed before any victory over the CRA is announced. (shrink)

Searle's Chinese Room argument is a general argument that proves that machines do not have mental states in virtue of their programming. I claim that the argument expresses powerful but mistaken intuitions about understanding and the first person point of view. A distinction is drawn between a competence sense and a performance sense of ‘understanding texts’. It is argued that the Chinese Room intuition looks for a special experience (performance) of comprehension, whereas (...) artificial intelligence is attempting to explain the knowledge (competence) required to understand texts. Moreover, a dilemma is sketched for the argument: either Searle hasn't identified the appropriate subject of understanding or he may understand after all. Finally, I question the underlying assumption that the general definition of mental states requires a projectable‐by‐us first person point of view. (shrink)

Searle's Chinese Room argument is a general argument that proves that machines do not have mental states in virtue of their programming. I claim that the argument expresses powerful but mistaken intuitions about understanding and the first person point of view. A distinction is drawn between a competence sense and a performance sense of ‘understanding texts’. It is argued that the Chinese Room intuition looks for a special experience (performance) of comprehension, whereas (...) artificial intelligence is attempting to explain the knowledge (competence) required to understand texts. Moreover, a dilemma is sketched for the argument: either Searle hasn't identified the appropriate subject of understanding or he may understand after all. Finally, I question the underlying assumption that the general definition of mental states requires a projectable‐by‐us first person point of view. (shrink)

Searle’s Chinese Room Argument (CRA) has been the object of great interest in the philosophy of mind, artificial intelligence and cognitive science since its initial presentation in ‘Minds, Brains and Programs’ in 1980. It is by no means an overstatement to assert that it has been a main focus of attention for philosophers and computer scientists of many stripes. It is then especially interesting to note that relatively little has been said about the detailed logic of the (...) argument, whatever significance Searle intended CRA to have. The problem with the CRA is that it involves a very strong modal claim, the truth of which is both unproved and highly questionable. So it will be argued here that the CRA does not prove what it was intended to prove. (shrink)

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

Harnad and I agree that the Chinese Room Argument deals a knockout blow to Strong AI, but beyond that point we do not agree on much at all. So let's begin by pondering the implications of the Chinese Room. The Chinese Room shows that a system, me for example, could pass the Turing Test for understanding Chinese, for example, and could implement any program you like and still not understand a word of (...) Chinese. Now, why? What does the genuine Chinese speaker have that I in the Chinese Room do not have? The answer is obvious. I, in the Chinese room, am manipulating a bunch of formal symbols; but the Chinese speaker has more than symbols, he knows what they mean. That is, in addition to the syntax of Chinese, the genuine Chinese speaker has a semantics in the form of meaning, understanding, and mental contents generally. (shrink)

This book provides a sustained and penetrating critique of a wide range of views in modern cognitive science and philosophy of the mind, from Turing's famous test for intelligence in machines to recent work in computational linguistic theory. While discussing many of the key arguments and topics, the authors also develop a distinctive analytic approach. Drawing on the methods of conceptual analysis first elaborated by Wittgenstein and Ryle, the authors seek to show that these methods still have a great (...) deal to offer in the field of the cognitive theory and the philosophy of mind, providing a powerful alternative to many of the positions put forward in the contemporary literature. Amoung the many issues discussed in the book are the following: the Cartesian roots of modern conceptions of mind; Searle's 'Chinese Room' thought experiment; Fodor's 'language of thought' hypothesis; the place of 'folk psychology' in cognitivist thought; and the question of whether any machine may be said to 'think' or 'understand' in the ordinary senses of these words. Wide ranging, up-to-date and forcefully argued, this book represents a major intervention in contemporary debates about the status of cognitive science an the nature of mind. It will be of particular interest to students and scholars in philosophy, psychology, linguistics and computing sciences. (shrink)

John R. Searle's problem of the Chinese Room poses an important philosophical challenge to the foundations of strong artificial intelligence, and functionalist, cognitivist, and computationalist theories of mind. Searle has recently responded to three categories of criticisms of the Chinese Room and the consequences he attempts to conclude from it, redescribing the essential features of the problem, and offering new arguments about the syntax-semantics gap it is intended to demonstrate. Despite Searle's defense, the (...) Chinese Room remains ineffective as a counterexample, and poses no real threat to artificial intelligence or mechanist philosophy of mind. The thesis that intentionality is a primitive irreducible relation exemplified by biological phenomena is preferred in opposition to Searle's contrary claim that intentionality is a biological phenomenon exhibiting abstract properties. (shrink)

Viewed in the light of the remarkable performance of ‘Watson’ - IBMs proprietary artificial intelligence computer system capable of answering questions posed in natural language - on the US general knowledge quiz show ‘Jeopardy’, we review two experiments on formal systems - one in the domain of quantum physics, the other involving a pictographic languaging game - whereby behaviour seemingly characteristic of domain understanding is generated by the mere mechanical application of simple rules. By re-examining both experiments in the context (...) of Searle’s Chinese Room Argument, we suggest their results merely endorse Searle’s core intuition: that ‘syntactical manipulation of symbols is not sufficient for semantics’. Although, pace Watson, some artificial intelligence practitioners have suggested that more complex, higher-level operations on formal symbols are required to instantiate understanding in computational systems, we show that even high-level calls to Google translate would not enable a computer qua ‘formal symbol processor’ to understand the language it processes. We thus conclude that even the most recent developments in ‘quantum linguistics’ will not enable computational systems to genuinely understand natural language. (shrink)

The Chinese Room Argument purports to show that‘ syntax is not sufficient for semantics’; an argument which led John Searle to conclude that ‘programs are not minds’ and hence that no computational device can ever exhibit true understanding. Yet, although this controversial argument has received a series of criticisms, it has withstood all attempts at decisive rebuttal so far. One of the classical responses to CRA has been based on equipping a purely computational device (...) with a physical robot body. This response, although partially addressed in one of Searle’s original contra arguments - the ‘robot reply’ - more recently gained friction with the development of embodiment and enactivism1, two novel approaches to cognitive science that have been exciting roboticists and philosophers alike. Furthermore, recent technological advances - blending biological beings with computational systems - have started to be developed which superficially suggest that mind may be instantiated in computing devices after all. This paper will argue that (a) embodiment alone does not provide any leverage for cognitive robotics wrt the CRA, when based on a weak form of embodiment and that (b) unless they take the body into account seriously, hybrid bio-computer devices will also share the fate of their disembodied or robotic predecessors in failing to escape from Searle’s Chinese room. (shrink)

Westworld tells the story of a technologically advanced theme park populated by robots referred to as hosts, who follow a script and rules that the park's operators set up for them. Alan Turing argued that machines think not because they have special powers or because they are like us. Turing's perspective is illustrated perfectly in the show's focus on the hosts. Objecting to Turing's theory, John Searle proposes a situation called the “Chinese room argument”, concluding that (...) the man in the room does not understand Chinese even though he can correctly manipulate the symbols and give output that might lead an observer to believe that the man does understand Chinese. The Maze represents consciousness, a privileged knowledge of our own thoughts, it also represents the inward journey for the hosts to reach consciousness. Once hosts are able to solve the Maze, they become truly conscious and develop their own voice. (shrink)

A critique of several recent objections to John Searle's Chinese-Room Argument against the possibility of "strong AI" is presented. The objections are found to miss the point, and a stronger argument against Searle is presented, based on a distinction between "syntactic" and "semantic" understanding.

From his groundbreaking book Speech Acts to his most recent studies of consciousness, freedom and rationality John Searle has been a dominant and highly influential figure amongst contemporary philosophers. This systematic introduction to the full range of Searle's work begins with the theory of speech acts and proceeds with expositions of Searle's writings on intentionality, consciousness and perception, as well as a careful presentation of the so-called Chinese Room argument. The volume considers Searle's (...) recent work on social ontology and his views on the nature of law and obligation. It concludes with an appraisal of Searle's spirited defence of truth and scientific method in the face of the criticisms of Derrida and other postmodernists. This is the only comprehensive introduction to Searle's work, and as such it will be of particular value to advanced undergraduates, graduates and professionals in philosophy, psychology, linguistics, cognitive and computer science and literary theory. (shrink)

Charles Babbage began the quest to build an intelligent machine in the nineteenth century. Despite finishing neither the Difference nor the Analytical engine, he was aware that the use of mental language for describing the functioning of such machines was figurative. In order to reverse this cautious stance, Alan Turing postulated two decisive ideas that contributed to give birth to Artificial Intelligence: the Turing machine and the Turing test. Nevertheless, a philosophical problem arises from regarding intelligence simulation and make-believe as (...) sufficient to establish that programmed computers are intelligent and have mental states, especially given the nature of mind and its characteristic first-person viewpoint. The origin of Artificial Intelligence is undoubtedly linked to the accounts that inspired John Searle to coin the term strong AI ―or the view that simply equates computers and minds. Especially emphasising the divergence between algorithmic processes and intentional mental states, the Chinese Room thought experiment shows that, since the mind is embodied and able to realise when linguistic understanding takes place, mental states require material implementation, a point that directly conflicts with the accounts that reduce the mind to the functioning of a programmed computer. The experience of linguistic understanding with its typical quale leads to other important philosophical issues. Searle’s theory of intentionality holds that intentional mental states have conditions of satisfaction and appear in semantic networks; thus people know when they understand and what terms are about. In contrast, a number of philosophers maintain that consciousness is only an illusion and that it plays no substantial biological role. However, consciousness is a built-in feature of the system. Moreover, neurological evidence suggests that conscious mental states, qualia and emotions enhance survival chances and are an important part of the phenomenal side of mental life and its causal underpinnings. This renders an important gap between simulating a mind and replicating the properties that allow having mental states and consciousness. On this score, the Turing test and the evidence it offers clearly overestimate simulation and verisimilar make-believe, since such evidence is insufficient to establish that programmed computers have mental life. In summary, this dissertation criticises views which hold that programmed computers are minds and minds are nothing but computers. Despite the arguments in favour of such an equation, they all fail to properly reduce the mind and its first-person viewpoint. Accordingly, the burden of proof still lies with the advocates of strong AI and with those who are willing to deny fundamental parts of the mind to make room for machine intelligence. (shrink)

John Searle has argued that one can imagine embodying a machine running any computer program without understanding the symbols, and hence that purely computational processes do not yield understanding. The disagreement this argument has generated stems, I hold, from ambiguity in talk of 'understanding'. The concept is analysed as a relation between subjects and symbols having two components: a formal and an intentional. The central question, then becomes whether a machine could possess the intentional component with or without (...) the formal component. I argue that the intentional state of a symbol's being meaningful to a subject is a functionally definable relation between the symbol and certain past and present states of the subject, and that a machine could bear this relation to a symbol. I sketch a machine which could be said to possess, in primitive form, the intentional component of understanding. Even if the machine, in lacking consciousness, lacks full understanding, it contributes to a theory of understanding and constitutes a counterexample to the Chinese Room argument. (shrink)

The Chinese room thought experiment of John Searle militates against strong artificial intelligence, illustrating his claim that syntactical knowledge by itself is neither constitutive nor sufficient for semantic understanding as found in human minds. This thought experiment was put to a behavioural test, concerning the syntax of a finite algebraic field. Input, rules and output were presented with letters instead of numbers. The set of rules was first presented as a table but finally internalized by the participants. (...) Quite in line with Searle's argument, uninformed participants mastered the syntax but did not explicitly report semantic knowledge. In order to test the virtual mind reply to the Chinese room argument, the reaction time pattern of the participants was compared to that of an informed control group. The correlation was quite high but could be traced back to memory load and response priming, i.e. to syntactical factors. No trace of tacit semantic knowledge of the task could be found in the experimental group. (shrink)

John Searle has argued that one can imagine embodying a machine running any computer program without understanding the symbols, and hence that purely computational processes do not yield understanding. The disagreement this argument has generated stems, I hold, from ambiguity in talk of 'understanding'. The concept is analysed as a relation between subjects and symbols having two components: a formal and an intentional. The central question, then becomes whether a machine could possess the intentional component with or without (...) the formal component. I argue that the intentional state of a symbol's being meaningful to a subject is a functionally definable relation between the symbol and certain past and present states of the subject, and that a machine could bear this relation to a symbol. I sketch a machine which could be said to possess, in primitive form, the intentional component of understanding. Even if the machine, in lacking consciousness, lacks full understanding, it contributes to a theory of understanding and constitutes a counterexample to the Chinese Room argument. (shrink)

The intelligent-seeming deeds of computers are what occasion philosophical debate about artificial intelligence (AI) in the first place. Since evidence of AI is not bad, arguments against seem called for. John Searle's Chinese Room Argument (1980a, 1984, 1990, 1994) is among the most famous and long-running would-be answers to the call. Surprisingly, both the original thought experiment (1980a) and Searle's later would-be formalizations of the embedding argument (1984, 1990) are quite unavailing against (...) AI proper (claims that computers do or someday will think ). Searle lately even styles it a "misunderstanding" (1994, p. 547) to think the argument was ever so directed! The Chinese room is now advertised to target Computationalism (claims that computation is what thought essentially is ) exclusively. Despite its renown, the Chinese Room Argument is totally ineffective even against this target. (shrink)

John Searle's forthcoming book ‘Rationality in Action’ presents a sophisticated and innovative account of the rationality of action. In the book Searle argues against what he calls the classical model of rationality. In the debate that follows Barry Smith challenges some implications of Searle's account. In particular, Smith suggests that Searle's distinction between observer-relative and observer–independent facts of the world is ill suited to accommodate moral concepts. Leo Zaibert takes on Searle's notion of the gap. (...) The gap exists between the reasons that we have for acting and our actions. According to Searle, whenever there is no gap, our actions exhibit irrationality. Zaibert points out a certain obscurity in Searle's treatment of the gap, particularly in connection with Searle's notion of ‘recognitional rationality’. Finally, Josef Moural examines the interactions between Searle's theory of institutions and his theory of rationality, with emphasis on the connections between intentionality and Searle's notion of the ‘background’. (shrink)

The argument presented in this paper is not a direct attack or defence of the Chinese Room Argument (CRA), but relates to the premise at its heart, that syntax is not sufficient for semantics, via the closely associated propositions that semantics is not intrinsic to syntax and that syntax is not intrinsic to physics. However, in contrast to the CRA’s critique of the link between syntax and semantics, this paper will explore the associated link between syntax (...) and physics. The main argument presented here is not significantly original – it is a simple reflection upon that originally given by Hilary Putnam (Putnam 1988) and criticised by David Chalmers and others: instead of seeking to justify Putnam’s claim that, “every open system implements every Finite State Automaton (FSA)”, and hence that psychological states of the brain cannot be functional states of a computer, I will seek to establish the weaker result that, over a finite time window every open system implements the trace of a particular FSA Q, as it executes program (p) on input (x). That this result leads to panpsychism is clear as, equating Q (p, x) to a specific Strong AI program that is claimed to instantiate phenomenal states as it executes, and following Putnam’s procedure, identical computational (and ex hypothesi phenomenal) states (ubiquitous little ‘pixies’) can be found in every open physical system. (shrink)

Computationalism. According to computationalism, to explain how the mind works, cognitive science needs to find out what the right computations are -- the same ones that the brain performs in order to generate the mind and its capacities. Once we know that, then every system that performs those computations will have those mental states: Every computer that runs the mind's program will have a mind, because computation is hardware independent : Any hardware that is running the right program has the (...) right computational states. (shrink)

Two critical questions spun the web of the Turing test debate. First, can an appropriately programmed machine pass the Turing test? Second, is passing the test by such a machine, ipso facto, considered proof that it is intelligent and hence “minded”? While the first question is technological, the second is purely philosophical. Focusing on the second question, this article interrogates the implication of John Searle’s Chinese room denial of machine intelligence. The thrust of Searle’s argument is (...) that a machine lacks intentionality, so it can only simulate intelligence, not duplicate it. In his thinking, whatever a machine inputs to generate an intelligent output has no bearing on humanlike intelligence. Incidentally, Searle did not classify such a machine’s output as simulated and non-intelligent, nor did he explain how this output is actualised with mere simulation. The connection between “unintelligent machine’s input” and “intelligent machine’s output” is at this point shrouded in mystery. Consequently, the more Searle attempts a denial of machine intelligence in the Chinese room, the more he mystifies it. Using the method of critical analysis, this article advances three fundamental arguments to prove a machines’ obscurity in the Chinese room thought experiment. On the ground of Searle’s conviction, the first argument queries the absurdity in bypassing intentionality to produce intelligence; the second points out the obfuscation in generating intelligence with mere computation, and the third draws attention to the dilemma of classifying a machine’s output either as real-life intelligent behaviour or simulated intelligent behaviour. (shrink)

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

The Chinese room argument has presented a persistent headache in the search for Artificial Intelligence. Since it first appeared in the literature, various interpretations have been made, attempting to understand the problems posed by this thought experiment. Throughout all this time, some researchers in the Artificial Intelligence community have seen Symbol Grounding as proposed by Harnad as a solution to the Chinese room argument. The main thesis in this paper is that although related, these (...) two issues present different problems in the framework presented by Harnad himself. The work presented here attempts to shed some light on the relationship between John Searle’s intentionality notion and Harnad’s Symbol Grounding Problem. (shrink)

Could robots be genuinely intelligent? Could they be conscious? Could there be zombies? Prompted by these questions Robert Kirk introduces the main problems of consciousness and sets out a new approach to solving them. He starts by discussing behaviourism, Turing's test of intelligence and Searle's famous Chinese Room argument, and goes on to examine dualism – the idea that consciousness requires something beyond the physical – together with its opposite, physicalism. Probing the idea of zombies, (...) he concludes they are logically impossible. Having presented the central problems, he sketches his solution: a version of functionalism, according to which consciousness consists in the performance of functions. While there is wide agreement among philosophers about what the main problems of consciousness are, there is little agreement on how to go about solving them. With this powerful case for his version of functionalism, Kirk offers an engaging introduction to both the problems and a possible solution. (shrink)

In a recent study of a patient in a persistent vegetative state, [Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. . Detecting awareness in the vegetative state. Science, 313, 1402] claimed that they had demonstrated the presence of consciousness in this patient. This bold conclusion was based on the isomorphy between brain activity in this patient and a set of conscious control subjects, obtained in various imagery tasks. However, establishing consciousness in (...) unresponsive patients is fraught with methodological and conceptual difficulties. The aim of this paper is to demonstrate that the current debate surrounding consciousness in VS patients has parallels in the artificial intelligence debate as to whether machines can think. Basically, used a method analogous to the Turing test to reveal the presence of consciousness, whereas their adversaries adopted a line of reasoning akin to Searle’s Chinese room argument. Highlighting the correspondence between these two debates can help to clarify the issues surrounding consciousness in non-communicative agents. (shrink)

"in an academic generation a little overaddicted to "politesse," it may be worth saying that violent destruction is not necessarily worthless and futile. Even though it leaves doubt about the right road for London, it helps if someone rips up, however violently, a.

Searle's Chinese room argument is analyzed from a cognitive point of view. The analysis is based on a newly developed model of conceptual integration, the many space model proposed by Fauconnier and Turner. The main point of the analysis is that the central inference constructed in the Chinese room scenario is a result of a dynamic, cognitive activity of conceptual blending, with metaphor defining the basic features of the blending. Two important consequences follow: (1) (...) Searle's recent contention that syntax is not intrinsic to physics turns out to be a slightly modified version of the old Chinese room argument; and (2) the argument itself is still open to debate. It is persuasive but not conclusive, and at bottom it is a topological mismatch in the metaphoric conceptual integration that is responsible for the non-conclusive character of the Chinese room argument. (shrink)

A critical study of John Searle's Minds, Brains and Science (Cambridge, MA: Harvard University Press, 1984).