Yes,She Was!

Ford’s “Helen Keller Was Never in a Chinese Room” claims that my argument in “How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room” fails because Searle and I use the terms ‘syntax’ and ‘semantics’ differently, hence are at cross purposes. Ford has misunderstood me; this reply clarifies my theory.     

A Logical Hole in the Chinese Room

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.

A Logical Hole the Chinese Room Avoids

Searle’s Chinese room argument (CRA) was recently charged as being unsound because it makes a logical error. It is shown here that this charge is based on a misinterpretation of the modal scope of a major premise of the CRA and that the CRA does not commit the logical error with which it is charged.     

How Helen Keller used syntactic semantics to escape from a Chinese Room

A computer can come to understand natural language the same way Helen Keller did: by using “syntactic semantics”—a theory of how syntax can suffice for semantics, i.e., how semantics for natural language can be provided by means of computational symbol manipulation. This essay considers real-life approximations of Chinese Rooms, focusing on Helen Keller’s experiences growing up deaf and blind, locked in a sort of Chinese Room yet learning how to communicate with the outside world. Using the SNePS computational knowledge-representation system, the essay analyzes Keller’s belief that learning that “everything has a name” was the key to her success, enabling her to “partition” her mental concepts into mental representations of: words, objects, and the naming relations between them. It next looks at Herbert Terrace’s theory of naming, which is akin to Keller’s, and which only humans are supposed to be capable of. The essay suggests that computers at least, and perhaps non-human primates, are also capable of this kind of naming.

Searle��s wager

Nicholas Agar has recently argued that it would be irrational for future human beings to choose to radically enhance themselves by uploading their minds onto computers. Utilizing Searle’s argument that machines cannot think, he claims that uploading might entail death. He grants that Searle’s argument is controversial, but he claims, so long as there is a non-zero probability that uploading entails death, uploading is irrational. I argue that Agar’s argument, like Pascal’s wager on which it is modelled, fails, because the principle that we (or future agents) ought to avoid actions that might entail death is not action guiding. Too many actions fall under its scope for the principle to be plausible. I also argue that the probability that uploading entails death is likely to be lower than Agar recognizes.     

The logic of Searle’s Chinese room argument

John Searle’s Chinese room argument (CRA) is a celebrated thought experiment designed to refute the hypothesis, popular among artificial intelligence (AI) 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 (due to Sorensen), 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(s) of possibility that one reads into the logical formalism.Based on a paper presented at International Congress on Thought Experiments Rethought, Centre for Logic and Philosophy of Science, Ghent University, Belgium, 24–25 September 2004.     

Russell’s Structuralism and the Supposed Death of Computational Cognitive Science

John Searle believes that computational properties are purely formal and that consequently, computational properties are not intrinsic, empirically discoverable, nor causal; and therefore, that an entity’s having certain computational properties could not be sufficient for its having certain mental properties. To make his case, Searle’s employs an argument that had been used before him by Max Newman, against Russell’s structuralism; one that Russell himself considered fatal to his own position. This paper formulates a not-so-explored version of Searle’s problem with computational cognitive science, and refutes it by suggesting how our understanding of computation is far from implying the structuralism Searle vitally attributes to it. On the way, I formulate and argue for a thesis that strengthens Newman’s case against Russell’s structuralism, and thus raises the apparent risk for computational cognitive science too.

Meaning in Artificial Agents: The Symbol Grounding Problem Revisited

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.     

Using argument schemes for hypothetical reasoning in law

This paper studies the use of hypothetical and value-based reasoning in US Supreme-Court cases concerning the United States Fourth Amendment. Drawing upon formal AI & Law models of legal argument a semi-formal reconstruction is given of parts of the Carney case, which has been studied previously in AI & law research on case-based reasoning. As part of the reconstruction, a semi-formal proposal is made for extending the formal AI & Law models with forms of metalevel reasoning in several argument schemes. The result is compared with Rissland’s (1989) analysis in terms of dimensions and Ashley’s (2008) analysis in terms of his process model of legal argument with hypotheticals.     

Virtual Symposium on Virtual Mind

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 meaninguful 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.     

On the Behavior of True and False

Uzquiano (Analysis 70:39–44, 2010) showed that the Hardest Logic Puzzle Ever (HLPE) [in its amended form due to Rabern and Rabern (Analysis 68:105–112, 2008)] has a solution in only two questions. Uzquiano concludes his paper by noting that his solution strategy naturally suggests a harder variation of the puzzle which, as he remarks, he does not know how to solve in two questions. Wheeler and Barahona (J Philos Logic, to appear, 2011) formulated a three question solution to Uzquiano’s puzzle and gave an information theoretic argument to establish that a two question solution for Uzquiano’s puzzle does not exist. However, their argument crucially relies on a certain conception of what it means to answer self-referential yes–no questions truly and falsely. We propose an alternative such conception which, as we show, allows one to solve Uzquiano’s puzzle in two questions. The solution strategy adopted suggests an even harder variation of Uzquiano’s puzzle which, as we will show, can also be solved in two questions. Just as all previous solutions to versions of HLPE, our solution is presented informally. The second part of the paper investigates the prospects of formally representing solutions to HLPE by exploiting theories of truth.     

Semantic Dispositionalism, Idealization, and Ceteris Paribus Clauses

Kripke (Wittgenstein on rules and private language: an elementary exposition. Harvard University Press, Cambridge Mass, 1982) rejected a naturalistic dispositional account of meaning (hereafter semantic dispositionalism) in a skeptical argument about rule-following he attributes to Wittgenstein (Philosophical investigation. Basil Blackwell, Oxford, 1958). Most philosophers who oppose Kripke’s criticisms of semantic dispositionalism take the stance that the argument proves too much: semantic dispositionalism is similar to much of our respected science in some important aspects, and hence to discard the former would mean to give up the latter, which is obviously wrong. In this paper, I shall discuss and reject a recent defense of Kripke by Kusch (Analysis 65(2):156–163 2005; Sceptical guide to meaning and rules: defending Kripke’s Wittgenstein. McGill-Queen’s, London, 2006). Kusch attempts to show that semantic dispositionalism differs from the sciences, and consequently, Kripke’s attack can only target semantic dispositionalism, but not the sciences. Specifically, Kusch identifies some important features of the sciences with regard to how it employs idealization and ceteris paribus clauses, and argues that the ways in which semantic dispositionalism uses them are dramatically different. I argue that, upon close examination, the two are more similar than otherwise in each of those features.     

Inferences,suppositions and explanatory extensions in argument interpretation

We describe a probabilistic approach for the interpretation of user arguments that integrates three aspects of an interpretation: inferences, suppositions and explanatory extensions. Inferences fill in information that connects the propositions in a user’s argument, suppositions postulate new information that is likely believed by the user and is necessary to make sense of his or her argument, and explanatory extensions postulate information the user may have implicitly considered when constructing his or her argument. Our system receives as input an argument entered through a web interface, and produces an interpretation in terms of its underlying knowledge representation—a Bayesian network. Our evaluations show that suppositions and explanatory extensions are necessary components of interpretations, and that users consider appropriate the suppositions and explanatory extensions postulated by our system. This article integrates and extends research described in George et al., 2004; Zukerman et al., 2004; Zukerman and George, 2005; George et al., 2005. The research described in this article was conducted while Sarah George was employed at Monash University and was supported in part by the ARC Centre for Perceptive and Intelligent Machines in Complex Environments.     

Minds,machines and Searle

Abstract

Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic (computational) model of the mind. Nonsymbolic modeling turns out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem.     

Deliberative discourse and reasoning from generic argument structures

In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that these types of deliberation dialogues supported by the GAAM comply with criteria for normative principles for deliberation, specifically, Alexy’s rules for discourse ethics and Hitchcock’s Principles of Rational Mutual Inquiry. The connection of reasoning to the community in a documented and transparent structure assists in providing best justified reasons, principles of deliberation and ethical discourse which are important advantages for reasoning communities.     

A survey of recursive analysis and Moore’s notion of real computation

The theory of analog computation aims at modeling computational systems that evolve in a continuous space. Unlike the situation with the discrete setting there is no unified theory of analog computation. There are several proposed theories, some of them seem quite orthogonal. Some theories can be considered as generalizations of the Turing machine theory and classical recursion theory. Among such are recursive analysis and Moore’s class of recursive real functions. Recursive analysis was introduced by Turing (Proc Lond Math Soc 2(42):230–265, 1936), Grzegorczyk (Fundam Math 42:168–202, 1955), and Lacombe (Compt Rend l’Acad Sci Paris 241:151–153, 1955). Real computation in this context is viewed as effective (in the sense of Turing machine theory) convergence of sequences of rational numbers. In 1996 Moore introduced a function algebra that captures his notion of real computation; it consists of some basic functions and their closure under composition, integration and zero-finding. Though this class is inherently unphysical, much work have been directed at stratifying, restricting, and comparing it with other theories of real computation such as recursive analysis and the GPAC. In this article we give a detailed exposition of recursive analysis and Moore’s class and the relationships between them.     

Why Computers Can’t Feel Pain

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.     

On Covering Problems of Rado

T. Rado conjectured in 1928 that if ℱ is a finite set of axis-parallel squares in the plane, then there exists an independent subset ℐ⊆ℱ of pairwise disjoint squares, such that ℐ covers at least 1/4 of the area covered by ℱ. He also showed that the greedy algorithm (repeatedly choose the largest square disjoint from those previously selected) finds an independent set of area at least 1/9 of the area covered by ℱ. The analogous question for other shapes and many similar problems have been considered by R. Rado in his three papers (in Proc. Lond. Math. Soc. 51:232–264, 1949; 53:243–267, 1951; and J. Lond. Math. Soc. 42:127–130, 1968) on this subject. After 45 years, Ajtai (in Bull. Acad. Polon. Sci. Sér. Sci. Math. Astron. Phys. 21:61–63, 1973) came up with a surprising example disproving T. Rado’s conjecture. We revisit Rado’s problem and present improved upper and lower bounds for squares, disks, convex bodies, centrally symmetric convex bodies, and others, as well as algorithmic solutions to these variants of the problem.     

Seeing the point of politics: exploring the use of CSAV techniques as aids to understanding the content of political debates in the Scottish Parliament

Governments now recognise the potential for ICTs to improve the way in which they can engage with the population, whether conducting online consultations to elicit the people’s views on proposed policy, or disseminating information via websites. However, much of the information remains in text format, leaving the task of extracting data the viewer’s responsibility. This can be a daunting prospect, especially in the case of reports of parliamentary proceedings. In the past, Argument Visualisation techniques were used in training law students to render legal cases easier to comprehend; now, enhanced by all the advantages ICT has to offer, these techniques are employed to help make sense of thorny problems in academia and business. The possibility exists that such methods might also serve to clarify complex political issues of interest to the public. This paper describes an investigation into such a possibility. Two debates taken from the Scottish Parliament 2003 Autumn session were converted into argument visualisations and presented for comparison with the ‘Official Report’ to assess whether the visualisations offered any advantages over the textual alternative.     

Is presence a technology issue? Some insights from cognitive sciences

The International Society of Presence Research, defines “presence” (a shortened version of the term “telepresence”) as a “psychological state in which even though part or all of an individual’s current experience is generated by and/or filtered through human-made technology, part or all of the individual’s perception fails to accurately acknowledge the role of the technology in the experience” (ISPR 2000, The concept of presence: explication statement. Accessed 15 Jan 2009). In this article, we will draw on the recent outcomes of cognitive sciences to offer a broader definition of presence, not related to technology only. Specifically, presence is described here as a core neuropsychological phenomenon whose goal is to produce a sense of agency and control: subjects are “present” if they are able to enact in an external world their intentions. This framework suggests that any environment, virtual or real, does not provide undifferentiated information, ready-made objects equal for everyone. It offers different opportunities and produces presence according to its ability in supporting the users and their intentions. The possible consequences of this approach for the development of presence-inducing virtual environments are also discussed.