Minds and Computers : An Introduction to the Philosophy of Artificial Intelligence
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Exercise 10.1
Construct unsound arguments against computationalism which trade on the other possible misconceptions we have considered. In each case, explain why the argument is unsound. If there is a false premise (attributing a claim to the computationalist) explain why the premise is false in light of a correct understanding of computationalism. If there is an invalid inference in the argument, give a counter-example to the validity of the logical form employed and explain how a particular misconception would lead one to believe that the argument instances a valid form. 10.2 SOFTWARE AND WETWARE Computationalism is often described as a ‘software’ view of the mind. The human brain is seen as providing the biological computational hardware – or wetware – which confers on humans the capacity to have a mind. Having a mind, on this view, is a matter of having the right program running in one’s wetware. This provides us with a solid methodological framework for investi- gating mentality. What we should be interested in, if computationalism 99 is correct, is determining the program(s) for various kinds of mental processes with a view to building up [MIND]. Computationalism has been widely embraced in the cognitive dis- ciplines and plays a large role in informing research programmes. Each of the empirical cognitive disciplines approaches the overarch- ing goal of investigating mentality in distinct fashion, commensurate with their disciplinary methods and assumptions. In each case, how- ever, a commitment to computationalism confers a broad methodol- ogy for pursuing these questions. Researchers who endorse the computational hypothesis will aim to deliver accounts which are in principle computationally implementable. That is to say, they will aim to develop accounts of mental processes as e ffective procedures. Very often, this will involve collaboration with computer scientists in devel- oping computational models of mental phenomena. This methodology has sparked o ff the research tradition known as artificial intelligence. There are weaker and stronger interpretations of ‘artificial intelligence’. The weak artificial intelligence research pro- gramme simply involves aiming to construct artefacts capable of instantiating particular functions which are held to be (albeit weakly) constitutive of intelligence. This is the kind of ‘artificial intelligence’ which is often used to sell white goods. The strong artificial intelligence research programme is of signifi- cantly more interest and of central concern in this volume. It commits to, and pursues, the possibility of developing artefacts which have minds in the sense that we take ourselves to have minds. There are certain mental capacities which appear to be unique to human minds. These include the ability to reason complexly and abstractly about such things as mathematics, logic and metaphysics, and the ability to use language. Both the rational capacity and the lin- guistic capacity implicate a number of what we might call lower-order cognitive processes, such as the abilities to discriminate, to learn and to remember. These lower-order processes are achieved to a greater or lesser extent by other animals. The higher-order cognitive functions of abstract reasoning, language production and language compre- hension, however, are uniquely human and, as such, will serve for our purposes as prime determinants of the kind of intelligence we attribute to humans. Consequently, in the following chapters, we are going to concen- trate on various methods of attempting to develop computational devices with rational and linguistic capacities. We will also have much more to say about the conditions under which we might attribute mentality to an artefact in the final section 100 of this chapter when we discuss the Turing test. Before we get to that, however, there is more to be said here about computationalism. To begin with, we can draw out some advantages of computationalism from our discussion so far. Firstly, and most obviously, computationalism fleshes out the func- tionalist framework. Recall from Chapter 6 that we found the functionalist account somewhat wanting as a ‘black box’ view of mentality. Computationalism tells us what is going on inside the black box, namely computation. Consequently, computationalism confers a clear methodology for investigating mentality – we should be aiming to provide computational accounts of cognitive capacities. Secondly, computationalism allows us to specify the relation between the mind and the brain by employing a useful wetware/soft- ware distinction. On this view, minds are what brains do. In other words, brains provide the computational resources to run [MIND]. We might also note at this point, that computationalism retains the substrate independence which functionalist theories enjoy and, con- sequently, is compatible with a purely material view of the mind without falling prey to either the multiple realisability objections which frustrate Australian materialism or the methodological vacu- ousness of token physicalism. Computationalism, then, appears to enjoy the strengths of other theories of mind without being subject to the worst of their weak- nesses. There are, however, a number of objections which we might mount against the view that all mental operations are computations. In the following sections, I will consider a number of prima facie objections – the kind typically raised against computationalism on first presentation. In each case, I will demonstrate how a computa- tionalist might defend the theory against the objection in question. We will leave consideration of more sophisticated philosophical argu- ments against computationalism until Chapters 17 and 18. 10.3 VARIATION The objection from variation runs as follows. Computationalism says that humans have minds by virtue of implementing [MIND], but human minds vary greatly. How can this be, given all minds are held to be isomorphisms of the same formal system? It is certainly the case that there is considerable variation among individual minds. We all have di fferent beliefs, desires, emotional responses and mental capacities. A computationalist will, of course, admit this – to deny it would be foolishness. This does not answer the 101 objection, however. To do so requires further reflection on the notion of isomorphism. Formal systems involve variables which are assigned values in any Download 1.05 Mb. Do'stlaringiz bilan baham: |
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