Advocates of Artificial Intelligence as Behaviourists

In extremely general terms, it can said that behaviourism was a response to the Cartesian (or, even more widely, Western) philosophical tradition in which behaviour, actions, and what is done by persons was seen as the outward expression of what goes on in the mind. Thus, in that sense, many of those who were initially involved in artificial intelligence (AI) were following in behaviourism's footsteps in that they believed that if a computer (or robot) behaved as if it had intelligence (or had a mind), then, almost by definition, it must actually be intelligent (or have a mind).

Many other currents in post-World War Two philosophy played-down the innards of the mind and, consequently, played-up behaviour. We had the work of the late Wittgenstein in which private mental states were seen as nothing more than "beetles in boxes". We also had Gilbert Ryle's The Concept of Mind and Quine saying that all there is to meaning is “overt behaviour”. And then functionalism (in the philosophy of mind) followed all that.

Specifically in terms of AI: it can fairly safely be said that many of the defenders of AI denied (or simply played-down) the distinction between actions (or behaviour) and what's supposed to be “behind” action (or behaviour). Thus if that "binary opposition" is rejected, then all we have to go on are the actions (or behaviour) of computers. And if computers pass the Turning test, then they're intelligent. Full stop. Indeed it's only a few behavioural steps forward from this to argue that computers actually have minds.

Of course if we follow this line to the letter, then it can be said that Zombies also have minds; as well as consciousness. And a thermostat has a little bit of a mind too.

If you think my last inclusion of a thermostat is ridiculous, then here's John Searle talking about the inventor of the term "artificial intelligence", John McCarthy. Searle writes:

“McCarthy says 'even a machine as simple as a thermostat can be said to have beliefs.' I admire McCarthy's courage. I once asked him 'What beliefs does your thermostat have?' And he said 'My thermostat has three beliefs – it believes it's too hot in here, it's too cold in here, and it's just right in here.'...” (1984)

Weak and Strong AI

This is where the distinction between strong and weak AI comes into play.

Weak AI proponents argue that it's unquestionably the case that some computers (or all computers?) act as if they're intelligent (or have minds). Though the operative words here are “as if”. Thus, they continue, it may take a little bit more time to develop computers which have "genuine intelligence" (whatever that is) or have minds. In other words, there has to be more than behaviour (or actions) to intelligence or mind.

Alan Turing himself put the weak AI position when he argued that it doesn't matter if a machine has a mind in the human sense: what matters is whether or not it can act in the way that human beings act – i.e. intelligently. (In those days that basically meant answering questions and solving mathematical problems.) In fact that was the crux of the Turing test which resulted in the Dartmouth proposal. Namely:

"Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it." (1955)

John Searle states the strong AI hypothesis (with all its behaviourist trappings) in the following way:

“The other minds reply (Yale). 'How do you know that other people understand Chinese or anything else? Only by their behaviour. Now the computer can pass the behavioural tests as well as they can (in principle), so if you are going to attribute cognition to other people you must in principle also attribute it to computers.'...” (1980)

Strong AI bites the bullet and denies the distinction between behaviour and mind/intelligence: 

If a computer acts (or behaves) as if it's intelligent (or has a mind), then it is intelligent (or has a mind). 

In other words, even though I've just written the words “as if”, there's no actual as if about it.

So why worry our pretty little heads about what must lie behind these expressions of mind or intelligence? In true behaviourist fashion, all we really need (or have!) is behaviour.

Sentience and Sapience

When it's said that there's no way that we can know (or tell) that a computer is sentient, it seems incredible. This is usually said about animals or even about other human beings. However, logically the same thing can indeed be said about computers; though, admittedly, not with the same force or implications.

Of course other human beings can tell us that they're sentient (even if they don't use the words “I'm sentient”). Animals, on the other hand, can hint (as it were) at their sentience. Then again, it's also possible that a future computer could do the same.

So let's get a little but more concrete about all this. 

I just mentioned that the display of intelligence (or mind) is deemed to be intelligence (or mind). And computers certainly display intelligence. For example, computers can solve problems, play games (e.g., chess), prove mathematical theorems, diagnose medical problems, use language and so on. What more do we want?

All these things are undoubtedly displays of intelligence; though are they also displays of mind? However, just as I mentioned the mind-behaviour binary opposition; so we have the intelligence-mind opposition too. That means we can construct an argument which takes us from behaviour to intelligence; and then from intelligence to mind. Thus:

         i) If a computer behaves intelligently,

        ii) then it is intelligent.
       iii) If computer is intelligent,
        v) then it must have a mind.

Prima facie, it does seem to be the case that when other people do intelligent things, then we (as good behaviourists) say that they're intelligent; whereas when the same actions are done by a computer it rarely evokes the same response (or, at the least, not exactly the same kind of response). After all, doesn't winning a game of chess match, etc. most people's criteria of a genuine display of intelligence?

References

Searle, John. (1984) Mind, Brains and Science. London: BBC Publications.

-- (1980) 'Minds, Brains, and Programs'. Behavioural and Brain Sciences 3.
J. McCarthy, M. L. Minsky, N. Rochester, C.E. Shannon. (1955) 'A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence'

Holisms (2) – Donald Davidson

We have many versions of semantic holism in the philosophy of language and the philosophy of thought.

Take Donald Davidson.

Davidson believed that the

“account of the truth-conditions for any one sentence is systematically related to the account of the truth-conditions for a whole range of other sentences”.

(We can now ask: How large must this range of other sentences be?)

We can clarify Davidson’s semantic holism in terms of the systematicity of a concept-expression and its possession. As Michael Luntley puts it:

“The axiom governing any single concept expression does not itself specify the meaning of the expression; it does so only in the context of an overall theory that employs that axiom in a systematic manner to compute the meaning of whole sentences in which the concept expression figures.” (1999)

The starting point of Davidson’s theory is Frege’s Context Principle in which the meaning of an expression is determined by its context and place within a truth-valued sentence. Davidson extends Frege’s Context Principle to include other sentences in which the said expression occurs. It's from this group of sentences (large or small) that we can compute the expression’s meaning within the context of an overall theory.

We also have a well-known statement from Davidson on meaning-holism that's sometimes taken as a criticism of holism; though, at other times, simply taken as an explanation of the phenomenon.

In his paper, ‘Truth and Meaning’, Davidson writes:

“If sentences depend for their meaning on their structure, and we understand the meaning of each item in the structure only as an abstraction from the totality of sentences in which it features, then we can give the meaning of any sentence (or word) only by giving the meaning of every sentence (and word) in the language.” (1967)

This may not mean that the individual speaker (or thinker) need understand (or know) every word and sentence in the language at the moment of his understanding: only that in effect the meaning of a word or sentence is ultimately determined by - and depends upon - the entire language (regardless of the complete understanding of the individual speaker or thinker).

For example, the possible moves in a game of chess are finite though very large. It needn't be the case that the individual chess-player understands (or knows) all the possible moves in the game of chess in order to make a single move (or understand the rules of chess generally).

The same with definitions.

There will come a time that the indefinite regress of definitions (or definitions of definitions) will come to end when the original definiendum comes back on the scene. However, it doesn't follow that the individual speaker (or thinker) need go through this indefinite regress in order to use (or understand) the word under definition - even if an indefinite regress is entailed by the original definition.

The individual speaker (or thinker) needs to begin somewhere; just as the epistemologist won't attempt to justify all his premises in an argument of justification. Even the semantic sceptic needs Wittgenstein’s ‘hinges’ to turn on in order to get his sceptical show on the road.

References

Davidson, Donald, 'Truth and Meaning' (1967)

Luntley, Michael, Contemporary Philosophy of Thought: Truth, World, Content (1999).

Holisms (1)

We can find non-semantic holisms in various areas of philosophy. For example, here's Christopher Peacocke giving an account of what may be called thing holism:

“Sometimes, perhaps always, a thing (property, relation) is individuated in part by its relations to other things, properties or relations.” (243)

Peacocke then goes into detail about what can also be called locational holism. He writes:

“First, what it is to be a particular place cannot be explained without mentioning the network of spatial relations in which the place stands.” (243)

This is why many philosophical atomists have been suspicious of holism/s in that if all an object (or word’s) relations are constitutive of its identity (or meaning), then such relations will be indefinite - if not infinite - in number. Thus, in order to identify an object (or understand a word) we'd have to take into account the whole universe (or every single other word in the language) in order to do so. In that case, we're not too far from the 19th century idealist’s Absolute.

An individual speaker or thinker needn't understand or know every word that has a definitional relation to the word he's thinking or speaking about. Similarly with holism about objects. In order to successfully identify, locate or individuate an object, we simply don't to identify or know all its relations (or relational properties) - even if such things are indeed indefinite - or even infinite - in number.

In the first case of holism about language: we have a question about the individual speaker or thinker and then another question about the language itself. Similarly with the person who identifies an object. At first we have a question concerning the way in which he identifies the object (in a single act of identification) and then we have a further question as to the entire set of relations (or relational properties) which the identified object may or may not possess. In both the language and object cases, the situation of the subject and the language or object as they are in themselves are different matters which shouldn't be confused.

Reference

Peacocke, Christopher, 'Holism' (1999), in A Companion to the Philosophy of Language, edited by Bob Hale and Crispin Wright.