Reith Lectures 1984 - John Searle: Minds, Brains and Science - part 2

Mental processes are caused by the behaviour of elements of the brain.

McCarthy says even a machine as simple as a thermostat can be said to have beliefs.

In my last lecture, I provided at least the outlines of a solution to the so-called ‘mind- body problem’.

In my last lecture, I provided at least the outlines of a solution to the so-called ‘mind- body problem’.

I think it’s important to emphasise that, because in these discussions the temptation is always to think that the solution to our problems must wait on some as yet uncreated technological wonder.

In my last lecture, I provided at least the outlines of a solution to the so-called ‘mind- body problem’.

I think it’s important to emphasise that, because in these discussions the temptation is always to think that the solution to our problems must wait on some as yet uncreated technological wonder.

Understanding a language, or, indeed, having mental states at all, involves more than having just formal symbols.

There’s more to having a mind than having formal or syntactical processes.

Mental processes are caused by the behaviour of elements of the brain.

And the argument has a very simple logical structure, so you can see whether it’s valid or invalid.

Now, I think this answer is consistent with standard biological approaches to biological phenomena.

Now, I think this answer is consistent with standard biological approaches to biological phenomena.

Now, I think this answer is consistent with standard biological approaches to biological phenomena.

Now, I think this answer is consistent with standard biological approaches to biological phenomena.

However, it’s very much a minority point of view.

The prevailing view in philosophy, psychology and artificial intelligence is one which emphasises the analogies between the functioning of the human brain and the functioning of digital computers.

But my all-time favourite in the literature of exaggerated claims on behalf of the digital computer is from John McCarthy, the inventor of the term ‘artificial intelligence’.

The prevailing view in philosophy, psychology and artificial intelligence is one which emphasises the analogies between the functioning of the human brain and the functioning of digital computers.

The prevailing view in philosophy, psychology and artificial intelligence is one which emphasises the analogies between the functioning of the human brain and the functioning of digital computers.

The prevailing view in philosophy, psychology and artificial intelligence is one which emphasises the analogies between the functioning of the human brain and the functioning of digital computers.

The prevailing view in philosophy, psychology and artificial intelligence is one which emphasises the analogies between the functioning of the human brain and the functioning of digital computers.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

According to the most extreme version of this view, the brain is just a digital computer and the mind is just a computer program.

One might summarise this view—I call it ‘strong artificial intelligence’, or ‘strong AI’— by saying that the mind is to the brain as the program is to the computer hardware.

And this third conclusion is a trivial consequence of our first premise: it’s a bit like saying that if my petrol engine drives my car at 75 miles per hour, then any diesel engine that was capable of doing that would have to have a power output at least equivalent to that of my petrol engine.

This view has the consequence that there’s nothing essentially biological about the human mind.

The brain just happens to be one of an indefinitely large number of different kinds of hardware computers that could sustain the programs which make up human intelligence.

The brain just happens to be one of an indefinitely large number of different kinds of hardware computers that could sustain the programs which make up human intelligence.

On this view, any physical system whatever that had the right program with the right inputs and outputs would have a mind in exactly the same sense that you and I have minds.

On this view, any physical system whatever that had the right program with the right inputs and outputs would have a mind in exactly the same sense that you and I have minds.

On this view, any physical system whatever that had the right program with the right inputs and outputs would have a mind in exactly the same sense that you and I have minds.

So, for example, if you made a computer out of old beer cans powered by windmills, if it had the right program.

And the point is not that for all we know it might have thoughts and feelings, but, rather, it must have thoughts and feelings, because that is all there is to having thoughts and feelings— implementing the right program.

Now, most people who hold this view think we have not yet designed programs which are minds.

But there is pretty much general agreement among them that it’s only a matter of time until computer scientists and workers in artificial intelligence design the appropriate hardware and programs which will be the equivalent of human brains and minds.

But there is pretty much general agreement among them that it’s only a matter of time until computer scientists and workers in artificial intelligence design the appropriate hardware and programs which will be the equivalent of human brains and minds.

But there is pretty much general agreement among them that it’s only a matter of time until computer scientists and workers in artificial intelligence design the appropriate hardware and programs which will be the equivalent of human brains and minds.

Many people outside the field of artificial intelligence are quite amazed to discover that anybody could believe such a view as this.

Many people outside the field of artificial intelligence are quite amazed to discover that anybody could believe such a view as this.

So, before criticising it, let me give you a few examples of the things the people in this field have actually said.

Well, fancy that!

Philosophers have been worried for centuries about whether or not a machine could think, and now we discover that they’ve already got such machines at Carnegie-Mellon.

Philosophers have been worried for centuries about whether or not a machine could think, and now we discover that they’ve already got such machines at Carnegie-Mellon.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Well, imagine that you are locked in a room, and in this room are several baskets full of Chinese symbols.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Simon’s colleague Alan Newell claims that we have now discovered (and notice that Newell says ‘discovered’ and not just ‘hypothesised’ or ‘considered the possibility’, but actually discovered) that intelligence is just a matter of physical symbol manipulation: it has no essential connection with any kind of biological or physical wetware or hardware.

Both Simon 2 and Newell, to their credit, emphasise that there’s nothing metaphorical about these claims: they mean them quite literally.

Marvin Minsky of MIT says that the next generation of computers will be so intelligent that we will ‘be lucky if they’re willing to keep us around the house as household pets’.

Marvin Minsky of MIT says that the next generation of computers will be so intelligent that we will ‘be lucky if they’re willing to keep us around the house as household pets’.

But my all-time favourite in the literature of exaggerated claims on behalf of the digital computer is from John McCarthy, the inventor of the term ‘artificial intelligence’.

But my all-time favourite in the literature of exaggerated claims on behalf of the digital computer is from John McCarthy, the inventor of the term ‘artificial intelligence’.

But my all-time favourite in the literature of exaggerated claims on behalf of the digital computer is from John McCarthy, the inventor of the term ‘artificial intelligence’.

McCarthy says even a machine as simple as a thermostat can be said to have beliefs.

And, indeed, almost any machine capable of problem-solving can be said to have beliefs.’

And, indeed, almost any machine capable of problem-solving can be said to have beliefs.’

I admire McCarthy’s courage.

I admire McCarthy’s courage.

Unlike most philosophical theses, they are reasonably clear, and they can be simply and decisively refuted.

Unlike most philosophical theses, they are reasonably clear, and they can be simply and decisively refuted.

It’s this refutation that I am going to undertake in this lecture.

It’s this refutation that I am going to undertake in this lecture.

The nature of the refutation has nothing whatever to do with any particular stage of computer technology.

The nature of the refutation has nothing whatever to do with any particular stage of computer technology.

I think it’s important to emphasise that, because in these discussions the temptation is always to think that the solution to our problems must wait on some as yet uncreated technological wonder.

I think it’s important to emphasise that, because in these discussions the temptation is always to think that the solution to our problems must wait on some as yet uncreated technological wonder.

I think it’s important to emphasise that, because in these discussions the temptation is always to think that the solution to our problems must wait on some as yet uncreated technological wonder.

But, in fact, the nature of the refutation is completely independent of any state of technology.

But, in fact, the nature of the refutation is completely independent of any state of technology.

It has to do with the very definition of a digital computer, with what a digital computer is.

It’s essential to our conception of a digital computer that its operations can be specified purely formally; that is, we specify the steps in the operation of the computer in terms of abstract symbols—sequences of zeros and ones printed on a tape, for example.

It’s essential to our conception of a digital computer that its operations can be specified purely formally; that is, we specify the steps in the operation of the computer in terms of abstract symbols—sequences of zeros and ones printed on a tape, for example.

It’s essential to our conception of a digital computer that its operations can be specified purely formally; that is, we specify the steps in the operation of the computer in terms of abstract symbols—sequences of zeros and ones printed on a tape, for example.

It’s essential to our conception of a digital computer that its operations can be specified purely formally; that is, we specify the steps in the operation of the computer in terms of abstract symbols—sequences of zeros and ones printed on a tape, for example.

It’s essential to our conception of a digital computer that its operations can be specified purely formally; that is, we specify the steps in the operation of the computer in terms of abstract symbols—sequences of zeros and ones printed on a tape, for example.

A typical computer ‘rule’ will determine that when a machine is in a certain state and it has a certain symbol on its tape, then it will perform a certain operation such as erasing the symbol or printing another symbol and then enter another state such as moving the tape one square to the left.

A typical computer ‘rule’ will determine that when a machine is in a certain state and it has a certain symbol on its tape, then it will perform a certain operation such as erasing the symbol or printing another symbol and then enter another state such as moving the tape one square to the left.

A typical computer ‘rule’ will determine that when a machine is in a certain state and it has a certain symbol on its tape, then it will perform a certain operation such as erasing the symbol or printing another symbol and then enter another state such as moving the tape one square to the left.

But the symbols have no meaning; they have no semantic content; they’re not about anything.

But the symbols have no meaning; they have no semantic content; they’re not about anything.

They have to be specified purely in terms of their formal or syntactical structure.

Indeed, it’s this feature of digital computers that makes them so powerful.

One and the same type of hardware, if it’s appropriately designed, can be used to run an indefinite range of different programmes.

One and the same type of hardware, if it’s appropriately designed, can be used to run an indefinite range of different programmes.

But this feature of programs, that they’re defined purely formally or syntactically, is fatal to the view that mental processes and program processes are identical.

But this feature of programs, that they’re defined purely formally or syntactically, is fatal to the view that mental processes and program processes are identical.

But this feature of programs, that they’re defined purely formally or syntactically, is fatal to the view that mental processes and program processes are identical.

Our internal mental states, by definition, have certain sorts of contents.

That is, even if my thoughts occur to me in strings of symbols there must be more to the thought than the abstract strings, because strings themselves can’t have any meaning.

In a word, the mind has more than a syntax, it has semantics, 3

In a word, the mind has more than a syntax, it has semantics, 3

To illustrate this point, I’ve designed a certain thought-experiment.

To illustrate this point, I’ve designed a certain thought-experiment.

Imagine that you (like me) do not understand a word of Chinese, but that you are given a rule-hook in English for manipulating these Chinese symbols.

Imagine that a bunch of computer programmers have written a program that will enable a computer to simulate the understanding of Chinese.

Imagine that a bunch of computer programmers have written a program that will enable a computer to simulate the understanding of Chinese.

Imagine that a bunch of computer programmers have written a program that will enable a computer to simulate the understanding of Chinese.

So, for example, if the computer is given a question in Chinese, it will match the question against its memory, or data base, and produce appropriate answers to the question in Chinese.

So, for example, if the computer is given a question in Chinese, it will match the question against its memory, or data base, and produce appropriate answers to the question in Chinese.

So, for example, if the computer is given a question in Chinese, it will match the question against its memory, or data base, and produce appropriate answers to the question in Chinese.

Suppose, for the sake of argument that the computer’s answers are as good as those of a native Chinese speaker.

Suppose, for the sake of argument that the computer’s answers are as good as those of a native Chinese speaker.

Now then, does the computer on the basis of this, understand Chinese, does it literally understand Chinese, in the way that Chinese speakers understand Chinese?

Imagine that you (like me) do not understand a word of Chinese, but that you are given a rule-hook in English for manipulating these Chinese symbols.

Suppose, furthermore, that the programmers are so good at designing the program, and that you are so good at manipulating the symbols, that very soon your answers are indistinguishable from those of a native Chinese speaker.

Chinese symbols and passing out Chinese symbols in response to incoming Chinese symbols.

On the basis of the situation as I have described it, there’s no way you could learn any Chinese simply by manipulating these formal symbols.

On the basis of the situation as I have described it, there’s no way you could learn any Chinese simply by manipulating these formal symbols.

The point of this whole story is simply this: by virtue of implementing a formal computer program, you behave exactly as if you understood Chinese, but all the same, you don’t understand a word of Chinese.

The point of this whole story is simply this: by virtue of implementing a formal computer program, you behave exactly as if you understood Chinese, but all the same, you don’t understand a word of Chinese.

All that the computer has is, as you have, a formal program for manipulating un-interpreted Chinese symbols.

To repeat, a computer has a syntax, but no semantics.

The whole point of the parable of the Chinese room is to remind us of a fact that we knew all along.

The whole point of the parable of the Chinese room is to remind us of a fact that we knew all along.

Understanding a language, or, indeed, having mental states at all, involves more than having just formal symbols.

It involves having an interpretation, or a meaning attached to those symbols.

It involves having an interpretation, or a meaning attached to those symbols.

And a digital computer, as defined, cannot have more than just formal symbols because the operation of the computer, as I said 4 earlier, can only be defined in terms of its ability to implement programs.

I think we can see the force of this argument if we contrast what it’s like to be asked and to answer questions in English, and to be asked and to answer questions in some language where we have no knowledge of any of the meanings of the words.

Now, what’s the difference between the Chinese case and the English case?

Well, again, if, like me, you understand no Chinese and you do understand English, then the difference is obvious.

Now, various replies have been suggested to this argument by workers in artificial intelligence and in psychology, as well as philosophy.

They all have something in common; they are all inadequate.

And there’s an obvious reason why they have to be inadequate, since the argument rests on a very simple logical truth, namely, syntax alone is not sufficient for semantics, and digital computers, in so far as they are computers have, by definition, a syntax alone.

And there’s an obvious reason why they have to be inadequate, since the argument rests on a very simple logical truth, namely, syntax alone is not sufficient for semantics, and digital computers, in so far as they are computers have, by definition, a syntax alone.

Some people attempt to answer the Chinese-room example by saying that the whole system understands Chinese.

And they argue that it’s the whole system, including the room, the baskets full of symbols, the ledgers containing the programs and, perhaps other items as well, taken as a totality, that understands

And they argue that it’s the whole system, including the room, the baskets full of symbols, the ledgers containing the programs and, perhaps other items as well, taken as a totality, that understands

And they argue that it’s the whole system, including the room, the baskets full of symbols, the ledgers containing the programs and, perhaps other items as well, taken as a totality, that understands

I, as the central processing unit have no way of figuring out what any of these symbols means, but then neither does the whole system.

If the robot moved around and interacted causally with the world, wouldn’t that be enough to guarantee that it understood Chinese?

If the robot moved around and interacted causally with the world, wouldn’t that be enough to guarantee that it understood Chinese?

Once again,, the inexorability of the semantics-syntax distinction overcomes this manoeuvre.

Once again,, the inexorability of the semantics-syntax distinction overcomes this manoeuvre.

Inside a room in the robot’s skull I shuffle symbols without knowing that some of them come in to me from television cameras attached to the robot’s head and others go out to move the robot’s arms and legs.

So suppose the robot picks up a hamburger and this triggers the symbol for hamburger to come into the room.

The causal interactions between the robot and the rest of the world are irrelevant unless those causal interactions are represented in some mind or other.

The causal interactions between the robot and the rest of the world are irrelevant unless those causal interactions are represented in some mind or other.

The causal interactions between the robot and the rest of the world are irrelevant unless those causal interactions are represented in some mind or other.

The causal interactions between the robot and the rest of the world are irrelevant unless those causal interactions are represented in some mind or other.

But there’s no way they can be if all that the so-called mind consists of is a set of purely formal, syntactical operations.

Suppose we ask the question that I mentioned at the beginning: Could a machine think?’

We can construe the stuff inside our heads as a meat machine.

But that wasn’t the question that really bothered us.

So let’s try a different formulation of it.

Well, once again, it depends on the kind of artefact.

Suppose we designed a machine that was, molecule for molecule, indistinguishable from a human being.

Well then, if you can duplicate the causes, you can presumably duplicate the effects.

Well then, if you can duplicate the causes, you can presumably duplicate the effects.

Well then, if you can duplicate the causes, you can presumably duplicate the effects.

So, once again, the answer to that question is, in principle at least, trivially yes.

Indeed, it would be a surrogate human being.

But now, once again, we have to be very careful in how we interpret the question.

So in an utterly trivial sense, the pen that’s on the desk in front of me can be described as a digital computer.

It just happens to have a very boring computer program.

That is to say, is instantiating or implementing the right computer program with the right inputs and outputs, sufficient for, or constitutive of, thinking?

And the answer to this question, unlike its predecessors, is clearly ‘no’.

My argument has nothing to do with the forthcoming, amazing advances in computer science.

My argument has nothing to do with the forthcoming, amazing advances in computer science.

My argument has nothing to do with the forthcoming, amazing advances in computer science.

No doubt we will be much better able to simulate human behaviour on computers than we can at present, and certainly much better than we have been able to in the past.

No doubt we will be much better able to simulate human behaviour on computers than we can at present, and certainly much better than we have been able to in the past.

But the point I am making is that if we are talking about having mental states, having a mind, all of these simulations are simply 6 irrelevant.

It doesn’t matter how good the technology is, or how rapid the calculations made by the computer are.

If it’s really a computer, its operations have to be defined syntactically, whereas consciousness, thoughts, feelings, emotions and all the rest of it involve more than a syntax.

And no simulation by itself ever constitutes duplication.

What I’ve done so far is to give a basis to the sense that those quotations I began this talk with are really as preposterous as they seem.

What I’ve done so far is to give a basis to the sense that those quotations I began this talk with are really as preposterous as they seem.

After all, we can do computer simulations of any process at all that can be given a formal description.

So, we can do a computer simulation of the flow of money in the British economy, or the pattern of power-distribution in the Labour Party.

So, we can do a computer simulation of the flow of money in the British economy, or the pattern of power-distribution in the Labour Party.

So, we can do a computer simulation of the flow of money in the British economy, or the pattern of power-distribution in the Labour Party.

Now, in each of these cases, nobody supposes that the computer simulation is actually the real thing; no one supposes that a computer simulation of a storm will leave us all wet, or a computer simulation of a fire is likely to burn the house down.

First of all, where the mind is concerned, a lot of people are still tempted to some sort of behaviourism.

Another assumption made by many people is that the mind is not part of the biological world; it’s not part of the world of nature.

The strong artificial intelligence view relies on that in its conception that the mind is purely formal; that somehow or other, it cannot be treated as a concrete product of biological processes like any other biological product.

The strong artificial intelligence view relies on that in its conception that the mind is purely formal; that somehow or other, it cannot be treated as a concrete product of biological processes like any other biological product.

AI partisans believe that the mind is more than a part of the natural biological world; they believe that the mind is purely formally specifiable.

And the paradox of this is that the AI literature is filled with fulminations against some view called dualism, but in fact the whole thesis of strong AI rests on a kind of dualism.

It rests on a rejection of the idea that the mind is just a natural biological phenomenon in the world like any other.

I want to conclude this lecture by putting together the thesis of the last lecture and the thesis of this one.

And indeed, I’m going to state them with perhaps excessive crudeness.

And the argument has a very simple logical structure, so you can see whether it’s valid or invalid.

And the argument has a very simple logical structure, so you can see whether it’s valid or invalid.

Well, of course, that’s really too crude.

Now let’s write proposition number two: 2.

That proposition is a conceptual truth.

It just articulates our distinction between the notions of what is purely formal and what has content.

It just articulates our distinction between the notions of what is purely formal and what has content.

Now, from these four premises, we can draw our first conclusion; and it follows obviously from two, three, and four; namely:

Now, from these four premises, we can draw our first conclusion; and it follows obviously from two, three, and four; namely:

Now, from these four premises, we can draw our first conclusion; and it follows obviously from two, three, and four; namely:

That’s a very powerful conclusion, because it means that the project of trying to create minds solely by designing programs is doomed from the start.

That’s a very powerful conclusion, because it means that the project of trying to create minds solely by designing programs is doomed from the start.

That’s a very powerful conclusion, because it means that the project of trying to create minds solely by designing programs is doomed from the start.

This is a purely formal, or logical, result from a set of axioms which are agreed to by all (or nearly all) of the disputants concerned.

That is, even the most hardcore enthusiast for artificial intelligence agrees that in fact, as a matter of biology, brain processes cause mental states, and they agree that programs are defined purely syntactically.

But if you put these conclusions together with certain other things that we know, then it follows immediately that the project of strong Al is incapable of fulfilment.

But if you put these conclusions together with certain other things that we know, then it follows immediately that the project of strong Al is incapable of fulfilment.

However, once we’ve got these axioms, let’s see what else we can derive.

Conclusion 2: The way that brain functions cause minds cannot be solely in virtue of running a computer program.

And this second conclusion follows from the first premise, as well as from our first conclusion.

We saw earlier that anything can be trivially described as if it were a digital computer, and brains are no exception.

But the importance of this conclusion is that the computational properties of the brain are simply not enough to explain its functioning to produce mental states.

But the importance of this conclusion is that the computational properties of the brain are simply not enough to explain its functioning to produce mental states.

But the importance of this conclusion is that the computational properties of the brain are simply not enough to explain its functioning to produce mental states.

And indeed, that ought to seem a commonsense scientific conclusion to us anyway, because all it does is remind us of the fact that brains are biological engines; that biology matters.

And this third conclusion is a trivial consequence of our first premise: it’s a bit like saying that if my petrol engine drives my car at 75 miles per hour, then any diesel engine that was capable of doing that would have to have a power output at least equivalent to that of my petrol engine.

Of course, some other system might cause mental processes using entirely different chemical or biochemical features from those that the brain in fact uses.

It might turn out that there are beings on other planets or in some other solar system that have mental states and yet use an entirely different biochemistry from ours.

It might turn out that there are beings on other planets or in some other solar system that have mental states and yet use an entirely different biochemistry from ours.

It might turn out that there are beings on other planets or in some other solar system that have mental states and yet use an entirely different biochemistry from ours.

Suppose that Martians arrived on earth, and we concluded that they had mental states.

Well, still, that green slime, if it functioned to produce consciousness and all the rest of their mental life, would have to have causal powers equal to those of the human brain.

Conclusion 4: For any artefact that we might build which had menial states equivalent to human mental slates, the implementation of a computer program would not by itself be sufficient.

Conclusion 4: For any artefact that we might build which had menial states equivalent to human mental slates, the implementation of a computer program would not by itself be sufficient.

The upshot of this entire discussion I believe is to remind us of something that we’ve known all along: namely, mental states are biological phenomena.

The upshot of this entire discussion I believe is to remind us of something that we’ve known all along: namely, mental states are biological phenomena.

Consciousness, intentionality, subjectivity, and mental causation are all a part of our biological lifehistory, along with growth, reproduction, the secretion of bile and digestion.

Consciousness, intentionality, subjectivity, and mental causation are all a part of our biological lifehistory, along with growth, reproduction, the secretion of bile and digestion.