For the final lecture, I'm going to draw some conclusions about Searle and Turing lost,
the last lecture may have seemed to come down rather more in cell's favour than
Turing's because we were seeing some serious problems with the Turing test.
Today, I'm going to be going somewhat in the other direction, as you'll see.
So a summary of where we are so far on Turing and on.
So first of all, Turing's predictions, the predictions that he made for the year 2000 I suggested look pretty plausible.
But as a criterion of intelligence, the Turing test looks very dubious if we interpret it generously, which one of his predictions kind of hints at.
Namely,
can it reduce the success of the interrogator to less than or equal to 70 per cent after five minutes of questioning and an average interrogator?
Then the trouble is that chat bots show it. It's an insufficient criterion.
It's too easy to fool the average interrogator for five minutes.
And even if current chat bots don't do that very well.
If A.I. researchers were to put their mind seriously to it,
I think they'd be able to adjust those in such a way as to get over that threshold relatively straightforwardly.
But if, on the other hand, we interpret the criterion of the Turing test more strictly,
then it becomes too demanding because computers give themselves away.
By not following the cultural cues and things like that, it becomes too easy to tell when the response is from a non-human rather than a human.
What about the Chinese room thought experiment of Searle?
Well, first of all, it's wildly implausible in terms of practicality.
And I've suggested that that casts some doubt on the intuitive responses we are inclined to make to it.
We should be at least hesitant about taking a thought experiment that's completely devoid from reality and simply applying our naive intuitions to it.
I'll be saying more on that later. We've noted two main objections the system reply and the robot reply.
We noted that the system reply, as Copeland points out, begs the question, but still seems to retain a bit of force.
Perhaps intuitive force, at least. We've yet to consider cells reply against the robot.
I mean, we've seen it, but we've not discussed it. I ended by suggesting a better test or what I think is a better test than the Turing test,
which is the idea of producing an intelligent tutoring system,
a system where the intelligence of the computer is revealed,
rather than resorting to the sort of hidden subtlety that is involved in the chat bots with chat bots.
What the chat bot is trying to do is disguise its lack of intelligence with the tutoring system.
The whole idea is to reveal the understanding of the complex web of concepts in,
say, chemistry or whatever it might be in order to present them to the duty.
Now suppose we have a system like that, a computerised tutoring system.
It's capable of highly sophisticated information processing in a complex domain, and it's able to convey that to the human with whom it's interacting.
It is responsive to information structures in ways that reflect how human experts would think, and it aims to convey that expertise to the Tutsi.
Now, cells objection to this is going to be exactly the same.
He's going to simply say, Well, the system's processing is merely semantic.
It is a syntactic sorry. It has no genuine semantics, no real understanding of the domain it's thought cannot reach out to the real world.
So even if this system actually is faithful to,
if you like the logical interactions and mathematical interactions and so on between the different concepts in chemistry,
the system itself has absolutely no awareness that the processing it's doing links in any way to chemicals out in the real world,
so therefore it has no intentionality. OK, now I want to highlight a distinction that cell draws.
This is in his book Rediscovery of the Mind Between Intrinsic ASAT, as if and derived intentionality.
And this lies behind quite a lot of what he says.
So what he's denying with the computer is intrinsic intentionality, the kind of intentionality that involves.
A real, intentional mental state.
So, for example, when I say I am now thirsty, I'm expressing a real mental state that has relation to things in the world, water wanting water.
Contrast that with as if intentionality. Suppose I say my lawn is thirsty, meaning my lawn could do with being watered.
Actually, the lawn has no genuine, intentional state. I'm just talking about it as though it did.
That's fake intentionality. Call it as if intentionality. And then there's another kind derived intentionality.
So suppose I say in French jagran, Swoff means I am very thirsty.
I'm expressing the meaning of a foreign phrase.
But that phrase? Well, what I'm doing is expressing the intentionality that a French person would express in using that phrase.
So we can say that the phrase is intentional in the sense, but it's a derived intentionality from the intrinsic intentionality of language uses.
Okay, so you'll find that on the pages I've mentioned in.
So. Okay, so let's go back now and think of the tutoring system,
and let's accept that in that system, the processed information has no intrinsic semantics.
There's no semantic or grasp within the system itself.
But I want to suggest that we might nevertheless consider the processing of the information to be intelligent.
This is something so seems not to consider. He assumes that intelligence requires intrinsic semantics.
But I think we can challenge that. We can say, OK, the system.
Admittedly, it has no clue that the processing it's doing relates to links between chemicals and, you know, atoms and molecules and quantum stuff.
And of course, it doesn't have any clue.
But nevertheless, the processing that it's doing is intelligent because it is relevantly similar to the reasoning that a human expert does.
OK, so that, it seems to me is is a possible reply here.
We can also consider ways in which computer systems might perhaps achieve intrinsic semantics.
So put that first response on one side for now, and let's consider whether a computer could achieve intrinsic semantics.
OK. Well, the objection does seem quite strong sales objection in terms of physical things,
you know that the system really it has this symbol inside it that represents H2O,
but it doesn't have a clue that that has anything to do with what I may produce a system that you know, thinks about plants.
It has a symbol for a tree, but it's got no idea that that actually relates to trees out there.
Mere internal processing of formal symbols cannot genuinely constitute thought about real trees.
That seems plausible. It's not so clear. We thought about abstract entities,
say numbers or chess positions where intelligent processing needn't be responsive to the properties of concrete things like trees,
but only to appropriate logical relations, and those can be represented formally.
So I just want to give you an example here of a simple programme, and you can actually run this programme for yourself within the turtle system.
It's available as a A. You can freely download this and it's one of the help, for example, files there.
Here we've got a simple programme. I'm playing blue and the thing's going to beat me, right?
Yeah, because I played a bad first move, right?
And if I play in the corner, I can guarantee that it will play in the middle because that's the only move that doesn't lose.
Gosh, it's taking a long time. Thinking hard, maybe are.
OK, now I want to point out that programme is not driven by a look up table.
OK? When it was working out to play in the middle,
it really was calculating all the possible lines of there's a recursive procedure that does all the work.
I mean, surprisingly short, really. But it is analysing all the way down the tree of analysis.
So the the point here is that the processing there really does reflect the logic of the problem domain.
When it decides which move to play, it is doing so in terms of the genuine relations between different positions.
Of course, the positions are represented in a way quite different from how they're represented in our minds.
But the links between the positions faithfully reflect the relationships that
we are aware of in terms of a move changing from one position to another.
So basically, it is doing what's called mini maxing.
At the end of the handout. I've put six slides which explain how the programme works.
If you've not come across this thing, this kind of thing that that will be illuminating, it's actually very straightforward.
The programme obviously isn't aware, but its processing is appropriately responsive to the real logic of the game.
So shouldn't that be enough for intelligence? It seems to me a reasonable claim or an arguable claim.
It at least that it is OK.
Having said that, I'm going to put all this on one side because I think getting into philosophy of mathematics,
understanding our thinking about numbers and abstract relationships between games, positions and all the rest really is quite difficult and obscure.
And in any case, soul is mainly concerned with the kind of thinking that we have in common with animals.
And he thinks not with computers, namely thoughts about things in the real world, physical things that's much more central.
So even if so, was to concede the point that that machines can be intelligent in an appropriate sense about abstract objects.
They it's really thinking about more everyday physical objects and so on that are his main concern.
Okay, so with apologies to Monty Python, you recognise that if you're familiar with it, I'm a lumberjack and I'm OK, I'm going to take on now.
The robot reply to the Chinese room, and I'm going to combine it with the system or.
So imagine a robotic crane armed with appropriate sensors and tours and tools, which is programmed to cut down trees intelligently and effectively.
OK, I'm not begging the question by saying intelligently.
All I mean is it's doing the kind of thing that an intelligent human would do in that position.
It senses for itself which trees are suitable for chopping or pruning and which of best left.
It takes account of relevant conservation needs. It's responsive to physical obstructions and other difficulties and real time events as it works.
OK, so this robotic crane if, say,
overnight some trees get blown down and are in the way it will respond appropriately will detect them using its sensors.
It will chop them up. Carry the bits to where bits should be carried.
Clear the lines and then get on with its job. So the internal states of the robot are responsive to physical things and impact causally on them.
So we've got to weigh causation, right? It senses real things and is able to act on real things.
OK, so the claim here is that robot.
The robotic crane literally reaches out to the real world when the symbol tree occurs within its thinking.
It actually does have an impact on the real world and is responsive to the real world.
So why doesn't that have real intentionality? Well, remember his response to the robot reply?
I would suggest we should consider a Chinese cabin in the grain fed,
with messages from the sensors written in Chinese characters processed purely
syntactically by the man inside and resulting in Chinese messages to the Cranes motors.
All of these messages being incomprehensible to the guy in the cabin.
So remember, his reply is a response to the robot reply.
It's exactly like that.
But this response is only conclusive is if his rebuttal to the system reply works okay because we can simply say, OK, so if you take the central.
As a unit of the computer that's there in the cabin of the robot and replace it with a person.
OK, let's agree that that person has no semantic grasp of what's going on.
They're just receiving symbols from the sensors and so forth and churning out symbols in response that work,
the motors and the saw and all that kind of stuff. No idea at all that they're even controlling a robotic lumberjack crane.
But as Copeland insists, that doesn't imply that the system as a whole lacks semantics that requires another argument.
So I'm appealing here to Copeland's point, but still has not refuted the system reply.
And because of that, the fact that the the central processor unit of the crane,
all the man who's taking that place doesn't have any semantic link with the world doesn't imply that the crane doesn't.
The crane has sensors and motors and saws and all the rest as well.
And in that case, I'm suggesting that the man's unawareness of that is irrelevant.
Or at least it's a challenge to sell to explain why.
It's not because if, if intentionality, you know, reaching out to the world, having reference to the real world is watching question.
Why doesn't the robotic crane achieve that? It's having a very real impact and is responding to things in the real world.
So what is it that machines are supposed to lack according to So?
Well,
the style of his arguments seems to suggest that the crucial thing is that they lack understanding internal conscious awareness of what's going on.
I note in passing that the word understanding is a very slippery one.
It quite often comes up in philosophical discussion whenever you see some philosopher saying understanding is required or something like that,
be very suspicious. Ask yourself what exactly that means, because it can mean a lot of different things anyway.
Animals, by the way, do have what computers lack, according to so visual and auditory experiences,
tactile sensations, hunger, thirst and sexual desire all caused by brain processes.
And they are realised in the structure of the brain, and they are all intentional phenomena.
It is just a plain fact about biological evolution that is produced certain type sorts of biological systems,
namely human and certain animal brains that have subjective features, and there are other passages that same effect.
OK, so it seems to be something like animal consciousness that so he's on to hear.
At other points, he recognises that there is another issue here, though our intentional state need not be conscious.
They can be unconscious, so not all of the processing that goes on in our brains is conscious.
What about that? Well, still draws a distinction between consciousness and unconsciousness,
but wants to insist isn't what characterises an unconscious, intentional state.
That is, that it is at least potentially conscious. Only a being that could have conscious intentional states could have intentional states at all,
and every unconscious, intentional state is at least potentially conscious.
OK, now we might ask questions about that. You know, can it really count as exactly the same state?
If it can be both conscious and unconscious? We won't go into that. We let so have that.
But I won't suggest that he's at risk of conflating two quite different things when he uses terms like semantic and intentionality.
And one notion is roughly that of internal symbols having objective significance representing external things in some
intrinsic way rather than being just thought of by some other agent as having such representative significance.
So take the robotic crane, for example, and contrast that with a piece of text.
The piece of text in itself has no intrinsic link to anything in the world,
any representational power that it has is purely in terms of our reading it and understanding it in a particular way.
But the robotic crane does have a direct links with the outside world.
It doesn't need an agent once it started going.
It is going to have links with the outside world so that the symbols within it
have objective significance without requiring any other agent in the picture.
At least Wally Power keeps getting. OK, so that's one notion.
The other notion is that of internal symbols having subjective significance to the agent
in question and hence requiring either consciousness or at least potential consciousness.
So this one is more demanding than that. And I'm suggesting that so kind of conflates them together.
So if we do conflate these notes, it's going to pretty much follow straight away that only conscious beings can have intelligence.
Now the point I'm making is that there's no obvious reason why we have to go with so on that.
So here's how I think is the simplest way to oppose.
So it's not to get into all sorts of nuances about philosophy of mind and all that kind of stuff.
But just let's draw a distinction between information processing and its characteristics and the extent to which that processing is conscious.
We could go further. The former category we could divide into information processing,
which is embodied in such as such a way is to have direct queasy semantic connexions with the relevant subject matter.
On the other hand, information processing, which requires interpretation by some external agent.
So if we take the tutoring system, the system that tutors about chemistry that isn't embodied OK,
in order to interpret its output as having anything to do with chemistry, it requires an agent doing it.
Where is the robotic lumberjack there? The information processing is embedded in the system through the sensors and the motors and all the rest.
So that has direct. I've called them crazy semantic connexions.
I don't want to argue about the word semantic. They are connexions there.
They link to the outside world. And that is a characteristic of that information processing, irrespective of whether it's conscious so distinguished.
In this way, we could have information processing that's conscious and embodied.
We have that higher animals have that unconscious and embodied the robotic lumberjack.
And here I don't mean unconscious in the sense that Searle is talking about with our unconscious states.
I mean, always unconscious, never conscious and embodied.
So that's the robotic lumberjack and then unconscious and second hand.
So that would be when we use artificial intelligence systems, we interpret the output in particular ways.
So, so effectively, you're saying, well, we ought to restrict intelligence to the first of those.
And I'm saying, why do you have a good reason for refusing to call these intelligent?
Because after all, if you think about it, suppose you've got a number of robotic lumberjacks.
Some of those might be better than others. Some might be extremely undiscriminating, you know, put them in the wrong place,
and they're just going to hack down everything, whether it requires preservation or not.
Others may be very discriminating. Well, don't we want to say that the latter is more intelligent than the former?
Maybe we do. Likewise, you can have artificial intelligence systems that are better or worse at the information processing.
Why can't we use the word intelligent genuinely to distinguish the ones that are good at it?
Is there any reason other than prejudice for saying we're only going to count things as intelligent if they are conscious?
A reminder now about something we saw a couple of lectures ago. Turing's response to Jefferson's argument from consciousness.
Turing seems to accept that to support mean machine intelligence,
he mistake machine consciousness to be a reasonable supposition, just as much with other people.
So he he is actually here taking for granted what it seems to me Searle is trying to insist on.
And I criticised him at the time, you may remember. I don't think Turing is right here.
He says this argument, the argument from consciousness appears to be a denial of the validity of our test,
according to the most extreme form of his view. The only way to know that either a machine or a man thinks is to be that particular man.
It is, in fact, solipsistic point of view. So you may remember that.
So Turing seems to be implying that in order to counter the argument from consciousness,
he he has to appeal to the difficulty of establishing that other humans are conscious and then sort of saying,
Well, we should apply the same presumption in favour of computers.
He goes on to give the voter vote sample about the summit.
You know, what would Jefferson say if the sonnet writing machine was able to answer like this in the Bible?
Okay, if the answers were satisfactory and sustained, as in the above passage, I suggested back in slide 194,
what Turing should have said is then there would be reason to call the machine intelligent, irrespective of whether or not it has genuine feelings.
Intelligent thinking need not require consciousness, nor even potential consciousness.
That's what I think he should have said. So let me now say more on that.
So most discussions of these sorts of debates seem to proceed on the assumption that
we should be looking for a verdict based on our current conceptual repertoire,
our ordinary common sense conceptual repertoire that we grow up with.
And I want to suggest that's wrong. That's not the way science works.
If. Science at work like that, it would never have gone forward in the way it has.
And I want to suggest the same applies to philosophy when we are considering a novel puzzle cases in philosophy.
We ought to be prepared to expand our conceptual repertoire to deal with them because when we reach,
when we meet new challenges, one of the things those challenges do is precisely to contest the traditional boundaries.
I say more about this in a paper. I refer to their philosophical significance of the Turing machine in the Turing test.
It was published in that that big collection of 2013 that I mentioned at the start of the lectures.
So let's go back to Turing's prediction that we talked about this last time.
The original question can machines think, I believe, to be too meaningless to deserve discussion?
Nevertheless, I believe the end of the century the use of words and general educated opinion will have altered
so much that one will be able to speak of machines thinking without expecting to be contradicted.
So I'm suggesting that we take this as a hint, and this leads in a different direction from Turing's response to Jefferson saying,
Oh, let's accept the fact that we're talking here about evolution of our concepts,
so we don't need to go along with Jefferson in just identifying intelligence and consciousness or assuming that one requires the other.
And an important point here, I want to make against a thought experiment or against their uses intuition pumps,
which we've been looking at in the last couple of lectures,
we saw Dennett discussing these very contemptuous into misleading or simplistic comparisons because
precisely they appeal to our intuitive assumptions and that can drown out unexpected differences.
So the problem we thought experiment is they are always appealing to something familiar
and inviting us to see something novel as relevantly similar to the familiar thing.
So let's make judgements accordingly. No, let's not. When we are faced with new realities,
sometimes we have to think those through in novel ways and not assume the categories that we brought with us will apply to them satisfactorily.
And I want to suggest that major scientific progress is very often involve these kinds of major novelties,
bringing what are called paradigm shifts and fundamental new methods of explanation.
And just as a matter of interest, before I get onto my rapid run through the history of science, it's very interesting to note that Luciano Floride,
like me, sees Turing's discovery in 1936 as a sort of conceptual revolution, but he interprets it in a different way.
I'm going to be talking about modes of explanation in science. He talks about humanity's fundamental nature and role in the universe.
We are not immobile at the centre of the universe. That's what Copernicus showed.
Personally, I'm a little bit more inclined to give the credit to Galileo. Copernicus came up with the theory.
Galileo proved it with this telescope. We are not unnaturally distinct and different from the rest of the animal world.
Darwin and we are far from being entirely transparent to ourselves.
Freud here I would give more credit to David Hume.
I would one day. But long before Freud, Hume had drawn this conclusion.
I think Hume's arguments are a lot more solid than Freud psychology, but anyway, similar kind of point.
We are now slowly accepting the idea that we might be informational organisms amongst many agents, Turing.
So as I say, I'm just going to very quickly give a similar sort of rapid history, except in terms of modes of explanation.
OK, so if you go back before 6500, before Galileo, more or less everything in the world is explained in terms of purpose.
God's purpose, of course, God has designed the world in the way it is, but other things to act according to purpose.
So obviously, humans, obviously animals, but actually also physical objects.
If I take a stone and I drop it, the stone falls downwards.
The reason it falls downwards is that it's striving to reach its natural place in the universe.
Its natural place in the universe is at the centre of the universe.
There are four main elements beneath the moon earth, water, air and fire, and they occupy places going outwards from the centre of the universe.
So a stone being made mainly of Earth naturally moves towards its natural place, which is the centre of the universe.
So stones are actually striving to achieve a certain purpose.
So more or less, you know, all of science is based on purposes.
Galileo turns his telescope up, shows that the Earth is not the centre of the universe, right?
Yes. All right. That is perhaps a bit damaging to human hubris, as Florida points out.
But I think more fundamentally, it completely scuppered the Aristotelian explanation.
The whole Aristotelian physics goes out of the window because if the Earth is not the centre of the universe,
then you can't explain the motion of rocks and things by their striving to reach the centre of the universe.
So we get a completely new physics based on the idea of inertia that things naturally
move at a constant speed in straight lines unless acted upon by some force.
And gravity remains a big problem in those terms.
Descartes comes up with a nice explanation in terms of the essence of matter being extension and therefore the universe working with vortices.
Newton more successfully postulate a completely new way in which science can work, not explaining things in terms of physical contact.
One thing bashing another, which is what Descartes had tried to do,
but instead postulating a force that acts according to certain mathematical properties proportional
to the the masses concerned and inversely proportional to the square of the distance.
That's a new kind of explanation in science. In the 18th century, Hume throws doubt on traditional conceptions of human behaviour.
Actually, humans are not nearly as based on reason as they like to think.
Moreover, more importantly, they could not be they could not be.
If you try to follow the ideal of Aristotle, for example,
and Plato and so forth of living a life purely according to reason, you won't be able to do anything.
So Hume is pointing out that animal instinct and feeling plays a much bigger role,
and that is obviously putting us closer to the animals rather than to gods.
And indeed, Hume argues that explicitly. Charles Darwin, of course, came along simultaneously with with with Wallace.
I mean, Darwin published his theory in the same year as Wallace and was prompted to do so by Wallace.
His theory of evolution biological organisms take the form they do not because of divine design, but because of evolution and natural selection.
So we inherit characteristics from our parents or organisms do.
And those characteristics that are better suited to our survival and reproduction naturally get better represented in the next generation.
So you get evolution because this doesn't imply that there isn't a god behind it all.
But the crucial point is it shows that a phenomenon which previously would incontrovertibly have been ascribed to intelligent design,
namely the exquisite adaptation of organisms to their environment now has an
alternative explanation doesn't require conscious purpose to get exquisite adaptation.
Moving on to our series of revolutions again, I mean,
do notice that both human Darwin there are bringing in new methods of explanation in science before Darwin.
Right? An evolutionary explanation wasn't there after Darwin.
We've got a new method of explaining things. General relativity brings in another one to do with curving space time.
Quantum mechanics brings in yet another.
So these major happenings in the history of science, all of them are bringing in new methods of explanation going beyond the natural,
intuitive explanation in terms of purpose, which seems to come in a most easily to us.
And they're bringing in fundamental changes in thinking they do change how we see our place in the universe, as Florida pointed out.
They also extend our understanding of the possibilities of scientific explanation mathematical forces rather than strivings,
inherited variation and selection rather than rational design curvature in spacetime rather than Newtonian forces.
And I want to point out that the philosopher sorry, the scientists who made these big advances were very,
very strongly influenced by philosophical thinking.
I mean, the backing Galileo and Descartes and Boyle's time, and so they styled themselves natural philosophers.
But it's interesting that Darwin was very influenced by Hume.
He was reading Hume on the reason of animals at the time he came up with the theory of evolution.
He'd read lots of stuff on him. Einstein, rather nicely as well, credited Hume with the insight that led to the theory of relativity.
I think that's particularly nice. You know, two centuries later and thinking in philosophical ways is prompting new thinking in science.
Now, going back to the physics again,
but relativity and quantum mechanics particularly illustrate how wrong our intuitive understanding of things can be.
I think evolution has now got sufficiently into our general consciousness that an educated people no longer find that particularly strange relativity,
curvature of space, time and quantum mechanics are seriously weird.
And I think anybody who isn't trained very heavily in physics is going to find those weird and.
Yet these are important conceptual advances.
OK, science is advanced by showing that there's something wrong or inadequate in our intuitive understanding.
And I want to suggest that Alan Turing's discovery of the Turing machine is comparable with those kind of innovations.
Obviously, he and girdle and so on have shown that some mathematical questions for which there's no possible method of solution.
So, you know, the the advances that came in the 1930s in philosophy of maths,
those shook very fundamental assumptions that had hitherto been more or less universal,
but also obviously more pertinent here with regard to the nature of thinking, we need to be open to the possibility of inanimate thought.
So what Turing showed is that information processing can be understood in terms of symbolic inputs
and outputs governed by explicit and automatic processes with a limited range of operations.
OK, we saw that in going through his 1936 paper.
We've got the Turing machine, very limited repertoire of possibilities.
And Turing argues that anything that can be calculated systematically can be calculated by such a machine.
And the Church Turing thesis backs that up. So information and information processing in this sense does not presuppose an understanding mind.
So we now have sophisticated information processing machines capable of doing anything that we can conceive how to do in a systematic way,
but they can do it without any conscious purpose at all.
And I want to suggest that that's somewhat similar to Darwin's innovation.
Darwin showed that you can have sophisticated adaptation without intentional design.
Turing showed that you can have information processing without that information existing in a conscious mind,
and that is a novelty, OK, before computers came along.
Words like intelligent were only associated with conscious things that had purposes agents applying their intelligence to the situation.
They understand themselves to be in performing sophisticated processing of
information in order to adapt their behaviour to achieve their own purposes.
By contrast, inanimate things just don't have purposes. So there's no question of them having intelligence.
But then what we have since Turing is intelligent processing of information,
apparently by things that are inanimate, that don't have their own purposes.
So what I want to suggest is when we're faced with that, what we should do is modify our concepts.
We shouldn't try to apply our pre-existing naive concepts to this new reality, just like with Darwin and Einstein and quantum mechanics and so on.
We have to invent new concepts. We have to divide things in new ways.
Now, there's a general point to be made actually about lots of our concepts, not just the special scientific ones.
Friedrich Weissman, who's a sort of follower of and Stein he set himself to write up in relatively clear language.
What he took to be the outcome of Vik and Stein's work. Of course, as a result, Vik and Stein hated it.
He came up with the very nice notion of open texture. So it's a kind of tinian notion.
But it's the idea is that most of our concepts are open, textured.
It's not clear in advance how we would apply them to all possible cases.
Now, open texture is actually particularly prominent as a concept in law because in law,
you can imagine you set out laws to prescribe what should happen in a particular situation, and it really matters, right?
Penalties could depend on this or what people are allowed to do depends on this.
So the categories really matter. It's not just like philosophers, you know, playing their word games, and sometimes this can impact with reality.
So suppose we have a society where marriage is understood as being between a man and a woman only no sex change is nothing like that.
No, no, that doesn't happen. But then maybe things change and we do get sex changes.
Or maybe we get new discoveries about, you know,
chromosomal abnormalities and whatever we discover more about humans or humans are presented with new possibilities.
Well, we have to wonder how the old law applies. We can't just apply it mindlessly.
We have to ask ourselves, how should this law be adapted in this new situation?
I mean, another example inheritance rights.
Suppose you have a society in which children are always, always stay with their parents and inheritance is understood accordingly.
But then adoption becomes common as a practise. Maybe because there's a nasty plague or something like that, a game like death.
And suddenly you get totally new social practises. You have to ask how the traditional laws are going to be applied.
And those of you who know about Theseus to shift the imagine Theseus, the Greek hero,
has a ship which he is regularly getting repaired and he takes it back to the ship, right?
Who built it and the ship right? Whenever he, whenever he replaces a plank, keeps the old one.
And then some years later, when all the planks have been replaced, the ship right builds a new the initial ship with the original planks.
Well, is that actually the same ship or not? Or should we say that the same ship is the one that Theseus has been sailing around it?
Well, again, this could matter in a legal context because maybe CCC ship has mooring rights in perpetuity somewhere.
So if the ship right now turns up with the ship and says, actually, this is the sister ship,
this is the one that has the mooring rights, well, does it or not? Probably not.
I rather like this punch cartoon from 1869. I think it's a nice example of open texture.
So it's a woman with a menagerie of creatures wanting to go on the train.
Right? And the the port is, as station master says, mum of cats is dogs and rabbits is dogs and those parrots.
But this year, tortoise is an insect, so there ain't no charge for it.
So the porter knows how to charge for dogs and people, but but not for an insect.
You don't charge for insects, but he doesn't know how to charge for cats and rabbits and parrots and tortoises,
so they have to be categorised under the existing categories.
OK, now open texture cut in two directions, first of all.
And this, by the way, at least Weisman claims,
I think quite plausibly is something a phenomenon that applies to a lot of our concepts, not just special ones.
You know, arguably most of our concepts are derived from our experience in the world and not necessarily defined beyond that.
We can't expect our concepts to be prepared in advance for all new eventualities.
They may have to be revised or tuned to new contexts, and especially, of course, when big new innovations come.
And another point is we needn't accept any requirement when reshooting our concepts to make them immune to future revision.
We don't have to take all future possibilities, let alone all logical possibilities into account.
So philosophers actually have a good reason when somebody says, Look, before we discuss X knowledge,
personal identity, whatever it might be, we've got to define it precisely.
Answer sorry, can't do it as the experience of philosophy shows.
And a point I want to draw from that is when revising our concepts, we have every right to ignore crazy thought experiments.
That's a controversial claim. I'm saying if it's true that in general, our concepts are tuned to the world as we experience it,
then imagining some world in which things are wildly different and being asked,
How is your concept going to apply there should you not be changing it?
My answer is going to be no. Maybe I need to tune it to realities.
Maybe I need to tune it to potential realities. But to impossibilities or complete implausibility is no, I'm not going to accept that obligation.
OK, against that background. Let's now ask ourselves how in general, we judge intelligence,
so I've argued that we should be prepared to consider intelligent things that are unconscious.
I have acknowledged that our everyday concept of intelligence, the one that we and our parents and our parents,
parents and our parents parents have grown up with has evolved to fit a world or being, you know,
created to fit a world in which the only intelligent things are conscious, purposive creatures.
I'm saying we now have a new reality. Apparently, intelligent processing going on within things that are not conscious or purposive.
How are we going to judge those? OK, how do we think about intelligence in ordinary life?
Well, first of all, its subject relative? Yeah.
Many of us here would be considered very intelligent about some things we're probably considered very far from intelligent about some others.
It's a matter of degree. We don't say some things intelligent or unintelligent.
We say some things more intelligent or person is more intelligent than another.
And hopefully, you know, when we study here, we get more intelligent and so forth.
It's generally measured by performance, including flexibility, speed, appropriateness of response to new requirements or new information.
So someone who's able to adapt to new things to learn new skills in relation to some domain,
we think of them as more intelligent than someone who's simply been trained to deal with a fixed repertoire.
It's not significantly correlated with feeling or consciousness. We don't judge someone as more intelligent because they Campbell agree.
So suppose we now distinguish sharply between the sophistication of information
processing and the phenomenology phenomenology is a technical philosopher's term,
meaning what it's like from the inside, right?
So we're going to distinguish between sophistication of information processing on one hand and the consciousness, the inner life on the other.
They often come apart. I mean, we've already seen hints of some of this.
Dogs can decide desire things as strongly as we do. Yes.
I mean, anyone who's seen a dog with a ball coming up to you and holding its mouth looking appealingly, please, please throw the ball.
I want to play. Right? Dogs can desire things very, very strongly.
That doesn't make us judge them extra intelligent.
I'm pretty intelligent compared to most animals, but it's not in proportion to the strength of their desires.
Experts are often less conscious than novices.
So, for example, expert drivers who are used to commuting along a particular road day after day after day,
it's absolutely familiar that they can come to the end of their journey and walk into work.
And somebody says, How was the drive today? I can't remember unless something special happened.
You just drive along. I mean, you're obviously taking note of things.
You're avoiding, you know, pedestrians, you're taking note of traffic lights, you're overtaking and being overtaken and, you know, driving safely.
But you're almost I mean, you wouldn't say you're unconscious while you're doing it, but it barely impacts on your consciousness,
whereas a novice driver someone is learning to drive is going to be aware of every single little thing.
The same is true, for example, chess players. It's very frustrating actually talking to an expert chess player and sometimes and saying,
Why did you play that move, just the right move to play in that kind of position?
Thanks very much. Where is the novice will be able to tell you exactly, Oh, I thought this and this and this and this and this.
Actually, the more expert we are, often the less conscious we become another.
I think corroborative piece of evidence. Our intuitive judgements about what is easy are often badly wrong.
So most people think arithmetic is really, really difficult.
We know, you know, from computers, arithmetic is comparatively trivial in terms of information processing,
whereas running and catching a ball, that's seriously difficult.
You know, you've got a balance and you've got to predict where the ball or anticipate where the ball's going to be.
You've got to reach out your hand appropriately and so forth. That's seriously difficult.
And yet we tend to think of it as easy. So our intuitive judgements about information processing tend to be pretty bad.
But dogs can do that pretty well. So in that respect, dogs are very intelligent.
OK, suppose we distinguish sophistication of information processing from the phenomenology,
I'm going to suggest it's clear that intelligence is far more a measure of the former than the latter.
But all all of the evidence I've given in the last two slides suggest that when we judge something's intelligence,
it's mainly a focus on the information processing, the power, the sophistication, the flexibility and so that the information processing.
It's not the phenomenology. And in our new world of unconscious but highly sophisticated information processes,
it makes sense to allow our concept of intelligence to evolve a court accordingly.
So I think Turing's main claim in the paper is vindicated, but not by means of the test that he proposed.
That is, I think, learning from the 1936 paper.
We should accept that you can have intelligent computers.
Coming back now to Turing's approach to this and what I call his solipsistic mistake, I mean, he didn't draw the distinction that I'm drawing.
And I think thus he that weakened his argument and he talked about how.
So if we followed the logical conclusion of Jefferson's objection, we would actually be reduced to solipsism denying consciousness to other humans.
I've got a very different way. I've said I fully accept that computers aren't conscious. That doesn't stop them being intelligent.
I don't want to go along with Turing in saying that if I deny consciousness to computers, I have to deny them to my fellow human beings.
Those are very different. We know, at least in outline, why the robot does what it does.
Suppose take a simple example, chess computer, I know in general terms what why the chess computer makes the moves that it does.
I've programmed games, playing programmes. I've read about them.
I know the kinds of algorithms that I know that the computer is doing what he's done because it's been programmed to do it.
I don't have to postulate a desire, a conscious desire on the computer's part because I know full well, a conscious desire plays no part.
Whatever in the causation of its doing its move.
So I might say, Oh, it moved 96, because that was only the the only way of avoiding Queen H7 meant right.
But I'm not attributing a conscious purpose with that.
So I may be applying an intentional description to it, but I'm not under the illusion that there's some consciousness that we all the humans.
It's quite different.
I know that other humans function biologically in broadly the same way as I do, and I know that in my life, consciousness plays an important role.
I'm aware of it. I'm aware of my conscious purposes and how they impact on what I do, a very good reason to think that other people are much the same.
Moreover, the phenomenal reality of consciousness, the fact that we are aware of it,
that we do ponder things consciously and that they affect how we behave strongly suggests it's something causally active.
It's not just an abstraction of information processing patterns.
So some people speculate that if you had a computer that reasoned in the same way as a human, then that would ipso facto make it conscious.
I don't see any reason for saying that. It seems to me consciousness has a reality.
It's terribly difficult to pin it down or to understand it. But it's not just a matter of information processing.
The evolutionary role of it is quite mysterious. Those philosophers like postulating the idea of zombies.
A zombie is a being that is physically the same as a human being.
But with nobody at home, why wouldn't that be possible? Being with all the same neurones as me, but no awareness.
Wouldn't they function physically in exactly the same way? Wouldn't they be just as successful?
In which case, what difference does consciousness make? Well, I want to suggest that the close correlation between consciousness,
the pleasures and pains that we feel and factors affecting our well-being is overwhelming evidence that consciousness is causally active.
The fact that we get pleasure from things like eating honey say which in the environment where we evolved, honey is valuable.
It's got calories in and getting calories, unlike in modern society 100000 years ago, is pretty difficult.
You get honey, you want it. It's nice or injuring yourself that that's that does you harm.
That's painful. And there are loads and loads of respect in which, you know, I mean, eating food is generally pleasurable.
Sex is generally pleasurable. The things that conduce to our evolutionary success are generally pleasurable and the things that harm us are not.
But that's not a coincidence. But conscious states can only track things that are good for us and bad for us if they are causally efficacious.
Consciousness could only evolve.
I want to suggest in a way that is so well tuned to our needs, giving us desires for things that are evolutionarily beneficial,
dislike of things that are harmful if it's cause negative, even if we're unable to work out.
How so? I fully accept that philosophers have great difficulty making sense of consciousness.
You know, there's lots of debate about at the moment.
I a personal suspicion is that this isn't going to be sorted out until we have at least one more conceptual revolution.
And I haven't a clue where that's going to come from. But, you know, I think it may be that trying to sort this all out in terms of current science,
it is just futile because we've got to wait for better understanding of the brain.
Much, much more investigation.
You know, maybe into biochemistry or maybe physics, whatever it won't, I, I expect that, you know, in the next 500 years,
whatever, there may be significant conceptual advances, which will allow us to tackle problems that at present, we can't tackle.
But if I have to make a bet as it were, evolutionary theory is well understood.
Supported by overwhelming empirical evidence, strong scientific evidence trumps armchair speculation.
So there are lots of philosophers speculating in their different ways about consciousness, its role and all the rest.
Where I'm going to plant my flag is I'm confident that consciousness has an
evolutionary role is causally efficacious because of the evolutionary argument.
OK, now we humans are all products of the same evolved biological processes.
Know you were born in much the same way as I was and by similar processes.
Even if we cannot work out how consciousness arises, we have very good reason to attribute it to each other.
That argument doesn't apply at all to computers. So there is no reason for supposing computers to be conscious.
But nevertheless,
I have argued we have strong reason in the wake of Turing and his monumental discoveries or inventions to allow that computers can be intelligent.
And that's it. Thank you.