In the history of science, metaphor has been an extremely powerful and abiding intellectual tool. People often understand one element of the world by making an analogy, a rich analogy to some other aspect of the world. And as the, it's fair to say that over time, as our technology grows, as we have more and more instances of technology around, we're able to use those instances as the sources of metaphor for still other phenomena in the world. What I'm getting at is that in the in the history of cognitive science in particular, there's been one reigning metaphor. One sort of, you know, foundational metaphor that has motivated a lot of the work in cognitive science. You might, in some sense, a just about all of the work in cognitive science over the past 60 or 70 years and that is the idea that the human mind or animal minds can be modeled by a digital computer. So we'll talk about that metaphor. But actually I want to introduce the idea by talking about an earlier metaphor from the history of science. Science is filled with these things, that is people continually sort of look to understand one phenomenon by linking it systematically to another. The example I have here is from the early days of the Scientific Revolution. The portrait is of William Harvey, who was an English physician and I believe he was actually the physician the Royal Physician to King James the first. And the page that you see is a page from a book that he wrote in the early 1600s about the workings of the heart. The main idea behind this book was a metaphor was to propose that the heart act like a pump. And that was a very innovative metaphor at the time because prior to Harvey's book, the sort of raining metaphor of the heart was that it was kind of a brewery. That was sort of the metaphor that was, would have been favored by the ancients, by writers like Galen, the classical physician. That is they felt that the heart's purpose was to purify blood and that it had two parts, two chambers. And in one chamber that was impure blood and then somehow that was transferred to the other chamber of the heart where became purified. That was sort of the portrait of the heart, Harvey proposed a different metaphor. He said no the heart is not like a brewery. It's more like a pump and he performed a variety of new experiments to show that that this was a rich metaphor. And you could take it very far for understanding what the nature of the heart was. So this is an early example. It's not by any means the first example of the use of metaphor in science, but the history of science is just filled with things like this. And I put up a few pictures from the web just to illustrate other sort of chapters in metaphor from the history of science. At the upper right there, there's the the idea that the the solar system is kind of like a clock. So in the sort of early investigations of the solar system by Newton and by Galileo and then prominently by Newton and then by successors. There was a kind of metaphor that the solar system works kind of like a clockwork, a giant sort of well-tuned mechanism. And as I say, that's an example of the use of technology, a clock, to motivate a metaphor for understanding the natural world. But then once you've got that idea of the solar system as a kind of working system. It could be used as a part of a metaphor that is the foundation of a metaphor for still later chapter in The History of Science where people could kind of understand the structure of the atom. As being sort of like a tiny little solar system and students of students of electricity are quite familiar with the common use in elementary electrical circuits of imagining that voltage. That is to say potential current and resistance can be made into you know can be treated analogously to water pressure and water flowing through pipes, okay? I should mention that none of these particular metaphors is exactly correct. They're helpful and a good metaphor is defined by its being helpful. It helps you to ask new questions, to propose new directions for research, to conduct new experiments, the way that William Harvey did. But that doesn't mean that a metaphor has to be a sort of perfect match. And in fact in none of these cases, is it a perfect match. The solar system is not quite like a clockwork. It was found in the 1990s, for example that the orbit of Pluto which I still wish I could call a planet but I guess technically it isn't. But the orbit of Pluto actually exhibits chaotic patterns in its movements in and out of the the orbit of Neptune. So the solar system is not quite a sort of regular clockwork nor of course is the atom a little solar system. Anyone who's studied quantum mechanics and chemistry knows that you there are limits to whether how you can treat the atom as a tiny little solar system. And similarly in electric circuits, you don't want to push this metaphor of water pressure and narrowness of pipes and so forth. You don't want to push that too far. It's pretty hard for example to imagine how you can treat a capacitor in this kind of model. So in any event, none of these metaphors are perfect. Metaphors aren't intended to be perfect. But in cognitive science, we have a kind of traditional metaphor, which is not in itself uncontroversial. Where historically, what we want to say is that the mind is kind of like in the strongest versions people might even make it a little more, a full-throated defense of the mind is a computer. I'm personally more comfortable with saying the mind is like a computer in some ways. In any event, the innovation here was that once computers arose, that is once there were computers to use as a foundation of this metaphor starting in the late 1940s and early 1950s and thereafter. People began to look at the operation of the computer as an information processing device. And they were willing to sort of go out on a limb with a new metaphor and say that the mind, the human mind is itself like a computer, it's an information processing device. This was seen at the time as a response to what was then the the raining tradition in American psychology, which is behaviorist psychology. So the behaviorists argued again, there were a variety of you know, philosophies that could go under the name of behaviorism. At its strongest, the behaviorists might argue that you really should not talk about things like ideas or concepts or beliefs or desires or anything internal to the mind. Because those things cannot be directly seen or measured. And since they cannot be directly seen or measured, they are scientifically illegitimate. So the the behaviorist at again, at their strongest, had this kind of rigid view that you should not be able to talk about the internal workings of the mind. The organism should be treated essentially like input output devices, like black boxes. If you give them a certain kind of input, you get a certain kind of output, so forth. So the the cognitive revolution in Psychology was based on a metaphor, was people were now able to say, no we can talk about things like ideas and concepts and beliefs and desires if we say that the mind is in fact like a computer. So just as we can stud the behavior of a computer and we can write programs for it. Similarly, we can use those programs as a metaphor for the operations of the mind. If you take the metaphor really seriously and by seriously, I mean sort of at its most at its most intense, you actually treat the metaphor as accurate. Not just a little bit of poetic license then you could make the argument that the software of the computer is rather like the operations of the mind within the brain. That is software is to hardware as mind is to brain. The the brain runs the mind as software much as a digital computer runs its software to perform all kinds of different actions. That's a very strong version of the computational metaphor of mind. There are far weaker versions and there are versions that allow for a lot of hand waving that in some respect. You can treat the mind as operating like a computer or you can write programs for computers that illuminate certain operations of the mind. Those are again, much gentler and usually less controversial versions of the computational metaphor. The most intense version is this one and if you take that seriously, then there are a couple of things that sort of follow from it. And these are again, controversial conclusions, but they follow from the sort of most direct interpretation of this metaphor. First, if software is to Hardware as mind is to brain, then if you want to understand the mind, you don't really have to understand the brain to do it. You don't have to, in other words, you don't have to explain the mind that the level of Neuroscience. Why would that be true? Well, if for those computer scientists who may be watching this, you know well that if you're a computer programmer, you don't really have to have a very deep idea about the hardware of the machine that you're writing for. Unless you're writing in a very, you know, sort of low level language like machine code or assembly code or something like that. But if you're writing in a high-level language, you don't really have to know much perhaps, you don't know anything about the hardware of the machine that is going to run the program that you're writing. So you can study the algorithms and the computational ideas in software without knowing much of anything about hardware. And the computer science students routinely take courses in algorithms. For example, where hardware is virtually never mentioned. If you understand the idea of a quick sort algorithm, you don't have to understand anything in particular about the the specific machines on which that quick sort algorithm is going to be run. You can talk about quicksort as an entity in its own right. You can talk about how long it takes to run, whether it's a good idea, whether it's an efficient algorithm, what its limitations are and you don't have to talk about hardware at all. Similarly, If you take this metaphor of mind seriously, then to talk about the mind in software terms, you need not talk about the brain. You could you could talk about certain, for example, the process of language acquisition or visual perception. Or a variety of things without necessarily referring to the implementation of those ideas in neurons in human neurons in the brain. That as I say is a rather controversial interpretation, and I think it's fair to say that most cognitive scientists, the great majority, do not hold to that interpretation anymore. However, this was a version of the computational metaphor that played an especially powerful role in the early years of cognitive science. A second thing, which is mentioned on this same slide is that if you take this metaphor seriously. Then just as computer scientists study algorithms and study things like arrays or lists or data structures or whatever. Then in the same vein, you could treat mental representations as the data structures and you could study those data structures. However they're implemented parse trees, symbols, rules, collections of rules sets of pixels as images all kinds of different representations. So you could study those representations and treat them as themselves the objects of study just as you would study data structures and algorithms in the realm of computer science. Again, that's that's a very interesting idea that now where the behaviorists would rule those things out of court. That is you you're not allowed to study things like parse trees and rules. Because we can't see them and we can't measure them directly. Now, since we can write programs which can mimic human behavior, we are allowed to talk about the the questions of whether humans at least behave as though they are running sets of rules. Or working with mental images or using, you know, context-free grammars as the basis of their language and so forth. Okay, so a corollary of this, the the sort of the the philosophical support for this idea of the computational metaphor goes by the name of functionalism. Actually, I think there's a few different uses of the word functionalism in philosophy. But this is a particular one that applies to cognitive science. So I'm just going to read off the slide here. It's generally summarized as the notion that mental states are characterized according to their causal roles in a system of mental states. In particular, doesn't matter in what physical substance these states have to be embodied. There's a resonance here again with the notion of a computer program. It doesn't matter whether the program happens to be rewritten for a Macintosh or cry or whatever the essential program remains the same. So the idea of functionalism is that you need that you can, you can study things like the mind as a working system of rules, states, computational elements. And what's important is how those things work together as a system, but it doesn't particularly matter what physical machinery or substrate those things are implemented in. Again, that this is just a another sort of fancy philosophical way of describing the strongest version of the computational metaphor of mind. As we talk about the variety of research efforts in cognitive science, we will also talk about the strengths and limitations and possible futures of this overall computational metaphor. The story of the computational metaphor of mind is not by any means finished but it's been an interesting saga. And we're going to be talking about both the criticisms of that idea and where that idea has had its own kinds of successes.