# HG changeset patch # User Robert McIntyre # Date 1376369221 14400 # Node ID a72ac82bb785062e61eedfdc643b35556f9b9a43 # Parent 05e666949a4faffd4072b32c23ac7a88fc56d986 add dylan's sloman transcript. diff -r 05e666949a4f -r a72ac82bb785 css/sloman.css --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/css/sloman.css Tue Aug 13 00:47:01 2013 -0400 @@ -0,0 +1,111 @@ +/*** RESETS ***/ +html,body{margin:0;padding:0;color:#4f4030;} +h1,h2,h3,h4,h5,h6 {font-size:inherit;line-height:inherit;margin:0;padding:0;font-weight:inherit;} +a{color:inherit;} + +/*** CORE SETTINGS ***/ + +body { + font-size:16px; + line-height:1.25em; + padding:1.5em; +} + +body { + /*width:36em; + margin:0px auto;*/ + padding:2.5em 5em; + background:#fff; +} +html { + +} + +.outline-3 a { +color:#369; +} +/*** TITLES AND OTHER HEADERS ***/ +h1.title { + text-align:left; + font-size:1.5em; + line-height:1.667em; + line-height:1em; + font-weight:bold; +} + + +h2 { + font-weight:bold; + margin-top:2.5em; +} +h3 { + text-align:center; + font-family:Cabin,Helvetica,Arial,sans-serif; + line-height:1em; + padding-top:1.5em; + padding-bottom:1.5em; + border-top:1px dotted #ccc; + color:#7f674; +} +h4 { + font-weight:bold; + font-size:1.25em; + line-height:1em; + margin-top:2em; +} + +.tag { + background:inherit; + color:#369; + color:#4d657f; + font-family:Cabin,Helvetica,Arial,sans-serif; + font-size:14px; +} + +/*** TABLE OF CONTENTS ***/ +#text-table-of-contents { + margin-bottom:4em; +} +#text-table-of-contents ul { + list-style-type:none; + padding:0; + font-weight:bold; + font-family:Cabin,Helvetica,Arial,sans-serif; +} + +#text-table-of-contents > ul li { + line-height:1.875em; + line-height:2.5em; + color:#7f674d; +} + + +#text-table-of-contents ul ul li { + line-height:1.25em; + line-height:1.25em; + padding-left:1.4em; + font-weight:normal; + font-family:Georgia,Times,Palatino,serif; + color:#4f4030; +} +#text-table-of-contents a { + text-decoration:none; +} +#text-table-of-contents a:hover { + text-decoration:underline; +} + + + +/*** AUXUILLARY STUFF (quotes, verses) **/ + +.verse { +font-size:1em; +line-height:1.125em; +color:#666; +color:#682; +color:inherit; +border-left:0.25em solid #eee; +padding-left:0.75em; + +} diff -r 05e666949a4f -r a72ac82bb785 org/sloman.org --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/org/sloman.org Tue Aug 13 00:47:01 2013 -0400 @@ -0,0 +1,936 @@ +#+TITLE:Transcript of Aaron Sloman - Artificial Intelligence - Psychology - Oxford Interview +#+AUTHOR:Dylan Holmes +#+EMAIL: +#+STYLE: + + +#+BEGIN_QUOTE + + + + + + + + + + + + + + + +*Editor's note:* This is a working draft transcript which I made of +[[http://www.youtube.com/watch?feature=player_detailpage&v=iuH8dC7Snno][this nice interview]] of Aaron Sloman. Having just finished one +iteration of transcription, I still need to go in and clean up the +formatting and fix the parts that I misheard, so you can expect the +text to improve significantly in the near future. + +To the extent that this is my work, you have my permission to make +copies of this transcript for your own purposes. Also, feel free to +e-mail me with comments or corrections. + +You can send mail to =transcript@aurellem.org=. + +Cheers, + +---Dylan +#+END_QUOTE + + + +* Introduction + +** Aaron Sloman evolves into a philosopher of AI +[0:09] My name is Aaron Sloman. My first degree many years ago in +Capetown University was in Physics and Mathematics, and I intended to +go and be a mathematician. I came to Oxford and encountered +philosophers --- I had started reading philosophy and discussing +philosophy before then, and then I found that there were philosophers +who said things about mathematics that I thought were wrong, so +gradually got more and more involved in [philosophy] discussions and +switched to doing philosophy DPhil. Then I became a philosophy +lecturer and about six years later, I was introduced to artificial +intelligence when I was a lecturer at Sussex University in philosophy +and I very soon became convinced that the best way to make progress in +both areas of philosophy (including philosophy of mathematics which I +felt i hadn't dealt with adequately in my DPhil) about the philosophy +of mathematics, philosophy of mind, philsophy of language and all +those things---the best way was to try to design and test working +fragments of mind and maybe eventually put them all together but +initially just working fragments that would do various things. + +[1:12] And I learned to program and ~ with various other people +including ~Margaret Boden whom you've interviewed, developed---helped +develop an undergraduate degree in AI and other things and also began +to do research in AI and so on which I thought of as doing philosophy, +primarily. + +[1:29] And then I later moved to the University of Birmingham and I +was there --- I came in 1991 --- and I've been retired for a while but +I'm not interested in golf or gardening so I just go on doing full +time research and my department is happy to keep me on without paying +me and provide space and resources and I come, meeting bright people +at conferences and try to learn and make progress if I can. + +** AI is hard, in part because there are tempting non-problems. + +One of the things I learnt and understood more and more over the many +years --- forty years or so since I first encountered AI --- is how +hard the problems are, and in part that's because it's very often +tempting to /think/ the problem is something different from what it +actually is, and then people design solutions to the non-problems, and +I think of most of my work now as just helping to clarify what the +problems are: what is it that we're trying to explain --- and maybe +this is leading into what you wanted to talk about: + +I now think that one of the ways of getting a deep understanding of +that is to find out what were the problems that biological evolution +solved, because we are a product of /many/ solutions to /many/ +problems, and if we just try to go in and work out what the whole +system is doing, we may get it all wrong, or badly wrong. + + +* What problems of intelligence did evolution solve? + +** Intelligence consists of solutions to many evolutionary problems; no single development (e.g. communication) was key to human-level intelligence. + +[2:57] Well, first I would challenge that we are the dominant +species. I know it looks like that but actually if you count biomass, +if you count number of species, if you count number of individuals, +the dominant species are microbes --- maybe not one of them but anyway +they're the ones who dominate in that sense, and furthermore we are +mostly --- we are largely composed of microbes, without which we +wouldn't survive. + + +# ** Many nonlinguistic competences require sophisticated internal representations +[3:27] But there are things that make humans (you could say) best at +those things, or worst at those things, but it's a combination. And I +think it was a collection of developments of which there isn't any +single one. [] there might be, some people say, human language which +changed everything. By our human language, they mean human +communication in words, but I think that was a later development from +what must have started as the use of /internal/ forms of +representation --- which are there in nest-building birds, in +pre-verbal children, in hunting mammals --- because you can't take in +information about a complex structured environment in which things can +change and you may have to be able to work out what's possible and +what isn't possible, without having some way of representing the +components of the environment, their relationships, the kinds of +things they can and can't do, the kinds of things you might or might +not be able to do --- and /that/ kind of capability needs internal +languages, and I and colleagues [at Birmingham] have been referring to +them as generalized languages because some people object to +referring...to using language to refer to something that isn't used +for communication. But from that viewpoint, not only humans but many +other animals developed abilities to do things to their environment to +make them more friendly to themselves, which depended on being able to +represent possible futures, possible actions, and work out what's the +best thing to do. + +[5:13] And nest-building in corvids for instance---crows, magpies, + [hawks], and so on --- are way beyond what current robots can do, and + in fact I think most humans would be challenged if they had to go and + find a collection of twigs, one at a time, maybe bring them with just + one hand --- or with your mouth --- and assemble them into a + structure that, you know, is shaped like a nest, and is fairly rigid, + and you could trust your eggs in them when wind blows. But they're + doing it, and so ... they're not our evolutionary ancestors, but + they're an indication --- and that example is an indication --- of + what must have evolved in order to provide control over the + environment in /that/ species. + +** Speculation about how communication might have evolved from internal lanagues. +[5:56] And I think hunting mammals, fruit-picking mammals, mammals +that can rearrange parts of the environment, provide shelters, needed +to have .... also needed to have ways of representing possible +futures, not just what's there in the environment. I think at a later +stage, that developed into a form of communication, or rather the +/internal/ forms of representation became usable as a basis for +providing [context] to be communicated. And that happened, I think, +initially through performing actions that expressed intentions, and +probably led to situtations where an action (for instance, moving some +large object) was performed more easily, or more successfully, or more +accurately if it was done collaboratively. So someone who had worked +out what to do might start doing it, and then a conspecific might be +able to work out what the intention is, because that person has the +/same/ forms of representation and can build theories about what's +going on, and might then be able to help. + +[7:11] You can imagine that if that started happening more (a lot of +collaboration based on inferred intentions and plans) then sometimes +the inferences might be obscure and difficult, so the /actions/ might +be enhanced to provide signals as to what the intention is, and what +the best way is to help, and so on. + +[7:35] So, this is all handwaving and wild speculation, but I think +it's consistent with a large collection of facts which one can look at +--- and find if one looks for them, but one won't know if [some]one +doesn't look for them --- about the way children, for instance, who +can't yet talk, communicate, and the things they'll do, like going to +the mother and turning the face to point in the direction where the +child wants it to look and so on; that's an extreme version of action +indicating intention. + +[8:03] Anyway. That's a very long roundabout answer to one conjecture +that the use of communicative language is what gave humans their +unique power to create and destroy and whatever, and I'm saying that +if by that you mean /communicative/ language, then I'm saying there +was something before that which was /non/-communicative language, and I +suspect that noncommunicative language continues to play a deep role +in /all/ human perception ---in mathematical and scientific reasoning, in +problem solving --- and we don't understand very much about it. + +[8:48] +I'm sure there's a lot more to be said about the development of +different kinds of senses, the development of brain structures and +mechanisms is above all that, but perhaps I've droned on long enough +on that question. + + +* How do language and internal states relate to AI? + +[9:09] Well, I think most of the human and animal capabilities that +I've been referring to are not yet to be found in current robots or +[computing] systems, and I think there are two reasons for that: one +is that it's intrinsically very difficult; I think that in particular +it may turn out that the forms of information processing that one can +implement on digital computers as we currently know them may not be as +well suited to performing some of these tasks as other kinds of +computing about which we don't know so much --- for example, I think +there may be important special features about /chemical/ computers +which we might [talk about in a little bit? find out about]. + +** In AI, false assumptions can lead investigators astray. +[9:57] So, one of the problems then is that the tasks are hard ... but +there's a deeper problem as to why AI hasn't made a great deal of +progress on these problems that I'm talking about, and that is that +most AI researchers assume things---and this is not just AI +researchers, but [also] philsophers, and psychologists, and people +studying animal behavior---make assumptions about what it is that +animals or humans do, for instance make assumptions about what vision +is for, or assumptions about what motivation is and how motivation +works, or assumptions about how learning works, and then they try --- +the AI people try --- to model [or] build systems that perform those +assumed functions. So if you get the /functions/ wrong, then even if +you implement some of the functions that you're trying to implement, +they won't necessarily perform the tasks that the initial objective +was to imitate, for instance the tasks that humans, and nest-building +birds, and monkeys and so on can perform. + +** Example: Vision is not just about finding surfaces, but about finding affordances. +[11:09] I'll give you a simple example --- well, maybe not so simple, +but --- It's often assumed that the function of vision in humans (and +in other animals with good eyesight and so on) is to take in optical +information that hits the retina, and form into the (maybe changing +--- or, really, in our case definitely changing) patterns of +illumination where there are sensory receptors that detect those +patterns, and then somehow from that information (plus maybe other +information gained from head movement or from comparisons between two +eyes) to work out what there was in the environment that produced +those patterns, and that is often taken to mean \ldquo{}where were the +surfaces off which the light bounced before it came to me\rdquo{}. So +you essentially think of the task of the visual system as being to +reverse the image formation process: so the 3D structure's there, the +lens causes the image to form in the retina, and then the brain goes +back to a model of that 3D structure there. That's a very plausible +theory about vision, and it may be that that's a /subset/ of what +human vision does, but I think James Gibson pointed out that that kind +of thing is not necessarily going to be very useful for an organism, +and it's very unlikely that that's the main function of perception in +general, namely to produce some physical description of what's out +there. + +[12:37] What does an animal /need/? It needs to know what it can do, +what it can't do, what the consequences of its actions will be +.... so, he introduced the word /affordance/, so from his point of +view, the function of vision, perception, are to inform the organism +of what the /affordances/ are for action, where that would mean what +the animal, /given/ its morphology (what it can do with its mouth, its +limbs, and so on, and the ways it can move) what it can do, what its +needs are, what the obstacles are, and how the environment supports or +obstructs those possible actions. + +[13:15] And that's a very different collection of information +structures that you need from, say, \ldquo{}where are all the +surfaces?\rdquo{}: if you've got all the surfaces, /deriving/ the +affordances would still be a major task. So, if you think of the +perceptual system as primarily (for biological organisms) being +devices that provide information about affordances and so on, then the +tasks look very different. And most of the people working, doing +research on computer vision in robots, I think haven't taken all that +on board, so they're trying to get machines to do things which, even +if they were successful, would not make the robots very intelligent +(and in fact, even the ones they're trying to do are not really easy +to do, and they don't succeed very well--- although, there's progress; +I shouldn't disparage it too much.) + +** Online and offline intelligence + +[14:10] It gets more complex as animals get more sophisticated. So, I +like to make a distinction between online intelligence and offline +intelligence. So, for example, if I want to pick something up --- like +this leaf --- I was able to select +it from all the others in there, and while moving my hand towards it, +I was able to guide its trajectory, making sure it was going roughly +in the right direction --- as opposed to going out there, which +wouldn't have been able to pick it up --- and these two fingers ended +up with a portion of the leaf between them, so that I was able to tell +when I'm ready to do that +and at that point, I clamped my fingers and then I could pick up the +leaf. + +[14:54] Whereas, --- and that's an example of online intelligence: +during the performance of an action (both from the stage where it's +initiated, and during the intermediate stages, and where it's +completed) I'm taking in information relevant to controlling all those +stages, and that relevant information keeps changing. That means I +need stores of transient information which gets discarded almost +immediately and replaced or something. That's online intelligence. And +there are many forms; that's just one example, and Gibson discussed +quite a lot of examples which I won't try to replicate now. + +[15:30] But in offline intelligence, you're not necessarily actually +/performing/ the actions when you're using your intelligence; you're +thinking about /possible/ actions. So, for instance, I could think +about how fast or by what route I would get back to the lecture room +if I wanted to [get to the next talk] or something. And I know where +the door is, roughly speaking, and I know roughly which route I would +take, when I go out, I should go to the left or to the right, because +I've stored information about where the spaces are, where the +buildings are, where the door was that we came out --- but in using +that information to think about that route, I'm not actually +performing the action. I'm not even /simulating/ it in detail: the +precise details of direction and speed and when to clamp my fingers, +or when to contract my leg muscles when walking, are all irrelevant to +thinking about a good route, or thinking about the potential things +that might happen on the way. Or what would be a good place to meet +someone who I think [for an acquaintance in particular] --- [barber] +or something --- I don't necessarily have to work out exactly /where/ +the person's going to stand, or from what angle I would recognize +them, and so on. + +[16:46] So, offline intelligence --- which I think became not just a +human competence; I think there are other animals that have aspects of +it: Squirrels are very impressive as you watch them. Gray squirrels at +any rate, as you watch them defeating squirrel-proof birdfeeders, seem +to have a lot of that [offline intelligence], as well as the online +intelligence when they eventually perform the action they've worked +out [] that will get them to the nuts. + +[17:16] And I think that what happened during our evolution is that +mechanisms for acquiring and processing and storing and manipulating +information that is more and more remote from the performance of +actions developed. An example is taking in information about where +locations are that you might need to go to infrequently: There's a +store of a particular type of material that's good for building on +roofs of houses or something out around there in some +direction. There's a good place to get water somewhere in another +direction. There are people that you'd like to go and visit in +another place, and so on. + +[17:59] So taking in information about an extended environment and +building it into a structure that you can make use of for different +purposes is another example of offline intelligence. And when we do +that, we sometimes use only our brains, but in modern times, we also +learned how to make maps on paper and walls and so on. And it's not +clear whether the stuff inside our heads has the same structures as +the maps we make on paper: the maps on paper have a different +function; they may be used to communicate with others, or meant for +/looking/ at, whereas the stuff in your head you don't /look/ at; you +use it in some other way. + +[18:46] So, what I'm getting at is that there's a great deal of human +intelligence (and animal intelligence) which is involved in what's +possible in the future, what exists in distant places, what might have +happened in the past (sometimes you need to know why something is as +it is, because that might be relevant to what you should or shouldn't +do in the future, and so on), and I think there was something about +human evolution that extended that offline intelligence way beyond +that of animals. And I don't think it was /just/ human language, (but +human language had something to do with it) but I think there was +something else that came earlier than language which involves the +ability to use your offline intelligence to discover something that +has a rich mathematical structure. + +** Example: Even toddlers use sophisticated geometric knowledge +#+<> +[19:44] I'll give you a simple example: if you look through a gap, you +can see something that's on the other side of the gap. Now, you +/might/ see what you want to see, or you might see only part of it. If +you want to see more of it, which way would you move? Well, you could +either move /sideways/, and see through the gap---and see it roughly +the same amount but a different part of it [if it's a ????], or you +could move /towards/ the gap and then your view will widen as you +approach the gap. Now, there's a bit of mathematics in there, insofar +as you are implicitly assuming that information travels in straight +lines, and as you go closer to a gap, the straight lines that you can +draw from where you are through the gap, widen as you approach that +gap. Now, there's a kind of theorem of Euclidean geometry in there +which I'm not going to try to state very precisely (and as far as I +know, wasn't stated explicitly in Euclidean geometry) but it's +something every toddler--- human toddler---learns. (Maybe other +animals also know it, I don't know.) But there are many more things, +actions to perform, to get you more information about things, actions +to perform to conceal information from other people, actions that will +enable you to operate, to act on a rigid object in one place in order +to produce an effect on another place. So, there's a lot of stuff that +involves lines and rotations and angles and speeds and so on that I +think humans (maybe, to a lesser extent, other animals) develop the +ability to think about in a generic way. That means that you could +take out the generalizations from the particular contexts and then +re-use them in a new contexts in ways that I think are not yet +represented at all in AI and in theories of human learning in any [] +way --- although some people are trying to study learning of mathematics. + +* Animal intelligence + +** The priority is /cataloguing/ what competences have evolved, not ranking them. +[22:03] I wasn't going to challenge the claim that humans can do more +sophisticated forms of [tracking], just to mention that there are some +things that other animals can do which are in some ways comparable, +and some ways superior to [things] that humans can do. In particular, +there are species of birds and also, I think, some rodents --- +squirrels, or something --- I don't know enough about the variety --- +that can hide nuts and remember where they've hidden them, and go back +to them. And there have been tests which show that some birds are able +to hide tens --- you know, [eighteen] or something nuts --- and to +remember which ones have been taken, which ones haven't, and so +on. And I suspect most humans can't do that. I wouldn't want to say +categorically that maybe we couldn't, because humans are very +[varied], and also [a few] people can develop particular competences +through training. But it's certainly not something I can do. + + +** AI can be used to test philosophical theories +[23:01] But I also would like to say that I am not myself particularly +interested in trying to align animal intelligences according to any +kind of scale of superiority; I'm just trying to understand what it +was that biological evolution produced, and how it works, and I'm +interested in AI /mainly/ because I think that when one comes up with +theories about how these things work, one needs to have some way of +testing the theory. And AI provides ways of implementing and testing +theories that were not previously available: Immanuel Kant was trying +to come up with theories about how minds work, but he didn't have any +kind of a mechanism that he could build to test his theory about the +nature of mathematical knowledge, for instance, or how concepts were +developed from babyhood onward. Whereas now, if we do develop a +theory, we have a criterion of adequacy, namely it should be precise +enough and rich enough and detailed to enable a model to be +built. And then we can see if it works. + +[24:07] If it works, it doesn't mean we've proved that the theory is +correct; it just shows it's a candidate. And if it doesn't work, then +it's not a candidate as it stands; it would need to be modified in +some way. + +* Is abstract general intelligence feasible? + +** It's misleading to compare the brain and its neurons to a computer made of transistors +[24:27] I think there's a lot of optimism based on false clues: +the...for example, one of the false clues is to count the number of +neurons in the brain, and then talk about the number of transistors +you can fit into a computer or something, and then compare them. It +might turn out that the study of the way synapses work (which leads +some people to say that a typical synapse [] in the human brain has +computational power comparable to the Internet a few years ago, +because of the number of different molecules that are doing things, +the variety of types of things that are being done in those molecular +interactions, and the speed at which they happen, if you somehow count +up the number of operations per second or something, then you get +these comparable figures). + +** For example, brains may rely heavily on chemical information processing +Now even if the details aren't right, there may just be a lot of +information processing that...going on in brains at the /molecular/ +level, not the neural level. Then, if that's the case, the processing +units will be orders of magnitude larger in number than the number of +neurons. And it's certainly the case that all the original biological +forms of information processing were chemical; there weren't brains +around, and still aren't in most microbes. And even when humans grow +their brains, the process of starting from a fertilized egg and +producing this rich and complex structure is, for much of the time, +under the control of chemical computations, chemical information +processing---of course combined with physical sorts of materials and +energy and so on as well. + +[26:25] So it would seem very strange if all that capability was +something thrown away when you've got a brain and all the information +processing, the [challenges that were handled in making a brain], +... This is handwaving on my part; I'm just saying that we /might/ +learn that what brains do is not what we think they do, and that +problems of replicating them are not what we think they are, solely in +terms of numerical estimate of time scales, the number of components, +and so on. + +** Brain algorithms may simply be optimized for certain kinds of information processing other than bit manipulations +[26:56] But apart from that, the other basis of skepticism concerns +how well we understand what the problems are. I think there are many +people who try to formalize the problems of designing an intelligent +system in terms of streams of information thought of as bit streams or +collections of bit streams, and they think of as the problems of +intelligence as being the construction or detection of patterns in +those, and perhaps not just detection of patterns, but detection of +patterns that are useable for sending /out/ streams to control motors +and so on in order to []. And that way of conceptualizing the problem +may lead on the one hand to oversimplification, so that the things +that /would/ be achieved, if those goals were achieved, maybe much +simpler, in some ways inadequate. Or the replication of human +intelligence, or the matching of human intelligence---or for that +matter, squirrel intelligence---but in another way, it may also make +the problem harder: it may be that some of the kinds of things that +biological evolution has achieved can't be done that way. And one of +the ways that might turn out to be the case is not because it's not +impossible in principle to do some of the information processing on +artificial computers-based-on-transistors and other bit-manipulating +[]---but it may just be that the computational complexity of solving +problems, processes, or finding solutions to complex problems, are +much greater and therefore you might need a much larger universe than +we have available in order to do things. + +** Example: find the shortest path by dangling strings +[28:55] Then if the underlying mechanisms were different, the +information processing mechanisms, they might be better tailored to +particular sorts of computation. There's a [] example, which is +finding the shortest route if you've got a collection of roads, and +they may be curved roads, and lots of tangled routes from A to B to C, +and so on. And if you start at A and you want to get to Z --- a place +somewhere on that map --- the process of finding the shortest route +will involve searching through all these different possibilities and +rejecting some that are longer than others and so on. But if you make +a model of that map out of string, where these strings are all laid +out on the maps and so have the lengths of the routes. Then if you +hold the two knots in the string -- it's a network of string --- which +correspond to the start point and end point, then /pull/, then the +bits of string that you're left with in a straight line will give you +the shortest route, and that process of pulling just gets you the +solution very rapidly in a parallel computation, where all the others +just hang by the wayside, so to speak. + +** In sum, we know surprisingly little about the kinds of problems that evolution solved, and the manner in which they were solved. +[30:15] Now, I'm not saying brains can build networks of string and +pull them or anything like that; that's just an illustration of how if +you have the right representation, correctly implemented---or suitably +implemented---for a problem, then you can avoid very combinatorially +complex searches, which will maybe grow exponentially with the number +of components in your map, whereas with this thing, the time it takes +won't depend on how many strings you've [got on the map]; you just +pull, and it will depend only on the shortest route that exists in +there. Even if that shortest route wasn't obvious on the original map. + + +[30:59] So that's a rather long-winded way of formulating the +conjecture which---of supporting, a roundabout way of supporting the +conjecture that there may be something about the way molecules perform +computations where they have the combination of continuous change as +things move through space and come together and move apart, and +whatever --- and also snap into states that then persist, so [as you +learn from] quantum mechanics, you can have stable molecular +structures which are quite hard to separate, and then in catalytic +processes you can separate them, or extreme temperatures, or strong +forces, but they may nevertheless be able to move very rapidly in some +conditions in order to perform computations. + +[31:49] Now there may be things about that kind of structure that +enable searching for solutions to /certain/ classes of problems to be +done much more efficiently (by brain) than anything we could do with +computers. It's just an open question. + +[32:04] So it /might/ turn out that we need new kinds of technology +that aren't on the horizon in order to replicate the functions that +animal brains perform ---or, it might not. I just don't know. I'm not +claiming that there's strong evidence for that; I'm just saying that +it might turn out that way, partly because I think we know less than +many people think we know about what biological evolution achieved. + +[32:28] There are some other possibilities: we may just find out that +there are shortcuts no one ever thought of, and it will all happen +much more quickly---I have an open mind; I'd be surprised, but it +could turn up. There /is/ something that worries me much more than the +singularity that most people talk about, which is machines achieving +human-level intelligence and perhaps taking over [the] planet or +something. There's what I call the /singularity of cognitive +catch-up/ ... + +* A singularity of cognitive catch-up + +** What if it will take a lifetime to learn enough to make something new? +... SCC, singularity of cognitive catch-up, which I think we're close +to, or maybe have already reached---I'll explain what I mean by +that. One of the products of biological evolution---and this is one of +the answers to your earlier questions which I didn't get on to---is +that humans have not only the ability to make discoveries that none of +their ancestors have ever made, but to shorten the time required for +similar achievements to be reached by their offspring and their +descendants. So once we, for instance, worked out ways of complex +computations, or ways of building houses, or ways of finding our way +around, we don't need...our children don't need to work it out for +themselves by the same lengthy trial and error procedure; we can help +them get there much faster. + +Okay, well, what I've been referring to as the singularity of +cognitive catch-up depends on the fact that---fairly obvious, and it's +often been commented on---that in case of humans, it's not necessary +for each generation to learn what previous generations learned /in the +same way/. And we can speed up learning once something has been +learned, [it is able to] be learned by new people. And that has meant +that the social processes that support that kind of education of the +young can enormously accelerate what would have taken...perhaps +thousands [or] millions of years for evolution to produce, can happen in +a much shorter time. + + +[34:54] But here's the catch: in order for a new advance to happen --- +so for something new to be discovered that wasn't there before, like +Newtonian mechanics, or the theory of relativity, or Beethoven's music +or [style] or whatever --- the individuals have to have traversed a +significant amount of what their ancestors have learned, even if they +do it much faster than their ancestors, to get to the point where they +can see the gaps, the possibilities for going further than their +ancestors, or their parents or whatever, have done. + +[35:27] Now in the case of knowledge of science, mathematics, +philosophy, engineering and so on, there's been a lot of accumulated +knowledge. And humans are living a /bit/ longer than they used to, but +they're still living for [whatever it is], a hundred years, or for +most people, less than that. So you can imagine that there might come +a time when in a normal human lifespan, it's not possible for anyone +to learn enough to understand the scope and limits of what's already +been achieved in order to see the potential for going beyond it and to +build on what's already been done to make that...those future steps. + +[36:10] So if we reach that stage, we will have reached the +singularity of cognitive catch-up because the process of education +that enables individuals to learn faster than their ancestors did is +the catching-up process, and it may just be that we at some point +reach a point where catching up can only happen within a lifetime of +an individual, and after that they're dead and they can't go +beyond. And I have some evidence that there's a lot of that around +because I see a lot of people coming up with what /they/ think of as +new ideas which they've struggled to come up with, but actually they +just haven't taken in some of what was...some of what was done [] by +other people, in other places before them. And I think that despite +the availability of search engines which make it /easier/ for people +to get the information---for instance, when I was a student, if I +wanted to find out what other people had done in the field, it was a +laborious process---going to the library, getting books, and +---whereas now, I can often do things in seconds that would have taken +hours. So that means that if seconds [are needed] for that kind of +work, my lifespan has been extended by a factor of ten or +something. So maybe that /delays/ the singularity, but it may not +delay it enough. But that's an open question; I don't know. And it may +just be that in some areas, this is more of a problem than others. For +instance, it may be that in some kinds of engineering, we're handing +over more and more of the work to machines anyways and they can go on +doing it. So for instance, most of the production of computers now is +done by a computer-controlled machine---although some of the design +work is done by humans--- a lot of /detail/ of the design is done by +computers, and they produce the next generation, which then produces +the next generation, and so on. + +[37:57] I don't know if humans can go on having major advances, so +it'll be kind of sad if we can't. + +* Spatial reasoning: a difficult problem + +[38:15] Okay, well, there are different problems [ ] mathematics, and +they have to do with properties. So for instance a lot of mathematics +that can be expressed in terms of logical structures or algebraic +structures and those are pretty well suited for manipulation and...on +computers, and if a problem can be specified using the +logical/algebraic notation, and the solution method requires creating +something in that sort of notation, then computers are pretty good, +and there are lots of mathematical tools around---there are theorem +provers and theorem checkers, and all kinds of things, which couldn't +have existed fifty, sixty years ago, and they will continue getting +better. + + +But there was something that I was [[example-gap][alluding to earlier]] when I gave the +example of how you can reason about what you will see by changing your +position in relation to a door, where what you are doing is using your +grasp of spatial structures and how as one spatial relationship +changes namely you come closer to the door or move sideways and +parallel to the wall or whatever, other spatial relationships change +in parallel, so the lines from your eyes through to other parts of +the...parts of the room on the other side of the doorway change, +spread out more as you go towards the doorway, and as you move +sideways, they don't spread out differently, but focus on different +parts of the internal ... that they access different parts of the +... of the room. + +Now, those are examples of ways of thinking about relationships and +changing relationships which are not the same as thinking about what +happens if I replace this symbol with that symbol, or if I substitute +this expression in that expression in a logical formula. And at the +moment, I do not believe that there is anything in AI amongst the +mathematical reasoning community, the theorem-proving community, that +can model the processes that go on when a young child starts learning +to do Euclidean geometry and is taught things about---for instance, I +can give you a proof that the angles of any triangle add up to a +straight line, 180 degrees. + +** Example: Spatial proof that the angles of any triangle add up to a half-circle +There are standard proofs which involves starting with one triangle, +then adding a line parallel to the base one of my former students, +Mary Pardoe, came up with which I will demonstrate with this --- can you see it? If I have a triangle here that's got +three sides, if I put this thing on it, on one side --- let's say the +bottom---I can rotate it until it lies along the second...another +side, and then maybe move it up to the other end ~. Then I can rotate +it again, until it lies on the third side, and move it back to the +other end. And then I'll rotate it again and it'll eventually end up +on the original side, but it will have changed the direction it's +pointing in --- and it won't have crossed over itself so it will have +gone through a half-circle, and that says that the three angles of a +triangle add up to the rotations of half a circle, which is a +beautiful kind of proof and almost anyone can understand it. Some +mathematicians don't like it, because they say it hides some of the +assumptions, but nevertheless, as far as I'm concerned, it's an +example of a human ability to do reasoning which, once you've +understood it, you can see will apply to any triangle --- it's got to +be a planar triangle --- not a triangle on a globe, because then the +angles can add up to more than ... you can have three /right/ angles +if you have an equator...a line on the equator, and a line going up to +to the north pole of the earth, and then you have a right angle and +then another line going down to the equator, and you have a right +angle, right angle, right angle, and they add up to more than a +straight line. But that's because the triangle isn't in the plane, +it's on a curved surface. In fact, that's one of the +differences...definitional differences you can take between planar and +curved surfaces: how much the angles of a triangle add up to. But our +ability to /visualize/ and notice the generality in that process, and +see that you're going to be able to do the same thing using triangles +that stretch in all sorts of ways, or if it's a million times as +large, or if it's made...you know, written on, on...if it's drawn in +different colors or whatever --- none of that's going to make any +difference to the essence of that process. And that ability to see +the commonality in a spatial structure which enables you to draw some +conclusions with complete certainty---subject to the possibility that +sometimes you make mistakes, but when you make mistakes, you can +discover them, as has happened in the history of geometrical theorem +proving. Imre Lakatos had a wonderful book called [[http://en.wikipedia.org/wiki/Proofs_and_Refutations][/Proofs and +Refutations/]] --- which I won't try to summarize --- but he has +examples: mistakes were made; that was because people didn't always +realize there were subtle subcases which had slightly different +properties, and they didn't take account of that. But once they're +noticed, you rectify that. + +** Geometric results are fundamentally different than experimental results in chemistry or physics. +[43:28] But it's not the same as doing experiments in chemistry and +physics, where you can't be sure it'll be the same on [] or at a high +temperature, or in a very strong magnetic field --- with geometric +reasoning, in some sense you've got the full information in front of +you; even if you don't always notice an important part of it. So, that +kind of reasoning (as far as I know) is not implemented anywhere in a +computer. And most people who do research on trying to model +mathematical reasoning, don't pay any attention to that, because of +... they just don't think about it. They start from somewhere else, +maybe because of how they were educated. I was taught Euclidean +geometry at school. Were you? + +(Adam ford: Yeah) + +Many people are not now. Instead they're taught set theory, and +logic, and arithmetic, and [algebra], and so on. And so they don't use +that bit of their brains, without which we wouldn't have built any of +the cathedrals, and all sorts of things we now depend on. + +* Is near-term artificial general intelligence likely? + +** Two interpretations: a single mechanism for all problems, or many mechanisms unified in one program. + +[44:35] Well, this relates to what's meant by general. And when I +first encountered the AGI community, I thought that what they all +meant by general intelligence was /uniform/ intelligence --- +intelligence based on some common simple (maybe not so simple, but) +single powerful mechanism or principle of inference. And there are +some people in the community who are trying to produce things like +that, often in connection with algorithmic information theory and +computability of information, and so on. But there's another sense of +general which means that the system of general intelligence can do +lots of different things, like perceive things, understand language, +move around, make things, and so on --- perhaps even enjoy a joke; +that's something that's not nearly on the horizon, as far as I +know. Enjoying a joke isn't the same as being able to make laughing +noises. + +Given, then, that there are these two notions of general +intelligence---there's one that looks for one uniform, possibly +simple, mechanism or collection of ideas and notations and algorithms, +that will deal with any problem that's solvable --- and the other +that's general in the sense that it can do lots of different things +that are combined into an integrated architecture (which raises lots +of questions about how you combine these things and make them work +together) and we humans, certainly, are of the second kind: we do all +sorts of different things, and other animals also seem to be of the +second kind, perhaps not as general as humans. Now, it may turn out +that in some near future time, who knows---decades, a few +decades---you'll be able to get machines that are capable of solving +in a time that will depend on the nature of the problem, but any +problem that is solvable, and they will be able to do it in some sort +of tractable time --- of course, there are some problems that are +solvable that would require a larger universe and a longer history +than the history of the universe, but apart from that constraint, +these machines will be able to do anything []. But to be able to do +some of the kinds of things that humans can do, like the kinds of +geometrical reasoning where you look at the shape and you abstract +away from the precise angles and sizes and shapes and so on, and +realize there's something general here, as must have happened when our +ancestors first made the discoveries that eventually put together in +Euclidean geometry. + +It may be that that requires mechanisms of a kind that we don't know +anything about at the moment. Maybe brains are using molecules and +rearranging molecules in some way that supports that kind of +reasoning. I'm not saying they are --- I don't know, I just don't see +any simple...any obvious way to map that kind of reasoning capability +onto what we currently do on computers. There is---and I just +mentioned this briefly beforehand---there is a kind of thing that's +sometimes thought of as a major step in that direction, namely you can +build a machine (or a software system) that can represent some +geometrical structure, and then be told about some change that's going +to happen to it, and it can predict in great detail what'll +happen. And this happens for instance in game engines, where you say +we have all these blocks on the table and I'll drop one other block, +and then [the thing] uses Newton's laws and properties of rigidity of +the parts and the elasticity and also stuff about geometries and space +and so on, to give you a very accurate representation of what'll +happen when this brick lands on this pile of things, [it'll bounce and +go off, and so on]. And you just, with more memory and more CPU power, +you can increase the accuracy--- but that's totally different than +looking at /one/ example, and working out what will happen in a whole +/range/ of cases at a higher level of abstraction, whereas the game +engine does it in great detail for /just/ this case, with /just/ those +precise things, and it won't even know what the generalizations are +that it's using that would apply to others []. So, in that sense, [we] +may get AGI --- artificial general intelligence --- pretty soon, but +it'll be limited in what it can do. And the other kind of general +intelligence which combines all sorts of different things, including +human spatial geometrical reasoning, and maybe other things, like the +ability to find things funny, and to appreciate artistic features and +other things may need forms of pattern-mechanism, and I have an open +mind about that. + +* Abstract General Intelligence impacts + +[49:53] Well, as far as the first type's concerned, it could be useful +for all kinds of applications --- there are people who worry about +where there's a system that has that type of intelligence, might in +some sense take over control of the planet. Well, humans often do +stupid things, and they might do something stupid that would lead to +disaster, but I think it's more likely that there would be other +things [] lead to disaster--- population problems, using up all the +resources, destroying ecosystems, and whatever. But certainly it would +go on being useful to have these calculating devices. Now, as for the +second kind of them, I don't know---if we succeeded at putting +together all the parts that we find in humans, we might just make an +artificial human, and then we might have some of them as your friends, +and some of them we might not like, and some of them might become +teachers or whatever, composers --- but that raises a question: could +they, in some sense, be superior to us, in their learning +capabilities, their understanding of human nature, or maybe their +wickedness or whatever --- these are all issues in which I expect the +best science fiction writers would give better answers than anything I +could do, but I did once fantasize when I [back] in 1978, that perhaps +if we achieved that kind of thing, that they would be wise, and gentle +and kind, and realize that humans are an inferior species that, you +know, have some good features, so they'd keep us in some kind of +secluded...restrictive kind of environment, keep us away from +dangerous weapons, and so on. And find ways of cohabitating with +us. But that's just fantasy. + +Adam Ford: Awesome. Yeah, there's an interesting story /With Folded +Hands/ where [the computers] want to take care of us and want to +reduce suffering and end up lobotomizing everybody [but] keeping them +alive so as to reduce the suffering. + +Aaron Sloman: Not all that different from /Brave New World/, where it +was done with drugs and so on, but different humans are given +different roles in that system, yeah. + +There's also /The Time Machine/, H.G. Wells, where the ... in the +distant future, humans have split in two: the Eloi, I think they were +called, they lived underground, they were the [] ones, and then---no, +the Morlocks lived underground; Eloi lived on the planet; they were +pleasant and pretty but not very bright, and so on, and they were fed +on by ... + +Adam Ford: [] in the future. + +Aaron Sloman: As I was saying, if you ask science fiction writers, +you'll probably come up with a wide variety of interesting answers. + +Adam Ford: I certainly have; I've spoken to [] of Birmingham, and +Sean Williams, ... who else? + +Aaron Sloman: Did you ever read a story by E.M. Forrester called /The +Machine Stops/ --- very short story, it's [[http://archive.ncsa.illinois.edu/prajlich/forster.html][on the Internet somewhere]] +--- it's about a time when people sitting ... and this was written in +about [1914 ] so it's about...over a hundred years ago ... people are +in their rooms, they sit in front of screens, and they type things, +and they communicate with one another that way, and they don't meet; +they have debates, and they give lectures to their audiences that way, +and then there's a woman whose son says \ldquo{}I'd like to see +you\rdquo{} and she says \ldquo{}What's the point? You've got me at +this point \rdquo{} but he wants to come and talk to her --- I won't +tell you how it ends, but. + +Adam Ford: Reminds me of the Internet. + +Aaron Sloman: Well, yes; he invented ... it was just extraordinary +that he was able to do that, before most of the components that we +need for it existed. + +Adam Ford: [Another person who did that] was Vernor Vinge [] /True +Names/. + +Aaron Sloman: When was that written? + +Adam Ford: The seventies. + +Aaron Sloman: Okay, well a lot of the technology was already around +then. The original bits of internet were working, in about 1973, I was +sitting ... 1974, I was sitting at Sussex University trying to +use...learn LOGO, the programming language, to decide whether it was +going to be useful for teaching AI, and I was sitting [] paper +teletype, there was paper coming out, transmitting ten characters a +second from Sussex to UCL computer lab by telegraph cable, from there +to somewhere in Norway via another cable, from there by satellite to +California to a computer Xerox [] research center where they had +implemented a computer with a LOGO system on it, with someone I had +met previously in Edinburgh, Danny Bobrow, and he allowed me to have +access to this sytem. So there I was typing. And furthermore, it was +duplex typing, so every character I typed didn't show up on my +terminal until it had gone all the way there and echoed back, so I +would type, and the characters would come back four seconds later. + +[55:26] But that was the Internet, and I think Vernor Vinge was +writing after that kind of thing had already started, but I don't +know. Anyway. + +[55:41] Another...I mentioned H.G. Wells, /The Time Machine/. I +recently discovered, because [[http://en.wikipedia.org/wiki/David_Lodge_(author)][David Lodge]] had written a sort of +semi-novel about him, that he had invented Wikipedia, in advance--- he +had this notion of an encyclopedia that was free to everybody, and +everybody could contribute and [collaborate on it]. So, go to the +science fiction writers to find out the future --- well, a range of +possible futures. + +Adam Ford: Well the thing is with science fiction writers, they have +to maintain some sort of interest for their readers, after all the +science fiction which reaches us is the stuff that publishers want to +sell, and so there's a little bit of a ... a bias towards making a +plot device there, and so the dramatic sort of appeals to our +amygdala, our lizard brain; we'll sort of stay there obviously to some +extent. But I think that they do come up with sort of amazing ideas; I +think it's worth trying to make these predictions; I think that we +should more time on strategic forecasting, I mean take that seriously. + +Aaron Sloman: Well, I'm happy to leave that to others; I just want to +try to understand these problems that bother me about how things +work. And it may be that some would say that's irresponsible if I +don't think about what the implications will be. Well, understanding +how humans work /might/ enable us to make [] humans --- I suspect it +wont happen in this century; I think it's going to be too difficult.