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6th HLF – Interviews with mathematics and computer science laureates: Butler W. Lampson

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Title 6th HLF – Interviews with mathematics and computer science laureates: Butler W. Lampson
Title of Series 6th Heidelberg Laureate Forum (HLF), 2018
Author Lampson, Butler W.
License No Open Access License:
German copyright law applies. This film may be used for your own use but it may not be distributed via the internet or passed on to external parties.
DOI 10.5446/40159
Publisher Heidelberg Laureate Forum Foundation
Release Date 2018
Language English

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Subject Area Computer Science, Mathematics
Abstract Laureates at the 6th HLF sit down with Tom Geller, Tom Geller Productions, to discuss their career, mentoring and their experience at the Heidelberg Laureate Forum (HLF). These renowned scientists have been honored with most prestigious awards in mathematics and computer science: Abel Prize, ACM A.M. Turing Award, ACM Prize in Computing, Fields Medal and Nevanlinna Prize. The opinions expressed in this video do not necessarily reflect the views of the Heidelberg Laureate Forum Foundation or any other person or associated institution involved in the making and distribution of the video. Background: The Heidelberg Laureate Forum Foundation (HLFF) annually organizes the Heidelberg Laureate Forum (HLF), which is a networking event for mathematicians and computer scientists from all over the world. The HLFF was established and is funded by the German foundation the Klaus Tschira Stiftung (KTS), which promotes natural sciences, mathematics and computer science. The HLF is strongly supported by the award-granting institutions, the Association for Computing Machinery (ACM: ACM A.M. Turing Award, ACM Prize in Computing), the International Mathematical Union (IMU: Fields Medal, Nevanlinna Prize), and the Norwegian Academy of Science and Letters (DNVA: Abel Prize). The Scientific Partners of the HLFF are the Heidelberg Institute for Theoretical Studies (HITS) and Heidelberg University.

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[Music]
first of all could you summarize the
work for which you're best known and for which you receive the Turing award that it's pretty clear that when I got the Turing I worked for was the work that we did on the alto at Xerox PARC in the 1970s where basically we invented all of modern personal computing except for spreadsheets it was way too soon for the web so we didn't have anything to do with that but we invented graphical user interfaces and local area networking and client-server computing and laser printing all those things that you are familiar to you we didn't invent spreadsheets I think because we felt we didn't have any use for them it turns out that nowadays most uses of spreadsheets don't involve numbers somebody did a within Microsoft did a survey and found I'm not sure I actually believe this but they found that according to their survey only 10% of the users of Excel know about the formula bar the other 90% basically is it for making lists and it has all kinds of wonderful facilities for doing database like things on the spreadsheet but anyway we didn't you couldn't do those things on the hardware of the 1970s and we didn't do spreadsheets because we didn't care about numbers what sort of applications did you foresee what we did word processing in fact and I'm not sure whether this is still true but it was certainly true five or ten years ago that the basic data structures that were used in Microsoft work were the ones that we invented at Xerox PARC in 1973 and drawing programs and and programs like Photoshop and distributed file systems and just pretty much the whole range of things that you see if you sit down in front of a personal computer now as I understand you also had something to do with multi-user multi-user systems way back and that was earlier we didn't do that work any of that kind of work at Parc that my interests of one of my major and system interests has always been in interactive computing and in the 60s interactive computing meant multi-user mount time sharing systems because the individual machines were so expensive that it was unthinkable that you would devote a whole machine to one person the alto really was the first point at which the evolution of hardware made it even conceivable to do that now going back to the earlier times because as I say part of the HLF is about mentorship and you were at Berkeley when you were doing the multi-user that's our systems can you describe sort of what what student life was like then as compared to now well there were many aspects to it I arrived at Berkeley as a graduate student in physics in September of 1964 and I looked around for roommates and I found three people who needed a fourth and I joined that group and two months later two of my new roommates have been arrested in the first Free Speech Movement demonstration so Student Life was I don't know that makes the same as it is today are different but it certainly wasn't what I had been expecting but as far as the academics with it was there anybody who really stood out at any point in your academic career as a mentor things were a little bit odd Berkeley of course in those days computer science didn't really exist the people the Berkeley EE Department changed its name to electrical engineering and computer science actually shortly before I got there in the fall of 1964 because it's then-chairman la posada was extremely far sighted but it's easy to change the name with the department it's not so easy to actually start doing computing and at that time there were a couple of people and the faculty that had built machines in the 50s but they were basically retired they were not doing active work anymore the titular leader of the time sharing project that I joined was Dave Evans who had done some pretty substantial computer design work in industry previously but he was in the process of packing up to move to Utah where he and Ivan Sutherlands started the Evans in southern computer corporation and did the first realistic airplane simulate in the airline pilot simulation systems so his interests were really diverted he wasn't paying that much attention to this project the actual leader of the project wasn't with and was a graduate student named Mel Pirtle and I learned a lot from him I did not learn all that much from the very small number of faculty members in computing that existed at Berkeley in the mid-60s now
at that time were you already thinking in terms of human-computer interaction absolutely the whole point of this time sharing project was to must have interactive computing and to do it on a substantially lower you know in a way that was much cheaper than the way it had been done for example at MIT with the compatible time sharing system three or four years earlier that was the first successful interactive computing project but that was done on a modified IBM 7090 and we were working well we were working with hardware that was maybe a tenth of the cost and the goal was to show that you could get similar results on a much smaller scale and that in fact led to the first general-purpose time-sharing systems that were actually sold so the period between let's say 64 when you entered Berkeley and Alto would have been 73 years we started it in the fall of 1972 okay so that would have been put you at about the same age and point in your career as a lot of the people here at the HLF meaning what were your thoughts about like whoa how are you trying to find your way in the world what did you think would happen I suppose well people often ask me when I was at Berkeley I was sort of following my nose on this project which had been conceived by other people by the time I got to Jaques Park people often ask me how much did you foresee if what would happen and I think it's pretty fair to say that we foresaw just about everything we really felt that what we were doing was the obvious thing to do and we we tried to it's always been the case in computing what's enabling is the hardware as the hardware gets better different kinds of applications become feasible that just weren't feasible with the earlier generations of hardware because it would they were too slow or too expensive or too big or too power hungry or whatever so you know random example you couldn't really have laptops much earlier than the late 80s because the processors in the memory and storage were just too heavy and consumed too much power we did actually at Xerox PARC in a different group built one of the very first maybe even v4 thing that was recognized at all recognizable as a laptop in the very late 70s but it was a complete bust because it weighed 20 pounds and it was so clunky and so slow that nobody actually wanted to use it another example why do we have deep learning now until around 2010 we just didn't have the hardware resources to train interesting deep learning systems um so I had to wait for that capability to come along similarly we built the alto essentially the first moment when memory got cheap enough that you could afford to use it to hold the display image previously it would have been too costly the Altos cost about fifteen or eighteen thousand dollars to build in nineteen seventy two dollars which means eighty or ninety thousand dollars in today's money so they were not commercially feasible by any stretch of the imagination we viewed them as time machines our notion was that we knew because of we understood Moore's law that ten years later they would be commercially similar devices would be commercially feasible and we did it figured it would take ten years to figure out how right the software to actually exploit them which indeed it did in the first machine that that was commercially feasible that was based on the ideas they all tell was the Apple Macintosh which came along in 1964 and it cost about five hundred dollars to build sold for 2,500 you're putting the the Apple Macintosh well I see as the graphical because I'm with the IBM PC was a different animal entirely in those days I think of the Apple - gyah well again was a different animal it was a much more primitive system it didn't have any meaningful graphical user interface it didn't have any networking it didn't have any laser printing it was just it was a good thing and people got a lot of value out of it but it was nothing like today's pcs whereas the alto was like today's species although I'm personally very interested in personal computing history I do feel that I should redirect it sort of to to again how you found your path and the people here for the for the researchers we're at the HLF who were just now finding their paths and I'm sorry is this your first date I left the first time I've been here oh really have you noticed much change over the years you know they seem to have found a fairly good formula now I think they're doing a better job you know each time
setting the thing up to facility
facilitate contact between the laureates and the young researchers of course the laureates instinct is to talk to other laureates and the young researchers for the most part are shy and don't like to bust in so you need various mechanisms to make it move more likely that they'll actually be interaction well tell me about the interaction that you have with the laureate with the excuse me I see with the researchers here the young researchers do how do they approach you and and what sort of question approach me perhaps I sit down at lunch and then other and yeah young researchers will come in and sit next to me and then we'll start to chat typically they tell me something about what they're doing and often it has some intersection with things that I've been interested in not look at the discussion going have have any of them brought up something that surprised you or or just made you realize wow there's a whole new field out there no I don't think so I think I can keep up pretty well with what the whole new fields are anyway because my interests are fairly eclectic how do you think the students are different today from when you were in school aside from the obvious that there were no computers well the most obvious difference for computing is that yeah in when I was in school everything was brand new and there was a huge amount of low-hanging fruit almost anything you do did was likely to be a significant success because no one had ever done any of those things before and nowadays the field is much much more developed and certainly in large parts of it it's much more like traditional fields of study but on the other hand there are also domains where it's still the Wild West what would you say some of those domains are they that you find well my gran fury of computing is that we started out using computers for simulation around 1950 and whether you simulated nuclear weapons or whether you simulated payrolls the basic idea was the same you built some model of the world inside the computer you run the model and it tells you something about what's happening in yeah in the world outside and that was enormous ly successful and it paid all the bills for the first 30 years and it's still going strong but around about 1980 30 years after computing got started Hardware got cheap enough that you could start to afford to use computers for facilitating communication between people and that brought us the Internet and email and the World Wide Web and Facebook and all those other things we know and love today and that's been even more successful than computers that simulation for simulation and that's still going strong and there's still lots to do for example the state of computer mediated meetings between people who are not in the same room is too still unbelievably bad compared to at least one can I met and they ought to be but it's been another 30 years and it's time for something new and I think it's crystal clear what the next great wave is gonna be and it's going to be non-trivial interactions with the physical world and whether that means sensors or speech recognition or vision or autonomous vehicles there's an enormous range of things which are going to have even much more economically and everyday impact than the communication which in turn had much more economic and everyday impact than the simulation so it's crystal clear to me that that's where the field is not that the other things are gonna go away cuz it's still it lots of value and lots of interesting things to do in the other spaces but this is gonna be the most the most exciting aspect of computing I think in the next two or three decades and for people who let's say are tangential to well no even let me rephrase it in a different way what you said is very inspiring especially showing the the history of how this could be a new way following the two previous waves do you think that people recognize that today that the young right researchers recognize that there's there's I think it's hard for them to see it because there's an awful lot of noise and you know she just pay attention to the noise what are you gonna think you're gonna think that machine learning which has been renamed AI and blockchain are the most important things and I don't really believe in blockchain at all and although I think machine learning is a good thing it's a long way from AI so those are those are ok things I'm not arguing against them but I don't think that it makes sense to think of them as being the foundation of the next great wave but if you just read um what you find either in the popular press press or even in the sort of popular technical press things like the communications of the ACM that's what you would think so I think it's actually hard for young people to see clearly what I see clearly of course maybe what I see is completely wrong that is what I see well and I do think it's hard for for young people to see it well if I make it sounds like you're you're primarily focusing on the application layer so to speak that is what what the technology means rather than how it's done well I've done a lot of work in the area of how it's done as well of course but now that I'm old and a tool to prove theorems or write code because I don't know oh and of concentration anymore to keep working on the same thing intensively for days or weeks
I spend my dear time thinking about the intersection between technology and various aspects of public policy or social life so for example I've been spending time trying to figure out how to keep Internet of Things devices from killing people which is partly a technical problem but it's been no means entirely a technical problem to put it another way where the interesting question is what sorts of regulations of safety critical devices would would be best you don't want regulations that allowed the marketing of devices that are gonna kill lots of people on the other hand if you make the regulations too tight then you won't have innovation and that's sacrificed a huge amount of value do you think that young researchers such as the ones here recognize the importance of that that layer of meaning behind what they do it's hard for me to judge some of them certainly um talk the talk it's not my guess is that yeah if you if you're a fast track young researcher you're really focused on on the technical things that you're doing and you don't really have enough experience or interest to think seriously about what if the broader implications are yeah I think I think I think that just naturally the way the world works and there's not a lot you can do about it other people are gonna have to take up that slack and there's certainly no shortage of people who are trying to take it up in many cases perhaps not very productively I mean just to pick a random example is a huge flap over the last few years about net neutrality my personal opinion but net neutrality is that's a problem that might come to pass I can think of a lot of scenarios in which it's not gonna be an issue at all and it's certainly not an issue a actual problem today and I think it's a way premature to bring your hands about it would be much better just let things slide for a few years and see if it turns out to be a problem or not and if it does then you could make some rules you'll have to excuse me I don't I don't remember how much time you spent in academia I know you spent quit it quit a bit in I've well I've been an adjunct professor at MIT for thirty years there we go but I was on the faculty at Berkeley in the late 60s for two or three years another thing that I have not been I have not been an academic but you have to have some experience of people coming to you as you know looking for looking for ideas and leadership and such what's your what's your style for when someone comes to you and says I you know I need help I want direction well it depends very very much on what sort of things they want to do and how close they are to something that I'm interested in there been a number of cases and by no means all cases where it's a student coming to me it might be a colleague in an industrial lamp as well where there's pretty close correspondence between what but if they're interested in something that I've been interested in and then typically we end up collaborating there have been other cases many other cases where people just want some advice and I tell them how I think the world works and what I think is gonna happen and then they have to run with it what about here at the HLF where interactions are of course by nature somewhat brief well I again I tell people what I think is important about something I was chatting with a couple of the researchers about my views about blockchain for example I don't know whether I made any converts my story for blockchain is the value of blockchain is shock value in fact I'm contemplating organizing a talk the title of which is gonna be block shock and what I mean by that is that the important thing about blockchain is not the distributed ledger or the crypto currencies or the smart contracts or any of those things it's that there are many many process processes that are important for the day-to-day operation of the real world that could benefit a lot from being rethought in the context of computing but there's a huge amount of inertia in the real world so you know real estate records for the state of Illinois it's a very primitive uses of technology there yeah it seems pretty clear that you could make things a lot better than intelligent computerization but there's also a lot of inertia in the system but now with blockchain people come to you if you have one of these processes and they say what are you doing about blockchain and if you don't have an answer you look like an idiot so you have to start thinking even though in the end probably what you do is not gonna have anything to do with blockchain this is not a popular doctrine I should say there's an example of a kind of discussions that I have had with some people some young people at this meeting and what are their reactions to that ah they're polite often if they're into it at all often they have a big emotional commitment to aspects of the blockchain phenomenon that I think are fairly bogus so you know it depends what do you hope that
the researchers here take away from you and in your communications with love them what do you find they actually take away well it's very hard for me to know what they actually take away often it takes a long time for these things to play out and typically I don't have that much contact with them afterwards well I I guess what I hope they take away is some sense of the scope of the enterprise that they're engaged in and how do they think but how to decide how to think about how to decide or decide when something is important and when it's not so important relatedly what do you think of the criteria are for that it's very hard to know a story I like to tell is for the first 30 years of the life of the internet overwhelmingly the most important application was email if you read the justification documents that were written to justify spending video government's money on the ARPANET which was the prototype for the internet email isn't mentioned why do you suppose that is it's because that hadn't been thought of so it's very hard to predict how things are gonna play out sometimes I think it's easy to predict I thought I thought at the time and I have continued to think that it was easy to predict predict what was gonna happen to the things that we did it at Xerox PARC in the seventies I thought that was really obvious but sometimes it's not obvious at all and things play out very differently then you then you imagined the ARPANET was justified in terms of sharing of expensive computing resources across the community of 20 or 30 ARPA contractors all over the US that turned out to be pretty unimportant but there are other ways it can play out for example the prototype conceptual prototype for the World Wide Web was Ted Nelson's hypertext which was invented in the late 60s and when absolutely nowhere for 30 years and Ted was heard to say in the mid 90s when it was clear that the web was a success he said I mistook a clear vision for a short distance so was that all clear clear from the beginning not really yeah I don't think anyone could really imagine what the web was gonna turn into is there anything else that you'd like to say either about the the forum or the state of your interests at the moment those are two very different questions let me put it a different way there anything else you'd like to say about about the future of of your particular interests well I think this broad question of how the technical aspects of computing are going to to play and in the in the larger world as I said before that's various aspects of that are the ones that have interested me in the last five years or so so I mentioned the blockchain where does blockchain really good for and another thing that has spent quite a bit of time on is the question of what are sensible regulate ways to regulate the use of personal data on the online I don't I don't think we've made a lot of progress on that question with things like the GDP are you take a negative view of the GDP I think the GDP are is no that's too strong but I I think it's clearly not the end of the line I think it's good that some yeah something like the g gr which is fairly unreasonable in a number of ways has at least been done because it gives you something to push against and it makes it clear that the the telecommunications and computing behemoths I are not completely in the driver's seat but I've you know I think there's a long long way to go basically my view is that the regulatory system should support the proposition that your personal data is yours and you can control it that's gonna be modulated by a whole bunch of social conventions of one kind or another that are going to be different in different parts of the world you know random example a tight young researcher was talking to me about recently you might think that the price you pay for your house is personal information well it's not in the u.s. anyway it's a matter of public record so him these are complex issues that have to be worked out in a very local in a way that's very sensitive to local needs and demands and history and the other part of that question was about the HLF about real to be coming back I assume in in future uhit's it's a pleasant experience I'm sure we'll be coming back yes anything else that we should have talked about nothing that springs to mind okay well thank you so much for taking the time I appreciate it you bet [Music]
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