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The HLF Portraits: Ronald L. Rivest

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The HLF Portraits: Ronald L. Rivest
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The Heidelberg Laureate Forum Foundation presents the HLF Portraits: Ronald L. Rivest; ACM A.M. Turing Award, 2002 Recipients of the the Abel Prize, the ACM A.M. Turing Award, the ACM Prize in Computing, the Fields Medal and the Nevanlinna Prize in discussion with Marc Pachter, Director Emeritus National Portrait Gallery, Smithsonian Institute, about their lives, their research, their careers and the circumstances that led to the awards. Video interviews produced for the Heidelberg Laureate Forum Foundation by the Berlin photographer Peter Badge. 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.
Axiom of choice Point (geometry) Computer programming Drag (physics) State of matter Direction (geometry) Multiplication sign Decision theory Insertion loss Amsterdam Ordnance Datum Water vapor Student's t-test Mereology Product (business) Expected value Frequency Mathematics Goodness of fit Latent heat Sign (mathematics) Term (mathematics) Körper <Algebra> Algebra Curve fitting Social class Physical system Standard deviation Process (computing) Ökonometrie Gradient Computability Physicalism Price index Calculus Cartesian coordinate system Numerical analysis Faculty (division) Spring (hydrology) Universe (mathematics) Right angle Figurate number Musical ensemble Family Local ring Spectrum (functional analysis)
Axiom of choice Point (geometry) Computer programming Group action State of matter Multiplication sign Decision theory Direction (geometry) 1 (number) Student's t-test Mereology Distance Theory Power (physics) Hypothesis Goodness of fit Mathematics Many-sorted logic Term (mathematics) Matrix (mathematics) Modulform Körper <Algebra> Computability theory Hill differential equation Combinatorics Position operator Set theory Decision tree learning Process (computing) Moment (mathematics) Graph (mathematics) Computability Content (media) Median Price index Complete metric space Numerical analysis Faculty (division) Hand fan Googol Right angle Figurate number Mathematician Resultant Thomas Bayes
Statistical hypothesis testing Complex (psychology) Group action Building Invertierbare Matrix Confidence interval Direction (geometry) Multiplication sign Decision theory Hierarchy Inverse element Parameter (computer programming) Mereology Order of magnitude Mathematics Many-sorted logic Lattice (group) Different (Kate Ryan album) Analogy Matrix (mathematics) Number theory Körper <Algebra> Social class Physical system Process (computing) Constraint (mathematics) Moment (mathematics) Computability Median Flow separation Wave Quantum Right angle Mathematician Point (geometry) Geometry Ramification Classical physics Computer programming Trail Functional (mathematics) Divisor Variety (linguistics) Student's t-test Rule of inference Theory Product (business) Goodness of fit Term (mathematics) Theorem Integer Computability theory Set theory Curve fitting Numerical digit Model theory Content (media) Algebraic structure Cartesian coordinate system Limit (category theory) Numerical analysis Quadratic form Faculty (division) Spring (hydrology) Loop (music) Inverse problem
Point (geometry) Statistical hypothesis testing Polynomial Group action Momentum Wage labour State of matter Transformation (genetics) Multiplication sign Decision theory Direction (geometry) Routing Insertion loss Open set Prime number Mereology Food energy Perspective (visual) Coefficient of determination Many-sorted logic Term (mathematics) Feasibility study Körper <Algebra> Physical system Area Time zone Standard deviation Numerical digit Dependent and independent variables Process (computing) Computability Cartesian coordinate system Numerical analysis Quadratic form Right angle Table (information) Spacetime Surjective function
[Music] well I'm interested in how you became who you are today so I want to start at the beginning and I'm gonna ask the question based on the lack of knowledge are you the son of scientists are you the son of people interested in mathematics or did you come out of nowhere in regard to your subject so I grew up in Schenectady New York it was born there the Ellis Hospital may 6 1947 and my mother was a homemaker my dad was a flexural engineer and worked in the Navy and radar and worked at GE Research Lab Schenectady as you may know was a town established by GE for a lot of production turbines and things like that too but my dad worked at the research lab which was and still is there and he was very interested in the new things computers as well as a lot of the the radar and other things that he were saying you didn't spring from nowhere intellectually there was this in the household there was already in the householder where there was a interest in science and technology were you an only child I was the oldest of four so all this before are you the only one whose career when somewhat in the direction of your father's SoDo Mike myself well I got a brother was going down top time he oldest yeah and my brother is a retired marine biology professor Oh my sister working pharmacology and my youngest sister is now a physical therapist in Seattle so should I imagine a household strewn with books on engineering and science or actually he didn't bring it home it's his particular interest there are a lot of toys and various things having educational things I remember the World Book Encyclopedia you know which we all looked looked out there and having a number of electronic gadgets and toys and that's all into so was that I remember my mother although she was not a technologist was always asking questions so she was very very curious Jenny she got us in the mode of you know always questioning we're there at whatever age you might have felt it ambitions specific ambitions for the children are you pretty well allowed to follow your interests you we'll follow they we followed our interest pretty much there was no expectation that you'd be a doctor or a lawyer or a journalist or whatever in fact when I was an undergraduate I didn't know what I wanted to do and I was you know using undergraduate program as it was intended to to explore different options well we already see one expectation for you and that is that you go to college yes so that at least was in the air yes yes yeah and both of my parents grew up on farms in Michigan and and my dad almost didn't go to college but was encouraged by his nap teacher to do so huh and my mom went to college and well you've you've introduced the subject of encouragement by teachers so I want you in school let's say at 11:00 what's the school like what's the preparation 11:00 would have been the sixth-grade express like that so sixth grade we had some excellent teachers I remember a biology professor there that was very very good and he would come around with my abortion so on you remember is they no no no mr. place I think was mr. police was his name it was that's not under them yeah yeah but yeah the teachers were very good miss Keon I had an astounding school system and I'm always meeting people from Miss Kuna have done well in their lives as the teachers have been let's talk about that so it's a suburb of a suburb of Schenectady it's near the research lab and it had many PhDs among the faculty which is unusual for high school in a school system high school is now in the 50s high schools 50s yeah sorry yes and is this a time when a lot of them are not able to get jobs in universities or was it just the habit of the system yeah you weren't in that was no task I didn't I find since I went to high school public high school in the fifties although in California that I was educated by a lot of very intelligent women yeah who as women could not get other jobs in the fields that interested them they have also been the case yeah I just didn't know what their personal Sidhu does fair enough well let's get you to middle school junior high I'm tracking the point of a particular spark it may not even happen through high school but are you are using a needle so junior high school in seventh grade seven yeah that's like seven eight or whatever we're right we're terrible I think as they are for many kids you're going to be really what everybody's misbehaving so it was nothing particularly loss period nothing else is happening right I do remember learning a little algebra then but that was about it in terms of so now I'm gonna put you in high school are you any more mature in your intellectual development I still was much more interesting it was a larger community it was much more technically oriented a good very good high school teachers were excellent I remember some of the teachers teaching writing teaching mathematics teaching science I was it was a great experience just a good high school there are you an extraordinary student or just a good one I'm a good student I'm a pretty good are you good yeah so I remember I remember being elected as treasurer of the class because I was so good at math right okay so I'm glad it's practical already in your life wasn't calculus or anything but it was if you're in an American high school in the fifties you're getting counseling as to where to go for university what is that discussion like I don't remember much of that I didn't apply very many places didn't I remember being courted by Michigan State which is where my dad had gone to because I was a National Merit Finalist and they were trying to attract national drag my enlist there and I ended up going to Yale forgive liberal education which I think was a good choice on the end heels not a bad choice in most cases but one doesn't even in the 50s I mean competition every decade has gotten more and more crazy but even in the 50s you didn't just waltz into Yale so your grades must have been pretty good Fred good grades I had like perfect scores of the SATs and things like that okay perfect scores in the SATs some indicator of something so I was doing well in a connect academically and you were doing well verbally as well as mathematically both both sides of the exercise yeah I enjoyed I enjoy the writing side of things as well ah yeah so that wasn't so usual yeah okay Yale bids for you tries to interest you or you just do I think I just went through the standard application process and it was except that they they have a interview process where you know there's some alum local tech community interviewed you and sees if you would be a good fit okay um the nice thing about undergraduate life in America is that the first year you don't have to choose a major yet you're now you're you're tasting the waters up tasting the water you're traveling the waters of tell me how you were beginning to make decisions about your future so well the nice thing about a school like Yale this is a liberal school broad spectrum of possible career paths and interest you could take and and so I was trying to decide I didn't know whether I wanted to be a technologist or maybe a lawyer or maybe a psychologist or something else but you're supposed to be wondering it yeah and I enjoy taking the professor's on film you know and other things so it was a good liberal education right I drifted in the end towards mathematics and part because the mathematics curriculum was the least demanding and I could explore all these other interests at the same time huh so you know I took some classes I didn't least demanding to the talented obviously it was but you mean just in terms of the course requirements course requiring with you yeah so the course requirements were I'm searching for the first sign of a mentor or a particularly inspiring figure him or her in the mathematics department no actually economics there were there was a professor there by the name of Richard Ruggles who hired me to work on computer programming for the econometrics Society and so I did that several summers working on price indices for Latin America and submitting decks of punch cards to be run through the IBM
7090 or whatever was we had then to compute price indices and so it was technical programming work which I enjoyed and got me more familiar with computers um many of the people watching this won't even be able to imagine the state of computer life at the time that you were an undergraduate Yale in terms of what was available what was being thought about it can you everybody didn't exist as a major then so I didn't have that as a choice if there had been a computer science major than I thought would have matrix would have done it wasn't engineering I took some of the CS courses that were in the engineering program computers were just starting to become part of the curriculum there was there's a couple of courses in programming that I took mostly they were punch card based write punch cards are hard to find these days my wife who does a teaching these days was looking for a deck of punch cards to show her kids fourth graders today what a punch card was just can't find that you can't find them that's hard to find so they're around but they're a great computer a Museum in Boston there's like there is a museum and they probably have some there but she was looking for something to bring into yes that they could actually I would but there's also gonna food machine with paper tape which you don't see anymore at all so so should I not be romantic and imagine you you begin to have access to computers in this form it interests you but there's not yet a Eureka or something about you're sensing the future it was something I was drifting into I think because it was fun it was interesting computers certainly had a power that you didn't see and other technologies is directly and immediately even submit something and get results back and it related to the mathematics I was doing but there wasn't any kinda remember any particular moment and that's an interesting question but of any particular moment said yes I want to be a computer scientist although I did drift into applying for computer science graduate school which I must have made a decision something exactly if you ask me out what when did I decide that that's what I wanted to do I actually don't remember crossing that threshold or just sort of drifted yeah I'm doing more and more computer science this looks like an interesting discipline why don't I go try it you wind up going to Stanford and we'll talk about that obviously but I'm wondering roughly how long Stanford has even had a ph.d program in computer Stanford had just started the PhD for that started so I finished Yale in 69 yeah I think Stanford started its program in 65 or something though so it just have been a few years have been a few PhDs out you just sound to me less clueless than your about what your future is going to be because it's a fairly bold decision I mean the other would have been to go to Matt in mathematics yes well it was partly tech field it was partly things like let's go live in California for a while - okay Stanford should be interested so Stanford at that point as you say just started the the ph.d program in 65 what other do remember programs are there around because you may have applied to other programs or maybe Stanford was one of the only ones to exist so at that time I think I applied to MIT as well it did not get in but that's a good lesson for people to know but and I think I applied a couple other places I don't remember MIT unfortunately has winter if you had gotten into both MIT and Stanford where would you have gone it's probably Stanford anyway yeah probably yeah so you're in Sanford what is the guidance such as a PhD student gets to you as you arrive in terms of this new field at least field so they're establishing the curriculum there they're putting together courses I got to meet the faculty you know Bob Floyd was my thesis advisor he taught a marvelous lucky yes last on algorithms Don Knuth was there so Herman on many other people were just
just a fantastic group of faculty and so part of it was the coursework and taking the the wonderful courses they were teaching and part of it was trying to integrate into research and figure out what kind of a research program you wanted to do and and there was also at the time just to set the context there was also the Vietnam War and so I was worried about the draft I'm trying to figure out what I my life might be like should that become a concern I did end up working at the artificial intelligence laboratory up in the hills behind Stanford it's no longer part of Stanford campus at least not part of the teaching campus anyway and we had I remember there was a cart there I think it's a computer museum now where they were to talk about autonomous vehicles this was one of the very first the Stanford card trying to drive around the parking lot and not hit any of the cars so I was working on some of the coding for that which allowed me to get a deferment for a while anyway on the right the Vietnam War situation I'm very interested in the and the past others this the formation of a community interested in questions obviously Berkeley is across the bay are you sensing as a graduate student a larger discussion going on some of that yeah there was for example one of the early papers that I worked on was a medium fast median finding algorithms are given a set of numbers how do you find the median of that yeah that was a sparked by some insights that Manny Blum had and Bailey's at Berkeley uh-huh and connected with Bob Floyd and then some of the graduate students and bond Pratt Bob target and myself got involved as well and so that that there is a larger intellectual big in the community there yeah as another example Don Knuth I used to run I was it was a weekly or monthly it's fairly often sessions at his house where he would might speakers in and so I remember dick carp coming down from Berkeley talking about NP completeness and so on to week so there was a community was starting to it was a bit of a distance but people would come back and forth and I remember going up to Berkeley wants to talk with some of the researchers there so so there was some back and forth between Stanford and Berkeley but computer science was still very small there's no industry you look like you have now all right which had its advantages yes because you could talk to everyone yeah at that point yes yes yeah um at the again you're doing graduate work you're man who likes to talk about ideas give me some insight into how you're beginning to think in terms of his direction to go and maybe the opportunities are not vast or maybe they are but how do we get you well let's just say through to your dissertation so my dissertation about the work the research I did ended up focusing on algorithms and I was interested in sort of the combinatorics the algorithmic content of how they got to get computers to do complicated things there are certain search algorithms remember also to bring up a side directly part of my thesis was on search algorithms and I remember being concerned at the time about the ethical implications of this you know that if we can make search so much more efficient you know what what about surveillance and what could the government do with this and so yes so we see all this resonating today with both the government and Google and other companies and actually throughout your career yeah because and we will talk more about the ethical issue because I think you have clearly early demonstrated and interests in the ethical implications interesting to me that it happened so yeah so early in the process um are you speculating at all this may be a classic retrospective question where we now know what's happening at that time but at the time you may not have known about the the future of this that field only but effect on society these perhaps it's hard to tell them you would hindsight you can say anything but yeah yeah you don't particularly remember feeling you were now rushing toward the future in a way perhaps one way of setting context is to make it just to say that I'm a big fan of science fiction as well and so imagining what the future could be like including the future of computers if you know the azimoff at Heinlein were big there and other writers now but you know trying to speculate as to where the field might be going as a society or technologically certainly always been a part of what I do and so I think that's a part of also part of the if you will the culture in which you're operating professionally you have any US I think I think that that's for two I mean I think the AI theme which has always been a part of what I you - well not as strong as perhaps some of the other things but it's you know Frank can you build an intelligent computer yes what was an issue that arose certainly in graduate school people were thinking about those things and throughout my career I've bounced back and forth thinking about these things off and on but the larger implications of what computer science might have an impact on society what can you do with computers is one of the big questions still of the day right right with attendant fears and hopes yes like are you are you at this point I'm also interested in the relationship between mathematics and computer theory but not in its formal aspects although I'm interested if you want to talk about that as in the position somebody who had elapsed mathematician although of course mathematics is in computer era choosing this field whether this was considered odd or you had gone bad or you were in worthy of mathematical theory I mean no I think I think it's not like that at all I think I think the the there was a blending of these fields when I was at Stanford Don Knuth was growing his group of researchers there and to the people in particular that I ended up spending a lot of time with where David Connor was a professor of combinatorics and washing Shabbat both was also similarly working in combinatorics and they taught courses which related to the combinatorics of algorithms and graphs and so on but also talked to the algorithmic side of things as well so I worked with it so I think he saw a blending of these keys fields more than any kind of in a way that that leads me to the opposite question why
did computer theory break off into its own program why didn't it stay within the mathematics so computer theory is in fact I mean it different places it's different things I mean when I came to MIT here there was an effort at one point by the part of them on the part of the mathematics department to take the theory group out of computer science and that's what I would move it in there we declined that invitation but it was an interesting one and nonetheless even so right now and at MIT in computer science theory we live within the computer csail laboratory which is interdepartmental and has mathematicians and computer scientists both in it and we were side by side all the time so it's it's a it's clearly a computer science theory as a feel that spans both computer science and mathematics right and people are happy with that back and forth in the blending your you've already gotten yourself to MIT but that's fair enough the the the the the PhD is well-received yeah I think a PhD MPH sees a demonstration did you've done some research and right so that was but it wasn't a breakthrough and it wasn't a breakthrough okay it was any waves really good to know because the stages of a career are very interesting yeah all the time it was probably badly written too I think I've learned to write better since then so even though you were not a bad writer as an undergraduate well it did I think it's the technical writing is hard it's challenging okay oh why you have to put your head in the mind of the reader first of all and you have to be very clear about the terms are using and that they're all well defined and the things that those do building the structure right the usual challenge of writing is trying to communicate the complicated structure to an audience that right doesn't know any of that the begin with the goal is that lyricism the goal is explanation that's right although you know lyricism in the sense of conciseness and elegance play a role in computer science but not not poetry I'm very struck this is really just aside a question we don't have to belabor it but just the use of words that are aesthetic words that mathematicians and computer theories which are a version of the same use elegance of course and there is a an act abuse of that language absolutely yeah I know that the simplicity and then trying to come up with theorems that are cleanly stated and simple to understand really matters in the field you can come up with very complicated structures and things that are true but interesting because they're just too complicated and your head around and so people look for the simplicity right well you haven't yet set the world on fire but you're not doing badly you get your PhD what do you do next so after the PhD it was interesting the ph.d program at Stanford had people from all over the world including a number of Frenchmen and so geo Khan and Shanti malware two of the colleagues I had there and they said Ron why don't you come to a postdoc in France afterwards I said that sounds marvelous I love to travel I had taken French in high school and I knew some French I figured I could get along and so I'd accepted we went there for a year lived in Paris this is that inria Institute Nationale de facie informatica dominique right look at the accent my French is mostly guys and so that was a postdoc working with John female mostly on algorithms and so on - it was an interesting challenge one of the interesting aspects of it was that they hadn't told me when I was accepted but the working language would be French so I were there all day I'm talking French all day and exhausted it but your French was up to it got to got to be up to Augusta and got to be after three mum we know the language we know that you're having a marvelous time in Paris but what is the quality of the inquiry there at that point so I think it was good I was afraid the French Research Lab was a first-rate research lab people they were doing interesting work largely theoretical and the work I was doing was Zhang Jian I was or combinatorial Naga rhythmic but it was it was good stuff I was pleased with what we did there it was gonna be a limited time there because you you know you had to get on with your career how do you make that decision so it was a clearly a one-year postdoc and so towards the end of that year I have to go around the u.s. dude it's like took time off in the spring to travel all around Seattle and under San Diego and Carnegie Mellon and MIT and everywhere big loop around the country try your what the opportunities were right and I became persuaded that MIT was the place education kind of offers but MIT is its own argument for itself but what about what they were doing at that point that might have so there was a good theory group here at MIT at the time Albert Meier was was the the person hide the main contact with Mike Fischer was here at the time number of other faculty were we're here then so it was a clearly a place where a theoretician could come in work happily and and I think things we're exciting at the time we the P equals NP question had just started bubbling up with further ways and people were wondering could we've resolved that and there was questions of circuit complexity and just algorithmic questions in general were we're of interest of course in the course of your career which will will will will get you as it develops you wind up coming up with insights with colleagues and so forth which we'll talk about that have very profound practical application but the fellow who's just shown up at MIT is a theorist who is or isn't interested in the application of his ideas so mit has a culture which is very much practice oriented as well so they've played way and when mi MIT likes theoreticians but they also would like to see people spam the bridge so there wasn't the the practice theory gap and so there was encouragement to to do that all particularly the teaching that some of the introductory and of course is I help teach we're systems classes and things like this so computer systems not but not just the theory classes so there were there was encouragement in those directions I wasn't personally in terms of the problems I was picking at that time White's oriented towards the practical stuff as I became later yes but but it's in the end there was there was encouragement motivation to think broadly dinner in part just interact with your colleagues better write in part because you know you want to have impact on society you've already made a decision and maybe also the time the era but you'll you'll tell me one way or the other not even to consider going into industry I mean you you sound like you are on so what an academic to reject yeah pretty much one of the I mean there were some research labs and I looked at Sandia laboratories for example when I my big tour of the country and there wasn't the kind of industrial research labs there are now so really the kind of questions were interested in asking yeah you would not have gone to uh there was no place you know the industry didn't really exist at the time I mean PC hadn't been invented yeah it's the year that you come to a mic so I come to MIT in 74 okay right the PC wasn't gonna happen for another six years anyway or something so is this whether we talk about going to industry there really wasn't an industry in any sense like there is now it is just you know many orders of magnitude different so know tortured decision-making this was this was a clear path yeah you know and I had done teaching at Stanford I thought summer courses I've done been a teaching assistant for a number of terms I enjoyed the teaching as well as the research so I think the academic path was pretty much clear we're very close to a Eureka moment at this point that's because the work year you're doing with colleagues and you talked about the the coming to the the insight in the end that will mark your career really so so the the work at MIT here was was primarily algorithmic and characters are looking for efficient ways of doing things and a lot of the work of a theoretician in computer science is precisely this trying to determine which problems you can solve it efficiently and find a good algorithm for them if you can and which problems are hard intrinsically so it said that's separating that we were there's just hundreds of problems that you might want to look at it turns out that you could say some of them were easy some of them are hard and some of them you're not sure but they're clearly the same and something that just recoding zuv the same problem so that sifting out of these various problems was was the bread and butter of what was going on in theoretical computer science at the time yeah trying to figure out which problems are easy on a computer which problems are hard and so that was part of what I was involved in looking for good algorithms I was also thinking about things like P equals I think at the time to try to prove the certain problems were hard well I didn't have the tools of the time in fact that's still an open problem uh very much so so so that drifted into working with a number of students on a variety of things some of which involve things like one-way functions and some of the cryptographic things I was working with a student by the name of Steven boy AK who was was now the NSA on you no inverse making matrice industries and when when our matrix inverse is easier to work with the matrix themselves and things like this so there was a lots of stuff in the air about complexity applied to computation which problems are easy which are hard and then the Eureka moment is as you said arose when Steven boy actually just mentioned gave me a paper from Diffie and Hellman which said you know New
Directions in cryptography and that paper was really what changed my life in many ways it said here's a set of problems that we don't know how to solve but which looked like they could have theoretical interest in practical impact and they're absolutely right they said this this is a beautiful paper nicely written and said here's the idea the vision of a public-key crypto graphic system and some ideas as to the kinds of things that relate to that and what how that might be achieved but they didn't have a working solution and so that why did we need a key system why-why-why public key system yeah yeah yeah so the vision was that everybody could make up their own public keys and distribute them publicly without the need for a centralized approach it's a little bit like the appeal that Bitcoin has today where Bitcoin is a decentralized cryptocurrency yes without having a centralized issuing rights all right well the public key vision is a bit like that although in fact you need to have some support for authenticating public keys if you give me your public key how do I know it's really you that's giving it to me right so there's some of that it aspect to it but it was a decentralized flavor and it really fit very well with the about to be born ecommerce market rather than the hierarchical sort of military situations that exists very closely so it was a different thing and one of the things that I found most inspiring about the diffie-hellman paper was their discussion of digital signatures so you can take a message and you can append something that comes from you as clearly from you can be verified as coming from you right verifies that it's from you if your fyz that it's the content that that message was was signed by you so it's the electronic analog of a handwritten signature and that was really novel I wasn't just confidentiality it was a sort of authentication that was achieved there and that I found to be a exciting notion as well and ahead as it turns out many more ramifications down the road as well so how do you dive into this I mean how do you is there a particular problem you embrace so they said basically you know you need to have inverse problems you need to have something that's easy to do but hard to undo right so it's sort of a one-way function the kind of thing I've been talking with c-boy yak a little bit on there and they gave some ideas for some ideas but the world is open you can take any kind of problem you like and in fact we're still looking at problems trying to see which one's fit this this model right so you can take a problem which is hard to hard to invert basically turn it into a public key cryptosystem with quantum and computing and things like that nowadays the question is what's hard to compute make it may have changed the ground rules may have changed over those days we had conventional computers classical conveyors at the time I was co-teaching a class on discrete mathematics and we were talking about number theory at the time so that was very much in my mind at the time and so we were looking at the approaches that a number theory can carry they say we so I got ID Jameer and my Needleman involved uh sooner on this product they said I'll you know I'd love to talk with you guys about this suite of problem you bring the question to them I bring the question to them I had this paper I said this is an exciting paper we should we should think about these questions and I started with with Adi and he odd he's always enthusiastic about new directions and new problems so we started start with him and then we brought let into it audience and given the context of the discussion we just had about math and computer science yes Adi and LAN we're in the mathematics department here at MIT of time we had offices adjacent to each other here in the lab for computer sciences that was called but you know so I was a computer scientist they were mathematicians the laboratory was set up to be interdisciplinary and really achieved that purpose of it at this point mathematicians working together with computer scientists and some since we would all say were theoretical computer scientists right right technically we're different departments now there's no of course simple answer to this but I'm gonna ask the question too because I'm interested also in just the process of collaboration yeah how does it work in this context I mean it's the three of you that in the end came up with the direction that Dell yeah no collaboration as usual I mean collaboration actually it's interesting to talk about collaboration over the decades because just a step back up yes it's always about it one of the works I did at Stanford as I mentioned earlier was this fast median finding algorithm there were five of us on the paper and I remember the program committees saying what is this you can't all be co-authors you know you're just trying to get travel money for the graduate students involved or something like this it really was caught you know co-authored in a collaborative way but that was unusual then collaboration is nowadays much more a thing and much more common and routine than it was back then at the time Lenin Adi and I started working the other three of us working together that wasn't so uncommon but it wasn't I mean single authored papers were perhaps much more common then than they are now so how do you how do you work on a problem together you sit down you talk about it what what are the constraints what do we know what are the approaches we generated lots of ideas about could we use number theory could we use some lattice based kinds of things can we use some other kinds of thing other constructions that we come up with there are lots of ideas about how you might try to do this so we just sort of like generating ideas as to what might work and mostly they didn't work this is a silly question but it it hits on a more important one and that is obviously there's trust in the collaboration I don't mean in terms of glory-seeking although that's a factor it's in human nature but separate from that does somebody come up with an idea and I'm simplifying it of course and the others say that's the stupidest thing I've ever heard but nobody disparages ideas you know that's probably the wrong way to put it but they're excited by that and we'll say you may have something cryptography is interesting is you don't know whether an idea is gonna work or not users say here's a construct it looks you know here's the way you would encrypt something here's the way you would decrypt something and then the key question is can the adversary also decrypt without the knowledge of the private key right and so that's a computational question which you may not know the answer to and you may not so even when we publish to the RSA paper W you know we didn't know whether it would ultimately be secure or not because you know the key problems involved were open problems and a cryptography is very much like that the difficulty for the adversary in breaking these schemes are generally open problems they may be problems that have been studied for a while and look like they're harvest Hoos are hard we don't know how to prove problems are hard very well yet so nobody says it's stupid or somebody says now here's a way that you can probably break it now you do this inadequately it's breakable and when Adi and LAN and I had this you've probably heard this story before but you know we had sort of a role different roles to play audio I would come up with ideas more often and Ladd would be the one to sing you know that's not gonna work guys here's a way to break it so he was expert at breaking schemes that we had so we went through a whole number of different ideas but not even I did not to break the month so how to take a part that's so it helps me understand yeah how you would work together also I guess implicit in what you're saying is maybe one day with different stage of computational capacity and Sun and on what is now unbreakable may turn out to be breakable one yes absolutely the things change so back back to the collaborating think for a second I mean that's one of the lessons that was learned during World War two apparently was in Germany the cryptographers who were making codes in the Crypt analysts who were assessing their security and daring to break them were in different buildings in different camps and they didn't communicate enough and had they done so they might have realized that their Enigma was was was breakable Wow so I think we learned today that it's very helpful to have people working both sides of the fence working together to build codes so anyway that that was and then we're talking about I gotta track it with that well we're really just developing the idea that will make the difference yes we had to we had a number of different ideas that we looked at and the thing that turned out to be RSA was not the first it was you know the 40th or something right and eventually you know I think it was me that put the with the pieces together in the particular way that ragaar say but there were pieces that we'd all studied carefully different framework something so put it together so yeah this might work so again it was another proposal that one of you know 40 wanders right at that right and it could have fallen down like the others it was nice and clean and simple so it seemed like it had a nice structure to it that you know could have turned out to be another something for the Dustin if I had seen a way to break that but you're developing confidence as a group that this this is something worth testing worth writing up so that was writing yeah the way these things work is you have an idea in the field and cryptography these days you publish it and you say you know we don't see how to break this it seems like it's here's what we can figure out about its strengths it relates to these other computational problems like factoring or something like that and you say these are this is what we know but you know it's an open problem to assess the security yeah it can you as a community now figure out the imitation Invitational to tell you the limitations yeah yeah yeah yeah and in fact the process for coming up with the new crypto systems has changed over the years to be one that's very much focused
on standardization and a community effort so at the National Institute of Standards technology has done a marvelous job of running competitions for the submission of it cryptographic algorithms and and having community conferences and community efforts to try to break things and so that's what's what's needed to really assess the strength of it because we don't know how to prove things are hard that that's the problem with cryptography is we don't know we don't have the technology it's one of the big open problems in computer science how do you show that a problem is really hard yeah let's go ideas on how to kind of maybe do it fast but it's it's a can't show that it's gonna you know how's it hard why is it hard my word case where skates how do you there Holly it's hard on the average how do you this paper works omitted it actually is an answer that people have been looking for it seems to seems to have worked well still stood the test of time so the paper came out it was it was a proposal everything yes you know we said this is well we know this is what we think we can do with this it doesn't seem to answer the question the Diffie and Hellman raise and they're wonderful paper New Directions cryptography it interested in the framework that they gave and it really said now there are new things you can do in cryptography so here's one that's an idea that's based on factoring that allows you to achieve a public key cryptosystem not only the encryption side but also the digital signature side would write which was really relies on particular did you hear from them by the way we talk we talk to them and then they they were you know interested in appreciative right supportive things I need to get you now from this point well to what we've been talking about the realization that this might actually be a solution to the implementation and the effect of the field yeah so it was the the implementation issues were interesting because at the time computers were slow they were very much slower than we had today I mean other 10,000 times slower so you know and so the process of finding prime numbers even which is an essential part of the IRS I think when you multiply two large prime numbers together yeah finding those prime numbers could take a half an hour on a computer or something like this yes it was Norman that wasn't the numbers that are considered short by today's standard so you know those have changed over time with Moore's law and computers getting faster but at the time the implementation was actually a serious issue this was a proposal that in some sense it was feasible because of the algorithms involved were all polynomial time if you look at how much time was actually required by the polynomials you know it took too much time to be a really a practical interest yet that that would soon change with as computers get faster well one of the things we did early on was to get interested in chip design so MIT at the time was in the process of building up a capability in VLSI fabrication so designing and implementing large-scale chips to do computations of various sorts so we actually put time in about 1980 to design and implement a prototype or a chip that would do the RSA computation huh would find a large prime numbers that would do the encryptions onto with special-purpose circuitry like that you can actually make it very feasible in the end of snow most special-purpose chips aren't needed so much because the chips are pretty fast now but it was it did the job I mean it demonstrated feasibility the time difference it was also an interesting just intellectual experience for us - how do you design a circuit chip Justin I'm gonna get real practically practical here and ask about the economic implications of this because they feel and the have proven profound in terms of your even patently this this concept and perhaps presiding over in the private as well as the public world its implementation how do you think about that so at the time we didn't know much about startups I think the culture of computer science departments has changed hugely since then at the time there were a few startups but not many if you try to find colleagues who had done startups or things like that right it's not like Stanford where everybody's out of their office golf during there's your star today or something so but we said yeah this looks interesting it looks usable and MIT was supportive of efforts like this so they said well this sure will pad it and then we said well the set up a little startup company - yeah there might be some applications I never application sketched in the new directions paper we were thinking of some - but mind you the worldwide web and not yet been invented and so all of the applications that flow out of that were still in the future and during the 80s when when the company was trying to get going it was all very difficult because there were no large-scale applications like you would get by having Amazon sales or something like that or ecommerce in general so from the time that we invented the system through the 80s up until the invention of the World Wide Web it was pretty much a barren market markets had to be created when the web happened things changed like that it was it was an amazing transformation all of a sudden everybody was using computers in the web to do commerce transactions had to be verified they wanted to be encrypted often you wanted to authenticate things you needed digital signatures so things changed remarkably with the invention of the web if you read David Kahn's book about the history of cryptography he talks about one of the large impetuses to cryptography earlier which was the invention of radio and during World War 1 radio was used for commanders to talk to their jerseys - but everything was broadcast so people could listen in you had to have cryptography so the invention of radio was was a first impetus for cryptography the world wide web is really the second that sort of the same kind of area nice parallel so a short layman's version of this is you didn't own the rights at a point where it was paying off in a big way right right and you lose the rights and the natural course of a patent right that expired right housing or something like that so it's it's gonna allow me to introduce a very important thing in your life which is even the ethics of this much of your approach in general anyway has been little fasten flowers bloom you know let as many people into the use of this as I can that I prepared to say yeah I think so I mean I think for this particular scheme we founded a company and there was a patent because I think that's the only way to get the energy in the investments and the food right to get that out there but then again the goal was to market that did you say a lot of thousand applications being yeah with the support of this company and the software provided by this company you can have lots of applications using it it wasn't trying to be restricted was trying to get things out there I really want to belabor because we don't have a lot of time this Labor's not the right word the the ethical questions that come into a researchers life your kind of research I guess part of that is the whole question of who has access to who can use it but also in the course of your life you come up with ideas that you've deliberately not taken possession of so to speak that you've wanted used and make decisions that allow it to happen widest use can you talk about that and because it is ethical look the question is well so I think the ethics of cryptography are very interesting mostly the community runs in an open manner like you're talking about where people publish designs and so on - occasionally they will patent and so on - but I think that the effort in cryptography these days has been pretty much through the standardization route people won't use cryptography unless they're standardized and and so that that's the route that people take now that's the recommended path you want a cryptographic algorithm you look for the US national standards you say what what are the algorithms are or published well that said back to the ethical issues of cryptography one of the big issues then and even now is government access to encrypted data and so I've been involved with that debate since the early days in the 90s the government tried to encourage everybody to use a certain encryption chip which wouldn't not only encrypt the data but also allow them access to the plaintext right right and that didn't go well and I was happy the other side to encourage that it not be adopted and today we see the US government pushing for access to iPhones where Apple and Facebook are saying you know this if you try to put backdoors - these phones you will weaken the overall infrastructure be worse for security over all the benefits you get aren't equal to the losses that you will see you will suffer and so the ethics of cryptography these are important policy issues they deserve debate their profound but but you know I think the my taster the answers are pretty clear that you we need good technology we need good strength particularly with foreign state actors attacking us left and right not only an efficient space but election space and so on - having good technology to protect us without the backdoors
built-in this is what we want to be the last question I'll ask because there's so much in your career we could talk about but you've tried to contribute to voting questions as well in the in ethical yeah perspective can you just end the conversation with a little bit so I think I drifted in the direction of looking for questions where technology comes to play and policy is relevant so this encryption debate is one of the areas encryption sorry elections are another one where technology is coming out we can see how to protect elections better than we used to know how to be able to do things like risk limiting audits the use of cryptography turn out to be powerful tools for securing elections yes and we'd like to see more of that so and that involves not only technology but also policy because people have to understand adopt and implement these kinds of things and and as you see on the books here at the table I guess that you know I get I guess I I'm attracted to areas where there's interesting policy questions climate change being the latest area that I've been looking at and it's not you are you getting a response I guess with the distinction of what you've achieved people do tend to listen a bit but you have to say no are you encouraged by I think it helps there's a lot of pushback on the part of the fossil fuel industry and so on to saying you know this is a hoax or whatever but I think that by and large the science is winning this debate and I'm happy to participate in the sciences winning this debate is a great way to have thank you very much I did it dog with you