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<\/h3>\n<\/h3>\nDr. Donald Kossmann<\/a> is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research\u2019s flagship lab in Redmond<\/a>, it\u2019s his job to inspire others to think big, too. But don\u2019t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path.<\/p>\n On today\u2019s podcast, Dr. Kossmann reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science\u2026 with marketing.<\/p>\n Donald\u00a0Kossmann:\u00a0We have been programming devices. We\u2019ve been programming mainframes. We\u2019ve been programming PCs. We\u2019ve been programming the web\u00a0and so on. I think we need to go to the extreme craziness and think that the world is one big computer. I think this is the big North Star goal that we have.<\/p>\n Host:\u00a0<\/b>You\u2019re listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. I\u2019m your host, Gretchen Huizinga.<\/b><\/p>\n Host:\u00a0<\/b>Dr. Donald\u00a0<\/b>Kossmann<\/b>\u00a0is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research\u2019s flagship lab in Redmond, it\u2019s his job to inspire others to think big, too. But don\u2019t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path.<\/b><\/p>\n On today\u2019s podcast, Dr.\u00a0<\/b>Kossmann<\/b>\u00a0reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science\u2026 with marketing.<\/b>\u00a0<\/b>That and much more on this episode of the Microsoft Research Podcast.<\/b><\/p>\n Host: Donald\u00a0<\/b>Kossmann<\/b>, welcome to the podcast.<\/b><\/p>\n Donald\u00a0Kossmann: Thanks. Thanks for having me.<\/p>\n Host: I like to start by situating my guests. It\u2019s such a research-y term. And you are very impressively situated here. So as a\u00a0<\/b>D<\/b>istinguished\u00a0<\/b>S<\/b>cientist, and the\u00a0<\/b>D<\/b>irector of Microsoft Research\u2019s Redmond Lab, what do you hope to accomplish here? What gets you up in the morning?<\/b><\/p>\n Donald\u00a0Kossmann: So what gets me up in the morning are the people. I\u2019m working with an incredible group of people. Researchers, engineers, designers, testers, program managers, biz operations people… They are all amazing and it\u2019s an incredible privilege to be given the opportunity to \u2013 to be their advocate. On the research front, what gets me up is democratizing technology.\u00a0<\/b>I think banks have democratized money,\u00a0right? And they\u2019ve made it,\u00a0for everybody,\u00a0possible to have money, to grow money. Cars have made it possible for everybody to move around in the world. Right? That is the democratizing mobility.\u00a0<\/b>So databases,\u00a0which is my background,\u00a0has democratized data,\u00a0which has made it possible for everybody to get the best value out of their data. If I want to get value out of my data, I need to get the tools to get the value. If we,\u00a0kind of,\u00a0go back to the metaphor of a bank,\u00a0right? How do I get value out of my money from a bank is also that I combine it with other people and the bank pools it and then\u00a0makes out of the mass something better and bigger and then lets me participate in that.\u00a0So my data,\u00a0my genome data alone,\u00a0is not very useful, but of a large population of people\u00a0pooling\u00a0this together, correlating it with things that happen, that is actually very valuable. And I think what we need to still do, and that\u2019s where democratization needs to happen, is that I, as an owner of my data, need to control how it is used and how I get the value back. And at the moment, we have just way too few offerings for that.<\/p>\n Host: Yeah. How does the cloud change that?<\/b><\/p>\n Donald\u00a0Kossmann: Well the cloud,\u00a0at the beginning,\u00a0is just like a bank. It\u2019s like a vault where you put your data and it\u2019s also kind of the opportunity to do something with the data. So it is a platform that then allows everybody,\u00a0at some point,\u00a0to kind of realize\u00a0their\u00a0visions and their dreams on what to do with data and how to create value with that data.<\/p>\n Host: Prior to MSR, you had a lengthy and notable career in academia. I\u2019m going to ask you more specifically about your life and your path to MSR later, but I think it\u2019s worth talking briefly about your time as a professor at ETH Zurich where you were a database person in the computer science department. Tell us a little about the history of database systems and what the landscape looks like now in the era of cloud computing.<\/b><\/p>\n Donald\u00a0Kossmann: One of the things I always say jokingly about databases, is that databases are boring and hard,\u00a0and that\u2019s why they make so much money.\u00a0Because nobody wants to do the boring stuff and nobody can do the hard stuff, so it\u2019s kind of a good combination.\u00a0But essentially, database\u00a0is a\u00a0fairly old technology, but it has always been about three things. One thing is value. How do you get the best out of your data, which is,\u00a0what are the features that you provide, the power of querying the data, of updating it,\u00a0of correlating it,\u00a0and\u00a0doing things with the data?\u00a0The second thing has been security. How do you make sure that the data stays under your control, that you own it and determine what happens with the data?\u00a0And the third is, I would call it cost or performance, is making sure that you don\u2019t overpay for the data, right? That it\u2019s kind of cheap to,\u00a0or kind of gets more and more affordable,\u00a0to do what you want to do with your data and control it.<\/p>\n Host: Al<\/b>l\u00a0<\/b>right. So what did you do as a database\u00a0<\/b>professor<\/b>?<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0Yeah, so one of the waves I was very involved in was the so-called semi-structured data wave.\u00a0The best way to process data\u00a0is if it\u2019s really structured and you know exactly what it is, right? And you have\u00a0a\u00a0schema, essentially. And I spent a lot of time working on semi-structured data, which has some structure that you kind of extract and that is kind of like getting good value out of all data, not just your structured data like your bank accounts, but also your email, the books you write, the word documents you write, getting some value out of that.<\/p>\n Host:\u00a0<\/b>Mmm<\/b>-h<\/b>m<\/b>m.<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0So that was a big phase of mine.\u00a0Another big phase of mine was distributed databases and how to optimize them and how to make them perform in a very scalable way.<\/p>\n Host: All right. So that\u2019s kind of three waves you\u2019re riding. Is there anything that you see out in the ocean right now that\u2019s a wave coming in that database people might be facing\u2026 new challenges that research could address?<\/b><\/p>\n Donald\u00a0Kossmann: I think it\u2019s still about value, security and cost,\u00a0and will always be in the database world. But I think what we\u2019ve seen of the generations, or\u00a0the eras of computing,\u00a0is this pendulum,\u00a0right?\u00a0We started with a mainframe computer, which is kind of very centralized. Then we got into the PC era, which is kind of decentralized, where you push to the customer. Then we went to the web, which is,\u00a0again,\u00a0centralized. We went back to the mobile phone and smartphone, which is decentralized. Then we went to the cloud, which is, again, logically centralized. And now we are hitting back again in this pendulum to what we now call the edge. And I think we haven\u2019t,\u00a0in databases,\u00a0even started to think about the edge because the edge for us is kind of like nine billion new machines. And nobody has thought about deploying databases on nine billion machines. We\u2019re now at hundred\u00a0thousands\u00a0or ten thousands of machines in the cloud, but nine billion is yet a totally different thing!<\/p>\n Host: How\u2026 how are you even thinking about that?<\/b><\/p>\n Donald\u00a0Kossmann: Well, of course my mental framework is pretty much always the same on the technology side: value, security and cost. But the best way to think about it is, if you believe in this as being the new machine or so, what is the killer application? What do you want to do with this data at the\u00a0edge? And what are the constraints?\u00a0So one way to do research is to look at what is happening today and think of one assumption that is going to go away, right? Or that has had it, but usually it\u2019s an assumption that goes away.\u00a0Of course, it has to be driven by some application so now,\u00a0if the assumption goes away,\u00a0it\u2019s centrally managed, what can you do with this data now\u2026<\/p>\n Host: Right.\u00a0<\/b><\/p>\n Donald\u00a0Kossmann: \u2026if you have such a system, and then that kind of inspires you to think about how to build such a system.<\/p>\n Host: Before you put on your visionary leader hat \u2013 I know you wear a lot of hats around here, Donald \u2013 I want you to tell us about some of your own research. Let\u2019s start with\u00a0<\/b>Cipherbase<\/b>, which is a SQL database system that stores and processes strongly encrypted data. Tell us about\u00a0<\/b>Cipherbase<\/b>, and how a database professor got involved in cyber security and cryptography.<\/b><\/p>\n Donald\u00a0Kossmann: When I was at ETH in the late 2000s, I was working with several companies. Among others, I was working with the Swiss banks. And so,\u00a0there was actually a very big\u00a0scandal in Switzerland and that is that the German government paid one of the Swiss database administrators to produce a CD of all German customers that had bank accounts in that bank. And of course, the assumption was,\u00a0those were all tax evaders and most of them were. So the problem with that was that in Switzerland, this is illegal.\u00a0But in Germany it\u2019s actually totally legal. So what happened is that the Swiss bank came to me,\u00a0because it was a database administrator and I was a database person,\u00a0they came to me,\u00a0and they said, okay, Donald, how can we prevent that that never happens again? And that kind of created my interest into encrypted databases or protecting data from the administrators but still letting the administrator do their job. They do a lot of important things with the database, but they don\u2019t have to really look at the data, right? The business needs to look at the data, but not the database administrator.<\/p>\n Host: Hmm.<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0And so we developed a bunch of technology, and we worked on that for two or three years and,\u00a0at some point,\u00a0a distinguished engineer from Microsoft visited ETH and he came to me and we talked about what I work on and I told him that story and he said, oh, actually we are,\u00a0at Microsoft,\u00a0very interested in that problem. And so I visited Microsoft and MSR and I learned about their solution and it was actually much, much better than what I had thought out over three years at ETH. So I said, oh, this is great. I want to work with you. And that was the\u2026<\/p>\n Host: Very interesting.\u00a0<\/b><\/p>\n Donald\u00a0Kossmann: \u2026birth of the\u00a0Cipherbase\u00a0project. And that\u2019s what,\u00a0then,\u00a0later on became the Always Encrypted feature of SQL.<\/p>\n (music plays)<\/i><\/b><\/p>\n Host:\u00a0<\/b>T<\/b>raditional database architecture has some significant limitations when it hits the cloud, and one of the most exciting projects that you\u2019re\u00a0<\/b>even\u00a0<\/b>currently involved with is an answer to that. It\u2019s called Socrates. As a kind of set up, I want you to unpack expectations versus reality with the move toward Database<\/b>-A<\/b>s<\/b>–<\/b>a<\/b>–<\/b>Service paradigms in the cloud<\/b>,<\/b>\u00a0and how this new architecture compares with the older, what you call, monolithic database architecture.<\/b><\/p>\n Donald\u00a0Kossmann: I think this question is best answered if I give an analogy,\u00a0and that is retail. There\u2019s the brick and mortar retail and then there\u2019s the online retail. And both are important, just like both database architectures\u2026<\/p>\n Host: Right.\u00a0<\/b><\/p>\n Donald\u00a0Kossmann: \u2026will be important, but they were designed with different assumptions and different goals in mind. So the brick and mortar, we want to\u00a0kind of\u00a0minimize the movement of\u00a0goods. So you go there, you try your new fancy suit on, it fits, you go home, you have almost zero returns because logistics are expensive.<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann: It is also about a kind of very specific experience that people want to have. It is all together. So this is what traditional databases do. They are designed for a particular experience and having a particular assumption. So moving data around is expensive. And the experience is, when I do a query to a database, I want to immediately get the answer\u2026<\/p>\n Host: Right.\u00a0<\/b><\/p>\n Donald\u00a0Kossmann: \u2026and I want it to be fast. Now let\u2019s go to online retail. Online retail has this big logistics problem, but it has some other features, right? Essentially you have virtually all products in one hand\u00a0at one fingertip\u2026<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0\u2026and if you think about why online retail is so successful is because it is cheap, right? That\u2019s what got people hooked up,\u00a0is low cost. And why is it so cheap? Because it never wastes any resources, right? If you look at a shop, there are people working there that,\u00a0sometimes there are no customers and they are just wasting resources. If you think about an online retailer, there\u2019re no wasted resources.\u00a0All the workers are constantly working and active. There\u2019s nobody standing around. And the same happens in the cloud. And that is essentially the Socrates architecture. It is really designed for not wasting any resources. And that\u2019s our kind of goal in the cloud to drive down cost and that\u2019s why we separate the resources and you just use resources and put them together as you need them.<\/p>\n Host: All right, so I want you to tell me a little bit more about Socrates, technically, and how you have achieved this reduction in cost and increase in efficiency with the architecture that Socrates presents.<\/b><\/p>\n Donald\u00a0Kossmann: Yeah, so, essentially what it is all about is separating concerns or disaggregating.\u00a0So, traditional databases are monoliths. All functionality is kind of intertwined and mingled together, but very highly-optimized to have that experience\u2026<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann: \u2026just like a shop. What Socrates does is\u00a0it\u00a0essentially separates compute, storage, and the log\u2026 Essentially, it separates concerns to make sure that we can optimize and can utilize these concerns in the best possible way. When we talk about disaggregation,\u00a0we typically talk about disaggregation of computing resources\u2026<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0\u2026and when we talk about the architecture that does it, we talk about decomposing it into mini-services.<\/p>\n Host: Interesting.<\/b><\/p>\n Donald\u00a0Kossmann: So there\u2019s a mini-service that runs queries. There\u2019s a mini-service that logs all the updates that happen. And then there\u2019s a mini-service that serves the data. In the retail environment, there\u2019s a mini-service that gives you the catalog and presents the goods to you. There\u2019s a mini-service that is the warehouse that ships the products to you. And then there\u2019s a mini-service that does the payment. And it\u2019s kind of like the analogy here.<\/p>\n Host: All right, so where is this in the pipeline because we\u2019ve got huge legacy systems. And now you\u2019ve got this new idea that\u2019s optimized for the cloud\u2026<\/b><\/p>\n Donald\u00a0Kossmann: In some sense, the good news is we don\u2019t have to change the API.\u00a0Kind of another analogy is if you buy an electric vehicle, you don\u2019t have to relearn how to drive\u2026<\/p>\n Host: No!<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0\u2026right?\u00a0So you\u2019ve changed the engine and you\u2019ve done something really big underneath, and that\u2019s one of the big achievements of the engineering effort of Socrates, is that we didn\u2019t change the API. So it\u2019s all under the hood!<\/p>\n Host: Failure has many faces and not all of them are ugly! You\u2019ve had some experience with failure. Sometimes you\u2019ve even called it miserable failure.\u00a0<\/b>So t<\/b>ell us\u00a0<\/b>about\u00a0<\/b>some work that you\u2019ve done that didn\u2019t work out and what lessons you learned while you were at it.<\/b><\/p>\n Donald\u00a0Kossmann: My favorite story is that of a failed start-up. So I\u2019ve also done start-ups. That\u2019s,\u00a0kind of for me,\u00a0is part of the academic experience that you do start-ups. And I had a grandiose failure of a start-up.<\/p>\n Host: I\u2019m not laughing at you\u2026<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0Yeah, well, it\u2019s actually fun now! It was a little bit less fun at the time.\u00a0So in 2006, Amazon kind of started with the cloud and I started a company that built a semi-structured database for the cloud. And it was a semi-structured database because I had been working on semi-structured databases. And it was the cloud because I thought the cloud was really cool and was going to be a game-changer and I wanted to be the first there! The problem was that these were two big bets. It was a big bet on the cloud and it was a big bet on semi-structured data. And if I had just made the cloud bet,\u00a0I\u00a0would have been great.\u00a0I mean,\u00a0the ideas of separating compute and storage,\u00a0that\u2019s exactly what I did at that time. And the semi-structured bet, I think it\u2019s still\u00a0going to pan out. It\u2019s still really important. It just didn\u2019t pan out at the same time. And with a start-up, if you make two bets, they need to all pan out at the same time. And that\u2019s just not going to happen, right? So bet on one miracle rather than two or three!\u00a0Finding the one miracle, that is the art of doing a start-up, but also doing a research project.<\/p>\n Host: Let\u2019s talk about superpowers. You wrote a blog post, which I loved, where you compared and contrasted super powers of academia, of product groups, of start-ups and Microsoft Research. So give us a superpower breakdown of these various institutions and entities and where you land personally on what\u00a0<\/b>we might<\/b>\u00a0call the value proposition of Microsoft Research.<\/b><\/p>\n Donald\u00a0Kossmann: Essentially,\u00a0the\u2026\u00a0what I believe the five super powers that the company gave us \u2013\u00a0this is really when Bill Gates kind of founded Microsoft Research\u00a0\u2013\u00a0this is freedom.\u00a0We can freely collaborate with everybody in the company. We are not tied to any organizational structure.\u00a0The second one is, we have time. We don\u2019t have product deadlines, shipping deadlines and so we have time to really think things through.<\/p>\n Host:\u00a0<\/b>Mmm<\/b>-hmm.<\/b><\/p>\n Donald\u00a0Kossmann: The third one is, we take risks. We can fail fast. We don\u2019t have legacy.\u00a0If we find that an idea is stupid, we just kill it. We just stop working on it, right?!\u00a0This is different\u00a0from\u00a0product groups. Creativity is a big part of our culture. We generate ideas constantly. This is kind of part of our job. And the fifth one is we build stuff,\u00a0we execute,\u00a0and, of course, we do that with the product groups.<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann: And so coming to your question, I think every\u00a0kind of\u00a0organization has a different mix of these.<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0I mean, academia is creative. Our product groups are creative, right? Start-ups have some of these. But this combination is unique. And so,\u00a0if we want to innovate, which is kind of our mission,\u00a0and what we want to achieve,\u00a0that\u2019s how we create value to the company, we have to use these five super powers. We were talking about some projects like Always Encrypted or\u00a0Cipherbase, that\u2019s exactly something that academia cannot do because academia doesn\u2019t have the execution part.<\/p>\n Host: Right.\u00a0<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0They just don\u2019t have the resources to do it.\u00a0A start-up cannot do it either because these projects take time and the time to do this, a start-up just doesn\u2019t have. And so\u00a0that\u2019s what we\u2019re looking for\u00a0and it\u2019s actually amazing,\u00a0in this time,\u00a0how many projects really need exactly this combination of super powers.<\/p>\n Host:\u00a0<\/b>There\u2019s\u00a0<\/b>been a long-standing debate between what I might call pure research purists and another group that I would call team tech transfer<\/b>,<\/b>\u00a0who are entrepreneurs. And the argument stems around purpose of research<\/b>,<\/b>\u00a0and how you measure it. And one side is always yelling\u00a0<\/b>\u201c<\/b>science!<\/b>\u201d<\/b>\u00a0and the other is always yelling\u00a0<\/b>\u201c<\/b>impact!<\/b>\u201d<\/b>\u00a0but you\u2019ve had actually argued that the argument is becoming moot. Why?<\/b><\/p>\n Donald\u00a0Kossmann: Well,\u00a0because it\u2019s both, right? And so I would have to kind of drill down a little bit what I think a good research project does and it has essentially three components. It has scientific insight, right?\u00a0Some idea, some secret sauce.\u00a0The second piece\u00a0is it has\u00a0execution. It executes on something. It creates something.\u00a0And the\u00a0third one\u00a0is, I call it marketing, but what it really means is having clarity on the impact. And the interesting thing is that the execution and marketing make the science better. I cannot explain it, but it\u2019s happening right now. When we do science and we execute, that actually is a feedback loop to our science. We see things that we wouldn\u2019t have seen if we hadn\u2019t executed on it. Or creating the clarity on how this is going to change the world makes us kind of question assumptions that we might have not done if we had just stayed in the scientific world, and actually makes the science much more interesting.\u00a0This is what I find so amazing about the job that I have and about Microsoft Research, if I see how researchers kind of get this insight and they say, yes, the execution makes my science better and the impact makes my science better, this is kind of like really deeply gratifying.<\/p>\n (music plays)<\/i><\/b><\/p>\n Host: Most people think, somewhat logically, that in order to innovate we need to think forward<\/b>,<\/b>\u00a0or think ahead. And you suggest<\/b>,<\/b>\u00a0<\/b>in another provocative blog post<\/b>,<\/b>\u00a0<\/b>that we actually need to think backwards. Tell us what you mean by thinking backwards and then unpack why we need to do it, why it\u2019s hard to do it<\/b>,<\/b>\u00a0and what happens when we do it.<\/b><\/p>\n Donald\u00a0Kossmann: Yeah. So I wrote this blog post as a reaction to comments that I heard often: \u201cWell, we\u2019ll cross that bridge when we get there.\u201d And often what happens is, you never get to that bridge or when you get there you\u2019re really stuck, right?<\/p>\n Host: Totally unprepared.<\/b><\/p>\n Donald\u00a0Kossmann: Unprepared and you don\u2019t know what\u2019s going on. So what thinking backwards does is, it starts with, what we call at Microsoft, defining a North Star goal, a really good North Star goal. And then not immediately jump,\u00a0oh, what is the best direction to this North star goal? But kind of creating landmarks.\u00a0And I call them landmarks because milestones are kind of like forward thinking, Milestone 1\u2026 what is your Milestone 1? But I actually think about landmark\u00a0N minus\u00a01. Because really what we do is we navigate uncertainty. We don\u2019t know where we will go. But if we know, oh,\u00a0there is somewhere there,\u00a0I need to get there. I don\u2019t know\u00a0exactly what will happen on the path, but I know the dimensions. I know I can go west and east. I can go north and south. I know essentially how I can maneuver. And if I know the landmarks, right?\u00a0then I can get there. And if I do get stuck, it kind of helps me not to get frustrated. So if I know this is my landmark and I get stuck,\u00a0I hit a dead end, which happens to all of us, I will find a solution to get to the landmark, or I will redefine the landmark. It gives me much more clarity to deal with these situations.<\/p>\n Host: Okay.<\/b><\/p>\n Donald\u00a0Kossmann: Whereas if you move forward and you hit a dead end, you\u2019re stuck.\u00a0And then you often give up and get frustrated.<\/p>\n Host: Well, Donald, we\u2019ve reached a part in the podcast where I always ask my guests what could possibly go wrong? And I do this because every line of research that has potential for great good also has potential for great risk or great harm. And as a leader, you don\u2019t only have to worry about your own stuff. You have to worry about all the stuff of all people that you shepherd and supervise. So what, if anything, keeps you up at night, metaphorically, and what responsibility do you have to identify and then try to mitigate the potential risks of the work that you do and the work that the people here do?<\/b><\/p>\n Donald\u00a0Kossmann:\u00a0So as a high order bid, I\u2019m an optimist and I just, well, move forward. We\u2019re just talking about thinking backwards, but I actually always think there is a way out. And one of the reasons why I think that is because,\u00a0in the bad situations I\u2019ve been in life,\u00a0there\u2019s always somebody with me, I\u2019ve always managed to never be alone because if things get bad,\u00a0it\u2019s much better not to be alone. I have also, I have\u00a0this, I think one of my biggest strengths is I can detach myself from myself. So sometimes if things go really wrong, I can look at myself and say, well, Donald, you really screwed up. Okay. And then I have a different perspective and it helps me to move on. In Microsoft Research we are about risk taking. We\u2019ve created something called Failure to Lunch, which is a seminar series where people of the lab talk about their failure and we celebrate the kind of,\u00a0what we call,\u00a0smart risk-taking but usually there\u2019s something to be learned. And we celebrate failure and that is great, I think.<\/p>\n Host:\u00a0<\/b>All right.<\/b>\u00a0<\/b>S<\/b>o let\u2019s move over and\u00a0<\/b>not<\/i><\/b>\u00a0talk about failure. Let\u2019s say you succeed wildly in some of these technologies that you\u2019re chasing, that are your North Star goals, and they have unintended consequences. How do you mitigate that?<\/b><\/p>\n Donald\u00a0Kossmann: That,\u00a0of course,\u00a0is a great question and I think,\u00a0when I started computer science,\u00a0we were innocent. I remember writing grant proposals and the question about ethical concerns, it was a no brainer.\u00a0And now, everything we do has an ethical side. We are dealing with technology that is dangerous and we know it, right? It can all be misused in many ways. As scientists,\u00a0we have a responsibility to think about how our technology can be misused and we have a big, big responsibility to educate society and do our best to explain the technology and possible misuses of technology.\u00a0If we do that, we kind of do the right thing and we also play our\u00a0role. It is not our decision how our technology is used.\u00a0We just need to be responsible and develop technology that makes the world a better place. We should think about the positive sides, but again, I\u2019m an optimist.<\/p>\n Host: All right, it\u2019s story time. We\u2019ve heard a bit about your academic and professional life. Let\u2019s rewind a bit and hear how you got there.<\/b><\/p>\n Donald\u00a0Kossmann: How I got into computer science is not a heroic story. I didn\u2019t know anything else what to do. It\u2019s kind of more random than really by design. I come from a family of lawyers.\u00a0And so I wanted to always become a chartered accountant, which\u00a0is\u00a0also\u2026 I mean,\u00a0database is just as boring as that\u2026<\/p>\n Host: You can make a lot of money!<\/b><\/p>\n Donald\u00a0Kossmann: Yeah! And, and so\u00a0I went to the Harvard summer school and I did a course on programming and it just infected me. I got the\u00a0bug and I love programming. And so that kind of changed my plans. I studied computer science and I think I just got lucky.<\/p>\n Host: So from there you went to be a professor. You got a PhD somewhere in the mix there. You were a professor at ETH Zurich. Connect the dots for us.<\/b><\/p>\n Donald\u00a0Kossmann: Here is the story.\u00a0I\u2026\u00a0So I had been working on this\u00a0Cipherbase\u00a0project with MSR and probably I was somehow on the watch list and I had visited. And I got an offer to join MSR. And for me, it was actually pretty clear that I would decline the offer. Unfortunately, not for my wife, or fortunately, not for my wife!\u00a0So my wife literally said,\u00a0\u201cDonald, you can stay happily senile at ETH or you can start from scratch.\u201d And\u00a0I thought,\u00a0well,\u00a0actually both of those options are pretty bad, right? I don\u2019t want to start from scratch, but I don\u2019t want to be senile either. And so, what we ended up\u00a0deciding, that I start from scratch,\u00a0because,\u00a0why have one career if you can have two careers, right?<\/p>\n Host: Right.<\/b><\/p>\n Donald\u00a0Kossmann: And so now I\u2019m in my second career. I started from scratch and it has been quite a ride.<\/p>\n Host: Tell us something interesting about yourself that we might not know, whether it\u2019s a characteristic, a life event,\u00a0<\/b>a<\/b>\u00a0side quest, something you\u2019ve done<\/b>\u2026<\/b>\u00a0and how it has affected or impacted your life or career? And if it didn\u2019t\u00a0<\/b>even\u00a0<\/b>affect yours, maybe somebody else\u2019s?<\/b><\/p>\n Donald\u00a0Kossmann: One thing I did this summer,\u00a0I wrote a small book. It\u2019s called\u00a0Wunder\u00a0Informatik\u2026\u00a0T<\/i>he Miracle of Computer Science<\/i>.\u00a0<\/b>So I actually wrote it in German because I have four children, three daughters,\u00a0I wrote it essentially for my daughters because they are kind of asking me all these questions. Why did you study computer science? How did you get there?\u00a0And I never had a good answer.\u00a0I felt like I weaseled my way through a whole career as a professor without knowing why to study computer science or why I was so lucky. I had to reflect on this and what is it that makes computer science so special?\u00a0I wrote it. I evangelized it a little bit in Switzerland. That\u2019s why I wrote it in German because I was invited to give a commencement speech at\u00a0one of the\u2026 a\u00a0high school in Switzerland, and that was kind of, I used that opportunity to kind of advertise the book and so I got a lot of feedback from that.\u00a0It has been great because, as it always is, when you teach you learn more than anybody else, right?<\/p>\n Host: We\u2019ve talked about the importance of thinking backwards and establishing North Star goals. Maybe you could give our listeners a little primer on how they could go about setting their own North Star goals, including what they should do if they run into one of those dead ends that you talked about earlier.<\/b><\/p>\n Donald\u00a0Kossmann: What I believe my biggest problem as a lab director,\u00a0or as a researcher,\u00a0is defining the right goal. That is the biggest problem of all. Essentially it defines our ambitions.\u00a0Getting the right level of ambition,\u00a0and rising because the opportunity is rising,\u00a0that\u2019s a very difficult task for a researcher. So I think that the thinking backwards framework is actually great to define a North Star goal and to get to the right level of ambition And the way it works is, if you don\u2019t find a path backward from your goal to where you are, your ambition is probably too high, right? Starting civilization in space, right? is probably too big of an ambition because we cannot execute on it, right? But if you kind of have not interesting landmarks, if they are boring, if they are not inspiring you,\u00a0then your ambition was probably too small. And so the framework allows you to, first of all, reason what your goal is and kind of dream of it and the implications that it has and the impact, but it is also a way to kind of keep you honest and validate things.<\/p>\n Host: As we close, I want to give you the last word. And as the leader of the MSR Lab in Redmond<\/b>,<\/b>\u00a0you\u2019re in a unique position to offer some advice and inspiration to our listeners. What\u2019s the next big north star goal for Microsoft Research?<\/b><\/p>\n Donald\u00a0Kossmann: Yeah, so of course now I have to think big and I have to think beyond to be inspiring. So I think\u00a0we have been programming devices. We\u2019ve been programming mainframes. We\u2019ve been programming PCs. We\u2019ve been programming the web\u00a0and so on.\u00a0I think we need to go to the extreme craziness and think that the world is one big computer. I think this is the big North Star goal that we have.\u00a0And I think, to break it down, and we were talking about the edge and the cloud, we are kind of making the world programmable by injecting computers,\u00a0or micro controllers,\u00a0into everything and that way,\u00a0we make the world programmable. But at the moment we\u2019re still doing that in isolation. And I would love us to think of it as a one big system\u00a0that we should program. And of course, we should think about, again, what are the things that we can enable? What are the killer applications of that computer? What are the ways to optimize it kind of in the same way as Socrates? How to secure it? If everything is connected, how do you draw lines? And,\u00a0essentially,\u00a0how to program it in an efficient way so that everybody can take advantage of this world computer. Again, it ties into our superpowers. We have the freedom to work on this. We have the skills to execute, maybe not on the complete vision, but on\u00a0pieces,\u00a0important pieces,\u00a0once we have clarity about the landmarks. We have time to do that. We\u00a0can\u00a0take risks, right? Some of the things\u00a0will\u00a0fail on that path. We have all the ingredients here that you need to address these really, really big dreams.<\/p>\n Host: Donald\u00a0<\/b>Kossmann<\/b>, thanks for taking time away from your own North Star goal and coming in!<\/b><\/p>\n Donald\u00a0Kossmann: Thank you so much!<\/p>\n (music plays)<\/i><\/b><\/p>\nRelated:<\/h3>\n
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\nTranscript<\/h3>\n
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","byline":"","formattedDate":"February 19, 2020","formattedExcerpt":"Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research\u2019s flagship lab in Redmond, it\u2019s his job to inspire others to think big, too. But don\u2019t be fooled. For him, thinking big involves what he calls thinking backwards,…","locale":{"slug":"en_us","name":"English","native":"","english":"English"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/636528"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/39507"}],"replies":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/comments?post=636528"}],"version-history":[{"count":6,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/636528\/revisions"}],"predecessor-version":[{"id":668142,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/636528\/revisions\/668142"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/636537"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=636528"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/categories?post=636528"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/tags?post=636528"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=636528"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=636528"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=636528"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=636528"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=636528"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=636528"},{"taxonomy":"msr-promo-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-promo-type?post=636528"},{"taxonomy":"msr-podcast-series","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-podcast-series?post=636528"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}