Chris Williams: Rick Rashid is one of the great minds in the world of computer science. He grew up in small town Iowa and ended up founding one of the world’s leading research institutions.
At the University of Rochester in the late 1970s, where Rick got his postgraduate degrees, he was among the first to work with the Xerox Alto. The Alto was the first computer to use a graphical interface and a mouse, a full decade before the Apple Macintosh, and two decades before Windows 95 made it ubiquitous.
Rick and his friend Gene ball developed Alto Trek, likely the first computer game ever to run across a network of computers. Later at Carnegie Mellon, Rick advanced many fields including artificial intelligence, networking, and programming languages. But his most famous work was the development of the Mach kernel that changed the way computer operating systems are built. If you use Apple products, whether a computer, tablet or phone, the underlying code can trace its heritage back to the Mach kernel.
Rick is however best known as the founding leader of Microsoft Research. The organization he created and led for over 20 years is consistently at the front edge of computer science. It’s been instrumental in developing fascinating technologies in a range of areas, including speech and language, data management and exploration, and user interfaces. He is a passionate advocate for research and researchers.
Rick Rashid: I think sometimes in our society, we forget how important it is that we have all those specialized bits of expertise. People that know how to do a really tiny thing really, really, really well.
CW: In our conversation, Rick and I talked about his journey from small town, Iowa to the bleeding edge of computer science. He described how he built and managed a global research organization. We later explored the impact of research on the current pandemic. And that’s what this is all about.
This is Leading Smart, the show about managing in the brainpower age. It’s a field guide to the joys and challenges of leading and working in the modern workplace.
I’m Chris Williams, your guide to the stories and ideas that I hope will inspire you to be a better leader in the world of knowledge work.
In this episode, I talk with the founding leader of Microsoft Research. This is Episode 209. my conversation with Rick Rashid.
Chris Williams: Rick Rashid, in many ways represents the best of the American dream. His grandparents escaped religious persecution in the Ottoman Empire in the late 1800s. And settled in Iowa. From there a passion for math and science landed him a spot at Stanford.
Rick Rashid: So always a scientist, I love, you know, tinkering, working on radios and TVs and doing science experiments. I was the president of the science club. You know, I did all the usual science things.
CW: Yeah. So So how does a kid from middle Iowa end up at Stanford?
RR: Almost completely by accident. The funny story there was that, you know, I was looking to figure out, you know, what universities I wanted to apply to. And my guidance counselor decided, really on his own, to put together an application for me for Stanford, which honestly, I didn’t know anything about Stanford at the time. And he thought I should apply there.
And so I applied to like University of Illinois, where I was accepted and some other places. And so I wound up eventually getting accepted to Stanford, and I honestly didn’t know where the heck it was. When I went to get a plane ticket to go there, it was like, Oh, it’s Northern California. I didn’t know what part of California was. Right. I’m flying to San Francisco. That’s interesting, you know, so yeah, it was really kind of an accident. I mean, it was a great place. I really, you know, enjoyed being there.
CW: Rick had the fortune to meet Dan Ling on his first day at Stanford. Dan went on to work at IBM Research where he advanced the state of the art in computer video, and eventually followed Rick to Microsoft Research. It was Dan, who introduced Rick to computers in his sophomore year,
RR: I was a undergraduate major in mathematics, and also in comparative literature. So I had a dual major, very weird to a major, not too many mathematics, Comparative Literature majors out there. And my good friend at Stanford, you know, I’d met the very first day I was there as Dan Ling. You know, who you eventually got to know, and became a corporate vice president of Microsoft as well. And Dan had taken this computer science class he was an Electrical Engineering major, but he took this computer science class. And it was like, Wow, he loved it. He thought it was the greatest thing. And said, Well, you’ve got to do this. It’s so much fun. You should take this.
And of course, I had a pretty full course load with two majors. But I said, Okay, sure, why not? add one more, you know, what the heck. And it was just, I just loved it. You know, it’s one of these you’ll love at first sight kind of things, where it’s like, this is a fabulous subject.
And then I, I took the next class, which was an art in architecture class. We had these these very early HP 2116 minicomputers, we had them for the class. And they were in a special room that was locked, you had to have a code to get in and everything. And you had to program this thing from the switches and from paper tape, because that was the only way it worked. Actually, there was no other way to program it. And for whatever reason, I just… that just appealed to me. I remember the first first I like spent all day getting this program to work, that would basically read in things for paper tape, sort them and print them back out again on a on a teletype. And I got that working. And I just floated across campus. It’s like midnight, you know, and I just floated up, it was just like, my intellect had had animated this piece of machinery. Right? It’s like, How cool is that? That is the coolest thing I could think of. And so I got just really fast. And I want to take in pretty much every course Stanford had on computer science. That was no major at the time. This is before there was a major. So I just took a whole bunch of classes and …
CW: Rick then got a chance to help start a computer science program at the University of Rochester in upper New York State.
RR: I was going to go to graduate school in mathematics, and I was accepted at Berkeley. And then I was contacted by Jerome Feldman, who was Associate Director of the AI lab at Stanford. And he had seen my resume and my information, you know, from the from the program, and he was starting a new computer science department at the University of Rochester. And he, he didn’t have his own admissions program or anything like that. So he, he was reached out to people he thought would be good students for him. And he convinced me that I didn’t really want to go on to graduate school of mathematics. I really wanted to join him and do this new computer science program at Rochester.
CW: Rochester was also the home of Xerox. On the strength of their massive copying machine empire, Xerox was funding a great deal of cutting edge research, both in Rochester and in their famous Palo Alto Research Center, or PARC in California.
Those connections helped land the new computer science department, some state of the art computers.
RR: We were also able to arrange to get Xerox Altos you know, as a new startup department when nobody else outside of Xerox had them. And you know, that was just a tremendous advantage as a young, you know, starting up your first year as a graduate student and you get access to, you know, the most powerful personal computer that anyone had ever created. And it was a unique resource for us.
CW: After getting both a masters and a PhD at Rochester, Rick found his way through a happy accident to Carnegie Mellon University.
RR: Well, that was also an accident. There are a lot of accidents in my life to be honest,
CW: Well, actually, I’ve interviewed a lot of people and there are accidents in every one of them.
RR: So, planning is definitely overrated.
RR: At least career planning.
RR: But, you know, in my case, what happened was I had not applied to CMU in any way. I was out interviewing at other universities and other research labs. And but there was some sort of conference where Jerry Feldman, who is the guy who started the department at Rochester, and he was the person who brought me in, and Raj Reddy who was one of the prominent professors at CMU, we’re out together and there was some cocktail party and, and Raj was asking Jerry, if he had any really great system students that he could, you know, bring in because they desperately needed, you know, a strong system student for a new project that they were doing. That within the area of, of networking and personal computing, and Jerry said, well, you should talk to Rick Rashad.
Raj literally called me up on the phone. I come back from a recruiting trip, you know, and Raj called me up at the phone and said, I want you to come out here. I want you to talk to us, you know, we need you here. And it wasn’t so much of an interview as it was a sell trip. He totally made up his mind, I think, you know, put on the full court sell and, and convinced me that I needed to go there and help start this project. You know, that was called the Spice project at CMU.
CW: Did you join as a as an assistant professor or just as a research student or
RR: No, I joined is that what they have a research scientist position, which they basically at CMU at that particular time, I assume it’s probably the same now but I don’t know for a fact. But at the time, they had both tenure track positions, which were the Assistant Professor, associate and so on. And they had the equivalent research track positions. And the only real difference between the research track, Research Scientist tracks and Senior scientists and so forth, and the professor track was soft money versus hardware. Right? So the professors were technically hard money tenure track positions, and the research positions, you know, we’re, we’re soft money not tenure track. But the reality is the people you did exactly the same thing, meaning I taught classes, I did everything … and eventually they actually moved me over to the to the tenure track and I got tenure there. But there was effectively no difference between the two, except for where the money came from.
CW: Rick spent over a decade at CMU, teaching and doing some seminal work in the area of computer operating systems. Rick and a team developed the Mach kernel, an operating system that forged all new ground and helped lay the foundation for many systems to follow.
Then along comes Microsoft looking to start a research lab, and they knew how to get Rick’s attention. They enlisted Gordon Bell one of the most famous names in early computer science. Bell had been instrumental in the development of the mini computer and lead some of the most important developments, both at Digital Equipment Corporation and at Carnegie Mellon. It was a phone call Microsoft was sure Rick would answer.
RR: Well, interesting enough. The first person that contacted me with my phone was Gordon bell. Well Gordon had been asked by Nathan Myhrvold to help him, you know, find a director for this new research lab that he had gotten approval from, from Bill and from the board of directors to create.
And so I’m in my home and in Pittsburgh, and it’s dinnertime, and I get this phone call. Now, you know, you get phone calls at dinnertime, right? They’re not usually anything very interesting. But this is Gordon Bell, right? So, you know, one of the more famous computer scientists in the world, you can’t really tell Gordon, hey, I’m having dinner. You know, can you call back later? So I assume this is why Nathan asked to do this because, again, you can’t really tell court that you’re having dinner.
So at any rate, I talked with Gordon and he convinced me to have him and Nathan come out to to Carnegie Mellon to talk with me about this lab that they wanted to create. The honest truth is I had very little reason to believe, this was something I wanted to do. Right. Microsoft was a very small company. You know, the record of companies started research labs wasn’t that great anyway. And small companies starting research labs was generally speaking, an oxymoron. Right? It just, it doesn’t doesn’t make any sense. Right? Why would they want to do this? And it Microsoft didn’t exactly have a great reputation in the academic community. It was just a small software company doing DOS, as far as anybody knew. So
CW: run by several college dropouts.
RR: Yeah, well, I didn’t even know very much about Bill in those days. So so they come out. And you know, they try to convince me that this is a great good idea and they didn’t get very far with that, but, you know, they’ve lots of enthusiasm and, and they convinced me Well, you should at least come out and visit us.
CW: So this is late 90 probably?
RR: This is the summer of, no sorry, this was the spring of 1991. Okay. All right. And so, so I, I go out to Microsoft. And the honest truth is I was very impressed with everybody I talked with. I talked with Jim Allchin, I mean, I talked with Nathan, of course, and I had a fabulous conversation with with with Bill. And I was just very impressed. I mean, these are very smart people. And they actually knew what they were doing and, and in they seem to have a pretty good idea of what they wanted out of a research lab and why they would want to start one and and how they thought it would, it would work.
In a particular Bill, it was it was a funny conversation with him because I kept expecting I would say something and he would contradict me. Because obviously he couldn’t possibly think about research and running a research lab at the same way that I did. And yet everything he, he seemed to agree with everything. And we, he actually came back to me with a lot of things that that made sense to me and I and I came out of meeting thinking, either one, you know, Bill really does understand what building a world class research lab lab would be like, or two, he just really wants to hire me. He’s gonna say yes to everything I said, right. And in you know, Bill, he’s actually not like that. If he if he disagrees with you, he doesn’t actually …
CW: there’s no hiding it right?
RR: Yeah, yeah, you can’t hide from Bill. So but I learned that years later, as I got to know him better, but at the time, I wasn’t really sure. So I went back by very impressed with my visit. But I still turned Nathan down again. Because, honestly, I just like being at Carnegie Mellon…
The University was also courting me at that time to, to be the Dean of what was becoming that school of computer science. And they wanted me to be its first Dean. And, and so I had this conflict going on, right? I didn’t, I was really happy doing what I was doing. And then all of a sudden, I have people trying to get me to do something different. And a lot of loyalty to Carnegie Mellon. And I felt strongly about wanting to to help the university. At the same time, I was intrigued by what I saw at Microsoft. And so it was a very interesting summer, as I tried to contemplate what I should do. Nathan kept pushing on me, I kept pushing back. He would refer to me as Doctor No. Cuz I kept telling him No. I think he thought maybe I was negotiating. I’m not sure. But it got to a point where I decided I was going to make a decision on a particular day. And, you know, let let Microsoft and Carnegie Mellon know on that day. So the end of basically the beginning of September end of August.
And eventually I decided I would go to Microsoft, and I think a lot of that was driven by my feeling that it was going to be more fun. You know, it was going to be something I could start from scratch. And you know, in a way that was very daunting. And most of my friends thought I was crazy, because they thought starting a research lab in this remote Pacific Northwest where nobody was. And you know, the it was not a place you could imagine building a research lab back in those days.
Basically, everybody thought if you’re going to be doing a research lab back then it needed to be Boston or or California. Right. And Pacific Northwest was considered to be extremely remote and, and it was going to be difficult to recruit. I mean, that’s what everybody would tell me. But I guess, I thought it was gonna be a fun challenge. And so I, I took up that challenge and didn’t really regret it.
CW: I wondered how Rick, a university professor could take on the challenge of starting a research institution from scratch. Had he done much leadership?
RR: Technically, I was a full professor there. But I had a fairly large organization that I was running, because the Mach research project got to be pretty large. And yeah, with a lot of funding from DARPA, and, you know, it also a number of companies were funding us. So, you know, it was one of these things where, where, you know, I, I had about 30-40 person organization, plus, plus, I, you know, I was heavily involved in running the department in those days, so, You know, certainly brought in a lot of the money the department was run with in those days. So, so in a way, I had a lot of opportunity to, to understand what it was like to at least run, you know, started run a research project from scratch.
CW: So when you got to Microsoft, I mean, one of the things that you mentioned and and that obviously was clear to me, I came to Microsoft, about a year later. One of the things that was just abundantly clear to me, and you brought it up was that it was filled with really smart people. I mean, it was just, it was if you were a fan of smart people, it was a kid in a candy store. I mean, there were just smart people everywhere. Was that invigorating, intimidating, was it competitive was it?
RR: It was tremendously invigorating. I mean, I just had, I mean, it in some ways, it was the best environment to to to start start a research group in because you could you could bring in candidates, and you could have them talk to some of these people and they’d realize, wow, you know, I didn’t realize there were so many incredibly smart people. And these were people doing products, right? A lot of times researchers grow up in an academic environment and you get a PhD, and you tend to think, oh, the PhDs are the smart people. No, really, they’re just a ton of incredible people in the proper organizations, many of whom had PhDs, by the way, but also maybe even we had PhDs and other subjects entirely, not computer science,
CW: English literature…
RR: English literature, physics was common, you know, that was actually fairly common. You know, and it’s, so it’s one of these things where, you know, it was a great environment to work in. And then also those people, I think, often appreciate it when you brought in a really smart person, you know, in a research role, they would appreciate that too. They didn’t think, oh, gosh, this is some pointy headed intellectual. They said, Oh, okay, I’ve read his paper right here, I’ve read her papers. I know what what she’s doing. Right. And, you know that that was that I think that was great.
I remember the first time we did a research review with Bill and and I kept trying to get the researchers to understand how much bill with would likely know about what they were doing, right, and but I don’t think they really got it until they were in that room doing the review. And they realized Bill probably knew more about a lot of the things related to their, their subject and they did
CW: and probably had read the work that they had done before they walked in the room and right and … right.
RR: yeah, and and their their competitors work and everybody basically, they realized they were gonna have to up their game and presentation from that point forward.
RR: That I wasn’t just kidding them. That that that this was an environment in which they were going to be intellectually challenged, and intellectually challenged not just by their academic peers, but by the people in the product organization.
One of the things I remember people asking me was what was different between the academic experience and working at Microsoft did I, I would always say just the speed and the intensity. Right? Everything was so much faster at Microsoft, and the intensity of the work was so much greater. And it’s not like, again, the academic world is, is, you know, has its own own intensity as well. But, but the stakes were very high.
I mean, always felt like the future of the company was at stake. Right, the future of the field was at stake, you know, and, you know, everyone was working, you know, at, at what I felt to be served, you know, peak velocity in trying to get things done. And that was that was invigorating.
CW: One of the challenges of doing research whether at a company or a university is getting the ideas and development into the products, into the real world.
RR: If that was really part of the.. I mean that that was the vision from the very beginning. The vision statement for research was move the state of the art forward in the areas that we’re working, so be at the at the state of the art in each area that we’re working in. And, and the second part of that was, when it makes sense to move that into products as quickly as we possibly can. You know, and Bill was on board with that. That was me, Nathan wanted to do that. And honestly, that was pretty much my career. I mean, if you look at my career, the things that I worked on, you know, got moved into various people’s products, you know, fairly quickly, I think they, you know, it’s one of the, the characteristics of maybe the systems area that I that I worked in is that you tended to work a lot with companies and you tended to work, you know, on things that actually got into products and got into use. And, and so that was kind of part that was part of the way I thought about my own work. And I, that’s the way I thought about Microsoft Research.
CW: Was that relationship with the product teams? Easy, good? Hard?
RR: I think it varies dramatically, with the individual teams and the people everything’s, everything’s person to person nothing is … there is no sort of organization right when it’s all about people who get to know people who get to trust people. You know, I would always talk about, you know, research is a full contact sport, you know, and by that I mean, it’s it’s person to person, right? It’s not something you do at a distance.
And I think very early on, there were some very specific situations that were where the product groups came to research to help solve problems, or to deal with, with, with situations that they found themselves in. And, and, you know, we would step up. And I mean, my philosophy was, if, if, if the company needs something, I’ll drop whatever I’m doing, let’s just do it, let’s figure it out and solve it. You know, and I and that was kind of an attitude that I felt that, that the research organization should take, you know, if we, the company needs help to make something happen. We should we should just say, Okay, what do we roll up our sleeves, let’s work together. And we had a lot of times where we did that with product teams, and I think we earned earned credibility as a result of that. And and I think when people see that you’re willing to work side by side. And that you can work as late as they can. And, and you can eat as much pizza as they can, you know, you know, that’s that’s when that’s when trust develops.
CW: Was there any kind of movement of people between research and products? I mean, there were, as you said, there were all these really smart people in the product groups. Did anybody move from one way to the other? Or was there a fairly crisp line there?
RR: No, it was it was a fluid line and tended to be fluid in the sense that, that we had a number of researchers that would move to product teams to either either to help solve a particular problem or to take their ideas. Sometimes they would stay within the research management structure, but physically reside over in the product organization. Other times they would just move into that structure.
But I always I always gave everyone a golden ticket to come back. Right. So, so part of making it easy for people to work in the product team was making sure that they understood that when they were done doing that they could come back to research and, and go back to doing what they’ve been doing before that they that they love.
And, you know, I think it was a sense of, of, they weren’t, you know, they could they could move, and it was okay. Right. And they could come back and it was going to be fine in their career, they were enhancing it. And I think that was a philosophy that I would exude. I mean, that was something I would tell people that this is this is the way I thought of it. And I think people believed it, or at least a number of them did enough to do it.
CW: Under Rick’s leadership, Microsoft Research grew from a small Redmond based group into a worldwide research organization.
RR: Well, it’s interesting because originally, I was not sure we could could do that. You know it, you know, we started our lab in Redmond. And, you know, my feeling was that it was important to have people together, you know that we could get the synergies of people working together. At the same time, you know, sort of gradually, as we established Redmond, right as it got to the point where it was clear that we were successful. You know, we were, we were dominating conferences in the areas we were doing our research, and we got to be about 100 people, I think by 1995, early 96. We’re about 100 people. And so, so that was pretty good. That was a good size for a research lab.
And Nathan Myhrvold who I reported to he, he always wanted to do research labs outside the United States. I was always opposed to it because I felt gosh, you know, this is just gonna be management headaches. I’m not … it’s going to dilute our focus. But we certainly reached the size where, where it started to make sense.
And we had a unique opportunity to hire a Roger Needham at the University of Cambridge. And Roger was being forced to retire because they have a forced retirement age there. And he didn’t want to retire really. And, you know, through his friends, you know, Chuck Bakker and and Butler Lampson and various other people made it be known that he was available. And, and so we decided to start a research lab in Cambridge, and it was the availability of roger that allowed us to do that. And we got go, you know, that that started very nicely and Roger was tremendously talented, a great person to bring other people in.
And we decided soon after that, well we should just take the plunge and start a lab in China. And it took us about a year and a half, I think for the time we started the lab in Cambridge to do the lab in China. But again, if we, we felt that was an opportunity to bring in a unique set of talent. And I think when you start expanding like that, it’s really to capture talent,
RR: That you couldn’t get any other way there. Clearly there, you know, tremendously bright young Chinese, who we could attract in China that we couldn’t bring to the United States. Similarly, there were people who didn’t want to leave Europe didn’t want to leave England, and we could we could tap into that resource. And, I think I’ve learned over time how to manage that, you know, in terms of, you know, obviously you need tremendously smart leaders in each group. But you also need, you know, to build an infrastructure where people people communicate where they interact remotely, right? That they, it’s not just about who is next to you, but it’s, it’s sharing experiences, you know, sending people back and forth having people in other labs for periods of time. You know, building a culture that is shared and similar across the different organizations, even though they’re not inside, the same, you know, macro culture.
CW: One of the challenges multiple locations introduces is communication. Building and retaining connections at a global distance is hard.
RR: We did create a number of opportunities for people to come to Redmond, you know, for for to do presentations to do to interact with researchers and of course, I would try to spend some time with them. I would go to China once a year and spend spend a week there They’re getting to know people going around, you know, getting a chance to, and also just get a chance to know China going to different universities and different research labs, they’re getting a chance to, to interact with, with, with people in that environment into that society.
But yes, you can’t, you can’t get to know everyone in a 1500 person organization, it that starts to become a little unwieldy. But when you can do I think, is, is true. Try to keep things informal, right? It can’t just all be formal meetings. It can’t just all be I’m interacting with you in a very set framework, you know, where we’re all you know, we all know what to expect before we start and we, we don’t learn that much by the time we’re finished. Right? I really like the the serendipitous interactions that occur when you just talk with people and interact with them.
When I was a professor at Carnegie Mellon never really found having meetings with large numbers of people to be super productive. I mean, there are times when you have to do your coordinating, right? The absolute requirements, and you get a lot of people in a room, in order to coordinate. Everybody has to hear the same voices at the same time. Most of the time, that’s not a really productive way to make things work is to get those people who need to be together and talk together together. And to do it, more often than not in informal situations where they’re actually solving a problem, as opposed to just being there.
CW: I think one of the things that strikes me in any interaction I’ve had with you, you have an upbeat, positive, you almost always have a smile on your face, as you do right at this moment. Do you think that that changes the way the whole organization works? Do you think having a having a positive, upbeat proactive perspective helps the whole organization?
RR: Yeah, I personally I do. I mean, I think it’s, I think it’s a force multiplier, right? optimism helps to drive people to do things that they would otherwise not necessarily believe they could do. Right. I mean, my joke about my own field of operating systems is that, you know, unless you were a wild optimist, there’s no way you would ever work in operating systems. Because it’s just, it’s way too hard. It’s way too complicated. And certainly, when you’re starting from scratch, the chances of success are close to zero. So why would you do that unless you were just like, unrealistically optimistic right? There is no reason.
I mean, you know, and and I think, similarly, you know, in, in a research environment, you know, there, you need to, you need to be able to tackle problems that, that most other people don’t think can be solved. Because that’s how you push the state of the art forward. So unless you were optimistic about your abilities to do that, you know, the chances of you actually pushing that boundary are pretty small.
And, you know, I, I think it’s the, one of one of the things that I did when I was at, in the latter days when I was running research was I, I, I pushed this initiative, which I call “the impossible things initiative”. And the idea is that we would take on a small number of things that people thought were just plain impossible. And and just see, I mean, just throw our heads and bodies against that wall and see what would happen.
I remember one of the things I originally proposed in the memo that I wrote was was speech recognition and translation, I said, what I want to be able to do is in my yearly trip to China, where I speak to, you know, thousands of students at various universities, I want to be able to talk and have have my voice translated into Chinese automatically. And, and I felt that was a an interesting challenge.
And I remember sitting down with some people in and having lunch again, randomly, because this is part of random management, right, sitting down having lunch with a group that happened to be the speech group, not long after that. And so I sat next to this guy who is a young speech researcher, and, and he was absolutely convinced I was just nuts. Right? He said, You just don’t understand, right? You’re some operating systems guy. You don’t understand. You know, this is incredibly hard problem. We’ve been working on this for 25 years, we’re making very tiny amounts of incremental progress. And, and this isn’t going to happen anytime soon. And I kept I kept trying to convince him in his own area, right? And I knew quite, honestly, I do know quite a bit about this particular area, but in every case, I tried to convince him, you know, no, we can do this. And I kept saying, well, but you know, we don’t have to do it all, you know, you know, first off, I would just hope you could just do me, right? You could just translate me. I can speak very clearly. I’m from Iowa. Right? I can enunciate really well. You know, I can speak slowly. I, you can get I have all these speeches of mine recorded. You can use all the data. It’s all transcribed by Microsoft, you can all you can, you can learn from all that data, right? I was I was trying to make it sound as easy as I possibly could. And he I don’t think I really convinced him very much, but, but there were people in that group that got really excited about the challenge. And and who believed, you know, well, hey, you know, if the head of the organization believes we can do this, maybe we can, and, you know, he’s willing to back us up and he’s willing to fund us. So what the heck, you know, and …
And it turned out it worked. You know, in 2012, I gave a speech and intention and China, and part of my speech was automatically translated into my own voice in Chinese, you know, and all done by computer and all done off the cuff, you know, as I was standing on stage there, and that was, that was a great moment.
CW: So that brings me around to I mean, we’ve talked a little bit about how you motivate researchers, how do you how do you performance review a researcher How do you decide if somebody is doing well or not doing well? How do you manage out a poor performer? How does that stuff work?
RR: Well, you know, top level research lab, in some sense, you have almost a bit of an advantage over what a product group might have or a more conventional organization because you have that external measure. Right? So you’re, it’s a little bit like a top level, a professional basketball or football or something like that. You’re measured against your peers on an ongoing basis around the world, right? You’re up against the very best. You’re publishing papers, you’re establishing a reputation. And either you succeed in doing that, or you don’t, you know, but you don’t have some internal metric that you worry about. This is an external one is is you know, can you get your papers published in the in the top conferences and journals? Can you get the level of recognition? Can you get the awards? Can you can you get your peers you Your community to recognize you for your accomplishments? And, and, you know, that’s how you measure people in a top level research organization. And it’s a pretty straightforward external. I mean, there’s no number associated with it, per se. But it’s pretty easy for both you and the researcher to know when you’re, when they’re succeeding and when they’re not.
And when they’re not, you encourage them to, you know, find other things that they could be doing, because they’re not going to be successful in your organization. So, and that means that people can contribute in a lot of different ways. It isn’t just a research organization isn’t just about, you know, the very top researchers. there are other people that contribute in other ways, that aren’t the ones that that necessarily are the are the ones that are publishing the most. You know, we obviously have developers and and, and other other people within the organization that play an important role. But you have to have those very top researchers, or you’re not going to be at the state of your, of the art in your field. And those are measured externally. And you can just point to the success or the failure. You, you celebrate the successes, and you move on from the failures.
CW: We then turned to the effect of the pandemic on the research working environment. In a way the multiple locations of the research group paved the way for the post pandemic world.
RR: Yeah, I think Well, I think for us at least it was already happening. I mean, when you when your organization is spread around the world, and I think the product group is beginning to see this too, because they were being spread around as well. You come to realize that there are really a lot of things you can do to manage projects, to keep people in touch, to maintain interactions.
And the honest truth is we have really pretty good tools. Now, by comparison. You know, if you look back 20 years when, you know, when we were trying to do this, when we were both much younger, you didn’t have GitHub, right? You didn’t have the the online meeting tools and you didn’t have the instantaneous communication that we do now. And I think there is a, a big change in, in the quality of the tools both to create software to manage projects to, to do research. I mean, researchers also now have, you know, online repositories, they share, they share their work, they share their their knowledge and not just in a single institution, they share them across institutions now, in ways that didn’t happen 20 years ago. And papers now that used to wait a year to get a paper published, now, if it’s online instantaneously, you can just get a pointer to it, read it, comment on it, you know, fix it, share data with that researcher, that that may help them or contradict what they were. They were doing it in some sense to accelerate science and accelerate the work that people are doing.
CW: But does this mean researchers working from home?
RR: Yeah, I think I think to some extent, that’s already happening.
RR: The pandemic is causing it to happen. But it was happening before. I mean, you were already having researchers that were working across organizations, whether within Microsoft or, you know, between universities, between companies, that was already happening, the extent to which you can talk about doing research in your house. depends a bit on what you’re doing.
RR: either. If you’re doing theoretical computer science, you can probably do in your house.
RR: You need access to computational resources. But luckily, the cloud has really solved that problem for us. For other researchers, in other fields, it gets to be more difficult if I’m building something physical, you know, I need access to physical right equipment,
CW: or chemistry lab or you know, any of those sorts of things. Right work.
RR: Yeah, or linear accelerator, or there are things that you can’t quite put in your backyard, right? The HOA is probably not going to allow. But at the same time, you know, we’re also getting better control remotely of equipment. So it isn’t just about, you know, can I? You know, do I have to be physically present, you know, these days I don’t, I can run a telescope from anywhere in the world and get the results. I don’t have to be at the top of of a mountain in Hawaii, right?
You know, I can I can run experiments. You know, at CERN, I don’t have to be at CERN. Personally. Now, we have to have technicians there, we have to have people there. And there are times when I need to have physical access to a piece of equipment in order to understand exactly what’s going on with it. If I’m doing biological research, I may need physical access to tissue to people, you know, to, to medical facilities. That’s probably not going to change immediately.
On the other hand, you know, we have doctors operating remotely now. You know, so I think we’re getting to a point where the promise of the digital revolution is getting to be fulfilled and alive. A lot of ways, in sometimes ways we weren’t necessarily expecting.
CW: On a personal note, Rick has recently recovered from a battle with leukemia that nearly killed him. Twice. Not surprisingly, he credits research with a great deal of his recovery.
RR: I was lucky in that my leukemia diagnosis happened just just on the cusp of a lot of new research coming online. And, you know, the combinations of monoclonal antibodies and targeted biologics have completely revolutionized cancer care. And, and really given a lot of people a lot of hope they wouldn’t otherwise have I mean, I I would just be dead I mean, I I almost died twice last year as my cancer became acute. And
CW: and now your trail running.
RR: And now I’m back to trail running, and I’m ahead of my all time, you know, best pace so
RR: So I think you know, I think it’s I think we’re lucky in a way a lot. I mean this is this is part of the reason why we do research. It doesn’t matter what area it’s in whether it’s computer science or biology or medicine or physics, you do research to solve problems, you know that are going to happen.
There were a lot of times when I was at Microsoft, when various people in the product groups would wonder about something we were doing. He said, Well, we don’t have that problem. Right. Why are you doing this? I said, Well, chances are we will have this problem. And we want to have a solution. For the time when we do.
Basic research, whether it’s for a company, whether it’s for a country or for a society, for humanity as a whole. It’s a form of an insurance policy. Right? It’s, it’s when, when when we have a pandemic like this, that we have researchers that can go out and, and solve those problems for us, they can develop those vaccines at a pace that have never been seen before, that can, you know, come up with new drugs on an accelerated schedule, and it can save lives.
It’s always you, you feel you feel badly about the fact that so many people have died in this particular pandemic. But you have to feel incredibly great that only that many people have died. Right that, you know, if you look at at past pandemics by this stage, in the pandemic, it would have been 10s or hundreds of millions dead.
CW: And we’re looking at a number of vaccine candidates, six months or eight months out from the start of the pandemic as opposed to three to five years out, which is what it would have been just a few years ago and the genetics research and those kinds of things have have laid the foundation for that.
RR: well, these new these new RNA vaccines, for example of a completely new area of vaccine research, you know, it started with some of the work on Ebola and SARS. But, you know, now with it, there’s a possibility those could be some of the very first vaccines that come online, and they could revolutionize the way we think about vaccination.
So I’m both a living example. But also, you know, it’s been my life’s work to invest in doing basic research well ahead of when we necessarily had to have it and, and being ready with solutions to problems when they actually occur.
And so many times, you know, during my time at Microsoft, you know, when the product groups needed something we would have already done research on it, we would have the best people in the world that knew about it. And we could put those people and treasure chest of ideas and technologies to work, you know, to solve the problem for those product teams. I think that’s what we’re doing now for this pandemic.
CW: Rick Rashid is both a personal and professional example of the best of pure research and the value it brings to the world. I can’t thank him enough for both the decades of work he has done and for spending the time with me
Leading Smart is from me, Chris Williams.
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That’s it for this episode. The next episode we return to the studio and to the topic of diversity. We’ll talk about how to actually build an organization that thinks differently. It’s called “It’s About Time”. I hope you’ll listen. Until then, please remember that each of the several dozen decisions you make today are part of Leading Smart.