Full Transcript for Called to serve: Tech, research, and positive impact with Chris White

00:04:38.080 which means—I'm going to generalize here—debate  team or math competition team or chess team? 00:04:38.080 --> 00:04:43.680 WHITE: Oh, it was the debate team. Yeah.  Debate was a really wonderful activity.   00:04:43.680 --> 00:04:47.760 It taught me how to understand many  sides of an issue and taught me how   00:04:47.760 --> 00:04:51.560 to think about evidence and research in that way. 00:04:51.560 --> 00:04:58.240 LIU: So, Chris, take me back again. Like,  we're talking a little bit about Oklahoma,   00:04:58.240 --> 00:05:03.920 and, you know, at some point, you chose  researcher. Like, I—for example—when I was a kid,   00:05:03.920 --> 00:05:09.680 I was convinced I would be an architect. I am  not an architect as you can see. But did you   00:05:09.680 --> 00:05:14.800 always think you were going to be a researcher?  Was there an epiphany there? Like … or was it   00:05:14.800 --> 00:05:18.713 always kind of like a slow hunch that you  were going to pursue research as a career? 00:05:18.713 --> 00:05:24.080 WHITE: Yeah, I kind of always felt like  it. You know, as I was applying for school,   00:05:24.080 --> 00:05:28.720 those were the kinds of jobs I was interested  in. You know, the kinds of things that you do,   00:05:28.720 --> 00:05:33.280 you know, once you finish degrees that have  research in them. Those were the people,   00:05:33.280 --> 00:05:38.800 when I visited their work, I was inspired by.  The people that were discovering, you know,   00:05:38.800 --> 00:05:43.040 that were inventing, that were innovating,  that were … they're pushing the boundaries   00:05:43.040 --> 00:05:47.440 that were kind of in that unknown, you  know, space and making sense of it. 00:05:47.440 --> 00:05:49.600 And so I've always had that curiosity, you know,   00:05:49.600 --> 00:05:57.840 and that approach to discovery. And so as I  increased my education, it just changed the   00:05:57.840 --> 00:06:05.600 nature of what research meant and the ways  in which I imagined that process evolving. 00:06:05.600 --> 00:06:11.120 LIU: Was a doctorate always on the  cards then? Or did that come, like,   00:06:11.120 --> 00:06:15.120 as you were in college and then gradually learned  and thought, you know, I could keep going? 00:06:15.120 --> 00:06:18.960 WHITE: Yeah, you know, I didn't know  about doctorates really when I went to   00:06:18.960 --> 00:06:24.960 college. I wasn't as familiar with higher  education. And so I knew that I wanted,   00:06:24.960 --> 00:06:28.960 you know, advanced degrees. And I knew that  I wanted more than was being taught in the   00:06:28.960 --> 00:06:34.000 undergraduate level. But I didn't know, you know,  for example, that when you apply to PhD programs,   00:06:34.000 --> 00:06:38.480 that often you get paid to go. You know,  you get admitted and you get a stipend. 00:06:38.480 --> 00:06:44.000 You know, I was familiar with law and medicine  and that you take out loans and you have to   00:06:44.000 --> 00:06:49.360 do it this way. And so for me, it was a  surprise to know that I could apply to PhD   00:06:49.360 --> 00:06:55.200 programs directly from college. And from  then, I just really was excited, you know,   00:06:55.200 --> 00:07:02.080 that I could explore different universities  and different areas of focus and build on,   00:07:02.080 --> 00:07:06.640 you know, strong technical foundations  of math and science and physics. 00:07:06.640 --> 00:07:13.520 And it was really amazing mentors that helped  me and opened doors and inspired me. You know,   00:07:13.520 --> 00:07:19.200 mentors at Oklahoma State University, Johns  Hopkins, and Harvard, really people that   00:07:19.200 --> 00:07:23.800 took their time and helped me. I'm  really grateful for my teachers. 00:07:23.800 --> 00:07:32.420 LIU: So let's talk about your first mentor  of your life, and I'm going to assume … Dad? 00:07:32.420 --> 00:07:34.520 WHITE: Yeah, Dad’s a big influence. 00:07:34.520 --> 00:07:40.800 LIU: OK, Dad's a big influence. And so we're going  to, I'm going to go down this path. So Catalyst   00:07:40.800 --> 00:07:46.240 Lab landed a huge commitment from our executive,  kind of, leadership team on a project that has   00:07:46.240 --> 00:07:52.320 been, I think, like a decade in the making. And  then … so we all, I know we all came together on   00:07:52.320 --> 00:07:57.440 a call. We're like, “Wow, let's debrief. Let's  talk about it.” Like, oh, energy's up. And   00:07:57.440 --> 00:08:03.243 then at the very end of the meeting, you said,  “OK, now I'm going to go clean some toilets.” 00:08:03.243 --> 00:08:03.275 WHITE: [LAUGHS] Mm-hmm. Mm-hmm. 00:08:03.275 --> 00:08:08.640 LIU: And I think all of us kind of  thought, like, wha-what does that   00:08:09.280 --> 00:08:14.560 mean? So before we get kind of more into  the specifics of mentorship and the,   00:08:14.560 --> 00:08:22.400 like, follow-on in your career, what— please tell  me—does cleaning toilets have to do with success? 00:08:22.400 --> 00:08:26.400 WHITE: Well, you know, like I said, Dad's a  big influence, and he taught me so many things,   00:08:26.400 --> 00:08:29.920 and he taught me about respecting  people. And most importantly,   00:08:29.920 --> 00:08:34.480 he taught me about humility and  service. And so his way of making   00:08:34.480 --> 00:08:37.920 sure I understood that was every time  something really good happened to me,   00:08:37.920 --> 00:08:44.560 he'd remind me to go clean some toilets and,  sort of, embody that. And so I did. I did it   00:08:44.560 --> 00:08:50.240 last weekend actually. I went to a community  event and volunteered to do bathroom clean. 00:08:50.240 --> 00:08:56.400 LIU: Is this like … are you … so in, like, the  household chores, are you, like, the bathroom   00:08:56.400 --> 00:08:59.109 cleaner? Like, is this just always your job  when we're dividing up chores in the house? 00:08:59.109 -->

00:09:04.320 WHITE: No, no, no. We trade off, and also we  have a complicated household, and so we have   00:09:04.320 --> 00:09:10.240 a lot of help that also helps with cleaning.  And so this is something that I choose to do,   00:09:10.240 --> 00:09:14.400 especially if I can do it in a community  context, because it again reminds me,   00:09:14.400 --> 00:09:20.160 you know, about humility and about service and  of respect for other people and other jobs. 00:09:20.160 --> 00:09:26.880 LIU: So I think this … there's some Eagle Scout  vibes that I'm getting from here, as well,   00:09:26.880 --> 00:09:35.280 based on sort of humility and service. What  is the Boy Scout badge you are most proud of? 00:09:35.280 --> 00:09:43.120 WHITE: Oh, that's really hard. Each badge is  something that you earn, including the Eagle   00:09:43.120 --> 00:09:48.320 Scout badge. And the Eagle Scout badge for me  was maybe the most difficult to earn because   00:09:48.320 --> 00:09:54.320 it requires an Eagle project. And I was really  close to my Eagle project. I was, I was … had   00:09:54.320 --> 00:10:01.440 it set up and it was ready to go. And it was in  this church in downtown Oklahoma City in 1995.   00:10:01.440 --> 00:10:08.378 And right as I was about to do this project, the  Murrah Building blew up in a terrorist incident, … 00:10:08.378 --> 00:10:08.389 LIU: Whoa. 00:10:08.389 --> 00:10:14.480 WHITE: … and it blew up part of the church. And,  therefore, my Eagle project was not realistic, and   00:10:14.480 --> 00:10:21.760 it was not a priority, and it got shelved. And it  took me several years after that to then come back   00:10:21.760 --> 00:10:28.538 to plan and execute an ambitious Eagle project  right before I turned 18. And so that badge, … 00:10:28.538 --> 00:10:30.640 LIU: Wow. WHITE: … you know, completing the project, 00:10:30.640 --> 00:10:36.400 overcoming significant setbacks, including  being a teenager and having other interests,   00:10:36.400 --> 00:10:41.000 to come through and finish it,  I'm really proud of finishing it. 00:10:41.000 --> 00:10:48.080 LIU: That's awesome. So you … so that was, so  there were a few years then in between when   00:10:48.080 --> 00:10:55.200 you ideated, had the idea for the project,  and then … I appreciate the story around   00:10:55.200 --> 00:11:02.880 resilience because of when you completed the  project. Like, what is the biggest takeaway   00:11:02.880 --> 00:11:08.160 that you took from there? Like what is that  big lesson? You turned 18, you finished it,   00:11:08.160 --> 00:11:11.600 you celebrate. Actually, you know, maybe  I'll ask you, how did you celebrate? 00:11:11.600 --> 00:11:17.760 WHITE: Oh, with my family. You know, the Boy  Scouts is a long process. It's many years, many   00:11:17.760 --> 00:11:23.440 kinds of roles, many kinds of learning, and to  finish it—I finished it with another of my fellow   00:11:23.440 --> 00:11:28.240 scouts that had been together for a long time.  And so our families, we had a ceremony, and it   00:11:28.240 --> 00:11:32.480 was something we could celebrate. And every time I  think about it, I think about the things that you   00:11:32.480 --> 00:11:37.840 keep repeating when you attend the scout things,  like the motto, “being prepared,” and the, kind   00:11:37.840 --> 00:11:42.720 of, laws about being respectful and courteous.  And those are things that continue to be,   00:11:42.720 --> 00:11:49.960 you know, principles that influence my priorities  and also inspire me and help me in my job. 00:11:49.960 --> 00:11:55.520 LIU: Before we get to your job then, we're  going to talk about this interim period   00:11:55.520 --> 00:12:04.000 where I'll just say you chose to go to war and a  few other things in between. Let's jump to 2010,   00:12:04.720 --> 00:12:09.360 when you joined DARPA, which is the  Defense Advanced Research Projects Agency,   00:12:09.360 --> 00:12:13.840 within the Department of War. And then, I  think, very quickly afterwards you were sent   00:12:13.840 --> 00:12:19.360 to Afghanistan to help implement a new  approach to wartime analysis. And then   00:12:19.360 --> 00:12:29.040 … but before that, I think you were a Harvard  postdoc, and you had actually mentioned it was   00:12:29.040 --> 00:12:35.360 a mentor who encouraged you to attend a meeting  with DARPA that resulted in this course change. 00:12:35.360 --> 00:12:43.280 And so now I'm super curious, how did  this conversation happen where you were,   00:12:43.280 --> 00:12:46.880 you know, promising Harvard postdoc,  which became a mentor going, “Hey,   00:12:46.880 --> 00:12:50.960 there's something happening. You should  go attend.” Like, what happened there? 00:12:50.960 --> 00:12:57.760 WHITE: Yeah. DARPA invests taxpayer  money, and they have a record of   00:12:57.760 --> 00:13:01.360 really creating innovations, massive  innovations. You know, the internet,   00:13:01.360 --> 00:13:07.920 GPS, stealth, UAVs. And at the time, there  was different ways of building programs,   00:13:07.920 --> 00:13:14.080 and one of the kind of tested ways was to  bring together different fields of expertise. 00:13:14.080 --> 00:13:21.520 And so we were in wartime in Afghanistan.  DARPA was not involved very much. And there   00:13:21.520 --> 00:13:28.080 was a question: you know, could we bring  together social scientists with math people,   00:13:28.080 --> 00:13:34.640 computer science and defense experts, and  together could they help us make sense of   00:13:34.640 --> 00:13:41.600 what's happening in the data? Could that be useful  to prevent violence and to protect our soldiers?   00:13:41.600 --> 00:13:46.080 And it was an experiment because it required  all these different areas of expertise coming   00:13:46.080 --> 00:13:53.200 together—from sensors through analysis  through social behavior—and a culture   00:13:53.200 --> 00:14:00.960 change. And so the

summer was a Skunk Works to  understand, was there something to contribute? 00:14:00.960 --> 00:14:04.480 And at the end of it, they asked  me, they said, “Well, you know,   00:14:04.480 --> 00:14:08.720 do you believe in your work?” And I was  like, “Yeah.” You know, like, “Well,   00:14:08.720 --> 00:14:15.200 do you … can you prove it? You know, can you  go see if it can help protect our soldiers   00:14:15.200 --> 00:14:21.280 and help prevent violence?” And so they  asked me to be of service, and I said yeah. 00:14:21.280 --> 00:14:28.000 And it was something that I was really unprepared  for. I was supposed to go for nine days the first   00:14:28.000 --> 00:14:32.880 time, and on the third day, I got a battlefield  promotion and was put in charge and then ended   00:14:32.880 --> 00:14:39.920 up staying for 90 days and then went back a few  times after that even. And so, you know, our work   00:14:39.920 --> 00:14:44.560 was towards … oriented towards protecting, you  know, soldiers and toward preventing violence   00:14:44.560 --> 00:14:53.840 and using AI and advanced technology to do  that. And it was a, really, a big opportunity. 00:14:53.840 --> 00:15:02.480 LIU: So you attended a meeting, you contributed  some work, and then, you know, “Do you believe   00:15:02.480 --> 00:15:09.360 in your work? Prove it.” What was the time frame  between, you know, like, showing up at meeting,   00:15:09.360 --> 00:15:15.009 participating in some of the research before,  like, “prove it”? Was it years, or was it months? 00:15:15.009 --> 00:15:19.840 WHITE: The … no, no, the … so the Skunk Works  was a summer. It was like, you know, 40 days of,   00:15:19.840 --> 00:15:25.040 kind of, like focused effort. But at the end  of it, I was expecting to go back to Harvard   00:15:25.040 --> 00:15:31.120 and continue my postdoc. But instead, you  know, they sat us down; they said, “Look,   00:15:31.120 --> 00:15:37.520 you know, we think this can make a difference.  You know, do you think so?” And when I said yeah,   00:15:37.520 --> 00:15:42.400 from then to getting over there was like  a week. It was an extremely fast ... 00:15:42.400 --> 00:15:43.029 LIU: What? 00:15:43.029 --> 00:15:49.960 WHITE: … turnaround. It was extremely  urgent and, you know, unexpected. 00:15:49.960 --> 00:15:56.000 LIU: OK, so, like, how … so you  said, yes, like I believe in my   00:15:56.000 --> 00:16:02.560 work. They gave you … they essentially  said, OK, then go next week. And how,   00:16:02.560 --> 00:16:07.480 how does somebody prepare for an experience  like that? If you can even prepare. 00:16:07.480 --> 00:16:11.440 WHITE: Yeah, I don't know. You know,  this was an experiment. You know, sending   00:16:11.440 --> 00:16:18.560 researchers—even having a presence from DARPA—in  the war zone, it was new. And the idea was there   00:16:18.560 --> 00:16:23.840 could be a difference made because technology  was advancing quickly. And that meant that

many   00:16:23.840 --> 00:16:28.640 of the mechanisms in place for other ways of  getting prepared were not available. And there   00:16:28.640 --> 00:16:33.600 was a bunch of training, like crash courses in  training on what to do in certain situations,   00:16:33.600 --> 00:16:40.560 how things work, you know, how to handle yourself  in different ways. But it was … it was very brief. 00:16:40.560 --> 00:16:44.960 And so there wasn't a lot of preparation  because also we were planning to be there   00:16:44.960 --> 00:16:49.360 for nine days. But because there was  an opportunity to do something good,   00:16:49.360 --> 00:16:56.320 that extended, and there was a lot of learning  on the job and a lot of support in theater,   00:16:56.320 --> 00:17:02.520 a lot of people really willing to  help us because we were helping them. 00:17:02.520 --> 00:17:09.920 LIU: So, OK, so you talked about lots of people  there, lots of people supporting. I'm not going to   00:17:09.920 --> 00:17:14.640 focus too much on your time in Afghanistan because  that was covered really well in a Popular Science   00:17:14.640 --> 00:17:23.504 article. But I do have to ask, can you tell me the  origin story of the nickname Dr. Spaghetti Man? 00:17:23.504 --> 00:17:30.000 WHITE: [LAUGHS] Sure. Sure. You know, I'm  a long-time yoga practitioner. You know,   00:17:30.000 --> 00:17:39.440 20-plus years. It's how I keep myself calibrated.  And in Kabul, I was practicing yoga in the gym,   00:17:39.440 --> 00:17:44.480 and all these people were staring at me. You know,  they were staring at me before their … they had   00:17:44.480 --> 00:17:49.840 a class; they had, like, a combatives class, a  kind of different judo-mixed-martial-arts class. 00:17:49.840 --> 00:17:52.720 And, you know, I had a little bit of  training, and so after a couple of times,   00:17:52.720 --> 00:17:59.840 I decided I'd just join in. And I joined in,  and I won a lot. I won a lot of the matches.   00:17:59.840 --> 00:18:05.600 And one of the matches I won, turns out, it  was against the Marine who was guarding the   00:18:05.600 --> 00:18:11.760 entrance to the building I was working  in across the headquarters. And he told   00:18:11.760 --> 00:18:19.840 everyone. He told everyone, you know, that  this, like, lanky spaghetti guy, you know,   00:18:19.840 --> 00:18:25.280 like, got out of things and beat him, and  he did it in such a way that everyone in   00:18:25.280 --> 00:18:33.280 the building knew. And so I got all this  respect, and I got that cool nickname. 00:18:33.280 --> 00:18:39.280 LIU: Did other folks challenge you as a  result of this Marine telling your story? 00:18:39.280 --> 00:18:44.480 WHITE: I mean, everyone that came to that  class was game, you know. And I didn't,   00:18:44.480 --> 00:18:48.800 you know, I couldn't beat everybody, but I  held my own, and that was really surprising   00:18:48.800 --> 00:18:53.520 to a lot of people. And again, once you 

establish yourself in different ways,   00:18:53.520 --> 00:18:57.960 you know, there is a lot of  respect and, um, camaraderie. 00:18:57.960 --> 00:19:05.200 LIU: So, you know, tell me, what did  that whole experience teach you about,   00:19:05.200 --> 00:19:09.600 like, a life lived, and how do those  lessons show up in your work today,   00:19:09.600 --> 00:19:13.920 including the, you know, Spaghetti Man experience? 00:19:13.920 --> 00:19:18.320 WHITE: You know, the whole thing,  it taught me about, you know,   00:19:18.320 --> 00:19:25.280 service and what it means to serve,  and it taught me about the reality of   00:19:25.280 --> 00:19:31.720 both peace and violence in the world. And that  continued to motivate me to make a difference. 00:19:31.720 --> 00:19:38.320 LIU: After your time in Afghanistan, you  continued on with DARPA as a program manager,   00:19:38.320 --> 00:19:43.840 and in that role, you developed Memex,  which I believe is a set of tools that   00:19:43.840 --> 00:19:49.200 could be mixed and matched to help uncover  some really shady and dark parts of the web,   00:19:49.200 --> 00:19:53.760 which from what I understand was  really hard to do up until that point. 00:19:54.320 --> 00:20:03.200 I think this work also is what helped you … what  you received your 2016 presidential award on. And,   00:20:03.200 --> 00:20:09.760 you know, like, can you … how do you explain  the Memex project and this dark web work to   00:20:09.760 --> 00:20:16.080 someone outside tech? And what about this project  inspired or appealed to you to even pursue it? 00:20:16.080 --> 00:20:22.480 WHITE: Yeah, well, the inspiration started when I  was overseas because I saw the benefit of evidence   00:20:22.480 --> 00:20:29.840 when it came to stopping bad things from happening  and prosecuting them. And coming back to the US,   00:20:29.840 --> 00:20:35.280 I saw more and more opportunities where  collecting evidence at large scale   00:20:35.280 --> 00:20:40.080 was a really useful mechanism. And so, you  know, people think of search engines a lot,   00:20:40.080 --> 00:20:45.920 and search engines are a great tool for finding  something, but when you need to connect the dots,   00:20:45.920 --> 00:20:51.520 there wasn't a great tool that could work at  the scale of the web and connect the dots,   00:20:51.520 --> 00:20:56.400 especially some of the dots being in  difficult places that were not very visible. 00:20:56.400 --> 00:21:01.520 And so by creating a technology that would  connect the dots across parts of the internet,   00:21:01.520 --> 00:21:06.000 it allowed the prosecution of these kinds  of really awful [trafficking] crimes,   00:21:06.000 --> 00:21:11.760 and so for example, in New York City, it allowed  them to increase their prosecutions by 10 times   00:21:11.760 --> 00:21:15.680 because it gave them new evidence and different  kinds of evidence than they had before,   00:21:15.680 --> 00:21:21.160 and they could use that in a way to  really deal with the issue differently. 00:21:21.160 --> 00:21:26.480 LIU: OK, from what I understand, the  dark web is a pretty—ha-ha—dark place,   00:21:26.480 --> 00:21:32.720 [LAUGHS] and so, like, you've worked in  some very dark spaces and close to some   00:21:32.720 --> 00:21:38.160 very dark uses of the technology. So, like,  how again, like, you and I interact a lot,   00:21:38.160 --> 00:21:47.040 and so it's always curious to me, how has that  not made you cynical and how do you stay hopeful? 00:21:47.040 --> 00:21:52.880 WHITE: You know, I think what it's done is  it's really increased my motivation. You know,   00:21:52.880 --> 00:21:55.840 my motivation to make a contribution. You know,   00:21:55.840 --> 00:22:03.440 my motivation to stay aware and be realistic.  And by being realistic and motivated to   00:22:04.880 --> 00:22:10.800 address some of these very challenging issues,  you know, around violence, around harm,   00:22:10.800 --> 00:22:18.640 and instead to focus on empowerment and to  focus on justice, it gave me something to do. 00:22:18.640 --> 00:22:28.240 And so I have seen a lot of really bad humanity,  you know. I've seen terrorism and trafficking and   00:22:29.120 --> 00:22:33.600 sophisticated organized crime, you know,  designed to take things from people.   00:22:33.600 --> 00:22:38.720 Designed to hurt people. And I just know  that I can do something about it, you know,   00:22:38.720 --> 00:22:44.720 and that I have and that we can. And so it's  really been inspiring to, you know, for example,   00:22:44.720 --> 00:22:49.680 come to Microsoft, where there is a mission  of empowerment and there is that perspective   00:22:49.680 --> 00:22:56.320 that technology can make a difference.  And so I think that light, you know,   00:22:56.320 --> 00:23:05.040 the light of making a difference, you know, allows  me to hold and handle, you know, the dark parts. 00:23:05.040 --> 00:23:10.240 LIU: I mean, that's a very powerful message,  right? Because even with the darkest parts of   00:23:10.240 --> 00:23:17.920 humanity, there is light, or, you know, you  cannot have darkness without light, as well. 00:23:17.920 --> 00:23:22.320 I think there may have been a 60 Minutes  interview that included a short snippet   00:23:22.320 --> 00:23:27.440 of you talking about your work, and you  had shared with me that—which, by the way,   00:23:27.440 --> 00:23:34.480 I cannot find the 60 Minutes episode,  and I desperately want to. But, you know,   00:23:34.480 --> 00:23:41.920 I heard perhaps through you, Chris, that that  60 Minutes episode actually contributed to you   00:23:41.920 --> 00:23:48.960 coming to Microsoft maybe or, you know, getting a  job at Microsoft, and that made me curious. Like,   00:23:48.960 --> 00:23:57.160 after some really incredible experiences, after  all of that, why did you choose Microsoft? 00:23:57.160 --> 00:24:05.280 WHITE: Oh, it was a …

it was a really good  choice. And at the time, I had a lot of options,   00:24:05.280 --> 00:24:13.040 and I was looking around, and this mix of the  mission of the company—this mission of empowering   00:24:13.040 --> 00:24:19.760 everyone—and the scope of the company, you know,  being, you know, IT for the world, you know,   00:24:19.760 --> 00:24:24.880 platforms and infrastructure for the world,  and my confidence in its leader. You know,   00:24:24.880 --> 00:24:30.000 the CEO was part of my interview process.  And, you know, that together gave me,   00:24:30.880 --> 00:24:33.600 you know, this perspective that I  could do something here. You know,   00:24:33.600 --> 00:24:40.400 that there … I could start to envision moving  from, you know, for example, very high-powered,   00:24:40.400 --> 00:24:47.760 expensive lasers to table knives. They  both cut, and the world needs both of them. 00:24:47.760 --> 00:24:53.520 LIU: One of the things that you talk a lot  about is problem selection. And I think   00:24:53.520 --> 00:24:58.960 sometimes that also gets referred to as taste  these days. So how do you think about problem   00:24:58.960 --> 00:25:05.760 selection in Microsoft Research, in Catalyst  Lab, given the breadth of what Microsoft does? 00:25:05.760 --> 00:25:10.480 WHITE: Oh, I think it's just the most  important part of research. You know,   00:25:10.480 --> 00:25:16.960 it's the place where the angle of the whole  thing changes, and it allows you to start to   00:25:16.960 --> 00:25:21.680 imagine a different future, you know, or to work  backward from that future that you want to see   00:25:21.680 --> 00:25:27.600 and see what you can do to contribute to it now.  And the amazing thing about Microsoft Research   00:25:27.600 --> 00:25:33.840 is there's tremendous freedom, and so there's  tremendous creativity in problem selection. 00:25:33.840 --> 00:25:39.760 And it's the kind of thing where you have  that latitude to go from idea to evidence   00:25:39.760 --> 00:25:45.040 to this potential for growth and thriving  and along the way get feedback about value   00:25:45.040 --> 00:25:54.000 and usability and benefit or policy or  adaptability, integration. And so its   00:25:54.000 --> 00:26:01.200 scope provides so many vehicles for growth  and utility of advanced research ideas. 00:26:01.200 --> 00:26:07.360 And its mission, you know, allows the focus of  those to address absolutely critical problems. You   00:26:07.360 --> 00:26:14.400 know, problems of, you know, impending security  challenges due to AI, problems of advanced,   00:26:14.400 --> 00:26:21.520 you know, memory and storage; it allows for, you  know, personalization automation, just, you know,   00:26:21.520 --> 00:26:30.640 for example. And I think that this mix of freedom  combined with responsibility and mechanisms,   00:26:30.640 --> 00:26:37.760 you know, to prove out and demonstrate value,  that that combination is just really remarkable   00:26:37.760 --> 00:26:44.320 and it really motivates me to  take the opportunity seriously. 00:26:44.320 --> 00:26:52.000 LIU: So it's almost going to be like asking you  about your favorite kids now. What are some, what   00:26:52.000 --> 00:27:00.080 are some accomplishments in Microsoft Research or  Catalyst Lab that you are particularly proud of? 00:27:00.080 --> 00:27:07.760 WHITE: Oh, you know, I think that, you know, right  now, for example—again, focusing on kind of where   00:27:07.760 --> 00:27:16.240 we are—I think that we have a real opportunity to  contribute something in the cyber defense space.   00:27:16.240 --> 00:27:25.280 I think our work on security and AI  and hacking, it's really in, you know,   00:27:25.280 --> 00:27:31.760 based on such a deep expertise and also based  on, you know, people with a lot of experience,   00:27:31.760 --> 00:27:36.640 and I think it's growing in need, you know,  the need to protect our digital infrastructure,   00:27:36.640 --> 00:27:44.800 the need to deter and interdict people that would  like to break systems or cause harm, that's really   00:27:44.800 --> 00:27:51.840 growing right now. And so being able to show up  in a way that creates breakthrough that can scale   00:27:51.840 --> 00:27:58.000 with relevance to address that growing need, it's  really something that's, you know, awesome to me. 00:27:58.720 --> 00:28:03.200 And also I think that again kind of extending  from the, sort of, Memex conversation,   00:28:03.200 --> 00:28:08.640 where we're trying to connect the dots, you know,  these days, trying to analyze lots of content as   00:28:08.640 --> 00:28:12.960 part of being more efficient, as part of being  more creative, as part of being more capable,   00:28:12.960 --> 00:28:19.040 you know, using tools to augment that human  taste and creativity and ingenuity, that's   00:28:19.040 --> 00:28:24.640 really never been as powerful as it is before  and continues to grow. And so I think making   00:28:24.640 --> 00:28:29.360 contributions in these areas, you know, where  we have state-of-the-art technology and we're   00:28:29.360 --> 00:28:35.200 creating changes in the way systems are getting  built and used, to me, it shows that, you know,   00:28:35.200 --> 00:28:43.040 despite the fast pace of change and despite the  extreme competitiveness in the technology sector,   00:28:43.040 --> 00:28:49.760 that specialized expertise with good problem  selection and an environment to grow and get   00:28:49.760 --> 00:28:55.600 feedback can create the kind of breakthroughs  that matter. And so I really like that. 00:28:55.600 --> 00:29:00.480 Maybe to give one more example from the past.  Just maybe something emblematic of the group   00:29:00.480 --> 00:29:08.800 and some of my predecessors was this underwater  datacenter called Project Natick, [LAUGHTER] where   00:29:08.800 --> 00:29:13.280 this experiment, you know, put a datacenter in a 

submersible on the bottom of the ocean connected   00:29:13.280 --> 00:29:18.560 to a wind farm, and it tested this design about,  could you build something that didn't require   00:29:18.560 --> 00:29:24.080 human intervention? Could it be more efficient  with power? Could it be more efficient with heat? 00:29:24.080 --> 00:29:29.360 And the program manager that created that is  one of the best I've ever worked with. And it   00:29:29.360 --> 00:29:35.920 just performed incredibly well as this  huge surprise, and it led to us being,   00:29:35.920 --> 00:29:38.400 you know, named the most innovative company  [World Changing Company of the Year] in 2021   00:29:38.400 --> 00:29:44.160 and other awards. And it's just an example  of really out-there thinking, imagining a   00:29:44.160 --> 00:29:51.360 world that had challenges with water access  and power access and land but where we need,   00:29:51.360 --> 00:29:57.680 you know, computation and data storage  and technical capability available. 00:29:57.680 --> 00:30:00.960 So a little bit out there, but  I really … I feel like we have   00:30:00.960 --> 00:30:04.640 to be imagining these different  futures. We have to be radical   00:30:04.640 --> 00:30:11.200 in that way so that we can start to  work back and make contributions now. 00:30:11.200 --> 00:30:19.600 LIU: I love the Natick example because I feel  like Natick is the gift that keeps on giving. And,   00:30:20.480 --> 00:30:27.120 you know, if I can digress for a minute, I  remember that I think one of the first TikTok   00:30:27.120 --> 00:30:35.600 videos that the Microsoft account posted  was of Natick, but it was using, like,   00:30:35.600 --> 00:30:41.920 a meme at the time which had, like, human eyes  and a mouth being lowered into, uh, and it was   00:30:41.920 --> 00:30:47.680 of Natick being lowered into the ocean, including  like a Clippy, like a real-life Clippy swimming   00:30:47.680 --> 00:30:55.760 across the … it was … I still love that video for  reasons why I don't understand. [LAUGHTER] But if   00:30:55.760 --> 00:31:00.214 you haven't seen it, highly recommend. Maybe we  can link it [LAUGHS] if the video still exists. 00:31:00.214 --> 00:31:04.703 WHITE: Definitely. Look, look, one  of the highlights was the fish cam. 00:31:04.703 --> 00:31:04.713 LIU: Yes! 00:31:04.713 --> 00:31:09.200 WHITE: You know, people were concerned that it  might disrupt the marine ecosystem. And we did   00:31:09.200 --> 00:31:15.983 a lot of preparation and study for that. And just  to be sure, we put cameras and watched it happen. 00:31:15.983 --> 00:31:15.993 LIU: Yep. 00:31:15.993 --> 00:31:20.480 WHITE: And all these fish kept coming around  and making it home. And there was, like,   00:31:20.480 --> 00:31:23.840 computer vision that was analyzing  which fishes and their movement,   00:31:23.840 --> 00:31:29.595 and it became like an always-on thing that people  would just tune in to online to watch the fish. 00:31:29.595 --> 00:31:33.737 LIU: There was a seal. There was a seal.  There were a couple seals that came by, … 00:31:33.737 --> 00:31:33.751 WHITE: Yeah. 00:31:33.751 --> 00:31:38.953 LIU: … too, which, yeah, I remember that.  That's really cool. Thanks for sharing. 00:31:38.953 --> 00:31:46.543 WHITE: Yeah, so you have to go not just  out of the box but out of the datacenter. 00:31:46.543 --> 00:31:50.320 LIU: [LAUGHS] Oh no. All right. All right. 00:31:50.320 --> 00:31:55.120 So, Chris, before letting you go, it  would be a missed opportunity if I did   00:31:55.120 --> 00:32:00.960 not ask you to share some practical advice and  reflections given the breadth of your experience   00:32:00.960 --> 00:32:04.880 and lessons that you learned. So I'm going to  do … maybe it doesn't have to be a super-fast   00:32:04.880 --> 00:32:09.102 lightning round, but it's going to be a  lightning round of a couple of questions. 00:32:09.102 --> 00:32:09.115 WHITE: Sure. 00:32:09.115 --> 00:32:13.440 LIU: All right. One, what is the  advice that you have received in   00:32:13.440 --> 00:32:16.880 your life that blew your mind  or changed your perspective? 00:32:16.880 --> 00:32:23.760 WHITE: You’ve got to look out for the right place  and the right time with the right people because   00:32:23.760 --> 00:32:29.120 it takes all those things to come together  for magic to happen and to make a difference. 00:32:29.120 --> 00:32:33.760 LIU: OK, I'm going to have to ask. This is not …  I'm breaking my own lightning round. How do you   00:32:33.760 --> 00:32:37.040 know? Like, how do you know if it's the right  place or the right time or the right people? 00:32:37.040 --> 00:32:39.840 WHITE: The universe gives a  lot of feedback. You know,   00:32:39.840 --> 00:32:45.840 it's something that with  good listening, you can hear. 00:32:48.560 --> 00:32:51.680 LIU: What did … what did the universe tell you? 00:32:51.680 --> 00:32:57.179 WHITE: Told me to marry my wife. 00:32:57.179 --> 00:33:00.067 LIU: [LAUGHS] Ohhhh. Good choice. Good  universe. Good universe. OK, next. 00:33:00.067 --> 00:33:02.778 WHITE: Yeah. Told me to have my kids. Absolutely. 00:33:02.778 --> 00:33:05.960 LIU: All right, next. Lesson you learned the  hard way or the misstep that humbled you? 00:33:05.960 --> 00:33:11.760 WHITE: I’ve got to slow down. My tendency  is to push too fast and too hard,   00:33:11.760 --> 00:33:18.000 and that can really lead to problems.  And slowing down, it doesn't in the end   00:33:18.000 --> 00:33:23.440 slow everything down. It just actually  makes it just right and just enough. 00:33:23.440 --> 00:33:26.400 LIU: What's an example of slow down? 00:33:26.400 --> 00:33:33.120 WHITE: Well, you know, I think there’s slowing  down in making decisions, especially about people,   00:33:33.120 --> 00:33:40.080 compared to other kinds of decisions.  Or even in my yoga practice. Slowing   00:33:40.080 --> 00:33:48.080 down the way

that I use my body so that it  can be healthy and strong for a long time. 00:33:48.080 --> 00:33:52.000 LIU: I do believe that one  of your … the advice that   00:33:52.000 --> 00:33:55.280 you often give us in Cat Lab is take a vacation. 00:33:55.280 --> 00:33:56.000 WHITE: Absolutely. 00:33:56.000 --> 00:34:00.080 LIU: So slow down definitely fits that. 00:34:00.080 --> 00:34:01.560 WHITE: Get some perspective. 00:34:01.560 --> 00:34:07.120 LIU: So next question: talent or  accomplishment you're most proud   00:34:07.120 --> 00:34:12.480 of if given the chance to brag. And you have  stated humility many times, and I'm going to   00:34:12.480 --> 00:34:16.960 ask you to just turn that bit off for a  little bit and brag a little bit instead. 00:34:16.960 --> 00:34:23.840 WHITE: Mm-hmm. Well, I think it would  be putting my leg behind my head and   00:34:23.840 --> 00:34:27.720 saying [LAUGHTER] the alphabet backwards  while playing a percussion instrument. 00:34:27.720 --> 00:34:33.259 LIU: Hold on. Like, this is for realsies, and this  is, like, this is not an AI-generated statement … 00:34:33.259 --> 00:34:33.271 WHITE: No. 00:34:33.271 --> 00:34:36.000 LIU: … or prompt? This is …  And you've done this before? 00:34:36.000 --> 00:34:41.026 WHITE: I have. I've done  it in a leadership offsite. 00:34:41.026 --> 00:34:41.800 LIU: [LAUGHS] You did not. 00:34:41.800 --> 00:34:43.880 WHITE: I did. 00:34:43.880 --> 00:34:49.040 LIU: I am going to need to ask  some of our colleagues about   00:34:49.040 --> 00:34:51.667 that particular experience, but  there was a percussion instrument? 00:34:51.667 --> 00:34:56.960 WHITE: Yeah. There was. But, you know, all kidding  aside, you know, the 2016 presidential medal,   00:34:56.960 --> 00:35:02.800 you know, being able to make such a difference  in a way for so many people that were affected   00:35:02.800 --> 00:35:08.000 and to also change the way technology was used  from the data collection evidence, you know,   00:35:08.000 --> 00:35:14.400 through judicial proceedings, that process  and arc, you know, is definitely something I'm   00:35:14.400 --> 00:35:19.480 extremely proud of, was extremely difficult,  and I would definitely go for it again. 00:35:19.480 --> 00:35:26.880 LIU: I love it. OK, I love asking this  one. You know I've asked people this a   00:35:26.880 --> 00:35:30.240 lot. Career path you would have chosen if you did   00:35:30.240 --> 00:35:34.944 not become a researcher—and you're  not allowed to say yoga teacher. 00:35:34.944 --> 00:35:38.040 WHITE: [LAUGHS] No, I would just  be a different kind of researcher. 00:35:38.040 --> 00:35:39.907 LIU: No! 00:35:39.907 --> 00:35:40.635 WHITE: Yeah, definitely. Yeah. 00:35:40.635 --> 00:35:44.240 LIU: Really? OK, so if not an AI  or computer science researcher,   00:35:44.240 --> 00:35:45.520 what else would we be researching? 00:35:45.520 --> 00:35:48.955 WHITE: Oh, the brain. You know, the … 00:35:48.955 --> 00:35:53.440 LIU: OK, how about a non-STEM  research topic? [LAUGHS] 00:35:53.440 --> 00:35:55.540 WHITE: Anthropology. 00:35:55.540 --> 00:36:01.600 LIU: OK, OK, fine. So, like, no, there's no  scenario where research is not in the picture. 00:36:01.600 --> 00:36:07.200 WHITE: No, it just seems to be part of me,  you know, part of my drive, you know, part of   00:36:07.200 --> 00:36:14.160 what gives me energy, keeps me motivated  and curious. And this, you know, frontier,   00:36:14.160 --> 00:36:17.680 it allows that evolution to keep unfolding. 00:36:17.680 --> 00:36:23.920 LIU: OK. All right. Good to know. So not  yoga teacher. Always some form of research. 00:36:23.920 --> 00:36:28.160 WHITE: Well, I mean, yoga teacher is a  kind of researcher into the universe. 00:36:28.160 --> 00:36:32.800 LIU: What?! [LAUGHS] WHITE: You know, it's a researcher  into the states of consciousness and being.   00:36:32.800 --> 00:36:38.800 Into the alignment between the mind and the body.  It's full of research. Full of personal research. 00:36:38.800 --> 00:36:48.560 LIU: This is why I believe when once upon a time  at a leadership offsite you were asked to prompt   00:36:48.560 --> 00:36:54.640 AI to demonstrate, to build, like, a mascot for  you, and I think that mascot was also doing yoga. 00:36:54.640 --> 00:36:59.600 WHITE: It was. I asked my … I asked one  of my copilots to generate a picture of   00:36:59.600 --> 00:37:04.520 me based on everything it knows,  and it created a cat doing yoga. 00:37:04.520 --> 00:37:11.520 LIU: [LAUGHS] I love it. OK, so lastly,  and this is less “lightning round” and   00:37:11.520 --> 00:37:16.880 more like “take your time.” What would you  like listeners of this podcast to take away   00:37:16.880 --> 00:37:21.360 from this conversation? You know,  about you, about professional life,   00:37:21.360 --> 00:37:25.640 about research, about making … or  maybe even just making choices. 00:37:25.640 --> 00:37:32.800 WHITE: You know, I think it's about the  power of adaptability and the diversity   00:37:32.800 --> 00:37:40.000 of experience. You know, it's about  being open to what wants to happen,   00:37:40.000 --> 00:37:47.640 what needs to happen. You know, being open,  called to serve, willingness to change. 00:37:47.640 --> 00:37:50.000 LIU: I like that. 00:37:50.000 --> 00:37:56.000 So thank you, Chris—Dr. White—for joining me,  and to our audience, thank you for listening. 00:37:56.000 --> 00:37:58.383 WHITE: Thanks, Wei. 00:37:58.383 --> 00:37:59.360 [MUSIC] STANDARD OUTRO: You’ve been listening to the 00:37:59.360 --> 00:38:02.480 Microsoft Research Podcast.  Check out more episodes of   00:38:02.480 --> 00:38:11.680 the podcast at aka.ms/researchpodcast or  on YouTube and major podcast platforms. 00:38:11.680 --> 00:38:12.204 [MUSIC ENDS]