Kevin Scott: Microsoft CTO | Lex Fridman Podcast #30

Lex Fridman and Kevin Scott on microsoft CTO Kevin Scott Envisions Democratic, Ethical, Platform-Powered AI Future.

Lex FridmanhostKevin Scottguest

Aug 1, 201957mWatch on YouTube ↗

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100 min read · 20,303 words

0:00 – 3:11
Microsoft’s breadth: cloud, SaaS, hardware, research, and major acquisitions
1. LFLex Fridman
  The following is a conversation with Kevin Scott, the CTO of Microsoft. Before that, he was the senior vice president of engineering and operations at LinkedIn, and before that, he oversaw mobile ads engineering at Google. He also has a podcast called Behind the Tech with Kevin Scott, which I'm a fan of. This was a fun and wide-ranging conversation that covered many aspects of computing. It happened over a month ago, before the announcement of Microsoft's investment in OpenAI that a few people have asked me about. I'm sure there'll be one or two people in the future that'll talk with me about the impact of that investment. This is the Artificial Intelligence podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter, @lexfridman, spelled F-R-I-D-M-A-N. And I'd like to give a special thank you to Tom and Ilanti Beckhausen for their support of the podcast on Patreon. Thanks, Tom and Ilanti. Hope I didn't mess up your last name too bad. Your support means a lot and inspires me to keep this series going. And now here's my conversation with Kevin Scott. You've described yourself as a kid in a candy store at Microsoft, because of all the interesting projects that are going on. Can you, uh, try to do the impossible task and give a, uh, brief whirlwind view of all the spaces that Microsoft is working in-
2. KSKevin Scott
  (laughs)
3. LFLex Fridman
  ... (laughs) both research and product?
4. KSKevin Scott
  If you include research, it becomes even, uh, even more difficult. So, so, like, I, I think broadly speaking, Microsoft's product portfolio includes everything from, you know, big cloud business, uh, like a big set of SaaS services. We have, you know, sort of the original, uh, or, like, some of what are among the original productivity, uh, software products that everybody uses. We have an operating system business. We have a hardware business, uh, where we make everything from, uh, computer mice and headphones to high-end, uh, high-end personal computers and laptops. We have a fairly broad-ranging research group where, like, we have people doing everything from economics, uh, research, so, like there's this really, uh, really smart, uh, young economist, Glen Weyl, uh, who, uh, like my group works with a lot, who's, uh, doing this research on, uh, these things called radical markets. Uh, like, he's written an entire, uh, entire technical book about, uh, about this whole notion of, uh, radical markets. So, like, the research group l- sort of spans from that to human computer interaction to artificial intelligence a- and we have, uh, we have GitHub, we have LinkedIn, uh, we have a search, advertising, and news business, and, and, like, probably a bunch of stuff that I'm embarrassingly, uh, not-
5. LFLex Fridman
  Forget, yeah.
6. KSKevin Scott
  ... recounting in, in this, uh, list.
3:11 – 4:14
Gaming as culture and product: Xbox and creative collaborations
1. LFLex Fridman
  Uh, gaming too, Xbox and so on, right?
2. KSKevin Scott
  Yeah. Gaming, for sure. Like, I was, uh, I was having a super fun conversation this morning with, uh, with Phil Spencer. So, when I was, uh, in college, there was this game that, uh, LucasArts made called Day of the Tentacle that my friends and I, uh, played forever. And, like, we're, you know, doing some, uh, interesting collaboration now with, uh, the folks who made, uh, Day of the Tentacle. And I was, like, completely nerding out with Tim Schafer, like, the guy who wrote, uh, Day of the Tentacle, uh, this morning, just a complete fanboy, uh, which-
3. LFLex Fridman
  (laughs)
4. KSKevin Scott
  ... uh, which, uh, you know, sort of, uh, it, like, happens a lot, uh, like, you know, Microsoft has been doing so much stuff, it's such breadth for such a long period of time that, uh, you know, like, being CTO, like, most of the time my job is very, very serious, and sometimes, like, I get to, I get caught up in, like, how, uh, amazing it is to be able to have the conversations that I have with the people I, I get to have them with.
4:14 – 8:00
Radical Markets: provocative market mechanisms to fix capitalism’s incentives
1. LFLex Fridman
  You have to reach back into the sentimental... And what's the, the, the rad- uh, radical markets and the, and the ec- economics?
2. KSKevin Scott
  So, the, the idea with radical markets is, like, can you come up with new market-based mechanisms to, uh, you know, I, I think we have this, uh, we're having this debate right now, like, does capitalism, uh, work? Uh, like, uh, free markets work? Uh, can the incentive structures that are built into these systems produce outcomes that are creating sort of equitably distributed benefits for every member of society?
3. LFLex Fridman
  Mm-hmm.
4. KSKevin Scott
  You know, and I think it's a reasonable, uh, reasonable set of questions, uh, to be asking. And so, what Glen... And, and so, like, you know, one mode of thought there, like, if you have doubts that the, that the markets are actually working, you can sort of, like, tip towards, like, okay, let's, uh, let's become more socialist, and-
5. LFLex Fridman
  Mm-hmm.
6. KSKevin Scott
  ... uh, you know, like, have central planning and, you know, s- government or some other central organization is, like, making a bunch of decisions about how, you know, sort of work gets done, and-
7. LFLex Fridman
  Yeah.
8. KSKevin Scott
  ... uh, you know, like, where the, you know, where the investments and where the outputs of those investments get distributed. Uh, Glen's notion is, like, l- lean more into, uh, like, the market-based mech- mechanism. So, like, for instance, uh, you know, this is one of the more radical ideas. Like, suppose that you had a radical pricing mechanism for assets like real estate, where, uh, you were, you could be bid out of your position in, in, in your home, uh, you know, for instance.
9. LFLex Fridman
  (laughs) Oh. Yeah.
10. KSKevin Scott
  So, like, if somebody came along and said, you know, like, "I've, I can find higher economic utility for this piece of real estate that you're running your, your business in, uh, like..."... then, uh, like, you either have to, you know, sort of bid to sort of stay or, like, the thing that's got the higher economic utility, uh, you know, sort of takes over the asset. Which would make it very difficult to have the same sort of rent-seeking, uh, behaviors that you've got right now because, uh, like, if you did speculative bidding, like, you would, you'd very quickly, like, lose a whole lot of money. And so, like, the prices of the assets would be sort of, like, very closely indexed to, uh, like, the value that they could produce.
11. LFLex Fridman
  Right.
12. KSKevin Scott
  And, like, because, like you'd have this sort of real time mechanism that would force you to sort of mark the value of the asset to the market, then it could be taxed appropriately. Like, you couldn't sort of sit on this thing and say, "Oh, like, this house is only worth 10,000 bucks," when, like, everything around it is worth 10 million.
13. LFLex Fridman
  That's really interes- so it's an incentive structure that, uh, where the prices match the value, uh, much better?
14. KSKevin Scott
  Yeah.
15. LFLex Fridman
  So, the, it, it...
16. KSKevin Scott
  And Glen does a much, much better job than I do at selling it, and I probably picked the world's worst example-
17. LFLex Fridman
  Yeah.
18. KSKevin Scott
  ... you know, and, and, and. But, like, it, and it's, it's intentionally provocative.
19. LFLex Fridman
  Right.
20. KSKevin Scott
  Uh, you know, so, like, this whole notion, like, I, you know, like I, I'm not sure whether I like this notion that, uh, like, we could have a set of market mechanisms where I could get bid out of-
21. LFLex Fridman
  Right. (laughs)
22. KSKevin Scott
  ... uh, out of my property.
23. LFLex Fridman
  (laughs) Yeah.
24. KSKevin Scott
  You know, but, but, you know, like, if you're thinking about something like Elizabeth Warren's wealth tax, for instance, like, you would have... I mean, it'd be really interesting in, like, how you would actually set the-
25. LFLex Fridman
  Mm-hmm.
26. KSKevin Scott
  ... the, the price on the assets and, like, you might have to have a mechanism like that if you put a tax like that in place. (laughs)
27. LFLex Fridman
  It's really interesting that that kind of research at least tangentially is touching Microsoft Research, right?
28. KSKevin Scott
  Yeah.
8:00 – 12:38
AI and jobs: why AI must be a democratized platform, not centralized power
1. LFLex Fridman
  That you're really thinking broadly. Uh, maybe you can speak to... This connects to AI. So, we have a candidate, Andrew Yang, who kind of talks about artificial intelligence and the concern that people have about arti- you know, uh, automation's impact on society, and arguably Microsoft is at, at the cutting edge of innovation in all these kinds of ways and so it's pushing AI forward. How do you think about... I mean, c- combining all our conversations together here with radical markets and socialism and innovation in AI that M- uh, that Microsoft is doing and then Andrew Yang's worry that, uh, that that will, that will result in job loss for-
2. KSKevin Scott
  Yep.
3. LFLex Fridman
  ... for the low end and so on. How do you think about that?
4. KSKevin Scott
  I think it's sort of one of the most important questions in technology, like, maybe even in society right now, uh, about how is AI going to develop over the course of the next several decades and, like, what's it gonna be used for and, like, what, uh, what benefits will it produce and what negative impacts will it produce and, you know, h- how, who, who, who gets to steer this whole thing? You know, I'll say at a, at the highest level, one of the real joys of, of getting to do what I do at Microsoft is Microsoft has this heritage as a platform company.
5. LFLex Fridman
  Mm-hmm.
6. KSKevin Scott
  And so, you know, like, Bill, Bill's g- has this thing that he said, uh, you know, a bunch of years ago where, you know, the, the measure of a successful platform is that it produces far more economic value for the people who build on top of the platform than, uh, is created for the, the platform owner or, or builder. And I think we have to think about AI that way. Like-
7. LFLex Fridman
  As a platform.
8. KSKevin Scott
  Yeah, it has to, like, it has to be a platform that other people can use to, uh, build businesses, to fulfill their creative objectives, to be entrepreneurs, to solve problems that they have in their work and in their lives. Uh, it can't be a thing where there are a handful of companies, uh, sitting in a very small handful of cit- cities geographically who are making all the decisions about, uh, what goes into the AI and, uh, and, and, like, and then on top of, like, all this infrastructure, then build all of the commercially valuable uses for it. So, like, I think, like, that's bad from a, you know, sort of, you know, economics and sort of equitable distribution of value perspective, like, you know, sort of back to this whole notion of, you know, like, do the markets work? Uh, but I think it's also bad from an innovation perspective because, uh, like, I, I have infinite amounts of faith in human beings that if you, you know, give folks powerful tools, they will go do interesting things and it's more than just a few tens of thousands of people with interesting tools. It should be millions of people with the tools. So, it's sort of like, you know, you think about the, um, the steam engine in the late, uh, 18th century. Like, it was, you know, maybe the first large-scale substitute for human labor that we've built, like, a machine.
9. LFLex Fridman
  Mm-hmm.
10. KSKevin Scott
  Uh, and, uh, you know, in the beginning when these things are getting deployed, the folks who, uh, got most of the value from the steam engines were the folks who had capital so they could afford to build them and, like, they built factories around them and businesses and the experts who knew how to build and maintain them. But access to that technology democratized over time. Like, now, like, uh, like, an engine is not a, it's not, like, a differentiated thing. Like, there isn't one engine company that builds all the engines and all of the things that use engines are made by this company and, like, they get all the economics from all of that, uh... Like, no, no, no. Like, fully democratized. Like, they're probably... You know, we're sitting here in this room, uh, and, like, even though they don't, they're, they're probably things, you know, like, the, the MIMS gyroscope that are in both of our pho-
11. LFLex Fridman
  Uh-huh.
12. KSKevin Scott
  Like, they're, like, little engines, uh, you know, sort of everywhere.... they, they're just a component in how we build the modern world. Like, AI needs to get there.
13. LFLex Fridman
  Yeah, so that's a really powerful way to think. If we think of AI as a platform versus a, a, a tool that Microsoft owns, as a platform that enables creation-
14. KSKevin Scott
  Yeah.
15. LFLex Fridman
  ... on top of it, that's the way to democratize it. That's really, that's really interesting actually. And Microsoft is, in its, throughout its history has been positioned well to do that.
12:38 – 16:38
Data dignity and ‘data as labor’: creating markets to value data contributions
1. KSKevin Scott
  And the, you know, the tie-back to the, uh, to this radical markets thing, like, the (laughs) so, my, my team has been working with Glen on this... and Jaron Lanier, actually. Yeah, so Jaron is the, like, the f- sort of father of virtual reality.
2. LFLex Fridman
  Oh.
3. KSKevin Scott
  Uh, like he's one of the most interesting human beings, uh, on the planet.
4. LFLex Fridman
  (laughs)
5. KSKevin Scott
  Like a sweet, sweet guy. Uh, and so Jaron and Glen, uh, and folks on my team have been working on this notion of, uh, data as labor, or, uh, like they call it data dignity as well. And so the, the idea is that if you, you know, again, going back to this, uh, s- you know, sort of industrial analogy-
6. LFLex Fridman
  Mm-hmm.
7. KSKevin Scott
  ... if you think about data as the raw material that, uh, is consumed by the machine of AI in order to do useful things, uh, then, like, we're not doing a really great job right now in having transparent marketplaces for valuing those data contributions. So, like, and we all make them, uh, like explicitly, like, you go to LinkedIn, you sort of set up your profile on LinkedIn. Like that's an explicit contribution. Like you know exactly the information that you're putting into the system, and like, you put it there because you have some nominal notion of like what value you're gonna get in return. But it's like only nominal. Like you don't know exactly what value you're getting in return. Like service is free, you know?
8. LFLex Fridman
  Right.
9. KSKevin Scott
  Like it's low amount of like perceived val- And then you've got all this indirect contribution that you're making just by virtue of interacting with all of the technology that's in your daily life.
10. LFLex Fridman
  Mm-hmm.
11. KSKevin Scott
  And so, like what Glen and Jaron and, and this data dignity team are trying to do is like, uh, "Can we figure out a, a set of mechanisms that let us value those data contributions, uh, so that you could create an economy, and like a set of controls, uh, and incentives that would allow people to like, maybe even in the limit, like earn part of their living through the data that they're creating?"
12. LFLex Fridman
  Right. Right.
13. KSKevin Scott
  And like you can sort of see it in explicit ways. There are these companies like, uh, Scale.ai, and like there are a whole bunch of them, uh, in, uh, in China right now that are basically data labeling companies.
14. LFLex Fridman
  Yes, yes.
15. KSKevin Scott
  So like you- you're doing supervised machine learning, you need, uh, you need lots and lots of label training data. And like those people are getting comp- uh, like who work for those companies are getting compensated, uh, for their data contributions into the system. And so ...
16. LFLex Fridman
  That's easier to put a number on their contribution 'cause they're explicitly labeling data.
17. KSKevin Scott
  Correct.
18. LFLex Fridman
  But you're saying that we're all contributing data in different kinds of ways.
19. KSKevin Scott
  We are.
20. LFLex Fridman
  And it would b- it's fascinating to start to explicitly try to put a number on it.
21. KSKevin Scott
  Yeah.
22. LFLex Fridman
  Do you think that's ev- that's possible?
23. KSKevin Scott
  I dunno, it's hard. It really is. Because, you know, we don't have as much transparency as, uh, as I think we need, uh, in like how the data is getting used. And it's, you know, super complicated. Like, you know, we, we, uh, you know, I think as technologists sort of appreciate like some of the subtlety there. It's like, you know, the data, the data gets created and then it gets, you know, it's not valuable-
24. LFLex Fridman
  Mm-hmm.
25. KSKevin Scott
  ... like, yeah, the, the data exhaust that you give off, uh, or the, you know, the explicit data that I am putting into the system isn't value, valuable, isn't super valuable atomically.
26. LFLex Fridman
  Mm-hmm.
27. KSKevin Scott
  Like it, it's only valuable when you sort of aggregate it together into, you know, sort of large numbers. This is true even for these, like folks who are getting compensated for like labeling things. Like for supervised machine learning now, like you need lots of labels to train a, you know, a model that performs well. And so, you know, I think that's one of the challenges. It's like how do you, you know, how do you sort of figure out like, because this data's getting combined in so many ways, uh, like through these combinations, like how the value is flowing.
28. LFLex Fridman
  Yeah, that's, that's fascinating. (laughs)
29. KSKevin Scott
  Tough. (laughs)
16:38 – 20:50
Microsoft’s evolution since Windows 3.0: platforms, ubiquity, and a new mission
1. LFLex Fridman
  (laughs) Yeah, and it's fascinating that you're thinking about this. And I wa- I wasn't even going to this conversation expecting the breadth (laughs) of, uh, of research really that, uh, Microsoft broadly is thinking about. You are thinking about at Microsoft. So, if we go back to, uh, '89 when Microsoft released Office, or 1990 when they released Windows 3.0-
2. KSKevin Scott
  (laughs)
3. LFLex Fridman
  ... (laughs) how's the, in, in your view... I know you weren't there the entire, you know, the, through its history, but how has the company changed in the 30 years since, as you look at it now?
4. KSKevin Scott
  The good thing is it's started off as a platform company. Like, it's still a platform company. Like the parts of the business that are like thriving and most successful are those that are building platforms. Like the mission of the company now is... The m- the mission's changed. It's like changed in a very interesting way. So, you know, back in '89, '90, like they were still on the original mission, which was like put a PC on every desk and in every home. Uh, like and, and it was basically about democratizing access to this, uh, new personal computing technology which, when Bill started the company, integrated circuit microprocessors were a brand new thing, and like people were building, you know, home brew computers, uh, you know, from kits like the way people build ham radios, uh, right now. Y- and I- and I think this is sort of the interesting thing for folks who build platforms in general, Bill saw the opportunity there, and what personal computers could do. And it was like a, it was sort of a reach. Like you just sort of imagine like where things were...... you know, when they started the company versus where things are now. Like, i- in success, when you democratize a platform, it just sort of vanishes into the platform-
5. LFLex Fridman
  Right.
6. KSKevin Scott
  ... and you don't pay attention to it anymore. Like, operating systems aren't a thing anymore.
7. LFLex Fridman
  Right.
8. KSKevin Scott
  Like, they're super important, like, completely critical and, like, when, you know, when you see one, you know, fail, like, you, you just, you sort of understand. But, like, you know, it's not a thing where you're, you're not, like, waiting for, you know, the next operating system thing, uh, in the same way that you were in 1995, right?
9. LFLex Fridman
  Sure. That's true.
10. KSKevin Scott
  Like, in 1995, like, you know, we had Rolling Stones on the stage with the Windows 95 rollout.
11. LFLex Fridman
  (laughs)
12. KSKevin Scott
  Like, it was, like, the biggest thing in the world. Everybody would... They lined up for it-
13. LFLex Fridman
  Yeah.
14. KSKevin Scott
  ... the way that people used to line up for iPhone. But, like, you know, eventually, and, like, this isn't-
15. LFLex Fridman
  Yeah.
16. KSKevin Scott
  ... necessarily a bad thing. Like, it just sort of, you know, it, it, the success is that it's sort of... It becomes ubiquitous. It's, like, everywhere and, like, human beings, when their technology becomes ubiquitous, they just, sort of, start taking it for granted. So, the mission now, um, that Satya re-articulated five-plus years ago now when he took over as CEO of the company, our mission is to empower every individual and every organization in the world to be more successful. And so, you know, again, like, that's a platform mission. And, like, the way that we do it now is, is different. It's like we have a hyperscale cloud that people-
17. LFLex Fridman
  Cloud, yeah.
18. KSKevin Scott
  ... are building their applications on top of. Like, we have a bunch of AI infrastructure that people are building their AI applications on top of. We have, uh, you know, we have a productivity suite of software, uh, like Microsoft Dynamics, uh, which, uh, you know, some people might not think is the sexiest thing in the world but it's, like, helping people figure out how to automate all of their business processes and workflows and to, you know, like, help those businesses using it to, like, grow and be more s-... So, it's a, it's a much broader vision-
19. LFLex Fridman
  Yeah.
20. KSKevin Scott
  ... uh, in a way now than it was back then. Like, it was, sort of, very particular thing. And, like, now, like, we live in this world where technology is so powerful and it's, like, such a basic fact of life-
21. LFLex Fridman
  Mm-hmm.
22. KSKevin Scott
  ... that it, uh, you know, that it, it both exists and is going to get better and better over time, or at least more and more powerful over time.
23. LFLex Fridman
  Yeah.
24. KSKevin Scott
  So, like, you know, what you have to do as a platform player is just much bigger.
20:50 – 23:07
Mixed reality as a real-world platform: HoloLens and frontline work
1. LFLex Fridman
  Right. There's so many directions in which you can transform. You, you didn't mention mixed reality-
2. KSKevin Scott
  Yeah.
3. LFLex Fridman
  ... too. You know, that's, uh-
4. KSKevin Scott
  Yep.
5. LFLex Fridman
  ... that's fa- that's probably early days, or depends how you think of it. Uh, but if we think in a scale of centuries, it's the early days of mixed reality (laughs) -
6. KSKevin Scott
  Oh, for sure.
7. LFLex Fridman
  ... and, uh, so, yeah, with HoloLens, uh, Microsoft is doing some really interesting work there. Do you, uh, do you touch that part-
8. KSKevin Scott
  Yeah.
9. LFLex Fridman
  ... uh, part of the effort? What- what's the thinking? Do you think of, uh, mixed reality as a platform too?
10. KSKevin Scott
  Oh, sure. When we look at what the platforms of the future could be, it's, like, fairly obvious that, like, AI is one. Like, you don't have to... I mean, like, that's, you know, you sort of say it to, like, someone and, you know, like, they, they get it. Um, but, like, we also think of the, like, mixed reality and quantum as, like, these two interesting, you know, potentially, uh-
11. LFLex Fridman
  Quantum computing?
12. KSKevin Scott
  Yeah.
13. LFLex Fridman
  Okay. So-
14. KSKevin Scott
  (laughs)
15. LFLex Fridman
  ... let's get crazy then. Uh, so... (laughs)
16. KSKevin Scott
  (laughs)
17. LFLex Fridman
  So, you're talking about some futuristic things here. Uh, well, the mixed reality, Microsoft is really... It's not even futuristic, it's here.
18. KSKevin Scott
  It is here.
19. LFLex Fridman
  Incredible stuff.
20. KSKevin Scott
  And- and it... And look, and it's having an, it's having impact right now. Like, one of the, one of the more interesting things that's happened with mixed reality over the past couple of years that I didn't clearly see is that it's become the computing device for, uh, for folks who... For, for doing their work who haven't used any computing device at all-
21. LFLex Fridman
  Right.
22. KSKevin Scott
  ... to do their work before. So, technicians-
23. LFLex Fridman
  Absolutely.
24. KSKevin Scott
  ... and service folks and, uh, people who are doing, uh, like, machine maintenance on factory floors. So, like, they, you know, bec- because they're mobile and, like, they're out in the world and they're working with their hands and, you know, sort of servicing these, like, very complicated things, uh, they're... They don't use their mobile phone, uh, and, like, they don't carry a laptop with them and, you know, they're not tethered to a desk. And so, mixed reality, like, where it's getting traction right now, where HoloLens is selling a lot of, uh, a lot of units is, uh, for these sorts of applications for these workers and it's become, like, I mean, like, the, the... People love it. Uh, they're like, "Oh, my God." Like, this is, like, for them, like, the same sort of productivity boost that, uh, you know, like an office worker, uh, had when they got their first personal computer.
23:07 – 26:07
How AI shows up in products: invisible improvements, not ‘AI-ness’ as the feature
1. LFLex Fridman
  Mm-hmm. Yeah, but you did mention, it's gl- certainly obvious AI is a platform, but can we dig into it a little bit? Uh-
2. KSKevin Scott
  Sure.
3. LFLex Fridman
  How- how does AI begin to infuse some of the products in, in Microsoft? So, currently providing, um, training of, for example, neural networks in the cloud-
4. KSKevin Scott
  Yep.
5. LFLex Fridman
  ... or providing pre, uh, pretrained models or, uh, just even providing computing resources, whatever different, uh, inference that you want to do using neural networks.
6. KSKevin Scott
  Yep.
7. LFLex Fridman
  What- what... How do you think of AI infusing the, um... As a platform that Microsoft can provide?
8. KSKevin Scott
  Yeah. I mean, I think it's, uh, it's super inter- it's, like, everywhere and, like, we, we run these, uh, we run these review meetings, uh, now where, uh, it's me and Satya and, uh, like, members of Satya's leadership team and, like, a cross-functional group of folks across the entire company who are working on, like, either AI infrastructure or, like, have some substantial part of their, uh-... of their product work using AI in some significant way. Now, the important thing to understand is, like, when you think about, like, how the AI is gonna manifest in, like, an experience for something that's gonna make it better, like, I think you don't want the, the AI-ness, uh, to be the first order thing. It's like-
9. LFLex Fridman
  Mm-hmm.
10. KSKevin Scott
  ... whatever the product is and, like, the thing that it's trying to help you do, uh, like, the AI just sort of makes it better. And it, you know, this is a gross exaggeration but, like, I, uh, you know, people get super excited about, like, where the AI is showing up in products and I'm like, "Do you get that excited about, like, where you're using a hash table, uh, like-"
11. LFLex Fridman
  Right. (laughs)
12. KSKevin Scott
  "... in your code?" Uh, like it's- it's just another-
13. LFLex Fridman
  It's just a tool.
14. KSKevin Scott
  It- it's a very interesting programming tool, but it's sort of a, like it's an engineering tool. And so, like, it- it shows up everywhere. So, like, we've got dozens and dozens of features now in Office, uh, that are powered by, like, fairly sophisticated machine learning. Our search engine, uh, wouldn't work at all if you took the machine learning out of it.
15. LFLex Fridman
  Right.
16. KSKevin Scott
  Uh, the, like, increasingly, you know, things like, uh, content moderation on our, uh, Xbox and xCloud, uh, platform, uh-
17. LFLex Fridman
  Y- you know, when you mean moderation, do you mean, like, the recommender is, like, showing what you want to, uh, look at next? Or what-
18. KSKevin Scott
  No, no, no. It's, like, anti-bullying stuff. (laughs)
19. LFLex Fridman
  Anti... So, the usual social network stuff that you have to deal with.
20. KSKevin Scott
  Yeah, yeah, correct. But it's, like, really, it's targeted, it's targeted towards a gaming, uh, audience.
21. LFLex Fridman
  Right.
22. KSKevin Scott
  So, it's, like, a very particular type of thing.
23. LFLex Fridman
  Yeah.
24. KSKevin Scott
  Where, you know, the, the line between playful banter and, like-
25. LFLex Fridman
  Yeah.
26. KSKevin Scott
  ... legitimate bullying is, like, a subtle one, and, like, you have to, like, and- and it's sort of tough. Like, I have, uh, I-
26:07 – 30:32
Content moderation and online safety: defining abuse across ‘vertical’ communities
1. LFLex Fridman
  I'd love to, if we could dig into it, 'cause you're also, you led the engineering efforts of LinkedIn.
2. KSKevin Scott
  Yep.
3. LFLex Fridman
  And, uh, if we look at, if we look at LinkedIn as a social network-
4. KSKevin Scott
  Yep.
5. LFLex Fridman
  ... and if we look at the Xbox Gaming as this, the social components-
6. KSKevin Scott
  Yeah.
7. LFLex Fridman
  ... the very different kinds of, I imagine, communication going on, on the two platforms, right?
8. KSKevin Scott
  Yep.
9. LFLex Fridman
  And the line in terms of bullying and so on is different on the two platforms.
10. KSKevin Scott
  Yep.
11. LFLex Fridman
  So, (laughs) how do you... I mean, it's such a fascinating philosophical discussion of where that line is. I don't think anyone knows the right answer. Uh, Twitter folks are under fire now, the, uh-
12. KSKevin Scott
  Yep.
13. LFLex Fridman
  ... Jack at Twitter for trying to find that line. Nobody knows what that line is. But how do you try to, uh, find the line, uh, for, you know, uh, trying to prevent abusive, uh, behavior, and at the same time let people be playful and joke around and that kind of thing?
14. KSKevin Scott
  I think in a certain way, like, you know, if you have what I would call vertical social networks, uh, it gets to be a little bit easier. So, like, if you have a clear notion of, like, what your social network should be used for-
15. LFLex Fridman
  Mm-hmm.
16. KSKevin Scott
  ... or, like, what you are designing a community around, then you don't have as many dimensions to your sort of content safety problem as, uh, you know, as you do in a general purpose platform. I mean, so like, on, on LinkedIn, like, the whole social network is about, uh, connecting people with opportunity, whether it's helping them find a job or to, you know, sort of find mentors or to, you know, sort of help them, uh, like, find their next, uh, sales lead-
17. LFLex Fridman
  Mm-hmm.
18. KSKevin Scott
  ... or, uh, to just sort of allow them to broadcast their, their, you know, sort of professional identity to their, um, their network of, of peers and collaborators and, you know, sort of professional community. Like, that is, I mean, like, in some ways, like, that's very, very broad. Uh, but in other ways, it's sort of, you know, it's narrow. And so, like, you can build AIs, uh, like machine learning systems that are, you know, capable with those boundaries of making better automated decisions about, like, what is, uh, you know, sort of inappropriate and offensive comment or dangerous comment or illegal content, uh, when you have some constraints. Uh, you know, same thing with, uh, yeah, same thing with, like, the- the gaming, uh, gaming social networks offer. It's just like, it's about playing games-
19. LFLex Fridman
  Mm-hmm.
20. KSKevin Scott
  ... about having fun, uh, and, like, the thing that you don't want to have happen o- on the platform is why bullying is such an important thing. Like, bullying is not fun. Well, so-
21. LFLex Fridman
  Right.
22. KSKevin Scott
  ... you want to do everything in your power to encourage that not to happen. And, yeah, I, but I think it's a, it's sort of a tough problem in general, and it's one where I think, you know, eventually we're gonna have to have some sort of clarification from our policymakers about what it is that we should be doing, like where the lines are. Because it's tough. Like, you don't, like, in democracy, right, like, you don't want, uh, you want some sort of democratic involvement. Uh, like, people should have a say in, like, where, where the lines, uh, lines are drawn. Like, you don't want a bunch of people making, like, unilateral decisions. And, like, we- we are in a, we're in a state right now for some of these platforms where you actually do have to make unilateral decisions where the policymaking isn't gonna happen fast enough-
23. LFLex Fridman
  Right.
24. KSKevin Scott
  ... in order to, like-
25. LFLex Fridman
  Exactly.
26. KSKevin Scott
  ... prevent very bad things from happening. But, like, we- we need the policymaking side of that to catch up, I think, as, as quickly as possible, because you want that whole process to be a democratic thing, not a, you know, not- not some sort of weird thing where you've got a non-representative group of people making decisions that have, you know, like, national and global impact.
27. LFLex Fridman
  And it's fascinating because the digital space is different than the, the physical space in which nations and governments were established. And so, what policy looks like globally, what bullying looks like globally, what's healthy communication looks like globally is, is an open question.
28. KSKevin Scott
  Yeah.
29. LFLex Fridman
  And we're all figuring it- figuring it out together, which is fascinating.
30:32 – 33:07
Fake news and deepfakes: society’s institutions lag decades behind tech acceleration
1. KSKevin Scott
  Yeah. I mean, with, with, uh, you know, sort of fake news, for instance, and-
2. LFLex Fridman
  Deepfakes and f- fake news generated by humans?
3. KSKevin Scott
  Yeah. So, and, I mean, we can talk about deepfakes. Like, I think that is another, like, you know, sort of v- very interesting level of complexity. But, like, if you think about just the written word, right?
4. LFLex Fridman
  Yeah.
5. KSKevin Scott
  Like, we have... You know, we invented papyrus, what, 3,000 years ago where we, you know, you could sort of, uh, put, uh, put word on, uh, on paper. And then, uh, 500 years ago, like, we, uh, we get the printing press, uh, like, where the word gets a little bit more ubiquitous. And then, like, you really, really didn't get ubiquitous printed word until the end of the 19th century when the offset press was invented. And then, you know, it just sort of explodes and like, you know, b- the cross product of that and the industrial revolution's need for educated citizens resulted in, like, this rapid expansion of literacy and the rapid expansion of the word. But, like, we had 3,000 years up to that point to figure out, like, how to, you know, like, what's, what's journalism? What's editorial integrity? Like, what's, you know, what's scientific peer review? Wh- and so, like, you built all of this mechanism to, like, try to filter through all of the noise that the technology made possible to, like, you know, sort of getting to something that society could cope with. And, like, if you think about just the piece, the PC didn't exist 50 years ago. Uh, and so in, like, this span of, you know, like, half a century, like, we've gone from no digital, you know, no ubiquitous digital technology to, like, having a device that sits in your pocket where you can-
6. LFLex Fridman
  Mm-hmm.
7. KSKevin Scott
  ... sort of say whatever's on your mind to, like, what, what, what did Mary have in her, Mary Meeker just released her new, uh, uh, like, slide deck last week. You know, we, we've got 50% penetration of the, of the internet, uh, to the global population.
8. LFLex Fridman
  Right.
9. KSKevin Scott
  Like, there are, like, three and a half billion people who are connected now. So, it's like, it's crazy.
10. LFLex Fridman
  (laughs)
11. KSKevin Scott
  Crazy, we're like, inconceivable, like, how fast all of this happened. So, you know, it's not surprising that we haven't figured out what to do yet. Uh-
12. LFLex Fridman
  (laughs) Exactly.
13. KSKevin Scott
  ... but, like, we gotta, like, we gotta really, like, lean into this set of problems, because, like, we basically have three millennia w- (laughs) worth of work to do about how to deal with all of this. And, like, probably what, you know, amounts to the next decade worth of time.
33:07 – 36:13
Facial recognition ethics: regulation, cautious deployment, and bias reduction research
1. LFLex Fridman
  So, since we're on the topic of tough t- you know, tough challenging problems, let's look at, uh, more on the tooling side in AI that Microsoft is looking at is face recognition software. So, there's, there's a lot of powerful positive use cases-
2. KSKevin Scott
  Yep.
3. LFLex Fridman
  ... for face recognition, but there are some negative ones and we're seeing-
4. KSKevin Scott
  Yep.
5. LFLex Fridman
  ... those in different, uh, governments in the world. So, how do you, how does Microsoft think about the use of face recognition software, uh, as a platform in-
6. KSKevin Scott
  Yep.
7. LFLex Fridman
  ... governments and, uh, companies? S- yeah. How do we strike an ethical balance here?
8. KSKevin Scott
  Yeah. I think we've articulated a clear point of view. So, Brad Smith, uh, wrote a blog post, uh, last fall, I believe, that sort of, like, outlined, like, very specifically what, uh, you know, what our, what our point of view is there. And, you know, I think we believe that there are certain uses to which face recognition should not be put, and we believe, again, that there's a need for regulation there.
9. LFLex Fridman
  Yeah.
10. KSKevin Scott
  Uh, like, the, the government should, like, really come in and say that, you know, this is, this is where the lines are. And, like, we very much want it to, like, figuring out where the lines are should be a democratic process, but in the short term, like, we've drawn some lines where, uh, you know, we push back against uses of face recognition technology. Um, you know, like, the City of San Francisco, for instance, I think has completely outlawed any government agency, uh, from using face recognition tech. Uh, and, like, that may prove to be a little bit overly broad. Um, but for, like, certain law enforcement things, like, you, you really... I, I, I, I would personally rather be overly sort of cautious in terms of restricting use of it until, like, we have, you know, sort of defined a reasonable, you know, democratically determined regulatory framework for, uh, like, where we, we could and should use it. And, you know, the, the other thing there is, um, like, we've got a bunch of research that we're doing and a bunch of progress that we've made on, uh, on bias, uh, there.
11. LFLex Fridman
  Mm-hmm.
12. KSKevin Scott
  And, like, there are all sorts of, like, weird biases that these models can have, like, all the way from, like, the most noteworthy one where, you know, you may have, um, underrepresented minorities who are, like, underrepresented in the training data and then you start learning, uh, like, strange things. But, like, there, there even, you know, other weird thi- like, we've, uh, I think we've seen in the public research, like, models can learn, uh, strange things, uh, like, uh, all doctors are men, uh, for instance. Uh, just-
13. LFLex Fridman
  That's
14. NANarrator
  Yeah.
15. KSKevin Scott
  Yeah. I mean, and so, like, it, it really is a thing where it's very important for everybody who is working on these things, before they push publish, uh, they launch the experiment, they, you know, push the code to-
16. LFLex Fridman
  Mm-hmm.
36:13 – 42:12
Deepfakes 대응: detection limits and ‘chain of custody’ via cryptographic provenance
1. KSKevin Scott
  ... you know, online, th- or they even publish the paper, that they are at least starting to think about what some of the-... potential negative consequences are of some of this stuff. I mean, this is where, you know, like, the deep fake stuff I find very worrisome (laughs) , uh, just because there are going to be some very good beneficial uses of, uh, like, GAN-generated, uh, imagery. And, like, and, and funny enough, like, uh, one of the places where it's actually useful is, uh, we're using the technology right now to generate synthetic, uh, synthetic visual data for training some of the-
2. LFLex Fridman
  That's right.
3. KSKevin Scott
  ... face recognition models to get rid of the bias.
4. LFLex Fridman
  Right. (laughs)
5. KSKevin Scott
  Uh, so, like, that's one, like, super good use of the tech. But, like, you know, it's getting good enough now where, you know, it's gonna sort of challenge a normal human being's ability to... Like, now you just sort of, say, like, it's, it's very expensive for someone to fabricate a photorealistic, uh, fake video. Uh, and, like, GANs are going to make it fantastically cheap to fabricate a photorealistic, uh, fake video. And so, like, what you assume you can sort of trust as true versus, like, be skeptical about is about to change. Uh-
6. LFLex Fridman
  Yeah.
7. KSKevin Scott
  ... and, like, we're not ready for it, I don't think.
8. LFLex Fridman
  The nature of truth, right. That's, uh, it's also exciting because I think, uh, both you and I probably would agree that the way to solve, to take on that challenge is with technology.
9. KSKevin Scott
  Yeah.
10. LFLex Fridman
  Right. There's probably going to be ideas of, of ways to verify which, uh, which kind of video is legitimate, which kind is not.
11. KSKevin Scott
  Yep.
12. LFLex Fridman
  So, uh, to me that's an exciting possibility, most, most likely for just the comedic genius that the internet usually creates with these kinds of videos.
13. KSKevin Scott
  Yeah.
14. LFLex Fridman
  And, uh, hopefully will not result in any serious harm.
15. KSKevin Scott
  Yeah, and l- it, it could be, you know... Like, I think we will have technology to, that may be able to detect whether or not something's fake or real. Although, yeah, uh, that's... The f- the fakes are pretty convincing even, like, when you subject them to machine scrutiny. But, you know, the, we, we also have these increasingly interesting social networks, uh, you know, that are under fire right now, um, for some of the bad things that they do. Like, one of the things that you could choose to do with a social network is, like, you could, you could use crypto and the networks to, like, have content signed where you could have a, like, full chain of custody that accompanied every piece of content. So, like, when you're viewing something and, like, you want to ask yourself, like, "How, you know, how much can I trust this?" Like, you can click something and, like, have a verified-
16. LFLex Fridman
  Mm-hmm.
17. KSKevin Scott
  ... chain of custody that shows like, "Oh, this is coming from, uh, you know, from this source, and it's, like, signed by, like, someone whose identity I trust."
18. LFLex Fridman
  Yeah.
19. KSKevin Scott
  Yeah, I think having that, uh, you know, having that chain of custody, like, being able to, like, say, "Oh, here's this video. Like, it may or may not, uh, have been produced using some of this deep fake technology," but if you've got a verified chain of custody where you can sort of trace it all the way back to an identity and you can decide whether or not, like, I trust this identity. Like, "Oh, no, this is really from the White House," or, like, "This is really from the, you know, the office of this particular presidential candidate," or, "It's really from, you know, Jeff Weiner, CEO of, uh, of LinkedIn, or Satya Nadella, CEO of Microsoft." Like, that might, that might be like one way that you can solve some of the problems.
20. LFLex Fridman
  Yeah.
21. KSKevin Scott
  And so, like, that's not the super high tech. Like, we've had all of this technology forever.
22. LFLex Fridman
  Right.
23. KSKevin Scott
  Um, and I, but, but I think you're right. Like, it has to, it has to be some sort of technological thing, because-
24. LFLex Fridman
  Yeah. Yeah.
25. KSKevin Scott
  ... the, the underlying tech that is used to create this is not gonna do anything but get better over time, and the genie is sort of out of the bottle.
26. LFLex Fridman
  Yeah.
27. KSKevin Scott
  Uh, there's no stuffing it back in.
28. LFLex Fridman
  And there's a social component which I think is really healthy for a democracy where people will be skeptical about the thing they watch-
29. KSKevin Scott
  Yeah.
30. LFLex Fridman
  ... in general. Uh, so, you know, which is good. Skepticism in general is good for
42:12 – 48:00
The future of Windows/Office: subtle AI assistance, unified search, and Fluid collaboration
1. LFLex Fridman
  So, I'm not a, a large business owner. Uh, so (laughs) I'm just...
2. KSKevin Scott
  (laughs)
3. LFLex Fridman
  I'm just a huge fan, uh, of many of Microsoft, uh, products. I mean, I still... Actually in terms of I generate a lot of graphics and images, and I still use PowerPoint to do that.
4. KSKevin Scott
  Yeah.
5. LFLex Fridman
  It beats Illustrator for me, even professional, uh, sort of, uh, it's, it's, it's fascinating. So, uh, I wonder what is the future of-... let's say, Windows and Office look like? Is- do you see it... I mean, I remember looking forward to XP. It was an exciting-
6. KSKevin Scott
  Yep.
7. LFLex Fridman
  ... uh, when XP was released, just like you said. I don't remember when 95 was released, but, uh-
8. KSKevin Scott
  (laughs)
9. LFLex Fridman
  ... XP for me was a big celebration. And, and when 10 came out, I was like, "Okay, well, it's nice. It's a nice improvement." But-
10. KSKevin Scott
  Yeah.
11. LFLex Fridman
  Uh, so what do you see is the future of these products? Uh-
12. KSKevin Scott
  You know, I think there's a bunch of excit- I mean, on the Office front, there's going to be this, uh, like, increasing productivity winds that are coming out of some of these AI powered features that are coming. Like, the products all sort of get smarter and smarter in, like, a very subtle way. Like, there's not going to be this big bang moment where, you know, like, Clippy is going to reemerge and it's going to be-
13. LFLex Fridman
  Wait a minute. Okay, we'll have to... Wait, wait, wait.
14. KSKevin Scott
  (laughs)
15. LFLex Fridman
  Is Clippy coming back?
16. KSKevin Scott
  (laughs) Yeah.
17. LFLex Fridman
  Well, but quite seriously, um, so injection of AI, there's not much, or at least I'm not familiar, sort of assistive type of stuff going on inside the Office products, like a Clippy style as- assistant, personal assistant. Do you think that's... there's a possibility of that in the future?
18. KSKevin Scott
  Yeah, like, I- I- So, I think there are a bunch of, like, very small ways in which, uh, like, machine learning powered assistive things are in the product right now. So, there are, uh, there are a bunch of interesting things, like, um, the auto response stuff's getting better and better, and it's, like, getting to the point where, you know, it can auto respond with, like, okay, let, you know, this person's clearly trying to schedule a meeting, so it looks at your calendar and it automatically, like, tries to find, uh-
19. LFLex Fridman
  Yeah.
20. KSKevin Scott
  ... like, a time and a space that's mutually interesting. Um, like, we, we have, um, this notion of Microsoft Search, where it's, like, not just web search, but it's, like, search across, like, all of your information that's sitting inside of, uh, like, your Office 365 tenant and, uh, like, you know, potentially in other products. And, like, we have this thing called the Microsoft Graph that is basically a API federator that, uh, you know, sort of, like, gets you hooked up across the entire breadth of, like, all of the, you know, like, what were information silos before they got woven together, uh, with a graph. Um, like, that is, like, getting increasing- with increasing effectiveness sort of plumbed into the, uh, into some of these auto response things, where you're going to be able to see the system, like, automatically retrieve information for you. Like, if, you know, like, I- I frequently send out, you know, emails to folks where I, like, I can't find a paper or document or whatnot. There's no reason why the system won't be able to do that for you. And, like, I think the, the... It's building towards, uh, like, having things that look more like a, like a fully integrated, uh, you know, assistant. But, like, you, you'll have a bunch of steps, uh, that you will see before you... Like, it, it will not be this, like, big bang thing where, like, Clippy comes back and you've got this, like, you know, manifestation of, you know, like, a fully, uh, fully powered assistant. So, I, I think that's, um, that's definitely coming out. Like, all of the, you know, collaboration and co-authoring stuff's getting better. Uh, you know, it's, like, really interesting. Like, if you look at how, uh, we use, uh, eh, the Office product portfolio at Microsoft, like, more and more of it is happening inside of, uh, like, Teams as a canvas, and, like, it's this thing where, you know, you've got... Collaboration is, like, at the center of the product, and, uh, like, we, we, we built some, like, really cool stuff that's... some of which is about to be open source that are sort of framework level things for doing, uh, for doing co-authoring. Uh-
21. LFLex Fridman
  That's awesome. So, uh, in... Is there a cloud component to that? So, uh, o- on the web, or is it, um... And forgive me if I don't already know this, but with Office 365, we still... the collaboration we do, if we do in Word, we still send the file around-
22. KSKevin Scott
  No, no.
23. LFLex Fridman
  ... uh, with everybody. So, so this is-
24. KSKevin Scott
  Yeah, no, no. It, we, it... We're, we're already a little bit better than that.
25. LFLex Fridman
  Yeah.
26. KSKevin Scott
  And like, you know, so, like, the fact that you're unaware of it means we've got a better job to do (laughs)
27. LFLex Fridman
  (laughs)
28. KSKevin Scott
  ... like helping you discover, uh, discover this stuff. But yeah, I mean, i- it's already, like, got a huge, a huge cloud compo... And, like, part of, you know, part of this, uh, framework stuff, I think we're calling it... Like, I, I, like, we've been working on it for a couple of years, so, like, I know the, uh, the internal, uh, code name for it. But I think when we launch it at Build, it's called the Fluid, uh, Framework. Um, and, uh, but, like, what Fluid lets you do is, like, you can go into a conversation that you're having in Teams and, like, reference, like, part of a spreadsheet that you're working on-
29. LFLex Fridman
  Mm-hmm.
30. KSKevin Scott
  ... uh, where somebody's, like, sitting in the Excel canvas, like, working on the spreadsheet with a, you know, chart or whatnot, and, like, you can sort of embed, like, part of the spreadsheet in the Teams conversation, where, like, you can dynamically update it, and, like, all of the changes that you're making to the-
48:00 – 52:43
Leading tens of thousands of engineers: foresight, infrastructure, culture, and mission as story
1. LFLex Fridman
  So, I, out of my own sort of curiosity as an engineer, I, I know what it's like to sort of lead a team of 10, 15 engineers.
2. KSKevin Scott
  (laughs)
3. LFLex Fridman
  Microsoft has, uh, I don't know what the numbers are, maybe 50, maybe 60,000 engineers, maybe 40.
4. KSKevin Scott
  A lot of engineers. I don't know exactly what the number is. It's a lot. (laughs)
5. LFLex Fridman
  Yeah. (laughs)
6. KSKevin Scott
  It's, it's tens of thousands.
7. LFLex Fridman
  Right. So, it's more than 10 or 15. What-
8. KSKevin Scott
  (laughs)
9. LFLex Fridman
  What, what, um... I mean, you've, uh, you've led, uh, g- different sizes, mostly large size of engineers. What does it take to lead such a large group into, um, eh, continued innovation, continued being highly productive, and yet develop all kinds of new ideas, and yet maintain... Like, wha- what does it take to lead-... such a large group of brilliant people?
10. KSKevin Scott
  I think the thing that you learn as you manage larger and larger scale is that there are three things that are, like, very, very important, uh, for big engineering teams. Like, one is, like, having some sort of forethought about what it is that you're going to be building over large periods of time. Like, not exactly, like, you don't need to know that, like, you know, "Oh, I'm putting all my chips on this one product, and, like, this is going to be the thing." But, like, it's useful to know, like, what sort of capabilities you think you're going to need to have to build the products of the future, and then, like, invest in that infrastructure, like whether...
11. LFLex Fridman
  Mm-hmm.
12. KSKevin Scott
  And, like, I'm not just talking about storage systems or Cloud APIs. It's also, like, what does your development process look like? What tools do you want? Like, what culture do you want to build around, like, how you're, you know, sort of collaborating together to, like, make complicated technical things? And so, like, having an opinion and investing in that is, like, it just gets more and more important, and, like-
13. LFLex Fridman
  Mm-hmm.
14. KSKevin Scott
  ... the sooner you can get a concrete set of opinions, uh, like, the better you're going to be. Like, you can wing it for a while, uh, at small scales, like, you know, when you start a company, like, you don't have to be, like, super specific about it, but, like, the biggest miseries that I've ever seen as an engineering leader are in places where you didn't have a clear enough opinion about those things, uh, soon enough, and then you just sort of go create a bunch of technical debt and, like, culture debt that is excruciatingly painful to, to clean up. So, like, that's one bundle of things.
15. LFLex Fridman
  Mm-hmm.
16. KSKevin Scott
  Like, the other, uh, the other, you know, another bundle of things is, like, it's just really, really important to, like, have a, a clear mission that's not just some cute crap you say because, like, you think you should have a mission-
17. LFLex Fridman
  Right.
18. KSKevin Scott
  ... but, like, something that clarifies for people, like, where it is that you're headed together. Like, I know it's, like, probably, like, a little bit too popular right now, but, uh, um, Yuval Harari's book Sapiens, one of the central ideas in, in his book is that, uh, like, storytelling is, like, the quintessential thing for coordinating the activities of large groups of people, like, once you get past Dunbar's number, and, like, I've really, really seen that, uh, just managing-
19. LFLex Fridman
  Yeah.
20. KSKevin Scott
  ... engineering teams. Like, you, you can, you can just brute force things when you're less than 120, 150, uh, folks, where you can sort of know and trust and understand what the dynamics are between all the people, but, like, past that, like, things just sort of start to catastrophically fail if you don't have some sort of set of shared goals that you're marching towards. And so, like, even though it sounds touchy feely, and-
21. LFLex Fridman
  (laughs)
22. KSKevin Scott
  ... you know, like, a bunch of technical people-
23. LFLex Fridman
  It's true.
24. KSKevin Scott
  ... will sort of balk at the idea that, like, you need to, like, have a clear, like, the mission's-
25. LFLex Fridman
  Yeah.
26. KSKevin Scott
  ... like, very, very, very important.
27. LFLex Fridman
  Yuval's right, right? Stories, that's how our society, that's the fabric that connects us, all of us, is these powerful stories.
28. KSKevin Scott
  Yeah.
29. LFLex Fridman
  And that works for companies too, right?
30. KSKevin Scott
  It works for everything.
52:43 – 57:51
20–30 year outlook: tech-driven optimism for climate, health, demographics, and global equity
1. LFLex Fridman
  They have platforms on which we define the future. So last question, what do you... Let's get philosophical maybe. Bigger than even Microsoft, what do you think the next 20, 30 plus years looks like for computing, for technology, for devices? Do you th- do you have crazy ideas about the future of the world?
2. KSKevin Scott
  Yeah, look, I think we, you know, we're entering this time where we've got, we have technology that is progressing at the fastest rate that it ever has, and you've got, and you got some really big social problems, like, society scale problems-
3. LFLex Fridman
  Yeah.
4. KSKevin Scott
  ... that we have to, we have to tackle. And so I, you know, I think we're gonna rise to the challenge and, like, figure out how to intersect, uh, like, all of the power of this technology with all of the big challenges that are facing us, whether it's, uh, you know, global warming, whether it's, like, the biggest remainder of the population boom is in, uh, uh, Africa, uh, for the next 50 years or so.
5. LFLex Fridman
  Mm-hmm.
6. KSKevin Scott
  And, like, global warming's gonna make it increasingly, uh, difficult to feed the global population in particular, like, in this place where you're gonna have, like, the biggest, uh, population boom. Um, I think we, you know, like, AI is gonna, uh, like, if we push it in the right direction, like, it can do, like, incredible things to empower all of us to achieve our full potential and to, um, you know, like, live better lives, uh, but, like, that also means focus, uh, on, like, some super important things, like how can you apply it to healthcare to-
7. LFLex Fridman
  Right.
8. KSKevin Scott
  ... make sure that, uh, you know, like, our, our quality and cost of and, and sort of ubiquity of health coverage is, uh, is better and better over time. Like, that's more and more important every day is, like, in the, uh, in the United States and, like, the rest of the industrialized world, so Western Europe, uh, China, Japan, Korea, like, you've got this population bubble of, uh, like, aging working, uh, you know, working age folks who are, you know, at some point over the next 20, 30 years they're gonna be largely retired, and, like, you're, you're gonna have more retired people than working age people.
9. LFLex Fridman
  Mm-hmm.
10. KSKevin Scott
  And then, like, you've got, you know, sort of natural questions about who's gonna take care of, uh, all the old folks and who's gonna do all the work, and-
11. LFLex Fridman
  Yeah.
12. KSKevin Scott
  The answers to, like, all these sorts of questions like where you're sort of running into, you know, constraints of the world and society has always been what tech is going to help us get around this? You know, when I was a kid in the '70s and '80s, we talked all the time about population boom, population boom, like we're not gonna be able to feed the planet. And we were right in the middle of the Green Revolution where there was this massive technology-driven increase in crop productivity worldwide. And some of that was taking some of the things we knew in the West and getting them distributed to the developing world. And part of it were things like just smarter biology helping us increase-- and we don't talk about overpopulation anymore because we can more or less-- we sort of figured out how to feed the world. That's a technology story. And so I'm super, super hopeful about the future and in the ways where we will be able to apply technology to solve some of these super challenging problems. Like one of the things that I try to spend my time doing right now is trying to get everybody else to be hopeful as well because back to Harari, we are the stories that we tell. If we get overly pessimistic right now about like the potential future of technology, you know, we may fail to-- fail to get all things in place that we need to have our best possible future.
13. LFLex Fridman
  And that kind of hopeful optimism, I'm glad you have it because you're leading large groups of engineers that are actually defining-- they're writing that story. They're helping build that future, which is super exciting.
14. KSKevin Scott
  Yeah.
15. LFLex Fridman
  And I agree with everything you said except I do hope Clippy comes back.
16. KSKevin Scott
  (laughs)
17. LFLex Fridman
  We miss him. I speak for the people. So Kellen, thank you so much for talking today.
18. KSKevin Scott
  Thank you so much for having me. It was a pleasure.

Episode duration: 57:43

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Microsoft’s breadth: cloud, SaaS, hardware, research, and major acquisitions

Gaming as culture and product: Xbox and creative collaborations

Radical Markets: provocative market mechanisms to fix capitalism’s incentives

AI and jobs: why AI must be a democratized platform, not centralized power

Data dignity and ‘data as labor’: creating markets to value data contributions

Microsoft’s evolution since Windows 3.0: platforms, ubiquity, and a new mission

Mixed reality as a real-world platform: HoloLens and frontline work

How AI shows up in products: invisible improvements, not ‘AI-ness’ as the feature

Content moderation and online safety: defining abuse across ‘vertical’ communities

Fake news and deepfakes: society’s institutions lag decades behind tech acceleration

Facial recognition ethics: regulation, cautious deployment, and bias reduction research

Deepfakes 대응: detection limits and ‘chain of custody’ via cryptographic provenance

The future of Windows/Office: subtle AI assistance, unified search, and Fluid collaboration

Leading tens of thousands of engineers: foresight, infrastructure, culture, and mission as story

20–30 year outlook: tech-driven optimism for climate, health, demographics, and global equity

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