← Lex Fridman

Jack Dorsey: Square, Cryptocurrency, and Artificial Intelligence

第91期2020-04-24English

嘉宾:Jack Dorsey

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§01Transcript · 00:00–09:04

00:00The following is a conversation with Jack Dorsey,

00:02co founder and CEO of Twitter

00:05and founder and CEO of Square.

00:08Given the happenings at the time related to Twitter leadership

00:12and the very limited time we had,

00:13we decided to focus this conversation on Square

00:16and some broader philosophical topics

00:18and to save an in depth conversation

00:20on engineering and AI at Twitter

00:23for a second appearance in this podcast.

00:25This conversation was recorded

00:27before the outbreak of the pandemic.

00:29For everyone feeling the medical, psychological

00:31and financial burden of this crisis,

00:33I'm sending love your way.

00:35Stay strong.

00:36We're in this together.

00:37We'll beat this thing.

00:39As an aside, let me mention

00:41that Jack moved $1 billion of Square equity,

00:45which is 28% of his wealth

00:47to form an organization that funds COVID 19 relief.

00:51First, as Andrew Yang tweeted,

00:53this is a spectacular commitment.

00:56And second, it is amazing that it operates transparently

00:59by posting all its donations to a single Google doc.

01:03To me, true transparency is simple.

01:06And this is as simple as it gets.

01:09This is the Artificial Intelligence Podcast.

01:11If you enjoy it, subscribe on YouTube,

01:13review it with five stars on Apple Podcast,

01:15support it on Patreon

01:17or simply connect with me on Twitter

01:18at Lex Friedman spelled F R I D M A N.

01:22As usual, I'll do a few minutes of ads now

01:24and never any ads in the middle

01:26that can break the flow of the conversation.

01:28I hope that works for you

01:29and doesn't hurt the listening experience.

01:32This show is presented by Masterclass.

01:34Sign up on masterclass.com slash Lex

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02:44And now, here's my conversation with Jack Dorsey.

02:48You've been on several podcasts,

02:50Joe Rogan, Sam Harris, Rach Roll, others,

02:53excellent conversations,

02:55but I think there's several topics

02:57that you didn't talk about that I think are fascinating

03:00that I'd love to talk to you about,

03:01sort of machine learning, artificial intelligence,

03:04both the narrow kind and the general kind

03:06and engineering at scale.

03:08So there's a lot of incredible engineering going on

03:11that you're a part of,

03:12crypto, cryptocurrency, blockchain, UBI,

03:16all kinds of philosophical questions maybe we'll get to

03:18about life and death and meaning and beauty.

03:21So you're involved in building some of

03:25the biggest network systems in the world,

03:27sort of trillions of interactions a day.

03:30The cool thing about that is the infrastructure,

03:33the engineering at scale.

03:35You started as a programmer with C building.

03:38Yeah, so.

03:39I'm a hacker, I'm not really an engineer.

03:41Not a legit software engineer,

03:43you're a hacker at heart.

03:44But to achieve scale, you have to do some,

03:47unfortunately, legit large scale engineering.

03:49So how do you make that magic happen?

03:52Hire people that I can learn from, number one.

03:57I mean, I'm a hacker in the sense that I,

04:00my approach has always been do whatever it takes

04:02to make it work.

04:04So that I can see and feel the thing

04:07and then learn what needs to come next.

04:09And oftentimes what needs to come next is

04:13a matter of being able to bring it to more people,

04:16which is scale.

04:17And there's a lot of great people out there

04:21that either have experience or are extremely fast learners

04:27that we've been lucky enough to find

04:30and work with for years.

04:33But I think a lot of it,

04:35we benefit a ton from the open source community

04:39and just all the learnings there

04:41that are laid bare in the open.

04:44All the mistakes, all the success,

04:46all the problems.

04:48It's a very slow moving process usually open source,

04:53but it's very deliberate.

04:54And you get to see because of the pace,

04:58you get to see what it takes

05:00to really build something meaningful.

05:02So I learned most of everything I learned about hacking

05:06and programming and engineering has been due to open source

05:11and the generosity that people have given

05:19to give up their time, sacrifice their time

05:21without any expectation in return,

05:24other than being a part of something

05:27much larger than themselves, which I think is great.

05:29Open source movement is amazing.

05:31But if you just look at the scale,

05:33like Square has to take care of,

05:35is this fundamentally a software problem

05:38or a hardware problem?

05:39You mentioned hiring a bunch of people,

05:41but it's not, maybe from my perspective,

05:45not often talked about how incredible that is

05:48to sort of have a system that doesn't go down often,

05:52that is secure, is able to take care

05:54of all these transactions.

05:55Like maybe I'm also a hacker at heart

05:58and it's incredible to me that that kind of scale

06:01could be achieved.

06:02Is there some insight, some lessons,

06:06some interesting tidbits that you can say

06:10how to make that scale happen?

06:12Is it the hardware fundamentally challenge?

06:14Is it a software challenge?

06:19Is it a social challenge of building large teams

06:23of engineers that work together, that kind of thing?

06:25Like what's the interesting challenges there?

06:28By the way, you're the best dressed hacker I've met.

06:31I think the. Thank you.

06:34If the enumeration you just went through,

06:36I don't think there's one.

06:37You have to kind of focus on all

06:39and the ability to focus on all that

06:43really comes down to how you face problems

06:47and whether you can break them down into parts

06:51that you can focus on.

06:53Because I think the biggest mistake is trying to solve

06:58or address too many at once

07:02or not going deep enough with the questions

07:05or not being critical of the answers you find

07:08or not taking the time to form credible hypotheses

07:15that you can actually test and you can see the results of.

07:19So all of those fall in the face of ultimately

07:25critical thinking skills, problem solving skills.

07:27And if there's one skill I want to improve every day,

07:30it's that that's what contributes to the learning

07:34and the only way we can evolve any of these things

07:38is learning what it's currently doing

07:41and how to take it to the next step.

07:44And questioning assumptions,

07:45the first principles kind of thinking,

07:47seems like a fundamental to this whole process.

07:50Yeah, but if you get too overextended into,

07:53well, this is a hardware issue,

07:54you miss all the software solutions.

07:56And vice versa, if you focus too much on the software,

08:01there are hardware solutions that can 10X the thing.

08:06So I try to resist the categories of thinking

08:13and look for the underlying systems

08:16that make all these things work.

08:18But those only emerge when you have a skill

08:22around creative thinking, problem solving,

08:27and being able to ask critical questions

08:33and having the patience to go deep.

08:36So one of the amazing things,

08:38if we look at the mission of Square,

08:40is to increase people's access to the economy.

08:45Maybe you can correct me if I'm wrong,

08:46that's from my perspective.

08:47So from the perspective of merchants,

08:49peer to peer payments, even crypto, cryptocurrency,

08:52digital cryptocurrency, what do you see as the major ways

08:56that our society can increase participation in the economy?

08:59So if we look at today and the next 10 years,

09:01next 20 years, you go into Africa, maybe in Africa

§02Transcript · 09:04–19:05

09:04and all kinds of other places outside of the North America.

09:09If there was one word that I think represents

09:13what we're trying to do at Square, it is that word access.

09:19One of the things we found is that

09:21we weren't expecting this at all.

09:23When we started, we thought we were just building

09:25a piece of hardware to enable people

09:29to plug it into their phone and swipe a credit card.

09:32And then as we talked with people

09:34who actually tried to accept credit cards in the past,

09:37we found a consistent theme, which many of them

09:40weren't even enabled, not enabled,

09:44but allowed to process credit cards.

09:46And we dug a little bit deeper, again, asking that question.

09:50And we found that a lot of them would go to banks

09:54or these merchant acquirers.

09:57And waiting for them was a credit check

10:01and looking at a FICA score.

10:03And many of the businesses that we talked to

10:07and many small businesses,

10:09they don't have good credit or a credit history.

10:15They're entrepreneurs who are just getting started,

10:17taking a lot of personal risk, financial risk.

10:21And it just felt ridiculous to us

10:24that for the job of being able to accept money from people,

10:31you had to get your credit checked.

10:33And as we dug deeper, we realized that

10:36that wasn't the intention of the financial industry,

10:38but it's the only tool they had available to them

10:42to understand authenticity, intent,

10:46predictor of future behavior.

10:49So that's the first thing we actually looked at.

10:50And that's where the, you know, we built the hardware,

10:52but the software really came in terms of risk modeling.

10:57And that's when we started down the path

11:00that eventually leads to AI.

11:03We started with a very strong data science discipline

11:08because we knew that our business

11:10was not necessarily about making hardware.

11:13It was more about enabling more people

11:17to come into the system.

11:18So the fundamental challenge there is,

11:21so to enable more people to come into the system,

11:23you have to lower the barrier of checking

11:26that that person will be a legitimate vendor.

11:30Is that the fundamental problem?

11:31Yeah, and a different mindset.

11:33I think a lot of the financial industry had a mindset

11:36of kind of distrust and just constantly looking

11:41for opportunities to prove why people shouldn't get

11:46into the system, whereas we took on a mindset of trust

11:50and then verify, verify, verify, verify, verify.

11:52Yes.

11:53So we moved, you know, when we entered the space,

12:00only about 30 to 40% of the people who applied

12:03to accept credit cards would actually get through the system.

12:05We took that knowledge, we took it to the next level.

12:08If we applied to accept credit cards,

12:11we'd actually get through the system.

12:13We took that number to 99%.

12:15And that's because we reframed the problem,

12:19we built credible models, and we had this mindset of,

12:25we're going to watch not at the merchant level,

12:28but we're gonna watch at the transaction level.

12:30So come in, perform some transactions,

12:35and as long as you're doing things

12:36with integrity, credible, and don't look suspicious,

12:40we'll continue to serve you.

12:43If we see any interestingness in how you use our system,

12:47that will be bubbled up to people to review,

12:50to figure out if there's something nefarious going on,

12:53and that's when we might ask you to leave.

12:56So the change in the mindset led to the technology

13:01that we needed to enable more people to get through,

13:06and to enable more people to access the system.

13:08What role does machine learning play into that,

13:11in that context of, you said,

13:15first of all, it's a beautiful shift.

13:17Anytime you shift your viewpoint into seeing

13:20that people are fundamentally good,

13:24and then you just have to verify

13:25and catch the ones who are not,

13:27as opposed to assuming everybody's bad,

13:30this is a beautiful thing.

13:31So what role does the, to you,

13:35throughout the history of the company,

13:37has machine learning played in doing that verification?

13:40It was immediate.

13:41I mean, we weren't calling it machine learning,

13:43but it was data science.

13:45And then as the industry evolved,

13:47machine learning became more of the nomenclature,

13:50and as that evolved, it became more sophisticated

13:54with deep learning, and as that continues to evolve,

13:58it'll be another thing.

13:59But they're all in the same vein.

14:02But we built that discipline up

14:04within the first year of the company,

14:06because we also had, we had to partner with a bank,

14:11we had to partner with Visa and MasterCard,

14:14and we had to show that,

14:16by bringing more people into the system,

14:19that we could do so in a responsible way,

14:21that would not compromise their systems,

14:23and that they would trust us.

14:25How do you convince this upstart company

14:27with some cool machine learning tricks

14:30is able to deliver on this trustworthy set of merchants?

14:35We staged it out in tiers.

14:37We had a bucket of 500 people using it,

14:41and then we showed results,

14:43and then 1,000, and then 10,000, then 50,000,

14:45and then the constraint was lifted.

14:49So again, it's kind of getting something tangible out there.

14:54I want to show what we can do rather than talk about it.

14:58And that put a lot of pressure on us

15:00to do the right things.

15:02And it also created a culture of accountability,

15:07of a little bit more transparency,

15:10and I think incentivized all of our early folks

15:15and the company in the right way.

15:18So what does the future look like

15:19in terms of increasing people's access?

15:21Or if you look at IoT, Internet of Things,

15:25there's more and more intelligent devices.

15:27You can see there's some people even talking

15:29about our personal data as a thing

15:32that we could monetize more explicitly versus implicitly.

15:35Sort of everything can become part of the economy.

15:38Do you see, so what does the future of Square look like

15:41in sort of giving people access in all kinds of ways

15:45to being part of the economy as merchants and as consumers?

15:49I believe that the currency we use

15:52is a huge part of the answer.

15:55And I believe that the internet deserves

15:58and requires a native currency.

16:01And that's why I'm such a huge believer in Bitcoin

16:07because it just,

16:11our biggest problem as a company right now

16:13is we cannot act like an internet company.

16:16Open a new market,

16:17we have to have a partnership with a local bank.

16:20We have to pay attention

16:21to different regulatory onboarding environments.

16:25And a digital currency like Bitcoin

16:29takes a bunch of that away

16:31where we can potentially launch a product

16:35in every single market around the world

16:38because they're all using the same currency.

16:41And we have consistent understanding of regulation

16:46and onboarding and what that means.

16:49So I think the internet continuing to be accessible

16:54to people is number one.

16:57And then I think currency is number two.

17:01And it will just allow for a lot more innovation,

17:04a lot more speed in terms of what we can build

17:07and others can build.

17:09And it's just really exciting.

17:11So, I mean, I wanna be able to see that

17:13and feel that in my lifetime.

17:16So in this aspect and in other aspects,

17:19you have a deep interest in cryptocurrency

17:22and distributed ledger tech in general.

17:24I talked to Vitalik Buterin yesterday on this podcast.

17:27He says hi, by the way.

17:29Hey.

17:29He's a brilliant, brilliant person.

17:33Talked a lot about Bitcoin and Ethereum, of course.

17:36So can you maybe linger on this point?

17:38What do you find appealing about Bitcoin,

17:42about digital currency?

17:43Where do you see it going in the next 10, 20 years?

17:46And what are some of the challenges with respect to Square

17:50but also just bigger for our globally, for our world,

17:55for the way we think about money?

17:59I think the most beautiful thing about it

18:01is there's no one person setting the direction.

18:05And there's no one person on the other side

18:07that can stop it.

18:08So we have something that is pretty organic in nature

18:15and very principled in its original design.

18:19And I think the Bitcoin white paper

18:22is one of the most seminal works of computer science

18:24in the last 20, 30 years.

18:28It's poetry.

18:30I mean, it really is.

18:30Yeah, it's a pretty cool technology.

18:32That's not often talked about.

18:33There's so much hype around digital currency

18:36about the financial impacts of it.

18:38But the actual technology is quite beautiful

18:40from a computer science perspective.

18:42Yeah, and the underlying principles behind it

18:44that went into it, even to the point

18:46of releasing it under a pseudonym.

18:48I think that's a very, very powerful statement.

18:51The timing of when it was released is powerful.

18:54It was a total activist move.

18:58I mean, it's moving the world forward

19:00in a way that I think is extremely noble and honorable

§03Transcript · 19:05–29:02

19:05and enables everyone to be part of the story,

19:08which is also really cool.

19:10So you asked a question around 10 years and 20 years.

19:13I mean, I think the amazing thing is no one knows.

19:17And it can emerge.

19:19And every person that comes into the ecosystem,

19:22whether they be a developer or someone who uses it,

19:27can change its direction in small and large ways.

19:31And that's what I think it should be,

19:33because that's what the internet has shown is possible.

19:36Now, there's complications with that, of course.

19:38And there's certainly companies that own large parts

19:42of the internet and can direct it more than others.

19:44And there's not equal access

19:47to every single person in the world just yet.

19:50But all those problems are visible enough

19:53to speak about them.

19:54And to me, that gives confidence that they're solvable

19:57in a relatively short timeframe.

20:00I think the world should be able to do that.

20:02I think the world changes a lot as we get these satellites

20:08projecting the internet down to earth,

20:11because it just removes a bunch of the former constraints

20:15and really levels the playing field.

20:18But a global currency,

20:20which a native currency for the internet is a proxy for,

20:24is a very powerful concept.

20:27And I don't think any one person on this planet

20:29truly understands the ramifications of that.

20:31I think there's a lot of positives to it.

20:34There's some negatives as well.

20:35But...

20:36Do you think it's possible, sorry to interrupt,

20:37do you think it's possible that this kind of digital currency

20:40would redefine the nature of money,

20:43so become the main currency of the world,

20:46as opposed to being tied to fiat currency

20:49of different nations and sort of really push

20:51the decentralization of control of money?

20:54Definitely, but I think the bigger ramification

20:58is how it affects how society works.

21:02And I think there are many positive ramifications

21:06outside of just money.

21:07Outside of just money.

21:08Money is a foundational layer that enables so much more.

21:12I was meeting with an entrepreneur in Ethiopia,

21:14and payments is probably the number one problem to solve

21:19across the continent,

21:21both in terms of moving money across borders

21:24between nations on the continent,

21:26or the amount of corruption within the current system.

21:33But the lack of easy ways to pay people

21:39makes starting anything really difficult.

21:42I met an entrepreneur who started the Lyft slash Uber

21:47of Ethiopia, and one of the biggest problems she has

21:49is that it's not easy for her riders to pay the company,

21:54it's not easy for her to pay the drivers.

21:57And that definitely has stunted her growth

22:00and made everything more challenging.

22:02So the fact that she even has to think about payments

22:07instead of thinking about the best rider experience

22:10and the best driver experience is pretty telling.

22:15So I think as we get a more durable, resilient

22:20and global standard, we see a lot more innovation everywhere.

22:26And I think there's no better case study for this

22:29than the various countries within Africa

22:32and their entrepreneurs who are trying to start things

22:35within health or sustainability or transportation

22:38or a lot of the companies that we've seen here.

22:42So the majority of companies I met in November

22:47when I spent a month on the continent were payments oriented.

22:52You mentioned, and this is a small tangent,

22:54you mentioned the anonymous launch of Bitcoin

22:58is a sort of profound philosophical statement.

23:00Pseudonymous.

23:02What's that even mean?

23:03There's a pseudonym.

23:04First of all, let me ask.

23:05There's an identity tied to it.

23:06It's not just anonymous, it's Nakamoto.

23:10So Nakamoto might represent one person or multiple people.

23:13But let me ask, are you Satoshi Nakamoto?

23:15Just checking, catch you off guard.

23:17And if I were, would I tell you?

23:18Yeah, that's true.

23:19Maybe you slip.

23:21A pseudonym is constructed identity.

23:25Anonymity is just kind of this random,

23:28like drop something off and leave.

23:32There's no intention to build an identity around it.

23:34And while the identity being built was a short time window,

23:39it was meant to stick around, I think, and to be known.

23:44And it's being honored in how the community

23:50thinks about building it,

23:50like the concept of Satoshi's, for instance,

23:55is one such example.

23:56But I think it was smart not to do it anonymous,

24:01not to do it as a real identity,

24:03but to do it as pseudonym,

24:05because I think it builds tangibility

24:07and a little bit of empathy that this was a human

24:13or a set of humans behind it.

24:14And there's this natural identity that I can imagine.

24:19But there is also a sacrifice of ego.

24:22That's a pretty powerful thing

24:23from your perspective. Yeah, which is beautiful.

24:25Would you do, sort of philosophically,

24:28to ask you the question,

24:29would you do all the same things you're doing now

24:32if your name wasn't attached to it?

24:35Sort of, if you had to sacrifice the ego,

24:39put another way, is your ego deeply tied

24:41in the decisions you've been making?

24:44I hope not.

24:45I mean, I believe I would certainly attempt

24:49to do the things without my name having

24:51to be attached with it.

24:53But it's hard to do that in a corporation, legally.

25:01That's the issue.

25:02If I were to do more open source things,

25:05then absolutely, I don't need my particular identity,

25:10my real identity associated with it.

25:12But I think the appreciation that comes

25:17from doing something good and being able to see it

25:21and see people use it is pretty overwhelming and powerful,

25:26more so than maybe seeing your name in the headlines.

25:29Let's talk about artificial intelligence a little bit,

25:33if we could.

25:3470 years ago, Alan Turing formulated the Turing test.

25:38To me, natural language is one of the most interesting

25:41spaces of problems that are tackled

25:44by artificial intelligence.

25:45It's the canonical problem of what it means

25:47to be intelligent.

25:48He formulated it as the Turing test.

25:50Let me ask sort of the broad question,

25:53how hard do you think is it to pass the Turing test

25:56in the space of language?

25:58Just from a very practical standpoint,

26:00I think where we are now and for at least years out

26:07is one where the artificial intelligence,

26:11machine learning, the deep learning models

26:13can bubble up interestingness very, very quickly

26:17and pair that with human discretion around severity,

26:22around depth, around nuance and meaning.

26:27I think for me, the chasm across for general intelligence

26:33is to be able to explain why and the meaning

26:38behind something.

26:40Behind a decision.

26:42Behind a decision or a set of data.

26:45So the explainability part is kind of essential

26:48to be able to explain the meaning behind something.

26:52To explain using natural language

26:54why the decisions were made, that kind of thing.

26:56Yeah, I mean I think that's one of our biggest risks

26:58in artificial intelligence going forward

27:01is we are building a lot of black boxes

27:03that can't necessarily explain why they made a decision

27:06or what criteria they used to make the decision.

27:09And we're trusting them more and more

27:11from lending decisions to content recommendation

27:14to driving to health.

27:18Like a lot of us have watches that tell us

27:20to understand how they're deciding that.

27:23I mean that one's pretty simple.

27:25But you can imagine how complex they get.

27:28And being able to explain the reasoning behind

27:32some of those recommendations seems to be an essential part.

27:34Although it's hard.

27:35Which is a very hard problem because sometimes

27:37even we can't explain why we make decisions.

27:40That's what I was, I think we're being sometimes

27:42a little bit unfair to artificial intelligence systems

27:45because we're not very good at some of these things.

27:48So do you think, apologize for the ridiculous

27:52romanticized question, but on that line of thought,

27:55do you think we'll ever be able to build a system

28:00like in the movie Her that you could fall in love with?

28:03So have that kind of deep connection with.

28:06Hasn't that already happened?

28:07Hasn't someone in Japan fallen in love with his AI?

28:13There's always going to be somebody

28:14that does that kind of thing.

28:15I mean at a much larger scale of actually building

28:19relationships, of being deeper connections.

28:21It doesn't have to be love, but it's just deeper connections

28:24with artificial intelligence systems.

28:26So you mentioned explainability.

28:27That's less a function of the artificial intelligence

28:29and more a function of the individual

28:32and how they find meaning and where they find meaning.

28:34Do you think we humans can find meaning in technology

28:37in this kind of way?

28:38Yeah, yeah, yeah, 100%, 100%.

28:40And I don't necessarily think it's a negative.

28:43But it's constantly going to evolve.

28:50So I don't know, but meaning is something

28:54that's entirely subjective.

28:56And I don't think it's going to be a function

28:59of finding the magic algorithm

§04Transcript · 29:02–38:53

29:02that enables everyone to love it.

29:07But maybe, I don't know.

29:09That question really gets at the difference

29:10between human and machine.

29:12So you had a little bit of an exchange with Elon Musk.

29:17Basically, I mean it's a trivial version of that,

29:20but I think there's a more fundamental question

29:22of is it possible to tell the difference

29:24between a bot and a human?

29:27And do you think it's, if we look into the future,

29:3110, 20 years out, do you think it would be possible

29:34or is it even necessary to tell the difference

29:36in the digital space between a human and a robot?

29:40Can we have fulfilling relationships with each

29:42or do we need to tell the difference between them?

29:46I think it's certainly useful in certain problem domains

29:49to be able to tell the difference.

29:52I think in others it might not be as useful.

29:56Do you think it's possible for us today

29:58to tell that difference?

30:00Is the reverse the meta of the Turing test?

30:02Well, what's interesting is I think the technology

30:07to create is moving much faster

30:10than the technology to detect, generally.

30:13You think so?

30:14So if you look at adversarial machine learning,

30:17there's a lot of systems that try

30:18to fool machine learning systems.

30:21And at least for me, the hope is that the technology

30:23to defend will always be right there, at least.

30:28Your sense is that...

30:30I don't know if they'll be right there.

30:31I mean, it's a race, right?

30:34So the detection technologies have to be two

30:38or 10 steps ahead of the creation technologies.

30:42This is a problem that I think the financial industry

30:44will face more and more because a lot of our risk models,

30:48for instance, are built around identity.

30:50Payments ultimately comes down to identity.

30:53And you can imagine a world where all this conversation

30:57around deep fakes goes towards the direction

31:00of a driver's license or passports or state identities.

31:06And people construct identities in order

31:09to get through a system such as ours

31:11to start accepting credit cards or into the cash app.

31:15And those technologies seem to be moving very, very quickly.

31:19Our ability to detect them, I think,

31:22is probably lagging at this point,

31:25but certainly with more focus, we can get ahead of it.

31:29But this is gonna touch everything.

31:33So I think it's like security.

31:38We're never going to be able

31:39to build a perfect detection system.

31:42We're only going to be able to...

31:45What we should be focused on is the speed of evolving it

31:50and being able to take signals that show correctness

31:55or errors as quickly as possible

31:58and move and to be able to build that

32:01into our newer models or the self learning models.

32:04Do you have other worries?

32:06Like some people, like Elon and others,

32:07have worries of existential threats

32:10of artificial intelligence,

32:11of artificial general intelligence?

32:13Or if you think more narrowly about threats

32:17and concerns about more narrow artificial intelligence,

32:20like what are your thoughts in this domain?

32:23Do you have concerns or are you more optimistic?

32:26I think Yuval in his book,

32:2921 Lessons for the 21st Century,

32:31his last chapter is around meditation.

32:34And you look at the title of the chapter

32:37and you're like, oh, it's all meditation.

32:39But what was interesting about that chapter

32:42is he believes that kids being born today,

32:48growing up today, Google has a stronger sense

32:53of their preferences than they do,

32:57which you can easily imagine.

32:59I can easily imagine today that Google probably knows

33:04my preferences more than my mother does.

33:08Maybe not me per se, but for someone growing up

33:12only knowing the internet,

33:13only knowing what Google is capable of,

33:16or Facebook or Twitter or Square or any of these things,

33:20the self awareness is being offloaded to other systems

33:25and particularly these algorithms.

33:28And his concern is that we lose that self awareness

33:32because the self awareness is now outside of us

33:35and it's doing such a better job

33:37at helping us direct our decisions around,

33:41should I stand, should I walk today?

33:43What doctor should I choose?

33:45Who should I date?

33:46All these things we're now seeing play out very quickly.

33:50So he sees meditation as a tool to build that self awareness

33:54and to bring the focus back on,

33:56why do I make these decisions?

33:58Why do I react in this way?

34:00Why did I have this thought?

34:02Where did that come from?

34:04That's a way to regain control.

34:07Or awareness, maybe not control, but awareness

34:10so that you can be aware that yes, I am,

34:13I am, I am, I am, I am.

34:15Yes, I am offloading this decision to this algorithm

34:19that I don't fully understand

34:21and can't tell me why it's doing the things it's doing

34:24because it's so complex.

34:26That's not to say that the algorithm can't be a good thing.

34:29And to me recommender systems,

34:31the best of what they can do is to help guide you

34:34on a journey of learning new ideas of learning period.

34:39It can be a great thing, but do you know you're doing that?

34:41Are you aware that you're inviting it to do that to you?

34:45I think that's the risk he identifies, right?

34:50That's perfectly okay.

34:51But are you aware that you have that invitation

34:55and it's being acted upon?

34:58And so that's a concern you're kind of highlighting

35:02that without a lack of awareness,

35:04you can just be like floating at sea.

35:06So awareness is key in the future

35:08of these artificial intelligence systems.

35:10Yeah, the movie WALLY.

35:12WALLY.

35:13Which I think is one of Pixar's best movies

35:15besides RATATOUILLI.

35:19RATATOUILLI was incredible.

35:20You had me until RATATOUILLI, okay.

35:22RATATOUILLI was incredible.

35:26All right, we've come to the first point

35:28where we disagree, okay.

35:29It's the entrepreneurial story in the form of a rat.

35:35I just remember just the soundtrack was really good, so.

35:38Excellent.

35:41What are your thoughts, sticking on artificial intelligence

35:43a little bit, about the displacement of jobs?

35:45That's another perspective that candidates

35:48like Andrew Yang talk about.

35:50Yang gang forever.

35:53Yang gang.

35:54So he unfortunately, speaking of Yang gang,

35:56has recently dropped out.

35:57I know, it was very disappointing and depressing.

36:00Yeah, but on the positive side,

36:02he's I think launching a podcast, so.

36:05Really, cool.

36:06Yeah, he just announced that.

36:07I'm sure he'll try to talk you into trying

36:09to come on to the podcast.

36:11I will talk to him.

36:12So. About RATATOUILLI.

36:14Yeah, maybe he'll be more welcoming

36:16of the RATATOUILLI argument.

36:18What are your thoughts on his concerns

36:20of the displacement of jobs, of automations,

36:22of the, of course there's positive impacts

36:24that could come from automation and AI,

36:26but there could also be negative impacts.

36:29And within that framework, what are your thoughts

36:31about universal basic income?

36:33So these interesting new ideas

36:36of how we can empower people in the economy.

36:40I think he was 100% right on almost every dimension.

36:46We see this in Square's business.

36:48I mean, he identified truck drivers.

36:52I'm from Missouri.

36:54And he certainly pointed to the concern

37:00and the issue that people from where I'm from

37:04feel every single day that is often invisible

37:07and not talked about enough.

37:09You know, the next big one is cashiers.

37:12This is where it pertains to Square's business.

37:15We are seeing more and more of the point of sale

37:19move to the individual customer's hand

37:22in the form of their phone and apps

37:24and preorder and order ahead.

37:27We're seeing more kiosks.

37:29We're seeing more things like Amazon Go.

37:32And the number of workers as a cashier in retail is immense.

37:40And, you know, there's no real answers

37:43on how they transform their skills

37:47and work into something else.

37:51And I think that does lead to a lot

37:53of really negative ramifications.

37:56And the important point that he brought up

37:59around universal basic income

38:01is given that the shift is going to come

38:04and given it is going to take time

38:07to set people up with new skills and new careers,

38:14they need to have a floor to be able to survive.

38:17And this $1,000 a month is such a floor.

38:22It's not going to incentivize you to quit your job

38:25because it's not enough,

38:26but it will enable you to not have to worry

38:30as much about just getting on day to day

38:35so that you can focus on what am I going to do now

38:39and what am I going to, what skills do I need to acquire?

38:44And I think, you know, a lot of people point

38:48to the fact that, you know, during the industrial age,

§05Transcript · 38:53–49:08

38:53we had the same concerns around automation,

38:55factory lines and everything worked out okay.

38:59But the biggest change is just the velocity

39:04and the centralization of a lot of the things

39:08that make this work, which is the data

39:11and the algorithms that work on this data.

39:14I think that the second biggest scary thing

39:18is just how around AI is just who actually owns the data

39:24and who can operate on it.

39:26And are we able to share the insights from the data

39:32so that we can also build algorithms that help our needs

39:36or help our business or whatnot?

39:39So that's where I think regulation could play

39:43a strong and positive part.

39:46First, looking at the primitives of AI

39:50and the tools we use to build these services

39:52that will ultimately touch every single aspect

39:54of the human experience.

39:56And then where data is owned and how it's shared.

40:05So those are the answers that as a society, as a world,

40:10we need to have better answers around,

40:12which we're currently not.

40:13They're just way too centralized

40:15into a few very, very large companies.

40:19But I think it was spot on with identifying the problem

40:23and proposing solutions that would actually work.

40:26At least that we learned from that you could expand

40:29or evolve, but I mean, I think UBI is well past its due.

40:38I mean, it was certainly trumpeted by Martin Luther King

40:41and even before him as well.

40:44And like you said, the exact $1,000 mark

40:48might not be the correct one,

40:50but you should take the steps to try to implement

40:54these solutions and see what works.

40:56100%.

40:57So I think you and I eat similar diets,

40:59and at least I was.

41:01The first time I've heard this.

41:04Yeah, so I was doing it before.

41:05First time anyone has said that to me, in this case anyway.

41:08Yeah, but it's becoming more and more cool.

41:12But I was doing it before it was cool.

41:13So intermittent fasting and fasting in general,

41:16I really enjoy, I love food,

41:18but I enjoy the, I also love suffering because I'm Russian.

41:23So fasting kind of makes you appreciate the,

41:29makes you appreciate what it is to be human somehow.

41:33But I have, outside the philosophical stuff,

41:36I have a more specific question.

41:37It also helps me as a programmer and a deep thinker,

41:41like from the scientific perspective,

41:43to sit there for many hours and focus deeply.

41:46Maybe you were a hacker before you were CEO.

41:50What have you learned about diet, lifestyle,

41:55mindset that helps you maximize mental performance,

41:57to be able to focus for,

42:00to think deeply in this world of distractions?

42:03I think I just took it for granted for too long.

42:08Which aspect?

42:09Just the social structure of we eat three meals a day

42:13and there's snacks in between.

42:15And I just never really asked the question, why?

42:18Oh, by the way, in case people don't know,

42:20I think a lot of people know,

42:22but you at least, you famously eat once a day.

42:26You still eat once a day?

42:27Yep, I eat dinner.

42:29By the way, what made you decide to eat once a day?

42:32Like, cause to me that was a huge revolution

42:33that you don't have to eat breakfast.

42:35That was like, I felt like I was a rebel.

42:37Like I abandoned my parents or something

42:39and became an anarchist.

42:41When you first, like the first week you start doing it,

42:43it feels that you kind of like have a superpower.

42:45Then you realize it's not really a superpower.

42:47But it, I think you realize,

42:50at least I realized like it just how much is,

42:53how much our mind dictates what we're possible of.

42:59And sometimes we have structures around us

43:02that incentivize like, this three meal a day thing,

43:05which was purely social structure

43:09versus necessity for our health and for our bodies.

43:14And I did it just, I started doing it

43:17because I played a lot with my diet when I was a kid

43:21and I was vegan for two years

43:23and just went all over the place just because I,

43:28you know, health is the most precious thing we have

43:31and none of us really understand it.

43:33So being able to ask the question through experiments

43:37that I can perform on myself

43:39and learn about is compelling to me.

43:44And I heard this one guy on a podcast, Wim Hof,

43:47who's famous for doing ice baths and holding his breath

43:50and all these things.

43:54He said he only eats one meal a day.

43:56I'm like, wow, that sounds super challenging

43:59and uncomfortable.

44:00I'm gonna do it.

44:02So I just, I learn the most when I make myself,

44:06I wouldn't say suffer,

44:07but when I make myself feel uncomfortable

44:10because everything comes to bear in those moments

44:14and you really learn what you're about or what you're not.

44:21So I've been doing that my whole life.

44:23Like when I was a kid, I could not,

44:25like I was, I could not speak.

44:27Like I had to go to a speech therapist

44:29and it made me extremely shy.

44:31And then one day I realized I can't keep doing this

44:34and I signed up for the speech club.

44:39And it was the most uncomfortable thing

44:45I could imagine doing, getting a topic on a note card,

44:49having five minutes to write a speech

44:51about whatever that topic is,

44:53not being able to use the note card while speaking

44:56and speaking for five minutes about that topic.

44:59So, but it just, it puts so much,

45:03it gave me so much perspective

45:06around the power of communication,

45:08around my own deficiencies

45:10and around if I set my mind to do something, I'll do it.

45:14So it gave me a lot more confidence.

45:16So I see fasting in the same light.

45:18This is something that was interesting,

45:21challenging, uncomfortable,

45:23and has given me so much learning and benefit as a result.

45:30And it will lead to other things that I'll experiment with

45:32and play with, but yeah,

45:35it does feel a little bit like a superpower sometimes.

45:39The most boring superpower one can imagine.

45:42Now it's quite incredible.

45:44The clarity of mind is pretty interesting.

45:47Speaking of suffering,

45:49you kind of talk about facing difficult ideas.

45:53You meditate, you think about the broad context of life,

45:58of our societies.

46:00Let me ask, sort of apologize again

46:02for the romanticized question,

46:03but do you ponder your own mortality?

46:06Do you think about death,

46:09about the finiteness of human existence

46:13when you meditate, when you think about it?

46:15And if you do, what,

46:18how do you make sense of it, that this thing ends?

46:22Well, I don't try to make sense of it.

46:23I do think about it every day.

46:25I mean, it's a daily, multiple times a day.

46:29Are you afraid of death?

46:30No, I'm not afraid of it.

46:32I think it's a transformation, I don't know to what,

46:36but it's also a tool

46:39to feel the importance of every moment.

46:44So I just use it as a reminder, like I have an hour.

46:48Is this really what I'm going to spend the hour doing?

46:52Like I only have so many more sunsets and sunrises to watch.

46:55Like I'm not going to get up for it.

46:58I'm not going to make sure that I try to see it.

47:02So it just puts a lot into perspective

47:06and it helps me prioritize.

47:09I think it's, I don't see it as something that's like

47:13that I dread or is dreadful.

47:15It's a tool that is available

47:18to every single person to use every day

47:19because it shows how precious life is.

47:21And there's reminders every single day,

47:24whether it be your own health or a friend or a coworker

47:27or something you see in the news.

47:30So to me it's just a question

47:32of what we do with our daily reminder.

47:34And for me, it's am I really focused on what matters?

47:40And sometimes that might be work,

47:42sometimes that might be friendships or family

47:45or relationships or whatnot,

47:47but it's the ultimate clarifier in that sense.

47:51So on the question of what matters,

47:53another ridiculously big question of

47:57once you try to make sense of it,

47:58what do you think is the meaning of it all,

48:00the meaning of life?

48:02What gives you purpose, happiness, meaning?

48:07A lot does.

48:08I mean, just being able to be aware

48:14of the fact that I'm alive is pretty meaningful.

48:20The connections I feel with individuals,

48:23whether they're people I just meet

48:25or long lasting friendships or my family is meaningful.

48:30Seeing people use something that I helped build

48:33is really meaningful and powerful to me.

48:38But that sense of, I mean,

48:40I think ultimately it comes down to a sense of connection

48:43and just feeling like I am bigger,

48:47I am part of something that's bigger than myself

48:49and like I can feel it directly

48:52in small ways or large ways,

48:54however it manifests is probably it.

48:59Last question.

49:00Do you think we're living in a simulation?

49:05I don't know.

49:06It's a pretty fun one if we are,

§06Transcript · 49:09–51:14

49:09but also crazy and random and wrought with tons of problems.

49:15But yeah.

49:17Would you have it any other way?

49:19Yeah.

49:20I mean, I just think it's taken us way too long

49:24as a planet to realize we're all in this together

49:27and we all are connected in very significant ways.

49:34I think we hide our connectivity very well through ego,

49:38through whatever it is of the day.

49:42But that is the one thing I would wanna work

49:46towards changing and that's how I would have it another way.

49:51Cause if we can't do that,

49:52then how are we gonna connect to all the other simulations?

49:55Cause that's the next step is like

49:57what's happening in the other simulation.

49:58Escaping this one and yeah.

50:03Spanning across the multiple simulations

50:05and sharing in and on the fun.

50:07I don't think there's a better way to end it.

50:09Jack, thank you so much for all the work you do.

50:12There's probably other ways that we've ended this

50:13and other simulations that may have been better.

50:16We'll have to wait and see.

50:18Thanks so much for talking today.

50:19Thank you.

50:21Thanks for listening to this conversation with Jack Dorsey

50:24and thank you to our sponsor, Masterclass.

50:26Please consider supporting this podcast

50:29by signing up to Masterclass at masterclass.com slash Lex.

50:34If you enjoy this podcast, subscribe on YouTube,

50:37review it with five stars on Apple Podcast,

50:39support on Patreon or simply connect with me on Twitter

50:42at Lex Friedman.

50:45And now let me leave you with some words

50:47about Bitcoin from Paul Graham.

50:50I'm very intrigued by Bitcoin.

50:52It has all the signs of a paradigm shift.

50:55Hackers love it, yet it is described as a toy,

50:58just like microcomputers.

51:01Thank you for listening and hope to see you next time.

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