Speaker 1: Hey, Dna, Hey Mark. Here we are middle of summer,
Speaker 1: but it seems BENF didn't really get the memo. It
Speaker 1: hasn't really slowed down that much around here, not at all. Actually,
Speaker 1: this week, on the second of August, B and F
Speaker 1: is having our new Delhi Summit. It is one of
Speaker 1: six market gatherings for business and government leaders. We bring
Speaker 1: together people to discuss innovation and the transition to a
Speaker 1: low carbon economy. If you're not lucky enough to attend
Speaker 1: in person, benef clients or BENOF users can still follow
Speaker 1: the action on the BENF mobile app. Just tap on
Speaker 1: the summit. Tap there you can see a full agenda
Speaker 1: with speaker bios and the presentation slides from the BENF talks.
Speaker 1: Those are talks from our BENF analysts. You can also
Speaker 1: see a full list of the attendees. Today, we are
Speaker 1: going to talk with the MC of the Delhi Summit,
Speaker 1: Nathaniel or not Bullard. He is the global head of
Speaker 1: Executive Insights for B and E F. And what does
Speaker 1: that title mean. Well, he wears many hats for us
Speaker 1: over here, and we'll hear all about that in the interview.
Speaker 1: One of those is writing a weekly op ed called
Speaker 1: spark Lines. It is published through Bomberg Opinion and you
Speaker 1: can find it on the terminal under Ni Bullard b
Speaker 1: U L L A R D or on Bloomberg dot
Speaker 1: com under spark Lines, or search for Bullard. In either location.
Speaker 1: You can sign up for a weekly distribution, which I
Speaker 1: must say I am a happy receiver of because his
Speaker 1: pieces are short and pithy and all around interesting. Today
Speaker 1: we're going to talk to him about two spark lines,
Speaker 1: among other things. And just as a quick reminder, B
Speaker 1: and the F does not provide investment or strategy advice.
Speaker 1: You can hear a full disclaimer at the end of
Speaker 1: the show. And right now let's jump in. Hi Na,
Speaker 1: thank you for joining us today. Hi Danna, him Mark,
Speaker 1: How are you guys doing well? So not Bullard, how
Speaker 1: would you describe your role within So? My role is
Speaker 1: a veteran analyst, and I say that very seriously, and
Speaker 1: that I've been doing this now for twelve years, since
Speaker 1: before we were required in a number of different sectors
Speaker 1: and a number of different markets. There are probably not
Speaker 1: that many people that have had that kind of great
Speaker 1: rotation through a lot of the things we do, and
Speaker 1: also are not currently running a big team. So years
Speaker 1: ago in television, we used to have a colleague who
Speaker 1: is described as an editor at large. This is a
Speaker 1: sort of an equivalent analyst at large position, and what
Speaker 1: that actually entails is about even thirds split between doing
Speaker 1: things with our own management committee, like with the two
Speaker 1: of you and with John morre CEO and with our
Speaker 1: other colleagues. Another third is doing public presentations, so the
Speaker 1: sort of classic I talk and travel kind of work
Speaker 1: that a lot of our analysts already do, but with
Speaker 1: a with a particular angle on it. Generally speaking, it's
Speaker 1: either very broadcast so it's something for like three four,
Speaker 1: five hundred or a thousand people, or very narrow cast
Speaker 1: to let's say a corporate board a lot of times
Speaker 1: asking about similar ideas but with a very different set
Speaker 1: of vectors for delivery. And then finally, I write every
Speaker 1: week I have a project that I started five years
Speaker 1: ago as an email essentially for friends and Emily of
Speaker 1: be in the f of the time, that was just
Speaker 1: published by us through our marketing capabilities and now is
Speaker 1: published by Bloomberg Opinion, which publishes well Opinion by Bloomberg authors.
Speaker 1: And it goes out as an email, which is how
Speaker 1: it originated, it goes out on the web, and it
Speaker 1: goes out on the Bloomberg terminal, usually on Friday's maybe
Speaker 1: sometimes with some flexibility depending on the timing of what
Speaker 1: I'm writing about. So you sent us a couple uh
Speaker 1: different pieces today to say, hey, guys, study up a
Speaker 1: little bit before we have a chat um. We can
Speaker 1: dive into those, but I think one that we were
Speaker 1: talking about that was pretty well received, just one called
Speaker 1: climate change is all most of us have ever known.
Speaker 1: That's right, So tell us a little bit about what
Speaker 1: you wrote there and what it means and really the
Speaker 1: message that you were trying to send with that. Certainly.
Speaker 1: So there's another contributor to Bloomberg in Singapore who was
Speaker 1: a former trader. His name is Mark Cutmore, and he
Speaker 1: did the ODDNS podcast a couple of years ago that
Speaker 1: Joe Wisenhal and Tracy All the Way Run, and he
Speaker 1: said something that is stuck with me and is a
Speaker 1: sort of guiding principle for a lot of this work,
Speaker 1: which is markets think in narratives. So we're often looking
Speaker 1: at things from either an intensely analytical or a very
Speaker 1: factual basis, but at the broadest sense of markets with
Speaker 1: the capital m They think in narratives and in stories.
Speaker 1: And one of the challenges that I find in dealing
Speaker 1: with a discussion about climate change in particular is that
Speaker 1: it is quite experiential for a lot of people. And
Speaker 1: I mean experience in a couple of ways. One how
Speaker 1: old you are, like, what you what you knew as
Speaker 1: a child, what informs your expectation based on what you
Speaker 1: knew when you were young? And also your experience within
Speaker 1: the corporate world. Are you nearer to retirement than you
Speaker 1: are to initiating your job, let's say, And in fact,
Speaker 1: if you are the kind of senior people that I'm
Speaker 1: engaging with most of the time, that's almost axiomatic. They're
Speaker 1: almost all that way. Very rare is it that you
Speaker 1: go to, say, a board of directors and somebody's like, yeah,
Speaker 1: I'm twenty four, and more likely they're double that or
Speaker 1: even triple that age, right, And so their their job
Speaker 1: is to sort of traffic in and build off of
Speaker 1: their years and decades of experience. But I think that
Speaker 1: has a way of conquering the ability to look at
Speaker 1: sort of forward narratives. And so my frame for this
Speaker 1: and thinking about climate change was a couple of the
Speaker 1: publications that had come out in from third parties, one
Speaker 1: of them was a precipitation chart in the United States.
Speaker 1: This is from Noah So, one of our research institutes
Speaker 1: in the US that it published that the trailing twelve
Speaker 1: months was the wettest twelve months in the United States
Speaker 1: since and probably forever. There's really no way of knowing before,
Speaker 1: and extremely wet, like much wetter than it's ever been. Now,
Speaker 1: that's a very noisy kind of signal, but if you
Speaker 1: smooth it out, you can see that it's like about
Speaker 1: ten percent wetter than the long term average has ever been.
Speaker 1: Um I also realized that if you if you fit
Speaker 1: these things against the average across the twentieth century, that
Speaker 1: it's been above average for about forty something years, right,
Speaker 1: so we loss the average on the way up, and
Speaker 1: we're still there and actually mean surface temperatures a global
Speaker 1: surface temperatures around the world have fallen on almost exactly
Speaker 1: the same kind of a pattern. There's a thirty year
Speaker 1: interval in which averages are determined and the average temperatures
Speaker 1: the benchmark is nineteen fifty one to night and in
Speaker 1: the mid nineteen seventies, the global surface temperature went above
Speaker 1: that mean and has never been below it. And so
Speaker 1: the reason that I thought that was useful was because
Speaker 1: we might be dealing with a business executive who's at
Speaker 1: the tail end of a long and illustrious career in
Speaker 1: his or her domain, and is mostly embedded in their
Speaker 1: own business. It may not necessarily be thinking on a
Speaker 1: thirty forty year time went ahead, but that interval of
Speaker 1: climate change and that interval of precipitation matches up very
Speaker 1: nicely with the global median age, which is about thirty
Speaker 1: seven which means that actually the median person on Earth
Speaker 1: has only known something that was hotter and wetter than
Speaker 1: it was before. And if you look at places that
Speaker 1: are not you know, the global average, and that's saying
Speaker 1: least developed countries. By the UN standard, the median age
Speaker 1: is nineteen point four years. So most people have had
Speaker 1: the entirety of their lifetimes within a system that is
Speaker 1: not variable and not fluctuating, or rather not just variable
Speaker 1: and fluctuating, but has a vector. And so if you're
Speaker 1: twenty and entering the workforce, your expectations are probably about
Speaker 1: always going to be more automation. It's also if you're
Speaker 1: looking at your macro environment. It's always going to be
Speaker 1: hotter and it feels like it, right, And this is
Speaker 1: a narrative, is something that helps to shape and drive
Speaker 1: the way that people construct their long term vision of
Speaker 1: the future. Companies do this in the form of scenario planning.
Speaker 1: I try to do it in six or seven hundred
Speaker 1: words in an email that people received with a few charts,
Speaker 1: but I think it's part of the same kind of idea.
Speaker 1: And I realized that the only the only way to
Speaker 1: sort of convince people about that that they are carrying
Speaker 1: their own stories with them is to tell another story.
Speaker 1: And it's a useful framework. I think we guess, for
Speaker 1: one thing, the numbers around it are inarguable. I mean,
Speaker 1: you can you can argue about mean surface temperature, but
Speaker 1: you're not really arguing with me, would be any of
Speaker 1: analysts you're arguing with, you know, laboratories and research institutes.
Speaker 1: So you mentioned the piece that sentiment is changing around
Speaker 1: these things. Can you describe kind of how some of
Speaker 1: the sentiments are changing. So very fewer and fewer people
Speaker 1: who do not believe in climate change, particularly people that
Speaker 1: are younger. More and more people believe that not only
Speaker 1: is it occurring, but it is anthropogenic, so it's caused
Speaker 1: by people, and there there is a reason to sort
Speaker 1: of disaggregate those those two beliefs, right well, giving that
Speaker 1: it happens means well, you know, we go through these
Speaker 1: periods once every million years or whatever, so what and
Speaker 1: and in truth that does happen globally or in the
Speaker 1: long geneologic timeline. It usually coincides with what we call
Speaker 1: greatest extinctions, but it does occur on its own. Pleasant pleasant,
Speaker 1: isn't it. But the next aspect, though, is that it's
Speaker 1: being caused by people, meaning that there is something to
Speaker 1: be There's both blame, but I would say more importantly,
Speaker 1: there's something to be done as opposed to nothing to
Speaker 1: be done. And I think that that's that's the sort
Speaker 1: of thing that we start to see show up in
Speaker 1: a business context, partly as imperative, you know, we have
Speaker 1: to do this, but depending on the company, partly as
Speaker 1: opportunity as well, Like if doing doing this, it might
Speaker 1: be a way to first of all, cap your downsides
Speaker 1: as much as possible, Right so the sort of sort
Speaker 1: of resilience dividend or robustness, and the other part is
Speaker 1: to capture some upside from it. We're we're better prepared
Speaker 1: and are therefore in a better position to provide for
Speaker 1: be meaningful in a future that is whether or more volatile.
Speaker 1: More everything you're writing specifically for business audience. You are,
Speaker 1: you are on the Bloomberg terminal and also have a
Speaker 1: newsletter to the wider world, but there there is a
Speaker 1: specific audience here. There are two other pieces that you wrote,
Speaker 1: the one called climate Change puts Insurers to the test
Speaker 1: and the other how far will Insurers go to detach
Speaker 1: from coal? Now, I'm really glad you brought up scenarios.
Speaker 1: Scenario planning is something that is kind of at the
Speaker 1: core of the TCFD Task Force for Climate related Financial disclosures. Additionally,
Speaker 1: it seems to be getting to be at the core
Speaker 1: for a lot of businesses, both corporates and finance UM
Speaker 1: and not just relegated to this insurance space. Whether they're
Speaker 1: constantly trying to come up with probabilities, but these probabilities
Speaker 1: of likelihood around these climate change scenarios seem to be
Speaker 1: going more mainstream. Do you see any evidence of that
Speaker 1: coming about UM or maybe that's illustrated in these two pieces.
Speaker 1: There's an interesting thing always about watching insurance because it's
Speaker 1: it's like a market of other markets, almost right, and
Speaker 1: it in turn has its own risk market called reinsurance.
Speaker 1: But the reason I think that it's very warden to
Speaker 1: watch is because it is both obviously the the arbiter
Speaker 1: and the underwriter of risk, but also it is a
Speaker 1: major investor in assets of all kinds of classes. So
Speaker 1: it has this this unusual exposure to basically anything. So
Speaker 1: let's say that you are you are a you're an
Speaker 1: orige insure and you underwrite the risks around a coal
Speaker 1: coal plant, qual fired power plant. You are exposed to
Speaker 1: anything that you have underwritten on the asset itself, but
Speaker 1: you also might have you might own equity in the
Speaker 1: company that in turn neither provides fuel to that or
Speaker 1: owns the company that owns the coal plant, or something
Speaker 1: like that, and so you're exposed to whatever business dynamics
Speaker 1: happen as well, both the physical risks and the financial
Speaker 1: risk that are associated with one of these assets. So
Speaker 1: insurance is a sort of a uniquely multifaceted way of
Speaker 1: looking at any kind of macro risk. That's generally why
Speaker 1: they're fairly risk averse. Um they're also really highly regulated,
Speaker 1: and that's the key part that I looked at in
Speaker 1: my piece, which was that the Bank of England's Prudential
Speaker 1: Regulation Authority, the regulator for in fiduciary institutions, puts out
Speaker 1: a stress test that it sends to all general insurers
Speaker 1: and I think they do them for banks as well,
Speaker 1: and a lot of it is usual stuff, tell us
Speaker 1: your capital ratios, tell us whatever, whatever kind of things,
Speaker 1: and then they like to and this is a good thing,
Speaker 1: sort of throw something else new in there each time,
Speaker 1: and they're they're sort of less official than the kind
Speaker 1: of standard stuff that always happens. But in the most
Speaker 1: recent one a few months ago, the Bank of England
Speaker 1: p r A says, tell us about your exposure to
Speaker 1: cyber security and to climate risk, and they do it
Speaker 1: by having you lot a spreadsheet that says I have
Speaker 1: X many assets and these these asset classes and in
Speaker 1: these scenarios, I'm going to write their book value down
Speaker 1: by this. So it's it's very it's very blunt. I mean,
Speaker 1: if I can figure it out, it can't be that complicated,
Speaker 1: So it's it's fairly simple. Uh, it's coming from a
Speaker 1: very serious regulatory institutions. You more or less have to
Speaker 1: do it. I don't think you running to punt on it.
Speaker 1: And it's it's got some very clear directives around it.
Speaker 1: So I looked at that as a way of saying, Okay, well,
Speaker 1: this is like what the regulator of the people who
Speaker 1: underwrite an assess risk thinks. The risks might be very
Speaker 1: a very interesting way for us to be to be
Speaker 1: approaching what might be happening and how companies might think
Speaker 1: about it. And it's they're not small numbers in terms
Speaker 1: of what a write down of asset classes would look like.
Speaker 1: I can one of the transition scenarios of climate change.
Speaker 1: They say, you write your cold book off by more
Speaker 1: than which ouch if you're you know, if you're an investor,
Speaker 1: that that's pretty that's pretty severe. And in fact they
Speaker 1: actually call it disorderly like it's not it's not a
Speaker 1: sort of like, well, we can smoothly transition out of this.
Speaker 1: It's more like things have changed so significantly that these
Speaker 1: assets are trending towards worthless, or they're they're so heavily
Speaker 1: impaired that there's something that you you have to get
Speaker 1: out of, no matter what that no matter what's happening.
Speaker 1: So when I think it is actually very useful that
Speaker 1: when looking at the two scenarios the Bank of eng
Speaker 1: And is asking for, is they on the surface of
Speaker 1: nothing in common with each other cybersecurity and climate risk.
Speaker 1: But the more I thought about it, they actually have
Speaker 1: quite a bit in common. They're both pervasive, very large.
Speaker 1: I guess mark what we would call an attack surface
Speaker 1: in which things can happen. Right in cybersecurity, it's everything
Speaker 1: from your connected doorbell or the you know, the connected
Speaker 1: pump in your fish tank can be used as a
Speaker 1: point of entry to somebody's CRM and you now stolen
Speaker 1: everybody's credit card information. So these think this bloomberg business.
Speaker 1: We actually wrote about this and I thought climate is
Speaker 1: actually kind of similar. Is that like, basically everything ends
Speaker 1: up affected by this. It's not just that it's hotter,
Speaker 1: it's also that things are more volatile. Most of our
Speaker 1: built environment was designed around some sort of standard that
Speaker 1: if it's no longer the standard, things just don't work
Speaker 1: as well. It creates brittleness throughout the system. Uh paradox,
Speaker 1: And it was actually easier to measure what might be
Speaker 1: problematic from climate change that was from cybersecurity, even though
Speaker 1: it's a really long term thing. But I like that.
Speaker 1: I think that that that construct that the Bank of
Speaker 1: England has helpfully put together is one that I would
Speaker 1: imagine comes into the scenario planning and the scenario thinking
Speaker 1: of a lot of the institutions that we deal with.
Speaker 1: Is it like, well, if you went to a company
Speaker 1: you said do you have a cybersecurity strategy and they
Speaker 1: said nah, we'd be a bit surprised. I would imagine
Speaker 1: that for pretty much any big institution we would have
Speaker 1: the same reaction if in five years time they said
Speaker 1: I don't have a climate change scenario policy or risk
Speaker 1: assessment or way of thinking about it. So do you
Speaker 1: think these things are things that happened in as curve,
Speaker 1: that just happened all of a sudden Very much so.
Speaker 1: I mean, if you if you look at them, if
Speaker 1: you look at these things again, thinking in stories, very
Speaker 1: few institutions want to be the first to do something,
Speaker 1: even fewer, very few institutions want to be the last
Speaker 1: to do something. So, particularly when you're talking about risk,
Speaker 1: when you're talking about standards and things like that, they
Speaker 1: tend to go slowly and then suddenly and then especially
Speaker 1: once you if you think about it, is a group
Speaker 1: of peers, right, they all want to be doing it.
Speaker 1: Who wants to be who wants to be the last
Speaker 1: insurance company that does not have a policy about thermal
Speaker 1: coal you don't write or you've relegated yourself to essentially
Speaker 1: a very specialty part of the business. Who wants to
Speaker 1: be the auto company that has zero electric vehicle strategy
Speaker 1: would be another analogy. I read Bob Dudley's talk at
Speaker 1: Chatham House a couple of weeks ago and scoring them
Speaker 1: to train in and it really seemed like vp IS
Speaker 1: is on its way right, not maybe not the first,
Speaker 1: but maybe the first oil major to really just go
Speaker 1: up the curve. And but they were the first for
Speaker 1: a while for a while and then backed out. But
Speaker 1: it looks like they're they're backing back in. But but
Speaker 1: so you know, Bob Doney, the CEO of BP and
Speaker 1: his colleague who is his counterpart rather at Shell Bend
Speaker 1: and Britain, they they are both quite vocal about these
Speaker 1: sorts of things. By the time that they've each that
Speaker 1: point of public discussion, it's probably relatively well considered within
Speaker 1: the rest of the organization there. Let's put it this,
Speaker 1: or they're probably not winging it it's it's going, it's
Speaker 1: going through a very thoughtful apparatus, especially for institutions that
Speaker 1: really do plan to So I but I, but I
Speaker 1: what I don't know yet and what is probably in
Speaker 1: a neutral statement unclear for quite some time as exactly
Speaker 1: what that means, you know, is for a company, is
Speaker 1: it primarily rated towards risk? Is is it primarily rated
Speaker 1: towards opportunity? If you think about it from a strategic
Speaker 1: planning perspective, do you think that there's an average time
Speaker 1: from announcement of change in a company to actual implementation.
Speaker 1: It's a fantastic question that I think depends much more
Speaker 1: upon the nature of the business and its own cultures,
Speaker 1: embrace of speed, openness to change, and where where it
Speaker 1: probably is along its own journey with its own from
Speaker 1: lack of a better word, stuff. So, companies that have
Speaker 1: lots of resources of various types, and I would put
Speaker 1: in this in this context, could say a diversified metals
Speaker 1: and mining company has upside scenarios and not upside scenarios
Speaker 1: within its portfolio of assets. In an electric vehicle high
Speaker 1: electric vehicle penetration future, in a very climate change the
Speaker 1: future and whatever there there's there's there's pluses and minuses.
Speaker 1: A lot of times those organizations tend to move sometimes
Speaker 1: actually more supp only because they can. It's Pewer play.
Speaker 1: Companies that have essentially no upside from a transition away
Speaker 1: from one resource towards another. That and I say this
Speaker 1: neutral e are fairly naturally less enthusiastic about such things.
Speaker 1: It's the more active fight rather than adapt. I think
Speaker 1: that's I think that's a way to say it, because
Speaker 1: adapt adaptation is it's not necessarily not in the d
Speaker 1: n A. It's more like not in the capability of
Speaker 1: the resources that are given. It would require doing something
Speaker 1: completely different, especially for institutions for which you know, a
Speaker 1: lot of the value and the way in which they
Speaker 1: are valued is in assets that they own, you know,
Speaker 1: years of future reserves and things like that. Those those
Speaker 1: are not a particularly resilient resource when it comes to
Speaker 1: when it comes to a future that might not be
Speaker 1: using so much. You had another piece, Actually they said,
Speaker 1: like they're those numbers becoming increasingly meaningless. Isn't that right?
Speaker 1: Was that not you? That was Liam Denning? Sorry, I wish,
Speaker 1: I wish I wrote something that good. Yeah, it was.
Speaker 1: It was great, so good in fact that it couldn't
Speaker 1: have been written by That's definitely on the Mdenning piece.
Speaker 1: When you're looking at the change curve, people do resist change,
Speaker 1: whether that be groups of people in a company or individuals.
Speaker 1: And I'm actually thinking, as you're talking about these company
Speaker 1: dynamics and change and opportunity and how you sipeon through that,
Speaker 1: on this very micro level, individuals are doing that. So
Speaker 1: I am actually going to pivot us to two other notes.
Speaker 1: So one is self driving fixed for a population problem,
Speaker 1: and the other is Hong Kong's taxi fleet pages in
Speaker 1: real time. Uh. Now, by Hong Kong's taxi fleet, you're
Speaker 1: talking about people. And I must say that we spend
Speaker 1: a lot of time talking about AI and self driving
Speaker 1: and whether or not this is going to replace physical
Speaker 1: drivers and then Uber indeedy and who those physical drivers
Speaker 1: are and those physical drivers, Yeah, they're They're real people
Speaker 1: who have adapted in many regards, or maybe in Hong
Speaker 1: Kong's case, not adapted to this rapid implementation of change
Speaker 1: in how we move people and things around and in
Speaker 1: what and how it all comes together. So as this
Speaker 1: change is happening to people around the world in real time,
Speaker 1: talk a little bit about those notes, because I think
Speaker 1: one of the fun things that you get to do
Speaker 1: is not just talk about implications for companies and opportunities,
Speaker 1: but actually how it's going to affect everyone's lives. Thank you,
Speaker 1: I I yeah, I had a lot of fun with
Speaker 1: that one. I didn't give in Hong Kong for four years,
Speaker 1: so it's close to heart. And actually marketing into this
Speaker 1: a bit light on how to you come up with
Speaker 1: an idea for something. A lot of them are actually experiential,
Speaker 1: even if it sounds kind of lame to talk about
Speaker 1: experiential in the context of like reading business reports, but
Speaker 1: it's experiential. There's an aha moment, and this was reading
Speaker 1: something in in the Hong Kong English language newspaper the
Speaker 1: South China Morning Post that just said something about Hong
Speaker 1: Kong's taxi drivers are like a record average old age
Speaker 1: and it is quite venerable, like unexpectedly old mid sixties.
Speaker 1: Mid sixties is a sort of median age for a
Speaker 1: for a taxi driver in Hong Kong, but there are
Speaker 1: actually a fair number that are significantly older than that
Speaker 1: are older than seventy yes eight percent of Hong Kong
Speaker 1: taxi drivers are older than seventy. And remember this is
Speaker 1: the this is the locality with the highest average average
Speaker 1: age population on Earth or sorry, average knife expectancy in
Speaker 1: the eighties. So there are plenty of people who are
Speaker 1: over seventy and if they're in good health, have potentially
Speaker 1: another fifteen or twenty years of working if ahead of them.
Speaker 1: And yeah, it's an it's an interesting sort of microcosm
Speaker 1: of many different aspects of transportation in the demographics and
Speaker 1: of society. But I thought about it particularly as like
Speaker 1: as something that is aging in real time and will
Speaker 1: not be replaced. And I used it, and this is
Speaker 1: not characteristic of my work all the time, to use
Speaker 1: it as a sort of metaphor for the rest of
Speaker 1: Hong Kong's economy that's also aging in real time and
Speaker 1: predominantly services, does not have an above replacement birth rate,
Speaker 1: and so is facing things that While we worry in
Speaker 1: a lot of economies that automation and AI and things
Speaker 1: like that will be putting people out of work, I
Speaker 1: sort of imagined in the context here, if they will
Speaker 1: be doing the work that needs to be done, because
Speaker 1: who else will be doing it? I don't know about it.
Speaker 1: If we're gonna have self driving cars in Hong Kong.
Speaker 1: The traffic is traffic, and most important to that, topography
Speaker 1: is incredibly complex, and so it's it's not the same
Speaker 1: thing as driving on an empty, prepared highway somewhere, but
Speaker 1: some something won't have to give in the way that
Speaker 1: people move around or the expectations of how one gets
Speaker 1: from place to place. Maybe in what or with whom
Speaker 1: If you continue to have the Hong Kong taxi drivers
Speaker 1: become older and older and there is no sort of
Speaker 1: replacement to go with it, I want to know more
Speaker 1: about the complex topography. So another city that you also
Speaker 1: lived in, San Francisco, has a lot of hills and
Speaker 1: a lot of technology implementation in this driving space, and
Speaker 1: I keep thinking it wouldn't exactly physically be where I
Speaker 1: would start, but it is where it is all kind
Speaker 1: of coming from. Um, how does what are the barriers
Speaker 1: that Hong Kong has so ongoing? Hong Kong is very dense, Uh,
Speaker 1: it has a very rich visual landscape if you will.
Speaker 1: There's often a lot of things going on, So there
Speaker 1: would be a really really really high amount of signal
Speaker 1: if you think about it, especially through through some kind
Speaker 1: of machine or computer vision, and that's so that's a
Speaker 1: sort of like the vision part of it. The driving
Speaker 1: part is that there's all kinds of like like narrow
Speaker 1: one way roads that wind through the mountains. UH signages
Speaker 1: and two languages. So you might find that the more
Speaker 1: prominent sign would be in Chinese characters, and you'd better
Speaker 1: make sure that your computer vision can read that if
Speaker 1: you need to be reading a sign. There's also lots
Speaker 1: of other traffic going on, everything from motorbikes to buses
Speaker 1: to billionaires going to play ma jong in a Bentley
Speaker 1: h two people darting in and out of traffic with stuff,
Speaker 1: either moving things or just commuting home or whatever it
Speaker 1: might be. So yeah, it's it's very complicated. I think
Speaker 1: about it's as it's like all edge cases all the
Speaker 1: way down. And it's funny when you said about San
Speaker 1: Francisco is good because as an engineer and Chris Rmson,
Speaker 1: who was part of the early days of Google self
Speaker 1: driving auto prob him and he said, yeah, we were
Speaker 1: doing this in pongo Alto or sorry, in Mountain View rather,
Speaker 1: which is a lower context environment, we might say. And
Speaker 1: he said, but one of the things that our cars
Speaker 1: encountered was a woman in a wheelchair chasing ducks across
Speaker 1: the street with a broom, And he said, no, obviously,
Speaker 1: this isn't something that we've programmed in. We didn't say
Speaker 1: let's sit down and have that Nadie in the wheelchair
Speaker 1: with the broom chasing ducks module. So that doesn't go
Speaker 1: in there. But you need to train train the machine
Speaker 1: on how to respond to it. But I feel like
Speaker 1: Hong Kong in particular would be nothing but that like
Speaker 1: it would it would be. It would be that pretty
Speaker 1: much straight through. And that's probably milder version than let's
Speaker 1: say Jakarta traffic or Negos or Bangkok or Manila. So
Speaker 1: I think about it's like, that's why this is so complicated,
Speaker 1: self driving self driving service automobiles to transfer people around.
Speaker 1: You already see them in early phases in retirement communities
Speaker 1: in the United States, where they make perfect sense. They're
Speaker 1: essentially an automation of a job that already exists, which
Speaker 1: is getting an electric golf cart and go from bingo
Speaker 1: to bed. But Hong Kong will be replacing this full
Speaker 1: stack of very rich and dense signals and possibilities and
Speaker 1: scenarios to be played through Sonat's got to jump off
Speaker 1: for a flight because he's just visiting us right now.
Speaker 1: So I'm going to catch him before he leaves, and
Speaker 1: I'm gonna ask him, as somebody who's trying to create
Speaker 1: a successful podcast, how do you create a successful storyboard
Speaker 1: of original ideas every single week? I can ask this
Speaker 1: question by our more recently arrived colleagues pretty much every week,
Speaker 1: and I say, well, you know, it takes. When they asked,
Speaker 1: usually how long has it taken? I said, well, it takes,
Speaker 1: you know, four or five hours plus a decade. Uh,
Speaker 1: you know, it's the it's the decade part of sort
Speaker 1: of a fairly rich repertory of stuff that you've seen before,
Speaker 1: and essentially doing an interrogation when you see something new,
Speaker 1: is this different enough? Is this different enough to be meaningful?
Speaker 1: Is it also different in a way that's useful? And
Speaker 1: let me see what I can do with it. I
Speaker 1: actually find it very helpful to have the imperative of
Speaker 1: doing something every week, right, And I actually I think
Speaker 1: that that's distinct in a lot of ways from the
Speaker 1: general research process. I have to do something, so that
Speaker 1: means find something that's interesting. A lot of times I
Speaker 1: have a sort of a bad catalog of data sets
Speaker 1: that I know will be useful and they're best when
Speaker 1: they're scarce, their best when they're not things that people
Speaker 1: have seen. This thing I mentioned from the Bank of
Speaker 1: England Credential Regulation Authority, I sincerely doubt that anyone outside
Speaker 1: of the world of insurance or other banking regulators or
Speaker 1: reporters on banking regulation would have looked at and even
Speaker 1: then I don't know that they would have taken the
Speaker 1: angle on it than I did. So the storyboarding for
Speaker 1: me is try to figure out what's first of all,
Speaker 1: what is new, and then is it new enough to
Speaker 1: be useful? Uh? And is it useful enough to be
Speaker 1: sort of durable? When worth telling a story about the
Speaker 1: definition of a patentable good in the United States, something
Speaker 1: for which you can get a patent is it has
Speaker 1: to be novel and non obvious. And I think of
Speaker 1: that as like essentially a pretty good, pretty good background.
Speaker 1: And I don't say that just because Mark and I
Speaker 1: used to work right down the street from the PTO
Speaker 1: of the Trade Office, but no, but that that that's
Speaker 1: actually it for me. And sometimes I have, like I
Speaker 1: do right now, about four or five of them not
Speaker 1: quite in the can, as they say, but more or
Speaker 1: less ready to go. Things that I can load up
Speaker 1: and write while i'm while I'm traveling. Sometimes it's a
Speaker 1: Wednesday night and I have no idea what I'm gonna
Speaker 1: be doing by Thursday morning. But that's that's that's common.
Speaker 1: So you're writing one in the plane today this time,
Speaker 1: I already wrote it, but I'll probably be editing. I'll
Speaker 1: be I'll be editing it. So I'm I'm editing something
Speaker 1: that that That originated from driving to the pool with
Speaker 1: my daughter through one of the worst intersections in the
Speaker 1: world in Washington, d C. Which is the original boundary
Speaker 1: line of Lanfrance City Plan, where it intersects with the
Speaker 1: Windy's and New York Avenue Florida Avenue. A bunch of
Speaker 1: the streets. Mark knows this one. It's dire, it's really awful,
Speaker 1: And there was a there was a man driving a
Speaker 1: convertible stuck in the middle of this traffic, and I
Speaker 1: was wondering, what's a convertible these days? And I thought
Speaker 1: that that's like, this looks really unpleasant, and so that
Speaker 1: was like, hmm, instead of just like leaving that there,
Speaker 1: actually then went into the research was like, how how
Speaker 1: are convertible sales doing in the US? It turns out
Speaker 1: rather poorly. They're shrinking as a percentage of total sales.
Speaker 1: I mean they were never like a lot of total
Speaker 1: sales of cars, but down from just under a percent
Speaker 1: of sales a few years ago to about half a
Speaker 1: percent right now. It's similar diminution in the number of
Speaker 1: models of cars that are being sold. And at the
Speaker 1: same time, ftuvs are are pretty much everything. And then
Speaker 1: the real hook for this was that Volkswagen announced, uh
Speaker 1: two days ago that for the first time since nineteen
Speaker 1: sixty six, it will not be selling station wagons in
Speaker 1: the United States. It just won't be selling them. So
Speaker 1: it's stop the Beetle nen station. The Beetle's gone, the
Speaker 1: the the golf sports wagon, and the all track are gone.
Speaker 1: So the base model b W is gonna be a
Speaker 1: t one. It'll be a tigue. And in fact, they
Speaker 1: it says in the press release it's an SUV world now.
Speaker 1: It sure is right, And I thought, okay, great, but
Speaker 1: you know, that just sort of confirms a prior so
Speaker 1: that we already know that. So I thought about it
Speaker 1: a little bit differently as well. There's all kinds of
Speaker 1: other things that people are now imputing to the car,
Speaker 1: including this fascinating study from Japan by NTT DoCoMo, which
Speaker 1: runs a car sharing service, that people in Japan, because
Speaker 1: cars are actually quite cheap to rent by the hour,
Speaker 1: are renting them to do things like take a nap,
Speaker 1: or practice their English, or change into a Halloween costume,
Speaker 1: or practice a speech or a talk or something like that.
Speaker 1: And this study ends with a great line sid like,
Speaker 1: the car is a private space. And I thought about
Speaker 1: that more. It's like, well, an suv is a private car,
Speaker 1: but it's not a great private space. And in the future,
Speaker 1: if these cars are going to be driving themselves, let's
Speaker 1: say twenty years from now, I don't know that the
Speaker 1: form factor of an suv is what you want. You
Speaker 1: probably want something more like giving room or the original
Speaker 1: Volkswagen camper van. Do you think that's why we see
Speaker 1: all those, you know, the prototype self driving cars. I do. Yeah,
Speaker 1: they yeah, they're they're boxing because you they have another
Speaker 1: element in them which they may not be owned by
Speaker 1: the drivers, so you're less attached to the form factor.
Speaker 1: But it also reminds me of a number of my
Speaker 1: friends in the United States, who mentioned with some chagrin
Speaker 1: at first and then amazement, I bought a Christco Pacifica.
Speaker 1: I bought a real many them. And though like it's
Speaker 1: kind of great like that, actually like the sound system
Speaker 1: is good, I can pack a lot of children in here.
Speaker 1: Like it's not the it's definitely not the most awesome car.
Speaker 1: But I'm a boring named dad anyways. So so there
Speaker 1: you go. For those that want to do more than
Speaker 1: just listen to your interesting stories and would like to
Speaker 1: read them, which actually takes substantially less time investment and
Speaker 1: listening to a podcast it does. Where can people subscribe
Speaker 1: to receive your goodness once a week? So on the
Speaker 1: web you can go to Bloomberg Opinion and there will
Speaker 1: be a list of contributors that I'm there. Go to
Speaker 1: any one of those stories, click on it, and at
Speaker 1: the bottom there will be a link to subscribe, and
Speaker 1: that way you can get it just through whatever email
Speaker 1: and address you would like. And then if you are
Speaker 1: a Bloomberg Professional Service user, then you can go on
Speaker 1: the terminal and I which is the news code, and
Speaker 1: I my surname the U L L A R D.
Speaker 1: You'll see all the stuff I write and then you
Speaker 1: can click on a subscribe button. You may occasionally get
Speaker 1: an update about the President of the St. Louis Federal Reserve,
Speaker 1: James Bullard, in there. You can ignore that that's not me.
Speaker 1: I do find myself all of the time looking at headline.
Speaker 1: It says Bullard says two rate cuts might be within range,
Speaker 1: And I think I don't remember saying that, but I
Speaker 1: agree with that. Yeah, I'm not saying it's wrong. I'm
Speaker 1: just saying I don't remember thinking that. Nat. Thank you
Speaker 1: very much for joining us today. Like folks, bloombergin e
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