1 October 2017

In this week’s episode, we talk to the New York Times Best-Selling author Martin Ford.  Martin is a futurist that writes about Artificial Intelligence (AI) and robotics.  This episode specifically covers the topics found in Martin’s book, Rise of the Robots.  This book was named Business Book of the year by McKinsey and also Financial Times.

During the interview, the Martin talks about various impacts of Artificial Intelligence.  He helps the listen distinguish between real opportunities/concerns and hyperbole.  Whether people realize it or not, AI is going to have a huge impact on society and the economy in the coming decade.

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  • How much hype and reality is behind much of the artificial intelligence stories you hear today
  • If the US or China is better positioned for the new wave of artificial intelligence
  • How artificial intelligence will disrupt your career in the finance industry
  • If artificial intelligence has changed valuation techniques
  • Ask the investors: How do I diversify my ETF portfolio?


Disclaimer: The transcript that follows has been generated using artificial intelligence. We strive to be as accurate as possible, but minor errors and slightly off timestamps may be present due to platform differences.

Preston Pysh  0:02  

Hey, how’s everyone doing out there? So 16 episodes ago, we had a famous Silicon Valley author on our show who wrote the New York Times best-selling biography on Jeff Bezos and Uber. His name is Brad Stone, and while we were chatting with Brad, he made the comment that the next big story coming out of Silicon Valley was definitely going to be artificial intelligence. 

After hearing him briefly tell us some of the advantages of A.I. and how it is likely going to impact the future jobs and labor market, Stig and I got really curious and really wanted to try to understand everything about the technology a lot better. 

So long story short, we found the number one selling author on artificial intelligence, and we got him on today’s show. The author is Martin Ford, and he’s the author of the book, “The Rise of the Robots.” This was a New York Times bestseller, and we’re really excited to bring this interesting discussion to you today.

Stig Brodersen  0:54  

On and off the show, Preston and I had talked about who will emerge as the winner in the new world of artificial intelligence. Would it be the US or China or perhaps someone else? We think it will disrupt all industries, especially in the financial sector. Now, all of this is guesswork. So, we decided to invite Martin Ford in the podcast to share with all of us what is hype and what is reality.

Intro  1:21  

You are listening to The Investor’s Podcast, where we study the financial markets and read the books that influence self-made billionaires the most. We keep you informed and prepared for the unexpected.

Preston Pysh  1:41  

All right, so wonderful to have everybody with us. Stig and I are super excited about this episode because one of the things that we’ve been really fascinated with recently is artificial intelligence. And so, we reached out on Twitter and we said to all of our followers, what is the best book we can read on our artificial intelligence or who’s a person we can talk to on the show that knows a ton about this stuff. And we got a resounding response from everybody. And they said, you need to get Martin Ford on your show, and his book, “Rise of the Robots” is the book you need to read. 

So there’s a lot of books out there. So Stig and I immediately went in and plowed through this book. And we love this thing. We really like this book, because it starts off with this discussion about macroeconomics, and then it goes into the rise of the robots and artificial intelligence, deep learning all of this stuff, we’re going to be talking about in today’s show. Martin, thank you so much for taking time out of your busy day to join us tonight. 

Martin Ford  2:40  

Well, thanks a lot. It’s great to be here. 

Preston Pysh  2:42  

All right. So Martin, I see on the cover of the book [that] it was a business book of the year by McKinsey. I see that you have been a founder of your own software development firm for 25 years of experience in computer design and software development. So with that said, I understand a little bit of your background, but why did you go out, because writing a book is such a huge undertaking. What captured your attention that you felt like you needed to write an entire book about this subject?

Martin Ford  3:11  

Well, partly is just that I’ve been very close to this technology, obviously for a long time. So I’ve seen the kind of acceleration in computing power, Moore’s law, and so forth are very close quarters. But probably the real catalyst for me was that I was running my own software company, and I saw a very rapid transition in the kinds of jobs and a number of jobs there. I started a small software company that basically what it did is it made very specialized tools for Microsoft Windows. Now, when I started that company in the 1990s, software was shipped on CD ROMs, it was a tangible product. And so there was a lot of work there for people to actually put that in a box and then ship it to a customer and all of that. And of course, those types of jobs are virtually gone now. In fact, they disappeared quite rapidly. 

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So I saw that transition happen, and I think that that’s what got me thinking about it. And the conclusion I came to is that eventually this is going to scale across the whole economy. It’s not going to be limited to the areas where we see it now, which is things like software and music and things that are really vulnerable to being digitized, but actually could scale across everything as we have robots and A.I. come online. And so that kind of got me thinking about that potential big impact, and I wrote my first book on this topic back in 2009. And then eventually, that led to an opportunity to write this latest book, “Rise of the Robots”.

Preston Pysh  4:30  

So we kind of came across this because we were talking to Brad Stone, who’s a huge writer out there in Silicon Valley. And during our interview, Brad told us, he says, “The thing out here right now is artificial intelligence.” That’s the next big story. Have you seen this ramp up in the last couple of years? Do you feel like it’s really starting to hit its stride? Or do you think that there’s a lot of hype around this, and that it might be 10 years off? Or how are you feeling about it in general?

Martin Ford  4:59  

Both of those things are crude. There’s definitely a very real ramp up, but there also is a lot of hype. And so making sense of that is not so easy. And to some extent, it’s very unpredictable. But what I can tell you is that there definitely has been a big change in the environment surrounding artificial intelligence and the kind of focus that’s now on it. I mean, 20 years ago, A.I. would have been something that people in universities did, or maybe in government research labs. 

Now, it is something that is just absolutely central to the business models. So these enormously powerful and wealthy companies like Google and Facebook and Amazon, and so forth, and it’s really become the parameter upon which they compete. I mean, it’s not just something that’s important. It’s arguably the main thing that they are focused on. And that means that there’s going to be enormous amounts of progress that is driven not just by the natural progress of technology, but really is driven specifically by this competitive dynamic. 

We are going to expect astounding things in the future. So that’s not hype. There may be some element of hype associated with some of it, like you hear people about Elon Musk warning us about how the machines are going to take over someday. And so, I think that that may be a legitimate concern at some point in the relatively far future, but right now, I’d put it more in the category of hype. But no doubt, artificial intelligence and the progress we’re going to see in the near term is going to be totally transformative.

Preston Pysh  6:23  

Yeah, so in an effort to give people an appetizer of how crazy some of this stuff is getting. I was up in New York about a month ago. And at the end of one of the events we were doing up there, I was talking to two young gentlemen that came up and they immediately wanted to talk about artificial intelligence. And they started telling me this story, and I hadn’t read this in the news. But they started telling me this story about Facebook running some software to help assist with some of the code writing that they were doing. And I guess that that deep learning machine neural network that Facebook was employing, it started coding in its own language. Are you familiar with the story?

Martin Ford  7:02  

Yeah, what actually happened, it wasn’t really coding. It was a negotiation. They had set up a system to help negotiate prices. So you might think of this as a system that someday might replace buyers and corporations to people that negotiate prices. So that’s one focus of this. And, they didn’t specify specifically that the conversation had to remain in English. And so it kind of invented its own language. And, and that’s one area where you could point to some hype going on. I mean, the media got a hold of this story, and they thought, oh my god, the machines are inventing their own language, and they’re thinking about things that we can’t understand. And that’s not quite what’s going on. They simply set up two systems to communicate. And there’s no particular reason that they would do that in English unless we tell them to do that. So it’s not quite as dystopian and horrifying as it sounds. It’s a story that is in part, it is a demonstration of remarkable progress, and on the other hand, it’s an example of hype. So you get both of those things rolled into one as is often the case.

Preston Pysh  7:59  

So I love your balance. I’m just going to throw that out there. I love how balanced you are in how you’re presenting this material because for me, I was just hearing the one side of it that was pretty extreme like, it was writing its own code and they had to shut it down. At the same time what you’re talking about is mindblowing to think that we have machines that are that intelligent to start transitioning into another more efficient language to be doing price negotiation. This stuff is fascinating. Absolutely fascinating. So I’m going to throw it over to Stig for his first question.

Stig Brodersen  8:32  

So Martin, as Preston mentioned before, one of the things I’ve really liked about the book was your take on macroeconomics and also the new economy of artificial intelligence. Because the US has largely been driven by consumption. I think it’s around 70% of GDP that’s consumption in the US, which is really high, even for a developed country. Now, I’m curious to hear what your thoughts are on how the US economy is positioned, now that the so-called positive feedback loop is broken. 

The positive feedback loop is that you have workers that are getting more productive, they’re getting higher wages, they can consume more, and then create a demand for more in society. I’m especially curious because how is this compared to China that might not realize mass consumption? I think it’s approximately half in the 30s as one of the growth drivers of the economy. Is the US positioned bad compared to China, in your opinion?

Martin Ford  9:31  

Okay. Well, as you say, this is a really important issue that I’ve really focused on a lot. There has been a tight relationship between technological progress and economic growth. I mean, these two things go together, and everyone sort of agrees on that. It’s generally true. I mean, technology has always made us better off and economists will talk about that in terms of productivity increases, and they’ll talk about how as productivity increases, countries become more wealthy. And in fact, increasing productivity is generally thought to be sort of the main measure of that. 

But if you look at actually a graph of wages and productivity in the United States, what you see is that they’ve kind of decoupled and that wages have basically flattened out, while productivity has continued to climb. And so what was once true in that sort of Golden Age, following World War II, when progress growth, productivity increases, and people had more money to spend, and then they spent that on buying cars and washing machines and all this stuff being produced by the economy, and that just created this virtuous cycle that drove everything to greater and greater prosperity for everyone, that kind of broken down. 

And so what you now see is a much smaller group of people that are thriving, and everyone else is to some extent being left behind. One of the basic issues that I really focused on here is that in order to have a thriving economy, you’ve got to have people. In fact, you’ve got to have huge numbers of people that have both the income and the confidence to go out and buy all the things that are being produced, whether that’s products or service. And we are I think entering an age when that’s becoming problematic. I mean, think in terms of any mass market product where there’s automobiles or smartphones or financial services. You can’t take just a few wealthy people and have them be able to drive demand in that whole industry. 

Think in terms of Bill Gates. Bill Gates in theory has got an infinite amount of purchasing power but he’s not going to go out and buy 1,000 cars or 1,000 smartphones. He’s not going to go to 1,000 restaurants and sit down and eat dinner in one night, right? So when you take money or income from 1,000 people and instead concentrate that into the hands of one very wealthy person, you’re clearly taking unit demand out of the economy. I do think that that is at least in par, the reason that we face the situation that we’re now in both in the US and in other advanced countries where you see very low rates of economic growth. 

I mean, it’s pretty stagnant growth in Europe. It’s arguably been almost zero, right? And yet, you see this scenario where even though we’ve got a relatively low unemployment rate, we’ve got interest rates at zero, we’ve got no inflation, something strange is going on relative to historical norms. I do think that it is probably in part, this inequality and the impact that that is having on consumer demand. 

Now, the second thing you asked was about China, and actually China is going to face exactly the same scenario. As you pointed out, consumption is a lot less in their economy. Their economy is largely driven by infrastructure, investment and exports and less by domestic consumption. But everyone agrees and has agreed that they need to fix that. They need to rebalance that. It’s not sustainable to just have an economy that’s forever driven by, and you’ve heard a lot of stories out of China about how already some of that investment is becoming less efficient, right? You heard stories about ghost cities and all that. So I think that the government understands that they need to rebalance it toward consumption. But the question is, how are we going to do that in the face of the robotic revolution?

Stig Brodersen  12:59  

Yeah. And it’s really interesting point that you have here about China because one of the things that are already a concern in China, even though that obviously, they would make a lot less per hour than for instance than would in the States. I mean, it’s already an expensive country, compared to say Vietnam to manufacturing. I guess the middle class boom that people have been talking about and what we see right now in China that’s driven largely by manufacturing. Do you think that will just come to a halt? Because of, if not artificial intelligence, then more technology-driven economy that is not as good for a very labor intensive workforce that they have in China. Do you see that as a huge problem for not just Chinese growth, but thereby also global growth?

Martin Ford  13:43  

It’s a question. I don’t really know the answer to it. But what we do know for sure is that if you look at the advanced countries in the world, they all became advanced or industrialized, according to a sort of a standard path, which is what it built lots and lots of factories. It created huge numbers of manufacturing jobs for relatively unskilled workers. Wages increased over time. Those workers became more wealthy. And then after they reached some certain point where they became wealthy enough, then they transitioned to service economy. 

And now, in countries like the United States and most European countries and Japan, now most people work in the service sector, even no career to varying extents. Manufacturing may still be very important in those countries. It’s not where vast numbers of people work anymore. The question is, the factories are going to automate it at a much more rapid pace, and that’s going to happen before the country is really established that vast middle class that has happened in other countries like the US and Japan and South Korea. 

And the other issue is that even as they try to make that transition to the service sector, even the jobs in the service sector are going to begin to automate. I mean, that’s what’s really different now. And that’s what’s going to have the biggest impact in countries like the US is the robots making hamburgers and it’s going to be online banking, retail automation, and all kinds of things coming to these jobs as well, which would normally be the place where these workers would move codes. So, China is coming relatively late, and then they’re even bigger questions for other countries. I mean, maybe China is just going to pull it off. China might be the last country in the world to really follow this standard path to industrialization.

Stig Brodersen  15:21  

And how about a country like India that has really tried to skip those steps you’re talking about, like how industrialized countries typically done so with like with agricultural reforms first, then manufacturing, then the service sector? It kind of seems like India has tried to go to the very end of setting up an IT industry which sounds really good and it sounds like it’s the way to go. If you really dig into the numbers, it’s actually a very, very small contribution to the economy. Would you agree with that assessment? Or do you think that this new IT wave that you see in India is actually able to pull India into more sustainable economic growth?

Martin Ford  15:55  

No, I think you’re right to worry about India. There are two things here. First of all, as you say, India made this decision to really emphasize the IT sector and outsourcing and so forth. And that’s been terrific for a relatively small fraction of the population that can participate in that. But it’s a pretty high hurdle in terms of education and skill being able to really participate in that. So, the impact there has not been anywhere near as broad based as manufacturing would be in terms of helping much broader range of people in the country. I think manufacturing in India, they are trying to emphasize that more but it’s going to face the same struggles with automation. 

But the other big thing that’s happening there is that the IT sector, and in particular, the outsourcing jobs are also subject to the same problems. I mean, artificial intelligence is encroaching on a lot of those offshoring jobs. That’s already happening. We already have cases where at one point, you would have caught up on the phone, and you have talked to someone in India. 

Now, you talk to a digital voice system that can answer your questions without dealing with a human being at all. And that’s going to get better and better, perhaps dramatically. So, you can look at technology like IBM’s Watson, for example, and its ability to handle natural language processing. It’s pretty obvious that there’s going to be a big impact there. 

So I do think it’s a big challenge for India, both in terms of the industry that has been doing well and offshoring, and also in terms of doing something to bring all those other people into the loop that haven’t been able to participate in that offshoring industry. So I think it’s an enormous challenge, really, for every country in the world.

Preston Pysh  17:29  

So Martin, in our audience, we have a lot of younger listeners that are in college. Stig and I get a lot of emails when we’re out doing live events. We have a lot of college students that are especially majoring in finance, come up and talk to us, and one of the questions that we get all the time is, what should I go into? Should I go into this form of banking or should I do fixed income? 

They always want to have that guidance of what should I do to set myself up for 10 years from now that I’d be in a key position to advance my career? And one of the things that I’ve been saying to people more recently, and I’m really curious to hear your thoughts on this, is I tell people, think about how artificial intelligence might impact what job you’re working at in the next 10 years. What’s that going to look like? How is artificial intelligence going to impact that landscape moving forward? 

And so, my question to you is: Where do you see things specifically in the finance sector 10 years from now? Do you see this deep machine learning having a huge impact? Because that’s personally how I see it. I’m just curious if a person like yourself with all your experience in this would see it the same way?

Martin Ford  18:36  

Yeah, I would definitely see a big impact. In fact, finance is probably one of the areas where we’re likely to see the most dramatic impact. In fact, we have already. There was a study done a few years ago by the Hackett group that showed that in the corporate finance department in corporations, and that would be jobs like accounting. There’s actually been about a 40% drop in headcount in that department in the largest US corporations relative to the revenue of the corporations. So a lot of those jobs are already disappearing. 

Right now at least, and for the foreseeable future, we’re primarily talking about more routine repetitive type jobs. The kind of thing where you do the same type of thing again and again, but that is clearly extending into even more skilled areas. 

For example, I know that Goldman Sachs recently bought a startup company that allows them to automate a lot of the work that’s done by their investment banking analysts. I mean, these are people that go to Harvard and Yale and schools like this, and they hire undergraduates to come work on Wall Street for a couple of years, work 100 hours a week or whatever, sitting in front of a spreadsheet. It was a highly sought after jobs. And yet, even those kinds of jobs are going to be increasingly subject to being automated. 

If the question you want to ask is what advice you would give to people that maybe want to work in finance in the future, I would say that it’s kind of the same advice I give anywhere, which is, you really want to make sure you’re avoiding doing things that are on some level, routine and fundamentally predictable. 

Probably the best ways to avoid that are to do things that are maybe genuinely creative, where you’re really generating new ideas and that I’m not sure how many of those jobs are in finance, probably not a whole lot. And then, the other thing would be jobs that really involve building deep relationships with other people, business relationships, and so forth. So, if you’ve got the kind of finance job where you’re really working with clients on a very deep level, then that may be relatively safe. 

One problem in the field of finance is that those jobs may be the higher level jobs. And the entry level jobs may tend to be the more routine predictable things. So, I think that’s one danger that we face is a lot of the more entry level jobs are going to be particularly susceptible to this.

Preston Pysh  20:44  

So whenever I think about routines, and kind of coming up with a checklist. We talk about this on our show all the time: come up with your investment checklist. Go through that checklist, [and] find the investments that make the most sense that you understand. 

So much of this, I watched a couple of videos on DeepMind, which is Google’s A.I., just mind blowing stuff that they’re doing. After watching that, I looked at the hedge fund industry and how so many of these people with these brand names that capture billions of dollars in investments from people to manage their money. 

And I’m thinking, if you take this DeepMind algorithm that they’ve developed, and you had it study the hundred best managers of all time and look at their trade decisions, and the similarities between those trade decisions, this thing would eat that stuff for lunch, right?

Martin Ford  21:37  

It’s quite possible. Look at what DeepMind did with this game of Go. It’s hugely popular in Asia. Its orders of magnitude more complex than chess. It’s a strategic game where as you play the game, there’s basically an infinite number of moves you can make at any point. And if you talk to the best Go players in the world, they often can’t really articulate exactly what they’re doing. 

They played a game. They’ll say, “Well, I had a feeling that I should make a particular move.” And so it really seems something that is fundamentally human. It’s something that only a person should be able to play this game at a world championship level, but DeepMind built a system that not only taught itself to play this game, but then became effectively superhuman at it. Now, you can make the same kind of arguments, right? If you find someone like Warren Buffett, for example, what is special about him as a human being. So it’s entirely possible.

Preston Pysh  22:26  

So I was so fascinated with DeepMind, which is Google’s A.I. Are there other ones out there that you’re more impressed with? Or would you say that DeepMind is the pinnacle of A.I. at this point out in the Valley?

Martin Ford  22:38  

I think it’s probably the most dramatic, and maybe the best example of it. There definitely is huge amounts of competition. Again, as I mentioned earlier, the thing that’s really driving this is that all these companies, Facebook, Google, Amazon, Chinese companies like Baidu are making enormous investments in this and are doing really remarkable things. Facebook has got a very highly capable A.I lab in New York City. 

So, we really don’t know exactly how fast this progress is going to unfold. But definitely, if you had to point to one particular company that is really just the poster child for this, it would probably be DeepMind. They’re doing amazing stuff and Demis Hassabis, the guy that runs that is an incredibly smart guy for sure. They’re not a bad one to bet on in terms of where the really, the most exciting developments are going to continue to emerge.

Stig Brodersen  23:26  

So Martin, I would really like to talk about how the educational system might change because it seems to me that it is inevitable that with the rise of artificial intelligence, big changes are going to happen. And I would just like to tell a story that happened to me not too long ago. I was meeting up with this friend here in Korea, and he was talking about how his kid was learning a new language. I think his daughter was six years old, and she was taught English which is very common in Korea. Like you will learn Korean then you’ll also be taught English, but she was also learning to program. And that was actually to his point, that yes, of course, we got to teach our kids to speak English, but she needs to learn the most important language, which would be a program. I think it was HTML. But that was kind of like his vision for his daughter because of artificial intelligence. That, English, that’s fine. It’s really HTML, and then we move on to more difficult programming languages. I’m curious to hear if you see programming to be a central skill taught in schools, not just here, I guess, but really across the globe?

Martin Ford  24:35  

Well, there are two sides to that. On one hand, I’m not opposed to that. I think that’s fine. If schools want to do that. I’ve heard similar stories out of New Zealand, I think. They’re thinking of teaching older kids to program. I think that’s great if they want to do it, but I would really caution people to understand that that is not a panacea for this. I mean, just learning how to program a computer is not going to be a defense against this. In fact, there are enormous efforts being put into automating computer programming. And of course, it’s already substantially subject to offshoring, right? 

We talked about offshoring in India later. That’s what a lot of those people are doing– offshore programming, and they’re doing it in wages that are very low relative to advanced countries. So, just teaching everyone to program a computer is not going to solve our problems here. 

There’s not going to be an infinite number of computer programming jobs in the future. In fact, I think that what’s going to happen across many, many professions, maybe virtually, all professions is that they’re going to see a kind of a superstar or winner take all effect, which means that if you are someone that is extraordinarily good at that particular profession, then you’ll do great. You’ll do fantastically, but if you’re just kind of a run of the mill person with average routine skills, then you’re really going to be in danger of being left behind. 

And that’s going to be true of computer programming. It’s going to be true of accounting and law. And that’s really the problem that we’re going to run into is that we’re just going to have this drive toward inequality as technology is increasingly able to do the routine run of the mill repetitive kinds of things where you come to work, and you do the same kinds of things again, and again, whether it’s going to be artificial intelligence, software automation, or robot technology in some form is going to take over more and more of that. 

And the opportunities that are going to be left for people are going to be those that are really, genuinely creative, or really at the top, that really require top of the line skills. The problem is that they’re not going to be enough of those jobs. And so we’re going to have to really think outside the box in terms of how we solve that problem.

Stig Brodersen  26:41  

So my next question would be about valuations and how to look at valuations and wealth in the future. One neat example is that back in 2007, YouTube was purchased by Google for $1.65 billion. You have this very interesting way of looking at what is that per employee. So for YouTube, that would be $25 million. And then you make a comparison of WhatsApp, 7 years later, that was acquired by Facebook for $19 billion. And there weren’t that many people. It actually turned out to be $345 million per employee that they bought it for. It’s $25 million in 2007 and then $345 in 2014. 

Now, as listeners of this show knows, there are definitely a lot more in terms of valuation metrics than just the number of employees. But I couldn’t help think of whenever I saw these stats was, do you think that the reason for this difference is because of the technological ownership? Is that kind of like a new measure of wealth in the future, compared to, I guess, more traditional measures as call it, the price to sales or price to earnings or whatnot? Do we need to rethink how we value things?

Martin Ford  28:01  

I think there’s an argument there. The point I was making in the book was that, basically, the value is in the technology and less in the people, right? And that’s why you have such a small number of people or maybe extraordinary people. And really, the value is in all of this technology. 

The other important point here is also largely about platforms. I mean, when you’ve got a start up company to start some kind of platform where people are attracted to it, and it looks like it’s going to be the leading platform in the future, then that has just extraordinary wealth. I mean, you look at YouTube and Google’s acquisition of it. I mean, in terms of a platform for videos, there’s nothing that even comes close to competing with YouTube, right? 

So there’s enormous value there. It’s not just about the technology that can render videos, but it’s about that platform and the interconnections between all the people that are on it. And so, you’ve got this just extraordinary, I think it’s kind of a first mover advantage where someone builds a system that’s really going to attract huge numbers of people and build that kind of a powerful platform that has just extraordinary value. I think that definitely needs to be taken into account in terms of how you value things.

Stig Brodersen  29:10  

So in that case, is it no longer a question about just looking at how much money can this generate? Is there like a second layer to this way of thinking?

Martin Ford  29:19  

Well, technically, the way you value a company is you look at the future cash flows. They’re going to come into that company, right? So, you can still look at it in that way, you just have to understand how something like a platform is going to be leveraged into those cash flows. And that’s, you look at something like Facebook has got such an extraordinary valuation because there’s this assumption that all of that control of massive amounts of data is at some point going to be converted into cash flows, right? I guess that’s what justifies that value. The basic principle is not range but you need to be more creative in terms of thinking about how those future cash flows are going to be generated.

Preston Pysh  29:26  

So Martin, I got a question for you. When we think about what’s going to play out in the next 10 years, what do you think is going to be the most surprising thing to people? Is it driverless cars? Like, what do you think is going to really make a person say, wow, I never saw that coming. And it’s just going to hit somebody from out of left field.

Martin Ford  30:19  

It’s hard to say that with any precision. You could say self-driving cars, but I mean, self-driving cars, I think people have already got fairly high expectations. To some extent, they may underperform some of the hype that’s out there. I don’t know that self driving cars are really going to be practical and on the road all over the place in 10 years. It might take 15 or 20 years, but I do think it’s going to be inevitable. A surprise might be in driverless trucks. Trucks might actually be a better candidate than cars for driverless technology, and the impact on employment could be that much more dramatic, so that might be one area. 

I also think that we’re going to see breakthroughs in areas, roughly comparable to what we saw with DeepMind and the game of Go, perhaps in things that are more immediate to us. I mean, we’ve seen a lot of examples of artificial intelligence playing games, chess, Go, Jeopardy and so forth. I do think that within 10 years, you’re going to see an impact in much more practical areas that you may find yourself increasingly having conversations with machines, and maybe not even knowing for sure if it’s a machine or if it’s a person. 

I think automation in retail is an area where we’re going to probably come in close juxtaposition with it. Amazon warehouses are another thing. Right now, what we’re seeing is that Amazon is growing rapidly, and it is hiring lots of people who are working in these warehouses. Those may not be the most desirable jobs, but at least they are jobs. 

I worried that that could change at some point in the relatively near future, maybe five years or so because Amazon is putting a lot of effort into building robots that can do what the people are now doing, which is things that really require hand-eye coordination, dexterity, picking an item off the shelf and then putting it into a box and so forth. They’re working on robots to do that. And that’s going to get better and better. 

So, I think we will definitely see disruptive things within the next 5 to 10 years. I don’t want to really go out on a limb and predict exactly what those things will be, but they definitely will take place. 

Preston Pysh  32:18  


Stig Brodersen  32:20  

Yeah, very fascinating. And another sector that we also briefly touched upon before that might be disruptive is the financial industry, especially the stock market. I guess I’m curious to see that you have this thesis that academics talk about the so-called efficient market hypothesis where everything is priced the way it’s supposed to because you can capture all the relevant information. 

How do you see this in the future, call it, in the next 5 or 10 years? Whenever you start having these machines that might be able to react to news but not really, really fast, do you see that the arbitrage opportunities might just close immediately, and thereby also the volatility in the market might become smaller and smaller?

Martin Ford  33:04  

That’s one possible outcome, certainly. It’s interesting that there is this theory in economics that basically says people are rational. You talk about the rational man or whatever. And all economists know them in terms of real human beings, that’s basically a myth. It’s kind of an approximation. And that’s what leads to efficient market theory. 

But people that have researched into artificial intelligence have actually embraced that theory to some extent, say, hey, you know what? When we have A.I., it’s really going to be that way. We don’t know if we’re really going to have these rational agents. 

So if you think in those terms, yes, maybe. Maybe you’re going to have machines that are able to almost instantly assimilate news, trade on that news, and that’s going to cause all the arbitrage opportunities to evaporate. But then on the other side of that, you have things like the flash crash that happened a few years ago, and people pointed to algorithmic trading as a cause of that. 

So you’ve also got these algorithms that do things that are unpredictable that maybe because they’re so smart, we’ll all make basically the same decision at the same time, and they’ll all sell at once, and so forth, then maybe that makes things more unstable. So, I think that we simply don’t know the answer to how that’s going to fall out. But that’s definitely a possibility.

Preston Pysh  34:17  

So Martin, I got the last question for you. One of the things that we really try to focus on is if we find somebody who’s really smart, we want to ask them, who do they admire, who do they look up to, so that we can then study that person. 

You had mentioned Demis Hassabis, the founder of Google’s DeepMind. I know I’ve watched some videos on him and it’s just mindblowing how intelligent this person is. Is there anybody else that you would identify and say, “Hey, if you’re not following this person on Twitter or trying to read anything that this person writes, you’re crazy because they’re doing huge things in A.I. or machine learning or whatever.” Who would that person be that you would identify?

Martin Ford  34:57  

Another really brilliant guy is Andrew Ng, who just left Baidu. And he’s actually now starting a company or an organization to teach people artificial intelligence. That’s Andrew Ng, spelled N-G. He’s one of the handful of really famous artificial intelligence researchers out there, and I would definitely follow him, especially if you’re interested in A.I., and maybe learning more about it because he’s actually putting together a platform where you can learn more about it. Maybe even if you’re someone who’s in college, you could consider that as a career, maybe working in A.I. So that’s incredibly important.

Preston Pysh  35:32  

Martin, we can’t thank you enough for coming on the show. Your book was absolutely fantastic. I thoroughly enjoyed reading this. It helped me learn so much about this field and everything that’s coming out right now. The name of the book is, “Rise of the Robots”, and we’ll have a link for that in our show notes. 

Martin, if anyone from our audience wants to learn more about you or research anything else, how can they find out more about you?

Martin Ford  35:56  

Well, I’m on Twitter @mfordfuture. Usually, I try to tweet everyday and place a couple of links that are relevant to this. Things about robots and A.I. I’ve got a website, also mfordfuture.com that you can find. And I’ve got an earlier book on Amazon called, “The Lights in the Tunnel”. That was the first book I wrote back in 2009. It takes on basically the same basic subject matter. It was written a while ago, but it’s also, I think, a book that might be of interest to you if you’re really interested in delving into this topic.

Preston Pysh  36:28  

Well, Martin, thank you so much for coming on the show, and we really appreciate your time.

Martin Ford  36:33  

Thanks a lot for having me.

Preston Pysh  36:35  

All right. So here at The Investor’s Podcast, we’d like to play some questions from our audience. We don’t do this nearly as much as we would like to, but today, we’re going to go ahead and do it. And our question today comes from Martin. So here goes Martin’s question.

Martin 36:48  

Hi, Preston and Stig. This is Martin here, listening from Galway, Ireland. I came across your show earlier this year. I’ve listened back to every episode since, and I really look forward to your new episodes coming out every week. I’ve heard you answer multiple times the question of what should a beginner investor do with $10,000 to $20,000, and your answer is usually for the passive investor to go for an ETF (exchange-traded fund). My question is about diversification and ETFs. Considering that ETFs are already a basket of stocks, can a beginner investor consider this diversification or would you recommend buying a few different ETFs in different industries or markets? Thanks again for all your help. I’ve learned a lot from your website and your YouTube videos, and I look forward to hearing your reply.

Preston Pysh  37:34  

All right, Martin, loved the question here. I’m sure there’s a lot of people in the audience that have a very similar question as you. Stig is going to take it away and start this one off.

Stig Brodersen  37:43  

So Martin, I really like your question and the way you think about diversification. So what you’re saying is that you might not have as much time as you want to, or perhaps not the same interest in investing but still you would like to invest, and you would like not to take too many chances. What people usually think of, whenever they have that type of mindset is that they would buy a market ETF. It makes a lot of sense because you would buy, for instance, the S&P 500. And then you will have 500 companies that will give you some sort of diversification. 

Now, we specifically talk about whether or not you should buy a market ETF or you should buy for the specific industries. I just wanted to point out then, for instance, if you bought the S&P 500, you wouldn’t necessarily need to buy, call it, a financial ETF because if you buy the S&P 500, you actually have almost 14% in financial stocks already. In a similar number for healthcare industries, that’s around 10%. So you’re already diversified. 

Now, if you’re talking about you to diversify more, I think it’s a good question. I mean, more than 500 stocks, probably not. You don’t add a lot of values doing that. You might consider diversifying outside of US if you think that would add value. I think to some extent it does, at least empirically. 

It does make sense do that from a diversification point of view. But one thing I just want to highlight, and I think that is really, really important is that just because you’re diversified, doesn’t mean that you don’t encounter risk. So for instance, if you buy into the American stock market right now. Currently, you can expect a, call it, 3% return, and you might have a 40% or 50% downside. So, if all the assets are just overpriced, regardless of how many assets you have, it’s not necessarily a good investment.

Preston Pysh  39:39  

I really like this question because you’re looking at how can you diversify into other ETFs that might be more advantageous moving forward. So, the way I look at this, and I agree with everything that Stig said, I think that investing in the market right now in the summer of 2017, probably isn’t one of the best decisions if you’re going after an equity-based ETF. Simply because I think it’s very highly priced in general, when I’m speaking in general here. 

Whenever I think about when I will enter and take a large equity position into the market, when that time comes, I’m thinking about industries that I think have a lot of promise moving forward. So let me give you an example of what one of those might be. 

I think robotics, and I think artificial intelligence is going to be huge, absolutely massive moving into the next 10 years. So there’s an ETF out there that focuses on robotics, and this automation type stuff, and here’s a ticker for you. It’s called, ROBO. And the expense ratio on this is a little higher than I typically like, which is it’s a .95% expense ratio. 

You get into a lot of the ones by BlackRock and some of the large like a Vanguard, you can get a very low expense ratio down to like a .3 or even lower. You can see some. So the expense ratio on this one’s a little high but you are getting something that I think has a lot of promise moving into the next 10 years.

That’s how I like to buy ETFs, if I’m going to do something that’s industry focused, I’m thinking what is the next big thing that’s going to really do well in the coming 10 years. So that’s my recommendation, kind of combining what Stig already said with maybe some of those thoughts. 

All right, Martin. So we have a paid course on our TIP Academy website that teaches somebody all about ETFs and ETF investing. We’re going to give you that course 100% for free, just for calling in and leaving your question. We really appreciate that, and we hope you get a lot of value out of the course. And for anybody else that’s interested in looking at the course go to TIP Academy, you can see it there. 

Alright, so if you want to get your question played, like our guests here, just go to asktheinvestors.com. And if you go to asktheinvestors.com, you will see there’s a little recorder there. You just hit record and you can ask your question, and then it goes right into our queue, and if we select it and played it on the show, you get access to one of our courses.

Stig Brodersen  41:56  

Alright guys, that was all that Preston and I have for this week’s episode of The Investor’s Podcast. We’ll see each other again next week. 

Outro  42:03  

Thanks for listening to TIP. To access the show notes, courses or forums, go to theinvestorspodcast.com. To get your questions played on the show, go to asktheinvestors.com and win a free subscription to any of our courses on TIP Academy. This show is for entertainment purposes only. Before making investment decisions, consult a professional. This show is copyrighted by the TIP Network. Written permission must be granted before syndication or rebroadcasting.


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