Voices in AI – Episode 28: A Conversation with Mark Stevenson

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In this episode, Byron and Mark discuss the future of jobs, energy and more.
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Byron Reese: This is “Voices in AI,” brought to you by Gigaom. I’m Byron Reese. Today I’m excited we have Mark Stevenson. Mark is a London-based British author, businessman, public speaker, futurologist and occasionally musician and comedian. He is also a fellow of The Royal Society for the Encouragement of Arts, Manufactures and Commerce. His first book, An Optimist’s Tour of the Future was released in 2011 and his second one, We Do Things Differently came out in 2017. He also co-founded and helps run the London-based League of Pragmatic Optimists. Welcome to the show, Mark! 
Mark Stevenson: Thank you for having me on, Byron! It’s a pleasure.
So, the subtitle of your Optimist’s Tour of the Future is, “One curious man sets out to answer what’s next.” Assuming you’re the curious man, what is next?
You can take “curious” in two ways, can’t you? Somebody is interested in new stuff, or somebody’s just a little bit odd, and I am probably a bit of both. Actually, I don’t conclude what’s next. I actually said the question is its own answer. My work is about getting people to be literate about the questions the future is asking them. What’s next will depend on how we collectively answer those questions.
What’s next could be a climate change, dystopian, highly unequal world; or what’s next could be a green-powered, prosperous, abundant, distributed economy for everybody. And each is likely. What’s next is what we decide to do about it, and that’s why I do the work I do, which is trying to educate people about the questions we’re being asked, and allowing them to imagine for themselves.
You said that’s why you do the work that you do. What do you do?
Well, I guess I am a professional irritant. I work with governments, corporations, universities helping them become literate about the questions the future is asking them. You’ll find that most organizations have a very narrow view of the world, because they are kind of governed by their particular marketplace or whatever, and same with governments and government departments.
So, I’ll give you an example, I was working with an insurance company recently who wanted me to come in and help them, and I just put up a picture of two cars having an accident and I said, “What happens if one or both of these is a driverless car?” and the head of insurance went, “I don’t know.” And I’m like, “Well, you should really be asking yourself that question because that question is coming.” And he said, “Mark, we insure drivers. If there aren’t any, it’s a real fucker on the balance sheet.”
It’s funny, but I used to work on old cars, and they were always junkers when I got them, and one time, I had one parked at the top of the hill and in the middle of the night, the brakes failed evidently and it rolled down the hill and hit another car. That scenario actually happened.
The other thing I said was, “What’s your biggest cost?” and he said, “Of course, it’s claims.” And ninety-seven percent or something of claims are because of human error, and it turns out driverless cars are way safer than cars with drivers in them; so maybe that’s good for him, because maybe it will reduce claims. My point was that I don’t know what he should do. He’s the expert in insurance, but my point is, you should be asking yourselves these questions.
Another example from insurance—I was working with the reinsurance industry, the insurers that insure the insurers. On the one hand, you’re being asked to underpin businesses that are insuring a coal-fired power plant. On the other hand, you’re being asked to insure businesses that are going to be absolutely decimated by climate risk.
And you can’t do both and it’s that lack of systems thinking, I suppose, I bring to my clients. And how the food system, the energy system, the government system, the education system, what’s happening in physics, what’s happening in the arts and culture, what’s happening in technology, what’s happening in economics, what’s happening in politics—how they all interrelate, and what questions they ask you?
And then what are you going to do about it, with the levers you have and the position you’re in, to make our world more sustainable, equitable, humane and just? And if you’re not doing that, why are you getting up in the morning and what is the point of you? That’s kind of my business.
When you deal with people, are they, generally speaking, optimistic, are they pessimistic, or are they agnostic on that, because they’re basically just looking at the future from a business standpoint?
That’s a really good question. They’re often quite optimistic about their own chances and often pessimistic about everybody else’s. [Laughter] If you ask people, “Are you optimistic about the future?” they’re going to go, “Yeah, I’m optimistic about the future.” Then, you go, “Are you optimistic about the future generally, like, for the human race?” And you hear, “Oh, no, it’s terrible.”
Of course, those two things are incompatible. People are convinced of their ability to prevail against the odds, but not for everybody else. And so, I often get hired by companies who are saying to me, “We want you to help us be more successful in the future,” and then, I’ll point out to them that actually there’s some existential threats to their business model that may mean they’ll be irrelevant in five years, which they haven’t even thought about.
A really good example of this from the past, which is quite famous, is what happened to Blockbuster. So Netflix went to Blockbuster—I think in 2006—and said, “You should invest in us. You should buy us. We’ll be your online distribution arm.” And the management at Blockbuster went, “I don’t know. I think people will always want to take a cassette home.” But also, Blockbuster made a large amount of their profits from late returns.
So they weren’t likely to embrace downloads, because that would kind of cannibalize one of their revenue streams. Of course, that was very short-sighted of them. And one of the things I say to a lot of my clients is, “Taking the future seriously is going to cost some people their jobs, and I am sorry about that, but not taking the future seriously is going to cost everybody their jobs. So it’s kind of your choice.”
Are your clients continental, British, American… primarily? 
All over. I’m under non-disclosure agreements with most of them.
Fair enough. My follow-up question is going to be, there’s of course a stereotype that Europeans overall are more pessimistic about the future and Americans are less so. Is that true or is it that there’s a grain of truth somewhere, but it’s not really material?
I think there is something in it, and I think it’s because certainly, people from the United States are very confident about the wonderfulness of the United States and how it will prevail. There’s that “American Dream” kind of culture, whereas Europe is in a lot of smaller nations that up until quite recently have been beating the crap out of each other. Perhaps we are a little bit more circumspect, but yeah, it’s a very slight skewing in one direction or the other.
You subtitle your book “What’s Next?” and then, you say, “The question is the answer,” kind of in this Zen fashion, but at some level you must have an opinion, like, it could go either way, but it will likely do what? What do you personally think?
 I don’t know. I feel it’s really up for grabs. If we carry on the way we’re going, it’s going to be terrible; there’s no doubt about that. I think it’s an ancient Chinese proverb that says, “If we don’t change the direction we’re going, we’re going to end up where we’re headed.” And where we’re heading to at the moment is a four-degree world, mass inequality, mass unemployment from the subject we’re going to get into a bit later, which is AI replacing a lot of middle-class jobs, etc. That’s certainly possible.
Then, on the other hand, because of the other work I do with Atlas of the Future, I’m constantly at the cutting-edge, finding people doing amazing stuff. There’s all sorts of people out there putting different futures on the table that make it imminently possible for us to have a humane and just and sustainable world. When you realize, for instance, that we’re installing half a million solar panels a day at the moment. Solar is doubling in capacity every two or three years, and it’s a sort of low starting point, but if it carries on like that, we’ll be completely on renewables within a generation.
And that’s not just good for the environment. Even if you don’t care about the environment, it’s really good for the economy, because the marginal cost of renewable energy is zero and the energy price is very, very stable, which is great when you want to invest long-term. Because one of the problems with the world’s economy is that the oil price keeps going up and down, and nobody knows what’s going to happen to their economy as a result.
You’ll remember—I don’t know how old you are, but certainly some of your listeners will remember—what happened after the Yom Kippur War, where the Arab nations, in protest of American support for Israel, just upped the oil price by about fivefold and suddenly, you had a fifty-five mile-per-hour speed limit, there were states that banned Christmas lights because it was a frivolous use of energy, there was gas rationing, etc. That’s a very extreme example of what’s wrong with relying on fossil fuels, just from an economic perspective, not even an environmental one.
So there are all sorts of great opportunities out there, and I think we really are on the dividing line at the moment. And I suppose I have just decided to put my shoulder against fighting for the side of sustainability and humanity and justice, rather than business as usual, and I don’t have a view. People call me an optimist because I fight, I suppose, for the optimistic side, but we could lose, and we could lose very badly.
Of course, you’re right that if we don’t change direction, you can see what’s going to happen. But there are other things that no force on heaven and earth could stop, like the trend toward automation, the trend toward computerization, the development of artificial intelligence, and those sorts of things.  
Those are known things that will happen. Let’s dive into that topic. Putting aside climate and energy and those topics for the moment, what do you think are just things that will certainly happen in the future?
This is really interesting. The problem with futurology as a profession—and I use that word “profession” very loosely—is that it’s associated with prediction, and predictions are usually wrong. As you said, there are some things you can definitely see happening, and it’s therefore very easy to predict what I would call the “first-order effects” of that.
A good example: When the internet arrived, it’s not hard to predict the rise of email, as you’ve got a network of computers with people sat behind them, typing on keyboards. Email is not a massive leap. So predicting the rise of email is not a problem, but does anybody predict the invention of social media? Does anybody predict the role of social media in spreading fake news or whatever? You can’t. These are second, third-order, fourth-order effects. So each technology is really not an answer, it’s just a question.
If you look at AI, we are looking very much at the automation of lots of jobs that previously we would’ve thought “un-automatable.” As already mentioned, driverless cars is one example of artificial intelligence. A great report came out last year from the Oxford Martin School listing literally hundreds of middle-class jobs that are on the brink of being replaced by automation—
Let me put a pin there, because that’s not actually what they say, they go to great pains to say just the opposite. What they say is that forty-seven percent of things people do in their jobs are potentially automatable. That’s why things on their list are things like pharmacist assistants or whatnot. So all they really say is, “We make no predictions whatsoever about what is going to happen in jobs.”
So if a futurologist does anything, the futurologist looks at the past, and says, “We know human nature is a constant, and we know things that have happened in the past, again and again and again. And we can look at that and say ‘Okay, that will probably happen again.’” So we know that for two hundred and fifty years, three hundred years since the Industrial Revolution in the West, unemployment has remained very narrow in this broad band of five to ten percent.
Aside from the Depression, all over the West, even though you’ve had, arguably, more disruptive technologies—you’ve had the electrification of industry, the mechanization of industry, the end of animal power being a force of locomotion, coal grew from generating five percent of energy to eighty percent of energy in just twenty years—all these enormous disrupting things that did, to use your exact words, “automated jobs that we would’ve thought were not automatable,” and yet, we never ever had a hiccup or a surge in unemployment from that. So wouldn’t it be incumbent on somebody saying something different is going to happen, to really go into a lot of detail about what’s different with this? 
I absolutely agree with you there, and I am not worried about employment in the long run. Because if you look at what’s happened in employment, it’s what you call “non-routine things,” things that humans are good at, that have been hard to automate. A really good example is the beginning of the Industrial Revolution, lots of farm laborers, end of Industrial Revolution, not nearly as many farm laborers—I think five percent of the number—because we introduced automation to the farming industry, tractors, etcetera; now far fewer people can farm the same amount of land.
And by the same token, at the beginning of the Industrial Revolution, not so many accountants; by the end of it, stacks of accountants—thirty times more accountants. We usually end up creating these higher-value, more complex jobs. The problem is the transition. In my experience, not many farm laborers want to become accountants, and even if they did, there’s no transition route for them. So whole families, whole swathes of the populace can get blindsided by this change, because they’re not literate about it, or their education system isn’t thinking about it in a sensible way.
Let’s look at driverless technology again. There’s 3.5 million truck drivers in the United States, and it’s very likely that a large chunk of them will not have that job available to them in ten or fifteen years, and it’s not just them. Actually, if you go to the American Trucking Association, they will say that one in fifteen of the American workforce are somehow related to the trucking industry.
A lot of those jobs will be at threat. Other jobs may replace them, but my concern is what happens to the people who are currently truck drivers? What happens to an education system that doesn’t tell people that truck drivers won’t be existing in such numbers in ten or fifteen years’ time? What does the American Trucking Association do? What do logistics firms that employ those truckers do?
They’ve all got a responsibility to think about this problem in a systemic way, and they often don’t, which is where my work comes in, saying, “Look, Government, you have to think about an education that is very different, because AI is going to be creating a job market that’s entirely different from the one you’re currently educating your children into.”
Fair enough. I don’t think that anybody would argue that an industrial economy education system is going to make workers successful in this world of tomorrow, but that set up that you just gave, it strikes me as a bit disingenuous. Which is to say, well, let’s just take truck driving for example. The facts on the ground are that it will be gradual, because you’ve got, likely, ten years to replace all the truckers, and it’s going to be gradual. So, fewer people are going to enter the field, people who might retire earlier are going to retire out of it. Technology seldom does it all that quickly.
But the thing that I think might be different is that, usually, what people say is, “We’re going to lose these lower-skill jobs and we’re going to make jobs for geneticists,” and those people who had these lower-skill jobs are going to become geneticists, and nobody actually ever says that that’s what happens.
The question is, “Can everybody already do a job a little harder than the one they presently have?” So, each person just goes up one layer, one notch in the food chain that doesn’t actually require that you take truck drivers and send them to graduate school for twelve years.
Indeed, and this is why having conversations like this is so important, because, as I said, my thing is about making people literate about the questions the future is asking them. And so, now, we’re having quite a literate conversation about that, and that’s really important. It’s why podcasts like this are important, it’s why the research you do is important. But in my experience, a lot of people, particularly in government, they would not even be having this conversation or asking this question. And the same for lots of people in business as well, because they’re very focused on a very narrow way of looking at things. So, I think I’m in violent agreement with you.
And I with you. I am just trying to dissect it and think it through, because one could also say that about the electrification of industry, all those things I just listed. Nobody said, “Electrification is coming.” We’ve always been reactive, and, luckily, change has come at a pace that our reactive skills have been able to keep up. Do you think this time is different? Are you saying there’s a better way to do it?
I just think it’s going to be faster this time. I think it’s an arguable truism in the work of futurism that technology waves speed up. If you look at, for instance, there are some figures I’ve got for the United States National Intelligence Council, and it’s really interesting just to look at how long it took the United States population to adopt certain technologies. It took forty-six years for twenty-five percent of the United States population to bring electricity into their homes from its introduction to the market.
It took just seven for the World Wide Web, and there were two and a half times as many citizens there. And that makes sense, because each technology provides the platform and the tools to build the next one. You can’t have the World Wide Web until you have electricity. And so you see this speeding up because now you have more powerful tools than you had the last time to help you build the next one, and they distribute much more quickly as well.
So what we have—and this is what my third book is going to be about—is this problem between the speed of change of technology and also, the speed of change of thought and philosophy and new ideas about how we might organize ourselves, and the speed of our bureaucracies and our governments and our administration, which is still painfully slow. And it’s that mismatch of those gears that I think causes the most problems. The education system being a really good example. If your education system isn’t keeping up with those changes, isn’t in lockstep with them, then inevitably, you’re going to do a disservice to many of the students going through it.
Where do you think that goes to? Because, if it took forty-seven years for electricity and seven for the web, eventually, it’s like that movie Spaceballs, where they had that scene where the video hits the video store before they finish shooting it. At some point, there’s an actual physical limit to that, right? You don’t have a technology that comes out on Thursday and by Friday, half the world is using it. So what does that world look like?
Exactly, and all of these things move at slightly different speeds. If you look at what’s happening with energy at the moment, which is one of my favorite topics because I think it kind of underpins everything else, the speed at which the efficiency of solar panels is rising, the speed at which the price of solar is going down, the invention of energy Internet technology, based on ideas from Bob Metcalfe, is extraordinary.
I was at the EU Commission a few weeks ago, talking to them about their energy policy and looking at it and saying, “Look guys, you have a fantastic energy policy for 1994. What’s going on here? How come I am having to tell you about this stuff? Because actually, we should be moving to a decentralized, decarbonized, much more efficient, much cheaper energy system because that’s good for everybody, but you’re still writing energy policy as if it was the mid ‘90s.” And that really worries me. Energy is not going to move as fast as a new social networking application, because you do have to actually build stuff and stick it in the ground and connect to each other, but it is still moving way faster than the administration, and that is my major concern.
The focus of my work for the next two-three years is working at, how do we get those things working at the same speed or at least nearly enough at the same speed so they can usefully talk to each other. Because governments, at the moment, don’t talk to technology in any useful way. Data protection law, I was just talking to a lawyer yesterday and he’s saying, “I’m in the middle of this data protection case. I am dealing with data protection law that was written in 1985.”
Let’s spend one more minute on energy, because it obviously makes the world go around, literally. My question is, the promise of nuclear way back was that it would be too cheap to meter, or in theory it could’ve been, and it didn’t work out. There were all kinds of things that weren’t foreseen and whatnot. Energy is arguably the most abundant thing in the universe, so do you think we’ll get to a point where it’s too cheap to meter, it’s like radio waves, it’s like the water fountain at the department store that nobody makes you put a quarter in?
Yeah, I think we will, but I think that comes from a distributed system, rather than a centralized one. One of my pet tropes that I trot out quite regularly is this idea that we’re moving from economies of scale to economies of distribution. It used to be that the most efficient way to do things was to get everything in a centralized place and do it all there because it was cheaper that way, given the technology we had at that time. Whether it was schools where we get all the children into a room and teach at them, whether it was power stations where we dig up a bunch of coal, take it to a big factory or power station, burn it and then send it out through the wires. Even though in your average coal-fired power plant, you would lose sixty-seven percent of the energy through waste-heat, it was still the most efficient way to do things.
Now, we have these technologies that are distributed. Even though they might be slightly less efficient or not quite as cost-effective, in and of themselves, when you connect them all together and distribute them, you start to see the ability to do things that the centralized system can’t. Energy, I think, is a really good example of that.
All our energy is derived from the sun, and the sun’s energy doesn’t hit just power plants. It hits the entire planet, and there’s that very famous statistic, that there’s more energy that hits the Earth’s surface in an hour than the human race uses in a year, I think. The sun has been waving this massive energy paycheck in our face every second since it started burning, and we haven’t been able to bank it very well.
So we’ve been running into the savings account, which is fossil fuels. That’s sunshine that has been laid down for us very dutifully by Mother Nature for billions of years and we can dig it up, thank you very much. Thank you for the savings account, but now, we don’t need the savings account so much because we can actually bank the stuff as it’s coming towards us with the improving renewable technologies that are out there. Couple that with an energy Internet, and you start to make your energy and your fuel where you are. I’m also an advisor to Richard Branson’s “Virgin Earth Challenge”, which is a twenty-five million dollar prize for taking carbon out of the atmosphere.
You have to be able to do that in an environmentally-sustainable way, and make a profit while you’re doing it. And I have to be very careful and say this is not the view of the Virgin Earth Challenge; it’s not the official view, but I am fairly confident that we will award that prize in the next three to four years, because we’ve got finalists that are taking carbon directly out of the air and turning it into fuel, and they’re doing it at a price point that’s competitive with the fossil fuel.
So if you distribute the production of liquid fuels and electricity and anybody can do it, that means you as a school can do it, you as a local business can do it. And what you find is when people do take control of the energy system, because they’re not so motivated by making a profit, the energy is cheaper, they maintain it better, and everybody’s happier.
There’s a town in the middle of Texas right now called Georgetown—65,000 Trump voters who I imagine are not that interested about the climate change threat, as conservatives generally don’t seem to think that that is a problem—and they’re all moving over to renewables, because it’s just cheaper than using oil, and they are in the middle of central Texas. I think we’re definitely going in that direction.
You’re entirely right. I am going to pull these numbers from my head, so they could be off, but something like four million exajoules of sunlight comes on the planet every year, and humanity needs five hundred. That’s what it is right now. It’s like four million raining down and we have to figure out how to pull five hundred of them and harvest those economically. Maybe, if the Virgin Earth Prize works, there’s going to be a crisis in the future—there’s not enough carbon in the air! They’ve pulled it all out at a profit.
That would be a nice problem to have, because we’ve already proven to ourselves that we can put carbon in the air. That’s not going to be a problem if it’s getting too low.
So let’s return to artificial intelligence for a moment. I want to throw a few things at you. Two different views of the world—I’d love to talk about each one by itself. One of them is that the time it takes for a computer to learn to do a task gets shorter and shorter as we learn how to do it better, and that there’s some point at which it is possible for the computer to learn to do everything a human can do, faster than a human can do it. And it would be at that point that there are literally no jobs, or could be literally no jobs if we chose that view. So, whether you think that or not, I am curious about, but assuming that that is true, what do you think happens?
I think we find new kinds of jobs. I really do. The thing is that the clue is in the name, “artificial intelligence.” We have planes; that’s artificial flying. We don’t fly the same way that birds fly. We’ve created an entire artificial way of doing it. And the intelligences that will come out of computers will not be the same as human intelligence.
They might be as intelligent, arguably, although I am not convinced of that yet, but they will be very different intelligences—in the same way that a dog’s intelligence is not the same as an ant’s intelligence, which is not the same as my Apple MacBook’s intelligence, if it has any, which is not the same as human intelligence. These intelligences will do different things.
They’ll be artificial intelligences and they’ll be very, very good at some things and very bad at other things. And the human intelligence will have certain abilities that I don’t think a machine will ever be able to replicate, in the same way that I don’t believe a wasp is ever going to be as good as me at playing the bass guitar and I am never going to be as good as it at flying.
So what would be one of those things that you would be dubious that artificial intelligence would be able to do?
I think it is the moral questions. It’s the actual philosophy of life—what are we here for, where are we going, why are we doing it, what’s the right thing to do, what do we value, and also the curiosity. I interviewed Hod Lipson at Columbia and he was very occupied with the idea of creating a computer that was curious, because I think curiosity is one of those things that sort of defines a human intelligence, that machines, to my knowledge, don’t have in any measurable sense.
So I think it would be those kind of very uniquely human things—the ability to abstract across ideas and ask moral, ethical questions and be curious about the world. Those are things that I don’t see machines doing very well at the moment, at all, and I am not convinced they’ll do them in the future. But it’s such a rapidly evolving field and I’m not a deep expert in AI, and I’m willing to be proved wrong.
So, you don’t think there will ever be a book One Curious Computer Sets Out To Answer What’s Next? 
Do you know what? I don’t, but I really wish there was because I’d love to go on stage and have that panel discussion with that computer.
Then, let’s push the scenario one step further. I would have to say it’s an overwhelming majority of people who work in the AI field who believe that we will someday—and interestingly, the estimates range from five to five hundred years—make a general intelligence. And it begins with the assumption that we, our brains and our minds, are machines and therefore, we can eventually build a mechanical one. It sounds like you do not hold that view.
It’s a nuance view. Again, it’s interesting to discuss these things. What we’re really talking about here is consciousness, because if you want to build an “artificial general intelligence,” as they call it, what you’re talking about is building a conscious machine that can have the same kind of thoughts and reflections that we associate with our general intelligence. Now, there are two things I’d say.
The first is, to build a conscious machine, you’d have to know what consciousness is, and we don’t. And we’ve been arguing about it for two thousand years. I would also say that some of the most interesting work in that field is happening in AI, particularly in robotics, because in nature, there is no consciousness without a body. It may be that when we say, “What is consciousness?” consciousness isn’t actually one thing; it’s actually eight separate questions we have to answer, and we worked out what those eight are, and we can answer with technology. I think that might be a plausible route.
And clearly, as you point out, consciousness must be computable, because we are computing it right now. Me and you are “just” DNA computer code being read, and that computer code generates proteins and lipids and all kinds of things to make us work, and we’re having this conversation as a result of these computer programs that are running in ourselves. So clearly, consciousness is computable, but I am still very much to be convinced that we have any idea of what consciousness really is, or if we’re even asking the right questions about it.
To your point, we’re way ahead of ourselves in one sense, but do you think that in the end, if you really did have a conscious computer, a conscious machine, does that in some way undermine human rights? In the sense that we think people have these rights by virtue of being conscious and by virtue of being sentient, being able to feel pain? Do you think that if all of a sudden, the refrigerator and everything in your house also made that claim, that we are somehow lessened by it, not that the machines are somehow ennobled by it?
I would hope not. George Church, who runs Harvard Medical School said to me, “If you could show me a conscious machine, I wouldn’t be frightened by it. I’d be emboldened by it, I’d be curious about how that thing works, because then I’d be able to understand myself better.”
I was asked just recently by the people who are making “The Handmaid’s Tale,” the TV series based on the Margaret Atwood book, “What do you think AI is going to do for humanity?” Hopefully, one scenario is that it helps us understand ourselves better, because if we are able to create that machine that is conscious, we will have to answer the question, “What is consciousness?” as I said earlier, and when we’ve done that, we will have also unlocked also some of the great secrets about ourselves, about our own motivations, about our emotions, why we fight, what’s good for us, what’s bad for us, how to handle depression. We might open a whole new toolbox on actually understanding ourselves better.
One interpretation of it is that actually creating artificial general intelligence is one of the best things that could happen to humanity, because it will help us understand ourselves better, which might help us achieve more and be better human beings.
At the beginning of our chat, you listed a litany of what you saw as the big challenges which face our planet. You mentioned income inequality. So, absent wide-scale redistribution, technology, in a sense, promotes that in a way, doesn’t it?
Microsoft, Google and Facebook between them have generated 12 billionaires, so it’s evidently easier to make a billion dollars now—not me, but for some people to make billions now—than it would’ve been twenty years ago or five hundred years ago for that matter. Do you think that technology in itself, by multiplying the abilities of people and magnifying it ever-more, is a root cause of income inequality? Or do you think that comes from somewhere else?
I think income inequality comes from the way our capital markets and our property law works. If you look at democracy for instance, there’s several pillars to it. If you talk to a political philosopher, they’ll say, you know, a functioning democracy has several things that need to be working. One is you need to have universal suffrage, so everybody gets to vote, you need to have free and fair elections, you need to have free press, you need to have a judiciary that isn’t influenced by the government, etcetera.
The other thing that’s mentioned but less talked about is working property rights. Working property rights say that you, as a citizen, have the right to own something, whether that’s some property or machinery or an idea, and you are allowed to generate an income from that and profit from it. Now that’s a great idea, and it’s part of entrepreneurship and going and creating something, but the problem is once you have a certain amount of property that you’ve profited from, you would then have more ability to go and buy some property from other people.
What’s happening is the property rights, whether they’re intellectual or physical, have concentrated themselves in fewer and fewer hands, because as you get rich, it’s easier to buy other stuff. And I know this from my own experience. I used to be a poor musician-student. Now, I’m doing pretty well and I find myself today buying some shares in a company that I thought was going to do really well… and they did. And I find myself just thinking, “Wow, that was easy.” It’s easy for me now because I have more property rights to acquire more property rights, and that’s what we’re seeing. There’s a fundamental problem there somewhere, and I am not quite sure how we deal with it.
After World War II, England toyed with incredibly high, sometimes over 100% marginal taxes on unearned income, and I think The Beatles figured they needed to leave. What is your take on that? Did that work, is that an experiment you would advocate repeating, or what did we learn from that? 
I think we’ve learnt that’s a very bad way of doing it. Again, it comes back to how much do things cost? If things are expensive and you’re running a state, you need to collect more taxes. We’re having this huge debate in the UK at the moment about the cost of National Health Service, and how do you fund that. To go back to some of our earlier conversation, if you suddenly reduce the cost of energy to very little, actually everything gets cheaper—healthcare, education, building roads.
If you have a whole bunch of machines that can do stuff for you cheaper that humans could do it, in one way, that’s really good, because now you can provide health care, education, road building, whatever… cheaper. The question is, “How does the job market change then? Where do human beings find value? Do we create these higher-valued jobs?” One radical idea that’s come out at the moment is this idea of universal basic income.
The state has now enough money coming in because the cost of energy has gone down, and it can build stuff much more cheaply. We’ll just get a salary anyway from the state to follow our dreams. That’s one plausible scenario.
Moving on, I would love to hear more about the book that’s just come out. I’ve read what I could find online, I don’t have a copy of it yet. What made you write We Do Things Differently, and what are you hoping it accomplishes?
So with my first book, which is really an attempt to talk about the cutting-edge of technology and what’s happening with the environment in an entertaining way for the layman, I got to the end of that book and it became very clear to me that we have all the technology that we need to solve the world’s grand challenges, whether that’s the energy price, or climate change, or problems with manufacturing.
We’re not short of technology. If we didn’t invent another thing from tomorrow, we could deal with all the world’s grand challenges, we could distribute wealth better, we could do all the things. But it’s not technology that’s the problem. It’s the administration, it’s the way we organize ourselves, it’s the way our systems have been built, and how they’ve become kind of fossilized in the way they work.
What I wanted to do with this book is look at systems and look at five key human systems—energy, healthcare, food, education and governance—and say, “Is there a way to do these better?” It wasn’t about me saying, “Here’s my idea.” It was about me going around the world and finding people who’ve already done it better and prevailed and say, “What do these people tell us about the future?”
Do they give us a roadmap to and a window on a future that is better run, more sustainable, kinder to everybody, etcetera? And that’s what it is. It’s a collection of stories of people who’ve gone and looked at existing systems, challenged those systems, built something better, and they’ve succeeded and they’ve been there for a while—so you can’t say it was just like a six-month thing. They’re actually prevailing, and it’s those stories in education, healthcare, food, energy and governance.
I think the saddest fact I know, in all the litany of the things you run across, any time food comes up, it jumps to the front of my mind. There’s a billion people more or less—960 something million—that are hungry. You can go to the UN’s website, you can download a spreadsheet, it lists them out by country.
The sad truth is that seventy-nine percent of hungry people in the world live in nations that are net food exporters. So, the food that’s made inside of the country can be sold on the world market for more than the local people can pay for it. The truth in the modern age is not that you starve to death if you have no food; it is that you starve to death if you have no money. What did you find?
 There’s an even worse fact that I can tell you, which is, the human race wastes between thirty and fifty percent of the food it makes, depending on where you are in the world, before it even reaches the market. It spoils or it rots or it gets wasted or damaged between the field and the supermarket shelf, and this is particularly prevalent in the global south, the hotter countries. And the reason is we simply don’t have enough refrigeration, we don’t have enough cold chains, as they’re called.
So one of the great pillars of civilization, which we kind of take for granted and don’t really think about, is refrigeration and cooling. In the UK, where I am, sixteen percent of our electricity is spent on cooling stuff, and it’s not just food as well. It’s medical tissues and medicines and all that kind of stuff. And if you look at sub-Saharan Africa, it’s disastrous because the food they are growing, they are not even eating because it ruins too quickly, because we don’t have a sustainable refrigeration system for them to use. And one of the things I look at in the book is a new sustainable refrigeration system that looks like it could solve that problem.
You also talk about education. What do you advocate there? What are your thoughts and findings?
I try not to advocate anything, because I think that’s generally vainglorious and I’m all about debate and getting people to ask the right questions. What I will do is sort of say, look, this person over here seems to have done something pretty extraordinary. What lessons can we draw from them?
So, I went to see a school in a very, very rough housing estate in Northern England. This is not an urban paradise; this is a tough neighborhood, lots of violence, drug dealing, etcetera, low levels of social cohesion, and in the middle of this housing estate there was a school that, I think the government called it the fifth worst school in the entire UK, and they were about to close it. A guy called Carl turns up as new headmaster and two years later, it’s considered one of the best schools in the world, and he’s done all that without changing any staff. It took the same staff everybody thought was rubbish and two years later, they’re regarded as some of the best educators in the world.
And the way he did that is not rocket science. It was really about creating a collaborative learning environment. One of the things he said was, “Teachers don’t work in teams anymore. They don’t watch each other teach. They don’t learn about the latest of what’s happening in education; they don’t do that. They kind of become automatized and do their lessons, so I’m going to get them working as a team.”
He also said they lost any culture of aspiration about what they should be doing, so they were just trying to get to the end of the week, rather than saying, “Let’s create the greatest school in the world.” So he took some very simple management practices which is about, ‘We’re going to aspire to be the best, and we’re going to start working together, and we’re going to start working with our kids.”
And he did the same with the kids, even though they were turning up at this school four years old, most of them still in nappies, most of them without language, even at four—by the time they were leaving, they were outperforming the national average, from this very rough working-class estate. By also working with the kids in the same way and saying, “Look, what’s your aspiration? How are we going to design this together collectively as a school—you the students, us the teachers?”
This is actually good management practice, but introduced into a school environment, and it worked very well. I am vastly trivializing the amount of effort and sweat and emotional effort he had to put into that. But, again, talking about teamwork: Rather than splitting the world up into subjects, which is what we tend to do in schools, he’s like, “Let’s pick things that the kids are really interested in, and we’ll teach the subjects along the way because they’ll all be interrelated with each other.”
I walked into a classroom there and it’s bedecked out like NASA headquarters, because they picked the theme of space for this term for this particular class. But of course, as they talk about space and astronauts, they learn about the physics, the maths, they learn about the communications, they learn about history…
And I said to Carl, “Once they’re given this free environment, how do they feel when exams come along, which is a very constraining environment?” He said, “Oh, they love it.” I’m like, “You’re kidding me!” He said, “No, they can’t wait to prove how much they’ve learnt.”
None of this is rocket science, but it’s really interesting that education is one of those places where, when you try and do anything new, someone is going to try to kill you, because education is autobiography. Everybody’s been through it, and everybody has a very prejudiced view of what it should be like. So for any change, it’s always going to upset somebody.
You made the statement that even if we didn’t invent any new technology, we would know how to solve all of life’s greatest challenges. I would like to challenge that and say, we actually don’t know how to solve the single biggest challenge.
This sounds good.
Death.
Death! That’s an interesting question, whether you view it as a challenge or not.
I think most people, even if they don’t want to live indefinitely, that the power to choose the moment of your own demise is something that I think many people would aspire to—to live a full life and then choose the terms of their own ending. Do you think death is solvable? Or at least aging?
 I think aging is probably solvable. Again, I am not a high-ranking scientist in this area, but I know a number of them. I was working with the chief scientist at one of our big aging charities recently, and if you look at the research that’s coming out from places like Stanford and Harvard, there’s an incredible roadmap to humans living healthy lives in healthy bodies till one hundred and ten, one hundred and thirty. Stanford have been reversing human aging in certain human cell lines since 2014.
The problem is, of course, it turns out that what’s good for helping humans live longer is also often quite good for promoting cancer. And so that’s the big conundrum we have at the moment. Certainly, we are living longer and healthier anyway. Average life expectancy has been rising a quarter-year for every year, for the last hundred years. Technology is clearly doing something in that direction.
Well what it seems to be doing is ending premature death, but the number of people who live to be supercentenarians, one hundred and ten and above is forty, and it doesn’t seem to be going up particularly.
Yeah, I think that’s true. But it depends what you call “premature death,” because actually, certainly the age at which we die is definitely creeping up. But if we can keep ourselves a bit younger, if we can, for instance, find a way to lengthen the telomeres in our cells without encouraging cancer, that’s a really good thing because most of the diseases we end up dying from are the diseases of aging—cardiovascular disease, stroke, etcetera.
We haven’t solved it yet. You asked me if I think it’s solvable. Like you, I think I am fairly optimistic about the human race’s ability to finally ask the right questions, and then find answers to them. But I think we still don’t really understand aging well enough yet to solve it, but I think we’re getting there much faster, I would say, than we are perhaps with an artificial general intelligence.
Talk about the “Atlas of the Future” project.
 Ah, I love the Atlas. The Atlas is kind of the first instantiation of something from the Democratizing the Future society. What we’re trying to do is to say, “Look, if we want the world to progress in a way that’s good for everybody, it needs to involve everybody.” And therefore, you need to be literate about the questions the future asks you, and not just literate about threats. Which is what we get from the media. The general media will just walk in and go, “It’s all going to be terrible, everyone’s trying to kill you.” They’ll drop that bomb and then just walk away, because that gets your attention.
We are trying to say, “Yeah, all those stories are worth paying attention to, and there are a whole other bunch of stories worth paying attention to, about what we can do with renewables, what we can do to improve healthcare, what we can do to improve social cohesion, what we can do to improve happiness, what we can do to improve nations understanding each other, what we can do to reduce partisan political divides, etcetera.” And we collect all that stuff. So it’s a huge media project.
If you go to “The Atlas of the Future,” you’ll find all these projects of people doing amazing stuff—some of them very big-picture stuff, some of it small-picture stuff. Subsequently, what we’re doing with that is we’re farming out that content either via TV series, the books I write, there’s a podcast—by The Futurenauts, which is me and my friend, Ed Gillespie—where we talk about the stuff on the Atlas and we interview people.
So it’s about a way of creating a culture of the future that’s aspirational, because we kind of feel that, at the moment, we’re being asked to be fearful of the future and run away in the opposite direction. And we’d like to put on the table the idea that the future could be great, and we’d like to run towards that, and get involved in making it.
And then, what’s this third book you are working on?
The third book is just an idea at the moment, but it is about how do we get our administration, our government, our bureaucracy to move at something like a similar pace to the pace of ideas and technology, because it seems to me that it’s that friction that causes so many of the problems—that we don’t move forward fast enough. The time it takes to approve a drug is stratospheric, and there’s some good reasons for that, I am not against the work the FDA does, but when you’re looking at, sometimes, twelve or thirteen years for a drug to reach the market, that’s got to be too slow.
And so, we have to think about ways to get those parts of the human experience—the technology, the philosophy and the bureaucracy—working at roughly the same clock speed, then I think things would be better for everybody. And that’s the idea I want to explore in the next book—how we go about doing that. Some of it, I think, will be blockchain technology, some of it might be the use of virtual reality, and a whole bunch of stuff I haven’t probably found out yet. I’m really just asking that question. If any of your listeners have any ideas about what some of the technologies or approaches or philosophies that will help us solve that, I’d love to hear from them.
You mentioned a TV program earlier. In views of the future, science fiction movies, TV, books, all of that, what do you read or watch that you think, “Huh, that could happen. That is a possible outcome”? What do you think is done really well?
It’s interesting, because I have a sixteen-month old child, and I am trying to write a book and save the world, so I hardly watch anything. I think it’s very difficult to cite fiction as a good source. It’s an inspiration, it’s a question, but it never turns out how we imagine. So I take all those things with a pinch of salt, and just enjoy them for what they are.
I have no idea what the future is going to be like, but I have an idea that it could be great, and I’d like it to be so. And actually, there is no fiction really like that, because if you look at science fiction, generally, it’s dystopian, or it’s about conflict, and there’s a very good reason for that—which is that it’s entertaining. Nobody wants to watch a James Cameron movie where the robots do your gardening. That’s not entertaining to watch. Terminator 3: Gardening Day is nothing that anybody is going to the cinema to see.
I’m in full agreement with that. I authored a book called Infinite Progress, and, unlike you, I have a clearer idea of what I think the future is going to be. And I used to really be bothered by dystopian movies, mainly because I am required to go see them. Because everybody’s like, “Did you see Elysium?” So, I have to go see and read everything, because I’m in that space. And it used to bother me, until I read a quote, I think by Frank Robert—I apologize if it isn’t him—who said, “Sometimes, the job of science fiction is to warn you of something that could happen so that you have your guard up about it,” so you’re like, “A-ha! I’m not going to let that happen.” It kind of lets the cat out of the bag. And so I was able to kind of switch my view on it by keeping that in mind, that these are cautionary tales.
I think we also have to adopt that view with the media. The media leads on the stuff that is terrifying, because that will get our attention, and we are programmed as human beings to be cautious first and optimistic second. That makes perfect sense on the African savanna. If one of your tribe goes over the hill without checking for big cats, and gets eaten by a big cat, you’re pretty cynical about hills from that moment on. You’re nervous of them, you approach them carefully. That’s the way we’re kind of programmed to look at the world.
But of course, that kind of pessimism doesn’t move us forward very much. It keeps us where we are, and even worse than that is the cynicism. And of course, cynicism is just obedience to the status quo, so I think you can enjoy the entertainment, and enjoy the dystopia, enjoy us fighting the robots, all that kind of stuff. One thing you do see about all those movies is that eventually, we win, even if we are being attacked by aliens or whatever; we usually prevail. So whilst they are dystopian, there is this yearning amongst us, saying, “Actually, we will prevail, we will get somewhere.” And maybe it will be a rocky ride, but hopefully, we’ll end up in the sunshine.
An Optimist’s Tour of the Future is still available all over the world—I saw it was in, like, nine languages—and you can order that from your local book proprietor and We Do Things Differently, is that out in the US? When will that be out in US? 
It’s out in the US early next year. We don’t have a publication date yet, but I am told by my lovely publishers that that will be sort of January-February next year. Yet you can buy the UK edition on Amazon.com and various other online stores, I’m sure.
If people want to follow you and follow what you do and whatnot, what’s the best way to do that? 
My Twitter handle is @Optimistontour. You can learn about me at my website, which is markstevenson.org, and check out “The Futurenauts” podcast at thefuturenauts.com where we do something similar to this, although we have more swearing and nakedness than your podcast. Also, get yourself down to “Atlas of the Future.” I think that would be the central place to go. It’s a great resource for everybody, and that’s not just about me—there’s a whole bunch of future, forward-thinking people on that. Future heroes. We should probably get you on there at some point, Byron.
I would be delighted. This was an amazing hour! There could be a Mark Stevenson show. It’s every topic under the sun. You’ve got wonderful insights, and thank you so much for taking the time to share them with us. Bye!
 Cheers! Bye!
Byron explores issues around artificial intelligence and conscious computers in his upcoming book The Fourth Age, to be published in April by Atria, an imprint of Simon & Schuster. Pre-order a copy here.
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Voices in AI – Episode 25: A Conversation with Matt Grob

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In this episode, Byron and Matt talk about thinking, the Turing test, creativity, Google Translate, job displacement, and education.
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Byron Reese: This is Voices in AI, brought to you by Gigaom. I’m Byron Reese. Today our guest is Matt Grob. He is the Executive Vice President of Technology at Qualcomm Technologies, IncGrob joined Qualcomm back in 1991 as an engineer. He also served as Qualcomm’s Chief Technology Officer from 2011 to 2017. He holds a Master of Science in Electrical Engineering from Stanford, and a Bachelor of Science in Electrical Engineering from Bradley University. He holds more than seventy patents. Welcome to the show, Matt.
Matt Grob: Thanks, Byron, it’s great to be here.
So what does artificial intelligence kind of mean to you? What is it, kind of, at a high level? 
Well, it’s the capability that we give to machines to sense and think and act, but it’s more than just writing a program that can go one way or another based on some decision process. Really, artificial intelligence is what we think of when a machine can improve its performance without being reprogrammed, based on gaining more experience or being able to access more data. If it can get better, it can prove its performance; then we think of that as machine learning or artificial intelligence.
It learns from its environment, so every instantiation of it heads off on its own path, off to live its own AI life, is that the basic idea?
Yeah, for a long time we’ve been able to program computers to do what we want. Let’s say, you make a machine that drives your car or does cruise control, and then we observe it, and we go back in and we improve the program and make it a little better. That’s not necessarily what we’re talking about here. We’re talking about the capability of a machine to improve its performance in some measurable way without being reprogrammed, necessarily. Rather it trains or learns from being able to access more data, more experience, or maybe talking to other machines that have learned more things, and therefore improves its ability to reason, improves its ability to make decisions or drive errors down or things like that. It’s those aspects that separate machine learning, and these new fields that everyone is very excited about, from just traditional programming.
When you first started all of that, you said the computer “thinks.” Were you using that word casually or does the computer actually think?
Well, that’s a subject of a lot of debate. I need to point out, my experience, my background, is actually in signal processing and communications theory and modem design, and a number of those aspects relate to machine learning and AI, but, I don’t actually consider myself a deep expert in those fields. But there’s a lot of discussion. I know a number of the really deep experts, and there is a lot of discussion on what “think” actually means, and whether a machine is simply performing a cold computation, or whether it actually possesses true imagination or true creativity, those sorts of elements.
Now in many cases, the kind of machine that might recognize a cat from a dog—and it might be performing a certain algorithm, a neural network that’s implemented with processing elements and storage taps and so forth—is not really thinking like a living thing would do. But nonetheless it’s considering inputs, it’s making decisions, it’s using previous history and previous training. So, in many ways, it is like a thinking process, but it may not have the full, true creativity or emotional response that a living brain might have.
You know it’s really interesting because it’s not just a linguistic question at its core because, either the computer is thinking, or it’s simulating something that thinks. And I think the reason those are different is because they speak to what are the limits, ultimately, of what we can build. 
Alan Turing way back in his essay was talking about, “Can a machine think?” He asked the question sixty-five years ago, and he said that the machine may do it a different way but you still have to call it “thinking. So, with the caveat that you’re not at the vanguard of this technology, do you personally call the ball on that one way or the other, in terms of machine thought?
Yeah, I believe, and I think the prevailing view is, though not everyone agrees, that many of the machines that we have today, the agents that run in our phones, and in the cloud, and can recognize language and conditions are not really, yet, akin to a living brain. They’re very, very useful. They are getting more and more capable. They’re able to go faster, and move more data, and all those things, and many metrics are improving, but they still fall short.
And there’s an open question as to just how far you can take that type of architecture. How close can you get? It may get to the point where, in some constrained ways, it could pass a Turing Test, and if you only had a limited input and output you couldn’t tell the difference between the machine and a person on the other end of the line there, but we’re still a long way away. There are some pretty respected folks who believe that you won’t be able to get the creativity and imagination and those things by simply assembling large numbers of AND gates and processing elements; that you really need to go to a more fundamental description that involves quantum gravity and other effects, and most of the machines we have today don’t do that. So, while we have a rich roadmap ahead of us, with a lot of incredible applications, it’s still going to be a while before we really create a real brain.
Wow, so there’s a lot going on in there. One thing I just heard was, and correct me if I’m saying this wrong, that you don’t believe we can necessarily build an artificial general intelligence using, like, a Von Neumann architecture, like a desktop computer. And that what we’re building on that trajectory can get better and better and better, but it won’t ever have that spark, and that what we’re going to need are the next generation of quantum computer, or just a fundamentally different architecture, and maybe those can emulate human brain’s functionality, not necessarily how it does it but what it can do. Is that fair? Is that what you’re saying? 
Yeah, that is fair, and I think there are some folks who believe that is the case. Now, it’s not universally accepted. I’m kind of citing some viewpoints from folks like physicist Roger Penrose, and there’s a group around him—Penrose Institute, now being formed—that are exploring these things and they will make some very interesting points about the model that you use. If you take a brain and you try to model a neuron, you can do so, in an efficient way with a couple lines of mathematics, and you can replicate that in silicon with gates and processors, and you can put hundreds of thousands, or millions, or billions of them together and, sure, you can create a function that learns, and can recognize images, and control motors, and do things and it’s good. But whether or not it can actually have true creativity, many will argue that a model has to include effects of quantum gravity, and without that we won’t really have these “real brains.”
You read in the press about both the fears and the possible benefits of these kinds of machines, that may not happen until we reach the point where we’re really going beyond, as you said, Von Neumann, or even other structures just based on gates. Until we get beyond that, those fears or those positive effects, either one, may not occur.
Let’s talk about Penrose for a minute. His basic thesisand you probably know this better than I dois that Gödel’s incompleteness theorem says that the system we’re building can’t actually duplicate what a human brain can do. 
Or said another way, he says there are certain mathematical problems that are not able to be solved with an algorithm. They can’t be solved algorithmically, but that a human can solve them. And he uses that to say, therefore, a human brain is not a computational device that just runs algorithms, that it’s doing something more; and he, of course, thinks quantum tunneling and all of that. So, do you think that’s what’s going on in the brain, do you think the brain is fundamentally non-computational?
Well, again, I have to be a little reserved with my answer to that because it’s not an area that I feel I have a great deep background in. I’ve met Roger, and other folks around him, and some of the folks on the other side of this debate, too, and we’ve had a lot of discussions. We’ve worked on computational neuroscience at Qualcomm for ten years; not thirty years, but ten years, for sure. We started making artificial brains that were based on the spiking neuron technique, which is a very biologically inspired technique. And again, they are processing machines and they can do many things, but they can’t quite do what a real brain can do.
An example that was given to me was the proof of Fermat’s Last Theorem. If you’re familiar with Fermat’s Last Theorem, it was written down I think maybe two hundred years ago or more, and the creator, Fermat, a mathematician, wrote in the margin of his notebook that he had a proof for it, but then he never got to prove it. I think he lost his life. And it wasn’t until about twenty-some years ago where a researcher at Berkeley finally proved it. It’s claimed that the insight and creativity required to do that work would not be possible by simply assembling a sufficient number of AND gates and training them on previous geometry and math constructs, and then giving it this one and having the proof come out. It’s just not possible. There had to be some extra magic there, which Roger, and others, would argue requires quantum effects. And if you believe that—and I obviously find it very reasonable and I respect these folks, but I don’t claim that my own background informs me enough on that one—it seems very reasonable; it mirrors the experience we had here for a decade when we were building these kinds of machines.
I think we’ve got a way to go before some of these sci-fi type scenarios play out. Not that they won’t happen, but it’s not going to be right around the corner. But what is right around the corner is a lot of greatly improved capabilities as these techniques basically fundamentally replace traditional signal processing for many fields. We’re using it for image and sound, of course, but now we’re starting to use it in cameras, in modems and controllers, in complex management of complex systems, all kinds of functions. It’s really exciting what’s going on, but we still have a way to go before we get, you know, the ultimate.
Back to the theorem you just referenced, and I could be wrong about this, but I recall that he actually wrote a surprisingly simple proof to this theorem, which now some people say he was just wrong, that there isn’t a simple proof for it. But because everybody believed there was a proof for it, we eventually solved it. 
Do you know the story about a guy named Danzig back in the 30s? He was a graduate student in statistics, and his professor had written two famous unsolved problems on the chalkboard and said, These are famous unsolved programs. Well, Danzig comes in late to class, and he sees them and just assumes they’re the homework. He writes them down, and takes them home, and, you can guess, he solves them both. He remarked later that they seemed a little harder than normal. So, he turned them in, and it was about two weeks before the professor looked at them and realized what they were. And it’s just fascinating to think that, like, that guy has the same brain I have, I mean it’s far better and all that, but when you think about all those capabilities that are somewhere probably in there. 
Those are wonderful stories. I love them. There’s one about Gauss when he was six years old, or eight years old, and the teacher punished the class, told everyone to add up the numbers from one to one hundred. And he did it in an instant because he realized that 100 + 0 is 100, and 99 + 1 is 100, and 98 + 2 is 100, and you can multiply those by 50. The question is, “Is a machine based on neural nets, and coefficients, and logistic regression, and SVM and those techniques, capable of that kind of insight?” Likely it is not. And there is some special magic required for that to actually happen.
I will only ask you one more question on that topic and then let’s dial it back in more to the immediate future. You said, “special magic. And again, I have to ask you, like I asked you about “think, are you using magic colloquially, or is it just physics that we don’t understand yet? 
I would argue it’s probably the latter. With the term “magic,” there’s famous Arthur C. Clarke quote that, “Sufficiently advanced technology is indistinguishable from magic.” I think, in this case, the structure of a real brain and how it actually works, we might think of it as magic until we understand more than we do now. But it seems like you have to go into a deeper level, and a simple function assembled from logic gates is not enough.
In the more present day, how would you describe where we are with the science? Because it seems we’re at a place where you’re still pleasantly surprised when something works. It’s like, “Wow, it’s kind of cool, that worked.” And as much as there are these milestone events like AlphaGo, or Watson, or the one that beat the poker players recently, how quickly do you think advances really are coming? Or is it the hope for those advances that’s really kind of what’s revved up?
I think the advances are coming very rapidly, because there’s an exponential nature. You’ve got machines that have processing power which is increasing in an exponential manner, and whether it continues to do so is another question, but right now it is. You’ve got memory, which is increasing in an exponential manner. And then you’ve also got scale, which is the number of these devices that exist and your ability to connect to them. And I’d really like to get into that a little bit, too, the ability of a user to tap into a huge amount of resource. So, you’ve got all of those combined with algorithmic improvements, and, especially right now, there’s such a tremendous interest in the industry to work on these things, so lots of very talented graduates are pouring into the field. The product of all those effects is causing very, very rapid improvement. Even though in some cases the fundamental algorithm might be based on an idea from the 70s or 80s, we’re able to refine that algorithm, we’re able to couple that with far more processing power at a much lower cost than as ever before. And as a result, we’re getting incredible capabilities.
I was fortunate enough to have a dinner with the head of a Google Translate project recently, and he told me—an incredibly nice guy—that that program is now one of the largest AI projects in the world, and has a billion users. So, a billion users can walk around with their device and basically speak any language and listen to any language or read it, and that’s a tremendous accomplishment. That’s really a powerful thing, and a very good thing. And so, yeah, those things are happening right now. We’re in an era of rapid, rapid improvement in those capabilities.
What do you think is going to be the next watershed event? We’re going to have these incremental advances, and there’s going to be more self-driving cars and all of these things. But these moments that capture the popular imagination, like when the best Go player in the world loses, what do you think will be another one of those for the future?
When you talk about AlphaGo and Watson playing Jeopardy and those things, those are significant events, but they’re machines that someone wheels in, and they are big machines, and they hook them up and they run, but you don’t really have them available in the mobile environment. We’re on the verge now of having that kind of computing power, not just available to one person doing a game show, or the Go champion in a special setting, but available to everyone at a reasonable cost, wherever they are, at any time. Also, to be able to benefit, the learning experience of one person can benefit the rest. And so, that, I think, is the next step. It’s when you can use that capability, which is already growing as I described, and make it available in a mobile environment, ubiquitously, at reasonable cost, then you’re going to have incredible things.
Autonomous vehicles is an example, because that’s a mobile thing. It needs a lot of processing power, and it needs processing power local to it, on the device, but also needs to access tremendous capability in the network, and it needs to do so at high reliability, and at low latency and some interesting details there—so vehicles is a very good example. Vehicles is also something that we need to improve dramatically, from a safety standpoint, versus where we are today. It’s critical to the economies of cities and nations, so a lot of scale. So, yeah, that’s a good crucible for this.
But there are many others. Medical devices, huge applications there. And again, you want, in many cases, a very powerful capability in the cloud or in the network, but also at the device, there are many cases where you’d want to be able to do some processing right there, that can make the device more powerful or more economical, and that’s a mobile use case. So, I think there will be applications there; there can be applications in education, entertainment, certainly games, management of resources like power and electricity and heating and cooling and all that. It’s really a wide swath but the combination of connectivity with this capability together is really going to do it.
Let’s talk about the immediate future. As you know, with regard to these technologies, there’s kind of three different narratives about their effect on employment. One is that they’re going to take every single job, everybody from a poet on down; that doesn’t sound like something that would resonate with you because of the conversation we just had. Another is that this technology is going to replace a lot of lowskilled workers, there’s going to be fewer, quote, lowskilled jobs,” whatever those are, and that you’re going to have this permanent underclass of unemployed people competing essentially with machines for work. And then there’s another narrative that says, “No, what’s going to happen is the same thing that happened with electricity, with motors, with everything else. People take that technology they use it to increase their own productivity, and they go on to raise their income that way. And you’re not going to have essentially any disruption, just like you didn’t have any disruption when we went from animal power to machine power. Which of those narratives do you identify with, or is there a different way you would say it?
Okay, I’m glad you asked this because this is a hugely important question and I do want to make some comments. I’ve had the benefit of participating in the World Economic Forum, and I’ve talked to Brynjolfsson and McAfee, the authors of The Second Machine Age, and the whole theme of the forum a year ago was Klaus Schwab’s book The Fourth Industrial Age and the rise of cyber-physical systems and what impact they will have. I think we know some things from history and the question is, is the future going to repeat that or not? We know that there’s the so-called Luddite fallacy which says that, “When these machines come they’re going to displace all the jobs.” And we know that a thousand years ago, ninety-nine percent of the population was involved in food production, and today, I don’t know, don’t quote me on this, but it’s like 0.5 percent or something like that. Because we had massive productivity gains, we didn’t need to have that many people working on food production, and they found the ability to do other things. It’s definitely true that increases in unemployment did not keep pace with increases in productivity. Productivity went up orders of magnitude, unemployment did not go up, quote, “on the orders of magnitude,” and that’s been the history for a thousand years. And even more recently if you look at the government statistics on productivity, they are not increasing. Actually, some people are alarmed that they’re not increasing faster than they are, they don’t really reflect a spike that would suggest some of these negative scenarios.
Now, having said that, it is true that we are at a place now where machines, even with their processing that they use today, based on neural networks and SVMs and things like that, they are able to replace a lot of the existing manual or repetitive type tasks. I think society as a whole is going to benefit tremendously, and there’s going to be some groups that we’ll have to take some care about. There’s been discussions of universal basic incomes, which I think is a good idea. Bill Gates recently had an article about some tax ideas for machines. It’s a good idea, of course. Very hard to implement because you have to define what a robot is. You know, something like a car or a wheel, a wheel is a labor-saving device, do you tax it? I don’t know.
So, to get back to your question, I think it is true that there will be some groups that are in the short term displaced, but there’s no horizon where many things that people do, like caring for each other, like teaching each other, those kinds of jobs are not going away, they’re in ever-increasing demand. So, there’ll be a migration, not necessarily a wholesale replacement. And we do have to take care with the transient effect of that, and maybe a universal type of wage might be part of an answer. I don’t claim to have the answer completely. I mean it’s obviously a really hard problem that the world is grappling with. But I do feel, fundamentally, that the overall effect of all of this is going to be net positive. We’re going to make more efficient use of our resources, we’re going to provide services and capabilities that have never been possible before that everyone can have, and it’s going to be a net positive.
That’s an optimistic view, but it’s a very measured optimistic view. Let me play devil’s advocate from that side to say, why do you think there’ll be any disruption? What does that case look like? 
Because, if you think about it, in 1995 if somebody said, “Hey, you know what, if we take a bunch of computers and we connect them all via TCP/IP, and we build a protocol, maybe HTTP, to communicate, and maybe a markup language like HTMLyou know what’s going to happen? Two billion people will connect and it’s going to create trillions and trillions and trillions of dollars of wealth. It’s going to create Google and eBay and Amazon and Baidu. It’s going to transform every aspect of society, and create an enormous number of jobs. And Etsy will come along, and people will be able to work from home. And all these thousands of things that float out of it.” You never would have made those connections, right? You never would have said, “Oh, that logically flows from snapping a bunch of computers together.” 
So, if we really are in a technological boom that’s going to dwarf that, really won’t the problem be an immense shortage of people? There’s going to be all of these opportunities, and very few people relatively to fill them. So, why the measured optimism for somebody who just waxed so poetic about what a big deal these technologies are?
Okay, that’s a great question. I mean, that was super. You asked will there be any disruption at all. I completely believe that we really have not a job shortage, but a skills shortage; that is the issue. And so, the burden goes then to the educational system, and the fabric of society to be able to place a value on good education and stick to it long enough that you can come up to speed in the modern sense, and be able to contribute beyond what the machines do. That is going to be a shortage, and anyone who has those skills is going to be in a good situation. But you can have disruption even in that environment.
You can have an environment where you have a skills shortage not a job shortage, and there’s disruption because the skills shortage gets worse and there’s a lot of individuals whose previous skills are no longer useful and they need to change. And that’s the tough thing. How do you retrain, in a transient case, when these advancements come very quickly? How do you manage that? What is fair? How does society distribute its wealth? I mean the mechanisms are going to change.
Right now, it’s starting to become true that just simply the manner in which you consume stuff; if that data is available, that has value in itself, and maybe people should be compensated for it. Today, they are not as much, they give it up when they sign in to these major cloud player services, and so those kinds of things will have to change. I’ll give you an anecdote.
Recently I went to Korea, and I met some startups there, and one of the things that happens, especially in non-curated app stores, is people develop games and they put in their effort and time and they develop a game, and they put it on there and people download it for ninety-nine cents or whatever, and they get some money. But, there are some bad actors that will see a new game, they’ll quickly download it, un-assemble the language back to the source, change a few little things and republish that same game that looks and feels just like the original but the ninety-nine cents goes to a different place. They basically steal the work. So, this is a bad thing, and in response, there are startups now that make tools that create software that makes it difficult to un-assemble. There are multiple startups that do what I just described and I’m sitting here listening to them and I’m realizing, “Wow, that job—in fact, that industry—didn’t even exist.” That is a new creation of the fact that there are un-curated app stores and mobile devices and games, and it’s an example of the kind of new thing that’s created, that didn’t exist before.
I believe that that process is alive and well, and we’re going to continue to see more of it, and there’s going to continue to be a skills shortage more than a job shortage, and so that’s why I have a fundamentally positive view. But it is going to be challenging to meet the demands of that skills shortage. Society has to place the right value on that type of education and we all have to work together to make that happen.
You have two different threads going on there. One is this idea that we have a skills shortage, and we need to rethink education. And another one that you touched on is the way that money flows, and can people be compensated for their data, and so forth. I’d like to talk about the first one, and again, I’d like to challenge the measured amount of your optimism. 
I’ll start off by saying I agree with you, that, at the beginning of the Industrial Revolution there was a vigorous debate in the United States about the value of post-literacy education. Like think about that: ipost-literacy education worth anything? Because in an agrarian society, maybe it wasn’t for most people. Once you learn to read, that was what you needed. And then people said, “No, no, the jobs of the future are going to need more education. We should invest in that now.” And the United States became the first country in the world to guarantee that every single person could graduate from high school. And you can make a really good case, that I completely believe, that that was a major source of our economic ascendancy in the twentieth century. And, therefore, you can extend the argument by saying, “Maybe we need grades thirteen and fourteen now, and they’re vocational, and we need to do that again. I’m with you entirely, but we don’t have that right now. And so, what’s going to happen? 
Here is where I would question the measured amount of your optimism which is… People often say to me, “Look, this technology creates all these new jobs at the high-end, like graphic designers and geneticists and programmers, and it destroys jobs at the low-end. Are those people down at the low-end going to become programmers?” And, of course, the answer is not, “Yes.” The answer isand here’s my questionall that matters is, “Can everybody do a job just a little harder than the one they’re currently doing? And if the answer to that is, “Yes, then what happens is the college biology professor becomes a geneticist, the high school biology teacher becomes a college teacher, the substitute teacher gets backfilled into the biology one, and all the way down so that everybody gets just a little step up. Everybody just has to push themselves a little more, and the whole system phase shifts up, and everybody gets a raise and everybody gets a promotion. That‘s really what happened in the Industrial Revolution, so why is it that you don’t think that that is going to be as smooth as I have just painted it? 
Well, I think what you described does happen and is happening. If you look at—and again, I’m speaking from my own experience here as an engineer in a high-tech company—any engineer in a high-tech company, and you look at their output right now, and you compare it to a year or two before, they’ve all done what you describe, which is to do a little bit more, and to do something that’s a little bit harder. And we’ve all been able to do that because the fundamental processes involved improve. The tools, the fabric available to you to design things, the shared experience of the teams around you that you tap into—all those things improved. So, everyone is actually doing a job that’s a little bit harder than they did before, at least if you’re a designer.
You also cited some other examples, a teacher at one level going to the next level. That’s a kind of a queue, and there’s only so many spots at so many levels based on the demographics of the population. So not everyone can move in that direction, but they can all—at a given grade level—endeavor to teach more. Like, our kids, the math they do now is unbelievable. They are as much as a year or so ahead of when I was in high school, and I thought that we were doing pretty good stuff then, but now it’s even more.
I am optimistic that those things are going to happen, but you do have a labor force of certain types of jobs, where people are maybe doing them for ten, twenty, thirty years, and all of a sudden that is displaced. It’s hard to ask someone who’s done a repetitive task for much of their career to suddenly do something more sophisticated and different. That is the problem that we as a society have to address. We have to still value those individuals, and find a way—like a universal wage or something like that—so they can still have a good experience. Because if you don’t, then you really could have a dangerous situation. So, again, I feel overall positive, but I think there’s some pockets that are going to require some difficult thinking, and we’ve got to grapple with it.
Alright. I agree with your overall premise, but I will point out that that’s exactly what everybody said about the farmers—that you can’t take these people that have farmed for twenty or thirty years, and all of a sudden expect them to be able to work in a factory. The rhythm of the day is different, they have a supervisor, there’s bells that ring, they have to do different jobs, all of this stuff; and yet, that’s exactly what happened. 
I think there’s a tendency to short human ability. That being said, technological advance, interestingly, distributes its financial gains in a very unequal measure and there is something in there that I do agree we need to think about. 
Let’s talk about Qualcomm. You are the EVP of technology. You were the CTO. You’ve got seventy patents, like I said in your intro. What is Qualcomm’s role in this world? How are you working to build the better tomorrow? 
Okay, great. We provide connections between people, and increasingly between their worlds and between devices. Let me be specific about what I mean by that. When the company started—by the way, I’ve been at Qualcomm since ‘91, company started in ‘85-‘86 timeframe—one of the first things we did early on was we improved the performance and capacity of cellular networks by a huge amount. And that allowed operators like Verizon, AT&T, and Sprint—although they had different names back then—to offer, initially, voice services to large numbers of people at reasonably low cost. And the devices, thanks to the work of Qualcomm and others, got smaller, had longer battery life, and so forth. As time went on, it was originally connecting people with voice and text, and then it became faster and more capable so you could do pictures and videos, and then you could connect with social networks and web pages and streaming, and you could share large amounts of information.
We’re in an era now where I don’t just send a text message and say, “Oh, I’m skiing down this slope, isn’t this cool.” I can have a 360°, real-time, high-quality, low-latency sharing of my entire experience with another user, or users, somewhere else, and they can be there with me. And there’s all kinds of interesting consumer, industrial, medical, and commercial applications for that.
We’re working on that and we’re a leading developer of the connectivity technology, and also what you do with it on the endpoints—the processors, the camera systems, the user interfaces, the security frameworks that go with it; and now, increasingly, the machine learning and AI capabilities. We’re applying it, of course, to smartphones, but also to automobiles, medical devices, robotics, to industrial cases, and so on.
We’re very excited about the pending arrival of what we call 5G, which is the next generation of cellular technology, and it’s going to show up in the 2019-2020 timeframe. It’s going to be in the field maybe ten, fifteen years just like the previous generations were, and it’s going to provide, again, another big step in the performance of your radio link. And when I say “performance,” I mean the speed, of course, but also the latency will be very low—in many modes it can be millisecond or less. That will allow you to do functions that used to be on one side of the link, you can do on the other side. You can have very reliable systems.
There are a thousand companies participating in the standards process for this. It used to be just primarily the telecom industry, in the past with 3G and 4G—and of course, the telecom industry is very much still involved—but there are so many other businesses that will be enabled with 5G. So, we’re super excited about the impact it’s going to have on many, many businesses. Yeah, that’s what we’re up to these days.
Go with that a little more, paint us a picture. I don’t know if you remember those commercials back in the 90s saying, “Can you imagine sending a fax from the beach? You will!” and other “Can you imagine” scenarios. They kind of all came trueother than that there wasn’t as much faxing as I think they expected. But, what do you think? Tell me some of the things that you thinkin a reasonable amount of time, we’re going to be able to do it, in five years, let’s say.
I’m so fascinated that you used that example, because that one I know very well. Those AT&T commercials, you can still watch them on YouTube, and it’s fun to do so. They did say people will be able to send a fax from the beach, and that particular ad motivated the operators to want to send fax over cellular networks. And we worked on that—I worked on that myself—and we used that as a way to build the fundamental Internet transport, and the fax was kind of the motivation for it. But later, we used the Internet transport for internet access and it became a much, much bigger thing. The next step will be sharing fully immersive experiences, so you can have high-speed, low-latency video in both directions.
Autonomous vehicles, but before we even get to fully autonomous—because there’s some debate about when we’re going to get to a car that you can get into with no steering wheel and it just takes you where you want to go; that’s still a hard problem. Before we have fully autonomous cars that can take you around without a steering wheel, we’re going to have a set of technologies that improve the safety of semiautonomous cars. Things like lane assist, and better cruise control, and better visibility at night, and better navigation; those sorts of things. We’re also working on vehicle-to-vehicle communication, which is another application of low-latency, and can be used to improve safety.
I’ll give you a quick anecdote on that. In some sense we already have a form of it, it’s called brake lights. Right now, when you’re driving down the highway, and the car in front puts on the lights, you see that and then you take action, you may slow down or whatever. You can see a whole bunch of brake lights, if the traffic is starting to back up, and that alerts you to slow down. Brake lights have transitioned from incandescent bulbs which take, like, one hundred milliseconds to turn on to LED bulbs which take one millisecond to turn on. And if you multiply a hundred milliseconds at highway speeds, it’s six to eight feet depending on the speed, and you realize that low-latency can save lives, and make the system more effective.
That’s one of the hallmarks of 5G, is we’re going to be able to connect things at low-latency to improve the safety or the function. Or, in the case of machine learning, where sometimes you want processing to be done in the phone, and sometimes you want to access enormous processing in the cloud, or at the edge. When we say edge, in this context, we mean something very close to the phone, within a small number of hops or routes to get to that processing. If you do that, you can have incredible capability that wasn’t possible before.
To give you an example of what I’m talking about, I recently went to the Mobile World Congress America show in San Francisco, it’s a great show, and I walked through the Verizon booth and I saw a demonstration that they had made. In their demonstration, they had taken a small consumer drone, and I mean it’s a really tiny one—just two or three inches long—that costs $18. All this little thing does is send back video, live video, and you control it with Wi-Fi, and they had it following a red balloon. The way it followed it was, it sent the video to a very powerful edge processing computer, which then performed a sophisticated computer vision and control algorithm and then sent the commands back. So, what you saw was this little low-cost device doing something very sophisticated and powerful, because it had a low-latency connection to a lot of processing power. And then, just to really complete that, they switched it from edge computing, that was right there at the booth, to a cloud-based computing service that was fifty milliseconds away, and once they did that, the little demo wouldn’t function anymore. They were showing the power of low-latency, high-speed video and media-type communication, which enabled a simple device to do something similar to a much more complex device, in real time, and they could offer that almost like a service.
So, that paradigm is very powerful, and it applies to many different use cases. It’s enabled by high-performance connectivity which is something that we supply, and we’re very proficient at that. It impacts machine learning, because it gives you different ways to take advantage of the progress there—you can do it locally, you can do it on the edge, you can do it remotely. When you combine mobile, and all the investment that’s been made there, you leverage that to apply to other devices like automobiles, medical devices, robotics, other kinds of consumer products like wearables and assistant speakers, and those kinds of things. There’s just a vast landscape of technologies and services that all can be improved by what we’ve done, and what 5G will bring. And so, that’s why we’re pretty fired up about the next iteration here.
I assume you have done theoretical thinking about the absolute maximum rate at which data can be transferred. Are we one percent the way there, or ten percent, or can’t even measure it because it’s so smallIs this going to go on forever?
I am so glad you asked. It’s so interesting. This Monday morning, we just put a new piece of artwork in our research center—there’s a piece of artwork on every floor—and on the first floor, when you walk in, there’s a piece of artwork that has Claude Shannon and a number of his equations, including the famous one which is the Shannon capacity limit. That’s the first thing you see when you walk into the research center at Qualcomm. That governs how fast you can move data across a link, and you can’t beat it. There’s no way, any more than you can go faster than the speed of light. So, the question is, “How close are we to that limit?” If you have just two devices, two antennas, and a given amount of spectrum, and a given amount of power, then we can get pretty darn close to that limit. But the question is not that, the question is really, “Are we close to how fast of a service we can offer a mobile user in a dense area?” And to that question, the answer is, “We’re nowhere close.” We can still get significantly better; by that, I mean orders of magnitude better than we are now.
I can tell you three ways that that can be accomplished, and we’re doing all three of them. Number one is, we continue to make better modems, that are more efficient, better receivers, better equalizers, better antennas all of those techniques, and 5G is an example of that.
Number two, we always work with the regulator and operators to bring more spectrum, more radio spectrum to bear. If you look at the overall spectrum chart, only a sliver of it is really used for mobile communication, and we’re going to be able to use a lot more of it, and use more spectrum at high frequencies, like millimeter wave and above, that’s going to make a lot more “highway,” so to speak, for data transfer.
And the third thing is, the average radius of a base station can shrink, and we can use that channel over and over and over again. So right now, if you drive your car, and you listen to a radio station, the radio industry cannot use that channel again until you get hundreds of miles away. In the modern cellular systems, we’re learning how to reuse that channel even when you’re a very short distance away, potentially only feet or tens of meters away, so you can use it again and again and again.
So, with those three pillars, we’re really not close, and everyone can look forward to faster, faster, faster modems. And every time we move that modem speed up, that, of course, is the foundation for bigger screens, and more video, and new use cases that weren’t possible before, at a given price point, which now become possible. We’re not at the end yet, we’ve got a long way to go.
You made a passing reference to Moore’s Lawyou didn’t call it out, but you referenced exponential growth, and that the speed of computers would increase. Everybody always says, Is Moore’s Law finally over? You see those headlines all the time, and, like all the headlines that are a question, the answer is almost always, “No. You’ve made references to quantum computing and all that. Do we have opportunities to increase processor speed well into the future with completely different architectures?
We do. We absolutely do. And I believe that will occur. I mean, we’re not at the limit yet now. You can find “Moore’s Law is over” articles ten years ago also, and somehow it hasn’t happened yet. When we get past three nanometers, yeah, certain things are going to get really, really tough. But then there will be new approaches that will take us there, take us to the next step.
There’s also architectural improvements, and other axes that can be exploited; same thing as I just described to you in wireless. Shannon has said that we can only go so far between two antennas in a given amount of spectrum, in a given amount of power. But we can escape that by increasing the spectrum, increasing the number of distance between the antennas, reusing the spectrum over and over again, and we can still get the job done without breaking any fundamental laws. So, at least for the time being, the exponential growth is still very much intact.
You’ve mentioned Claude Shannon twice. He’s a fascinating character, and one of the things he did that’s kind of monumental was that paper he wrote in 49 or 50 about how a computer could play chess, and he actually figured out an algorithm for that. What was really fascinating about that was, this was one of the first times somebody looked at a computer and saw something other than a calculator. Because up until that point they just did not, and he made that intuitive leap to say, “Here’s how you would make a computer do something other than mathbut it’s really doing math. There’s a fascinating new book about him out called A Mind at Play, which I just read, that I recommend. 
We’re running out of time here. We’re wrapping up. I’m curious do you write, or do you have a place that people who want to follow you can keep track of what you’re up to? 
Well, I don’t have a lot there, but I do have a Twitter, and once in a while I’ll share a few thoughts. I should probably do more of that than I do. I have an internal blog which I should probably do more than I do. I’m sorry to say, I’m not very prolific on external writing, but that is something I would love to do more of.
And my final question is, are you a consumer of science fiction? You quoted Arthur C. Clarke earlier, and I’m curious if you read it, or watch TV, or movies or what have you. And if so, do you have any visions of the future that are in fiction, that you kind of identify with? 
Yes, I will answer an emphatic yes to that. I love all forms of science fiction and one of my favorites is Star Trek. My name spelled backwards is “Borg.” In fact, our chairman Paul Jacobs—I worked for him most of my career—he calls me “Locutus.” Given the discussion we just had—if you’re a fan of Star Trek and, in particular, the Star Trek: The Next Generation shows that were on in the ‘80s and early ‘90s, there was an episode where Commander Data met Mr. Spock. And that was really a good one, because you had Commander Data, who is an android and wants to be human, wants to have emotion and creativity and those things that we discussed, but can’t quite get there, meeting Mr. Spock who is a living thing and trying to purge all emotion and so forth, to just be pure logic, and they had an interaction. I thought that was just really interesting.
But, yes, I follow all science fiction. I like the book Physics of Star Trek by Krauss, I got to meet him once. And it’s amazing how many of the devices and concepts from science fiction have become science fact. In fact, the only difference between science fiction and science fact, is time. Over time we’ve pretty much built everything that people have thought up—communicators, replicators, computers.
I know, you can’t see one of those in-ear Bluetooth devices and not see Uhura, right? That’s what she had.
Correct. That little earpiece is a Bluetooth device. The communicator is a flip phone. The little square memory cartridges were like a floppy disk from the ‘80s. 3-D printers are replicators. We also have software replicators that can replicate and transport. We kind of have the hardware but not quite the way they do yet, but we’ll get there.
Do you think that these science fiction worlds anticipate the world or inadvertently create it? Do we have flip phones because of Star Trek or did Star Trek foresee the flip phone? 
I believe their influence is undeniable.
I agree and a lot of times they say it, right? They say, “Oh, I saw that and I wanted to do that. I wanted to build that.” You know there’s an XPRIZE for making a tricorder, and that came from Star Trek.
We were the sponsor of that XPRIZE and we were highly involved in that. And, yep, that’s exactly right, the inspiration of that was a portable device that can make a bunch of diagnoses, and that is exactly what took place and now we have real ones.
Well, I want to thank you for a fascinating hour. I want to thank you for going on all of these tangents. It was really fascinating. 
Wonderful, thank you as well. I also really enjoyed it, and anytime you want to follow up or talk some more please don’t hesitate. I really enjoyed talking with you.
Byron explores issues around artificial intelligence and conscious computers in his upcoming book The Fourth Age, to be published in April by Atria, an imprint of Simon & Schuster. Pre-order a copy here.
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LinkedIn expands Lynda.com to Roku with new learning channel

LinkedIn is expanding its Lynda.com platform to Roku devices, and in doing so it might prove streaming video services can be more than mindless entertainment.
First some background. LinkedIn spent $1.5 billion to buy Lynda.com in April. The platform boasts more than 4,000 courses featuring 150,000 videos made by expert instructors, and despite an emphasis on high production values, LinkedIn said in an email that it’s adding more lessons to the platform every single day.

A shot of Lynda's new channel on Roku set-top boxes.

A shot of Lynda’s new channel on Roku set-top boxes.


The app available on Roku devices will provide access to all of these videos. It will even synchronize a user’s position in various lessons across devices, so they don’t have to worry about losing their place if they move from a TV to a laptop. The catch: Most videos are exclusive to members who pay $20 to $35 per month.
“Our goal is to extend the Lynda.com footprint and create a new channel for users to engage with our content, while providing a consistent and seamless experience across multiple screens,” a LinkedIn spokesperson said. “Now you or your family members can learn new skills from the comfort of your couch.”
Or they could do something cheaper. They could get access to countless movies and television shows from Netflix for $10. They could watch commercial-free television on Hulu for $12. Hell, they could even get access to HBO’s original programming and videos unavailable on other streaming services for just $15.
Compare that to the $25 a single month of Lynda.com access costs — the lower $20 price is for people who pay for the service annually instead of monthly — and it’s easy to see where a budget-conscious person might choose to spend their money. How’s education supposed to compete with endless entertainment?
There are some real benefits to having an app available for set-top boxes, prime among them is the ability to follow along with a lesson on a laptop without having to switch between multiple windows. It could also help more people learn about a skill in a group setting instead of being an otherwise individual activity.
Existing subscribers to Lynda.com might rejoice at being able to view the platform’s lessons on television sets. But with a monthly fee that could cover two other streaming services (almost three for Lynda.com’s premium members) it’s hard to see the Roku expansion getting more people to sign up to the platform.
That might change if Lynda.com’s subscriptions ever fall in price. Until then, however, it looks like the mindless entertainers are going to remain undefeated.

How PenPal Schools could change what we expect from education

There was a time, back in the early 90’s, in the days of AOL, You’ve Got Mail, and dial-up modems, when something of a utopian future and/or shared delusion existed around the Internet. We’d envisioned it as the realization of the EPCOT dream — a connected world with no borders in which we’d be able to reach, interact with, and learn from one another without barriers. In reality, a look at nearly any comments section will quickly zap much of your remaining optimism about the benefits of this so-called open forum.
However, education startup PenPal Schools is looking to make good on those early promises by bringing back one key component that technology seems to have eclipsed: the human element.
The startup offers an online platform used by over 70,000 pen pals in over 90 countries that connects students and individual learners with pen pals in other states or countries. It’s free and built for use by any and everyone who wants to participate in an exchange, whether it’s through a class at school or on an individual level. The goal of the service is to provide students with coursework that will expand their education while also providing insight into the culture, lives, and learning process of students in another region.
“We see our program as oftentimes so eye-opening for students, and it’s their first glimpse into culture and understanding a way of life so different from our own,” says PenPal Schools founder Joe Troyen, adding that the startup recently rolled out a suite of new apps and features for the education platform that reinforces a mobile-first strategy that takes into account the limited Internet connectivity throughout the world’s many classrooms.
Pen pal exchanges have been a great way to connect people from across cultures for decades, and it’s on the foundation of exchanges like those that society built early universities and formal education. Troyen says the platform his startup has developed is no different from the collaborative exchanges of yore, except that technology has allowed for innovation focused on the education aspect. “[One] big innovation is curriculum. We connect students to not only write back and forth to each other as they did in the old days, but also to learn together through online, interactive courses,” he says.

Beyond textbooks and news articles

PenPal Schools offers several courses that focus on current events, culture and traditions, and the historical struggle against discrimination. In these courses, learners are paired up with a pen pal from another state or country who is taking the same course. Through correspondence that revolves around a guided curriculum, learners can exchange ideas and perspectives around certain topics and content.
PenPalSchools_Argentina_Studentsedit
Troyen gives me the example of Brendan from New Jersey and Moneer from Kabul, Afghanistan. Through their guided exchanges, they discussed news items and current events where they live. One of the topics of conversation? Ongoing U.S. presence in Afghanistan. Because their personal experiences with the war in the Middle East are dramatically different, Brendan began to view the war in a new light. On the flip side, Moneer got some insight into the way the war is perceived by many in the United States and helped Brendan gain a new understanding of what, exactly, U.S. troops were doing in Afghanistan and why they were doing it.
The obvious question is this: how, exactly, does PenPal Schools improve upon the age-old, time-honored tradition of simply writing letters? Surely there are other places connecting pen pals digitally in the name of swapping knowledge. How’s this any different? While there are other sites matching up pen pals, the PenPal Schools difference lies in the way in which they’re leveraging technology and simplicity to create the best platform for both connecting and learning.
“PenPal Schools is the first to combine high quality curriculum and the best technology with multi-week 1-to-1 pen pal exchanges, which all adds up to a great experience for learners,” says Troyen. “We’re focused on providing a simple, fun experience with the kind of support students and teachers can’t find anywhere else.”
The proof, as they say, is in the pudding. Or, in this case, in the completion rate. While most online courses see a completion rates under 20 percent, the average rate for PenPal Schools is at 88 percent, the company tells me.
In taking courses through PenPal Schools, students receive weekly assignments replete with instructional texts, videos, and prompts designed to kick-start the conversation. From there, pen pals communicate via a chat-like interface. There’s no limit to the number of students who can take a course at a time, and students from all over the world can participate. For security reasons, classroom students are paired with other classroom students while individuals are paired up with other individuals. No personally identifying information is exchanged or revealed, and pen pals are always matched with someone close to his or her own age.
For now, all communication is written, but looking forward, Troyen says that PenPal Schools plans to offer video messaging and collaborative tools. That seems fairly logical, considering the penetration mobile chat apps (WhatsApp, Snapchat, Kik, Facebook Messenger, etc.) have had in the last couple years, especially as many of those apps attempt to integrate ways to follow and discuss the news directly from those digital conversations.
“We’ll continue to focus on asynchronous communication because it’s easier for teachers to coordinate, works across time zones, enables students to learn at their own pace, and meet the needs of learners who may not always have reliable internet access,” says Troyen.

Pulling a “TOMS Shoes” for education

Speaking of access, not every student or school has the funds available to participate in such a country-scaling education platform. Yet, if money is the main barrier to entry, PenPal Schools wouldn’t be nearly as potent as it would limit the diverse background of students.
Troyen also mentions that the plan going forward is to offer premium courses for a fee. While all of PenPal Schools’ original courses will remain on offer for free, these courses will offer premium features and content with the help of partners like textbook publishers. The fee structure will be designed around the concept of “buy one, give one”, meaning that when someone pays the fee for a premium course, a student who may not otherwise have access to the funds necessary to enroll will be able to participate.
And participation certainly seems to be enjoying some seriously mounting interest. Troyen tells me that just last week, nearly 200 new teachers from more than 20 different countries enrolled in PenPal Schools. The vast majority of PenPal Schools’ growth comes through word-of-mouth amongst teachers, making educators by far one of its most valuable assets.
The startup’s monetization strategy also involves partnerships with well-known education publishing companies, with PenPal Schools collaborating to create courses that compliment the learning process from teacher instruction, textbooks, and other interactive lessons. (For example, you’d gain access to a specific PenPal Schools course when purchasing a new set of textbooks for a class.) Beyond that, the startup also wants to move into new subjects to generate additional revenue.
Although the current crop of courses focus on history, culture, and current events, Troyen says PenPal Schools will soon offer new classes for persuasive writing and language-learning. And in the future, PenPal Schools courses could expand to non-traditional subjects, like music and cooking.

These cities should follow de Blasio’s plan for computer science education

Only three major cities in the country seem interested in advancing education so their students will have a better shot at co-mingling with their robot bosses. That will have to change as technical knowledge becomes more important to people in the workforce — and as cities around the United States try to become hubs for the startups attempting to produce new and innovative technologies.
First, some backstory. A new education plan from New York City Mayor Bill de Blasio has been announced, and in addition to boosting graduation rates, it will require schools in the city to offer computer science courses within the decade. The courses won’t be mandatory, like they will be in San Francisco or Chicago, but students will at least have the option of signing up for the classes.
An important part of de Blasio’s plan involves expanding school budgets. Capital reports that schools will be given $81 million over a ten-year period to comply with this new requirement. That could help fix one of the biggest reasons many schools don’t have these courses already — dwindling budgets.
As I wrote when Google and Gallup said earlier this year that many students aren’t able to take any classes related to this subject despite parental interest:

More students qualify for free or reduced-price meals at school (a sign of belonging to a low income family) than ever before. Yet the schools these children attend receive less than their fair share of state or federal funding, according to a 2011 report published by the US Department of Education.

That could help explain why many superintendents who responded to the survey said there isn’t enough money to train or hire a teacher (57 percent); nor a sufficient budget to purchase necessary equipment (31 percent) or software  (33 percent); nor enough equipment (20 percent) or software (27 percent) already in their schools for them to introduce computer science courses.

All of which got me thinking: What other cities might benefit from expanding their school budgets for computer science classes? And, since the answer is likely all of them, which cities with expanding tech communities fit the bill?

To answer that, I looked at the U.S. Census Bureau data for several cities known for their startup communities, or for their potential growth in the sector. Some are more established (Chicago, Boulder) while others are just starting to be recognized as potential tech hubs (Atlanta, Nashville) by the wider industry.

I was looking for one statistic in particular: The percentage of households within those cities below the poverty line. Gallup’s survey found that many poor parents want their children to learn computer science skills — ostensibly so their kids will have opportunities that would otherwise be unavailable to them — and that those schools are the least equipped to offer those courses.

What I found is that a larger-than-average percentage of families in these cities live in poverty. Nashville and Austin fared the best, with 18.9 and 19.1 percent, respectively, of their population falling below the poverty line. That’s slightly more than the country’s average, which the census bureau pegs at 14.5 percent.

Cities like Boulder, Chicago, and Atlanta didn’t fare so well — between 22.6 and 25 percent of their population lives in poverty. That doesn’t come as much of a surprise, given reports that 51 percent of students lived in poverty during the 2012-2013 school year, but that clearly doesn’t make it any less of a problem.

All of these cities have, to varying degrees, become known for fostering tech communities. Perhaps allocating more resources to teaching children the skills that will quickly become necessary for them to hold well-paying jobs could help them bridge the gaps between them and more-established startup hubs.

Though I suppose each of them is off to a better start than Irving, Texas, which handcuffed a ninth-grader for bringing a homemade clock to school. That might not count for much, but it’s good to know there’s space between Irving and New York. That makes the dismal state of computer science teaching seem a smidgen less awful.

ScholarshipOwl uses big data, machine learning to fix the convoluted scholarship application process

Earlier this year, a bipartisan bill was put forward in Congress to fix one of the biggest impediments preventing hopeful American high school students from receiving an affordable higher education: the Free Application for Federal Student Aid, otherwise known as FAFSA.
Although it sounds ludicrous, the 10-page, 100 question document, which students (or, more likely, their families) are expected to complete in order to receive government-backed college grants or qualify for loans, has become so burdensome that some 2 million students who would have qualified for Pell grants in 2011 and 2012 did not file a FAFSA form, according to voxgov.com.
As a recent New York Times piece on the ridiculous financial aid form put it, “The Fafsa burdens families and prevents students from attending college, while doing little to target federal aid.” The bill, sponsored by Sen. Lamar Alexander (R-Tenn.) and Sen. Michael Bennet (D-Colo.), would reduce the complicated form down to two questions, a move that would likely lead to more applicants as well as more grants and loans being distributed.
However, purely bureaucratic means aren’t the only way that some are trying to make an affordable college education more accessible. Kenny Sandorffy and his team at ScholarshipOwl are trying to leverage big data and machine learning to make students more aware of the scholarships that they may qualify for, but don’t even know about.
The Tel Aviv-founded company, which has its U.S. headquarters in Santa Monica, has simplified what was almost an impossible task for individuals looking to find ways to make higher education — which now has an average price tag of about $30,000 per year. It takes a few data points — questions answered by students looking for scholarships — and then matches its users with the more than 3.5 million possible scholarships that they may qualify for.
As Sandorffy told me, as users add more information to their profile, the potential scholarships that may be available to them become more personalized and expansive.
What’s more telling is that ScholarshipOwl also streamlines the application process for most of the scholarships it presents to qualifying students on its site. (Some scholarships that require specific essays as part of the application process can also be completed through the site.)
Additionally, the company is hoping to expand upon its existing features by implementing an automatically recurring process for applications that need to be renewed. As Sandorffy explained, some scholarships can be reapplied for every month, which many applicants do not know, so ScholarshipOwl will complete the renewal process for its users to get them more tuition savings.
Sandorffy took up the crusade to find a better way to discover and apply for scholarships after his own personal frustrations with the process. Looking into the problem led him to start a blog that covered different types solutions available for finding ways to lower the high cost of college education; as part of the blog project, Sandorffy would write about scholarships and grants that many students weren’t aware of as well as tips and tricks for applying.
“One thing led to another, and while writing and researching about scholarships, I started to wonder why there wasn’t a process to make it easier for students to get scholarships,” Sandorffy said.
“Why don’t more students have access to the $16 billion that is given out every year in the U.S. for scholarships and grants, especially the one’s who need it?” he said. “I’ve come to realize that the inequality comes from a lack of connection. Students who need scholarships the most are the one’s who have the least amount of time to complete the process.”
So ScholarshipOwl was created to automate the entire process to solve the problem.
“At the end of the day, we want more students applying and getting scholarships,” Sandorffy said.

Here’s why American students don’t learn computer science

America’s youth isn’t getting a decent education when it comes to the basics of technology, and now we’re seeing some data on why that’s the case.
A survey conducted by Google and Gallup shows that many Americans believe computer science should be taught between kindergarten and the 12th grade. Yet most schools don’t offer the courses due to budget constraints, a lack of teachers, and the need to focus more on subjects included in standardized tests.
The results are another mark against standardized tests, which have become a point of contention among parents, students, teachers, principals, and essentially anyone else who doesn’t profit off their continued existence. Yet these reviled constructs aren’t the only cause of computer science courses’ woes.
Another problem might be the lack of communication between administrators, parents, students, and teachers. The survey showed that 91 percent of parents want their children to learn computer science; less than 8 percent of principals thought demand for the courses was that high. That can’t be blamed on tests — it’s simply the byproduct of a good-ol’ fashioned breakdown in communication.
The rising number of low-income students also contributes to the problem. More students qualify for free or reduced-price meals at school (a sign of belonging to a low income family) than ever before. Yet the schools these children attend receive less than their fair share of state or federal funding, according to a 2011 report published by the US Department of Education.
That could help explain why many superintendents who responded to the survey said there isn’t enough money to train or hire a teacher (57 percent); nor a sufficient budget to purchase necessary equipment (31 percent) or software  (33 percent); nor enough equipment (20 percent) or software (27 percent) already in their schools for them to introduce computer science courses.
All those factors combine to create a system where computer science is limited to students privileged enough to belong to schools that value the subject, have the equipment necessary to teach it, and reliable Internet access they can use to complete any homework. The barriers to computer science being taught more widely don’t end with schools; they extend into student’s home lives, too.
None of these problems are unique to computer science. The influence of standardized tests, budget shortfalls, and a student’s lack of resources at home aren’t limited to this one aspect of education held near-and-dear by the tech industry’s top companies. They pervade every aspect of America’s education system — and that means introducing computer science courses shouldn’t necessarily be a goal unto itself, but should instead be another bullet point in any argument meant to overhaul much of this country’s education system.

Education startup Galvanize buys data science school Zipfian Academy

An education startup called Galvanize, which focuses on tech workers and entrepreneurs, has acquired a San Francisco company called Zipfian Academy that offers a 12-week program in data science. Zipfian’s instructors have data analysis and engineering backgrounds at a variety of companies ranging from software startups to Facebook. One of them, Adam Gibson, is the founder of a deep learning startup called Skymind. Galvanize currently has locations in San Francisco, Denver and Boulder, Colorado, and will offer the Zipfian program, as well as a new master’s degree in big data, at the San Francisco campus.