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Journalist Markham Hislop interviews leading energy experts from around the world about the energy transition and climate change.
Welcome to episode 285 of the Energy Talks podcast. I'm energy and climate journalist, Markham Hislop. My guest today is highly influential among energy systems thinkers. By that I mean folks who grapple with the enormous complexity of the modern energy system and the best way to navigate the global energy transition. Among other positions, Doctor.
Markham:Duane Farmer is the Bayley Gifford Professor of Complex Systems Science at the Smith School of Enterprise and the Environment at Oxford University. He's the author of Making Sense of Chaos, A Better Economics for a Better World that will be published by Alan Lane on April 25th. Welcome to the interview, doctor Farmer.
Doyne:Thank you.
Markham:I'm fascinated by this because so many of my, acquaintances within the energy space speak very highly of your work, and they often talk about the importance of integrating systems thinking into policy making. And I asked for an interview because a particularly someone I respect quite a bit suggested that I that I do so, and I come at this as someone who is understands the, energy, but not necessarily energy systems thinking. And so I and I suspect that many of my readers and listeners are the same. So I'm wondering if we can start with some general discussion of complexity, theory, systems thinking, and then more for, you know, segue into a discussion of how that might apply to the global energy system and the energy transition, if that works for you.
Doyne:Sure. That sounds fine. So complex systems is about a complex system science is about understanding what we call emergent phenomena. So an emergent phenomenon is one that happens when the building blocks generate behavior that's qualitatively different from themselves. So easy example, a neuron, it's a complicated cell, but no one would ever argue a neuron was conscious.
Doyne:Yet you hook 80,000,000,000 of them together in the right way, and you get this conversation we're having. So you have an emergent phenomenon that just looks qualitatively different from what's underneath it. Lots of other examples, ant colonies. And and even simpler examples, sometimes the weather can be an emergent phenomenon because how do you get hurricanes and droughts and all the things you get from a situation where you have a very steady changing of the forces acting on the earth, causing consequences that seem hard to infer from what you put in. So the key issue is that because it is a system and because the components of the system can interact with each other to create in nontrivial ways to create rich phenomena.
Doyne:You really have to understand the system properties of these kind of things to get at the basis of what's going on. And the economy is, of course, is a very great example of a complex system.
Markham:In your work, you've done some very interesting things like, there was, I was reading on some of your back your background systems or or, yeah, systems, we'll call them, in order to, predict the stock market or to to pick stocks, that sort of thing. Is that a practical application of the general principle?
Doyne:Well, I have to say it was more just I I mean, I did maybe just to clarify your remark. I I was involved in starting one of the early quant trading firms that actually operated out of Santa Fe, New Mexico. And we did beat the market quite substantially and consistently. You know, we did view it as a system, but we a lot of it was about pattern recognition. To us, we didn't know much about stocks and what makes them go up and down.
Doyne:They were just data streams, and we spotted things in those data streams that were out of the ordinary in such a way that when we saw one set of indicators line up, we knew something else was about to follow. We just thought of some clever ways to search through the data to find those kind of events.
Markham:That sounds like the kind of, big data analytics, number crunching that we're seeing more and more in industry. For Exactly. Predictive analytics, that sort of thing?
Doyne:We were one of the early examples of big data and using serious computer power to milk knowledge out of big data.
Markham:So you were talking about, well, I guess what I would call an anomalies that that, emerge out of these complex systems. And what role would human innovation play, in a, you know, in complexity theory and in in systems?
Doyne:Well, human innovation is certainly one of the things that we're very understanding how it comes about, understanding its characteristics, and and something I've been involved in quite a lot is trying to understand technological progress. You you might think, oh, innovation, we can't predict it. But, actually, in some cases, we can't we can't predict what the innovations will be, but we can predict how fast things will progress. Moore's law being the great example. You know, in 1965, Gordon Moore said, I observe that, the density of electrical electronics components on integrated circuits is doubling every 18 months.
Doyne:I expect that'll keep happening. Well, he later adjusted to be every 2 years rather than every 18 months. But since he made that adjustment, his prediction has been remarkably accurate. And since he made the prediction, computers were a 1000000000 times more powerful than they were then. So he predicted it a long way out and and through an enormous amount of change.
Doyne:Now we used to think that that was just something very special. But what we see now from collecting a lot of data is that there are many technologies that improve, not all of them. In fact, most don't improve enough to be even easily measurable, but many of them do. Other examples relevant to your space besides, transistors are solar photovoltaic, wind, lithium ion batteries, and hydrogen electrolyzers. So those are all examples of technologies that improve.
Doyne:In contrast, the price of oil now is roughly the same as it was a century ago. The price of, coal is about the same as it was a century ago. The the the the cost of making a solar module is 1 10000th what it was when they were first used commercially in the Vanguard satellite in 1958.
Markham:I wanna ask you about, corollary theory, which is Wright's law, because you you conjoin them in your work in some way. And, and I have actually have a a some interviews that I've done with an a fellow who's in the solar industry that I'll get into in a moment, But if you could tell us how Wright's Law fits into this.
Doyne:So Wright's Law is a precursor of Moore's Law. It was postulated in 1936 by Theodore Wright, who was in the aviation business. He actually went on to run aviation manufacturer for the United States in World War 2. And he noted that the cost of an airplane of producing an airplane, dropped by 20% every time the cumulative production of that airplane from a specific factory doubled. And so it's originally a very narrow thing about airplanes and about specific factories.
Doyne:We've now seen that it applies to many other technologies, not just airplanes, and it also applies broadly globally. So, every time we double the production of solar photovoltaic cells, the the cost drops by about 20%, much like it did airplanes. Actually, maybe even a a little more. Can't remember the exact number. Maybe more like 25.
Doyne:And now you might think, oh, that's completely different than Moore's law, and it looks that way at first. But if the production is increasing exponentially in time, then, you get the same behavior from Wright's Law as from Moore's Law. Now there's still conceptual and and by the way, we've tested that. And in many circumstances, it's hard to say which one works better. Wright's law works at least as well as Moore's law for predicting computer production or predicting computer costs.
Doyne:Excuse me. Predicting computer costs. Now, but Wright's law is different because production is something we can control. Governments can have incentives to boost it and so forth, and it's it can be difficult to say which way the causation goes because is production going up because costs are going down or costs going down because production's going up? We did a study on that out of World War 2 where we kinda knew the causality, and we showed that it is at least 50% of the drops in costs are caused by increases in production.
Markham:There is a fellow that I've interviewed a couple times. His name is Mike Andrade. He's based in Toronto, and he's the CEO of of Morgan Solar. And he's been in this industry for about 30 years, and he's a very smart guy, and he has conjoined Wright's Law with Moore's Law in many of the the same ways that you have. And he says, based on my experience in the electronics manufacturing industry, he said, the way I he thinks about it is 1 is the is like the numerator and one is the denominator, and Wright's law will explain the drop in cost, and Moore's law will explain the continual rise in efficiencies.
Markham:And he says the reason why this energy transition is is different is that now energy, for the first time, it really is in a is a technology that's produced in a factory. And so it will obey the laws that govern electronics manufacturing. Like, when I was when I was a young fellow in high in grade 8, I think it was, I had to buy a calculator. It was, like, $80 or a $100. It was this enormous sum at the time, and now the marginal cost of, making in a calculator is 0 because it comes on my phone.
Markham:Just it's a simple app, and and it's far more, and it's that kind of drive to the marginal cost of 0, he says, that will govern energy technologies like solar panels, like wind wind turbines, like batteries, and so on, and that is a inherently more efficient and better than a commodity driven energy system like fossil fuels. I I just want curious about what you think about that.
Doyne:Well, I I agree with him that, it's a very different situation because the technologies I mentioned, including solar photovoltaic, which is the most striking example, are manufactured goods that have dropped in in cost fairly consistently. There's some wiggles in the curves, but, and I think energy is gonna get cheaper than it's ever been as a result and substantially cheaper. Now efficiency is not as clear because efficiency, you know, pushes up against limits. I don't efficiency is not playing a a big role in drop in cost for solar energy that we've had. We may find other processes that are more efficient, So I I don't think it's as clear how it's gonna play out there.
Doyne:I think things will get more efficient over time, but but unlike cost, which can just go down and down, it can't go below 0, but it can still drop exponentially. And it's not as clear to me what efficiency is gonna do.
Markham:Yeah. He I think he would point to things like battery energy density, for instance. It's going up about an average of 7% a year, and it looks like we're headed to some step changes maybe with solid state batteries in a few years. Those sorts
Doyne:of things. Agree with that.
Markham:Yeah.
Doyne:Totally agree. And I think and
Markham:he would also think I think point to, his field, which is solar, where they're talking about integrating perovskites with polysilicon to increase efficiencies from, you know, 22 to maybe 30, 35%. And we just that our our ability to innovate seems to keep pushing those limits all the time even if they're not quite as neat and tidy, so that they could be described as a law.
Doyne:Yeah. No. I totally agree with all of that. And, you know, in batteries, I think we I agree with them. We may see a real breakthrough because, I mean, if you look at, capacitors, which are in a sense a very sim simple solid state energy storage device, The cost and performance have been the costs have been dropping at, like, 30% per year for a long time.
Doyne:So if we can get on that curve, we'll really see things take off.
Markham:The, there's a lot of attention being paid to China these days, and I have to say that in the past year, China has come on my radar. And I've spent a lot of time looking at the the IEA data, about China's investment in clean energy technologies and how that came about. And it seems to me that the Chinese have, figured out long before the Europeans and the North Americans that the fundamental difference between energy as a technology and energy as a commodity, and that and they seem to have been able to scale. They seem to have been able to increase efficiencies, and now they dominate all of these supply chains and products that we we know so well. And what are the limits to that?
Markham:You know, if you're looking at China, can they're at 6¢ sorry, 11¢ a watt for solar, panels now. Can they go to 1 or 2¢? What what how how high can their efficiencies go? Where are the limits to this, do you think?
Doyne:I don't think there are known limits. You know, many people have postulated something called floor costs. There's just some limit below which you can't go. And in one of our papers, we document the floor costs that were postulated by integrated assessment models, which try and study the transition of the integrate of the energy system. And we show all the postulated floor costs as lines, and then we show how the the the price of solar modules has just punched through them again and again and again.
Doyne:And I've looked at a lot of data on lots of technology costs through time. There's really no evidence for floor costs. And now bear in mind that Wright's law does mean a sort of asymptotic slowing down on the rate of improvement. Or to put it differently, to keep at the same rate of improvement, you have the production has to increase exponentially. But as soon as the production isn't increasing exponentially, then that means every tie every time you want the cost to drop by another, whatever the increment is, 20%, then you need to double the cumulative production.
Doyne:So double the production you know, produce as much as you produced up until that point in time to get that next 20%. So it means it gets harder and harder to drive the cost down. That doesn't mean it hits a floor that you can't go underneath.
Markham:Yeah. The the the, example often used is, is is solar, and the it's taken us 20 years to get to where we are now. In the next 3 years, apparently, we're supposed to double that again, so we'll see some a fairly major cost reduction. Then only 18 months to double it again, but it would seem that at some point, there is a limit to to the growth. You know?
Markham:Yeah. When when solar and wind and whatever other hydro and nuclear, when we've when we've squeezed fossil fuels out of the system, when we no longer have to grow power grids, we're basically electrified, then the rate of growth, it would seem, would would drop. And I guess the only question is then is when? Is that 10 years, 20 years, 50 years from now?
Doyne:Yeah. I I agree. Though, it's not clear because let me back up and say a little bit about Moore's Law versus Wright's Law and maybe a different way to think about it. There's a certain component of technological progress that happens from the economy as a whole. So the the example I like to imagine is suppose, all the autumn automobile designers in the world, like Rip Rip Van Winkle, they suddenly fell asleep.
Doyne:The rest of the economy went on. Bars just went as they were for 20 years. Now those designers wake up. Imagine they fell asleep in 1970, and they woke up in 1990. What would they say?
Doyne:They'd look around. They go, oh my god. There are these new things called microprocessors. We could put these in cars and and do all kinds of things that we're doing with primitive mechanical computers, much better, and suddenly, full. Cars would get better.
Doyne:So the point is, progress just chunks away, and oftentimes we're drawing on elements from other parts of of the technosphere to improve a specific part of the technosphere. And so that's the inexorable part. But, specifically, for solar cells, something's gonna slow down when we reach the point where we've saturated because solar cells have been growing at the order of 25 or 30% per year for a long time now, the energy consumption's only growing at about 2% per year globally. So that's a much slower rate. Now even if because energy gets cheaper, it starts to go faster, we're still talking 3% or maybe 4%, but not 20 or 30%.
Doyne:So, yes, insofar as rights law is the right description, we expect that will slow down.
Markham:Now the I just
Doyne:I just wanted to give you all the caveats because, you know, there's a lot of doubles in the details of these things.
Markham:Fair enough. I wanna ask a question about systems that enabling technologies, and I'll get tell a little story to illustrate my point. Last September, the World Petroleum Congress was held in Calgary, Alberta, and I went and reported on it for 3 days. And I was walking down the the looking for, you know, people to interview, and I came across a technical section on materials. And there was a a session going on, and the moderator was a fellow called doctor Ibrahim Abba.
Markham:He was the VP of technology at Saudi Aramco. And he said something I'd never I should have maybe known, but I didn't know. He said, yes, we're having an energy transition, but we're also having a materials transition. And I thought he said, we're figuring out how to make materials out of hydrocarbons in ways we never did before, and this will probably be how oil and gas survives in some form or another, in a low carbon world. And since then, I've thought, well, what other enabling technologies or what other sectors are being transformed?
Markham:And we can think of artificial intelligence and supercomputers and on and on and on and on. And it seems like there has never been a time in history where there were so many advances going on in so many other sectors that all can come together to enable innovation in in energy.
Doyne:Yeah. I I agree with him. You know, in a sense, technological progress boils down to energy materials and information, and and we're making rapid progress on all of those fronts. So and and they're interacting, of course, because, you know, information, better AI, better computing allows us to design better materials, allows us to make progress on the energy front. So I completely agree with what you just said.
Markham:The one of the reasons I I asked to interview you is because a a fellow that, who reads your work is a big fan, but he lives in a rural Alberta community that has access to clean energy, they have a wind, wind turbine farms nearby, and the question that occurred to me was, okay we have these new systems emerging around energy, and to some extent they'll be decentralized. What does this mean for smaller communities that aren't located in the metropolises, they're out in the hinterland, can they plug into this new system and have development opportunities that maybe were not available to them 10 years ago, 50 years ago, a 100 years ago?
Doyne:Well, I mean, on one hand, most metropolises have access to electricity, which is from a grid, and it costs a little more one place than the other. So we've already democratized energy in that regard. But it is true that anybody who wants it now could have energy independence by, you know, putting enough solar cells on their roof and buying enough batteries. And so and that applies at all scales. Now it's true that residential solar is still substantially more expensive than commercial, and I think that dichotomy will continue, but it gives us a lot more choice.
Doyne:And I think it's important to realize with the renewable energy revolution, we're gonna win not just by getting dealing with 75% of greenhouse gas emissions, but we're gonna make energy cheaper than it's ever been. We're gonna make it cleaner than it's ever been. We're gonna make it more sustainable than it's ever been. We're going to, we're going to reduce energy volatility because prices will be much steadier. So and and, of course, energy security.
Doyne:We all can get energy security if we want it. It may cost a little bit, but it's now available to just about anybody.
Markham:What about the, the opportunities that come with, electricity being eventually the cost of dropping to the point of the marginal where the marginal cost is 0. And I I think of, Tony Seba. I've interviewed him a a few times over the years, and this is one of his original ideas back in, oh, 2017, I think, when he first started talking about it. And his point was that once the enter the cost of energy, drops to that level, the systems will change in ways we could never imagine. Humans will take advantage of them, and they'll do things with them that we maybe wouldn't never have thought of otherwise.
Markham:What what what's your take on that? Well, I
Doyne:think he has a good point. I mean, history just shows that energy powers everything. Without energy, civilization grinds to a halt. And, you know, it's only 4% of GDP, but every bit if you look at the input table for any kind of business, everybody requires energy. So now and and if you have the energy allows you to do things that that you know, to automate activities, to do many things.
Doyne:I think one of the biggest beneficiaries is gonna be the global south, underdeveloped countries who, you know, I think there's a good chance they're going to be able to leapfrog by going directly to renewables and and having a solid energy supply without ever having to really go the fossil fuel route. And particularly, if it gets cheap and plentiful, they will really benefit from that.
Markham:That raises a very interesting question because, as you know, there are competing narratives for how fast the energy transition will go. I think the leader of the slow energy transition narrative is OPEC, and they released their world, oil outlook 2045 last, last fall. And I read it, and it's loaded with assumptions about what will happen in the non OECD world is how they think about it. And they argue that the, electric technologies are still too expensive. Governments are tired.
Markham:They they either haven't got the money or taxpayers are tired of subsidizing them. And so the the non OECD world will stick with oil and gas for decades to come, and that's the basis for their increasing demand forecast out to 2045. But that doesn't I it's counterintuitive, I think, because I'm with you. I would think, you know, if I'm Africa and I have this incredible solar resource, why would I not go with the lowest cost form of energy? And not only is it low cost, but it's flexible.
Markham:I can do a microgrid. I can put it on my my my house and be my own microgrid. I can do virtual power plants. I there's so much more as an emerging economy that I can do with this technology at lower cost than I can do with the old hydrocarbons. What what would be your take on, you know, that debate?
Doyne:I totally agree with you. I mean, we, of course, need to get, better and cheaper energy storage solutions for pure renewable energy systems. But, I think I think the factors you just said are just gonna get stronger and stronger through time. It's hard for me to imagine that in 20 years, peep those countries aren't gonna be exclusively buying renewables because they'll be a factor of 5 or 10 cheaper. Now that said, I think the Saudis will be able to hang on for a while.
Doyne:Why? Because as they get squeezed, as the oil market gets squeezed, the, the demand will go down, but the supply will be the same. So cost will go prices will go down. And so we'll see all the expensive providers pushed out of business, but the really cheap providers like the Saudis will be able to go on for a while. But but their markets are gonna be dropping through time faster than faster than they realize.
Doyne:I think maybe if I could just add something else on that. You know, we we are looking at the data on technology deployment. Technologies follow something that's called an s curve where it starts out slow and then it accelerates and then it flattens out again, and hence, s because it looks a little bit like an s. And, so we've collected data on many different technologies that have gone through their s curves from canals to mobile phones. And what we see is they're remarkably universal.
Doyne:They explain more about what happens than the specific factors that make each technology different. And and if you apply the we've developed a method for making probabilistic forecasts for things like solar and wind. And when we apply that, it looks like the transition's gonna happen pretty fast. So in other words, because the change is exponential, exponential looks small, it looks small, and then it suddenly appears on stage and gets big, and we're gonna see that happening.
Markham:Yeah. The old saying, slow, slow, slow, really, really fast. Yeah. I think applies here. We're big fans of the s curve here, as well as the bell curve to explain consumer adoption of of technologies.
Markham:And one of the when I give presentations as I often do on the on the energy transition, I make the point that this transition has a very long tail on that s. If you go back, solar panels first appeared in the seventies, and then wind turbines in the eighties, and lithium ion batteries in 91 and EV prototypes in the late 19 nineties, on and on. We've had we've really been at this energy transition for 30 to 50 years already, which is why they those technologies come to the inflection point when the the round part of the bottom of the of the s curve, and suddenly they grab our attention, and we think, oh my god. The energy transition started yesterday. No.
Markham:It started many decades ago, which is why we're now in the fast part of it. We're up on the hockey stick part of the curve. Would is that what your probabilistic
Doyne:That's exactly what we think. We think we're not at the peak yet. The peak's still several years out. Quite a few years out. Yeah.
Doyne:And and when we get at the peak growth rate, we're only 50% done. So but once we as we get into that zone, growth rate gets faster every year, the absolute growth rate of how many, you know, watts get deployed. It increases exponentially. So and and I think I think we've been on the transition even longer than you said. I mean, goes back to 1958 in the Vanguard satellite.
Doyne:Electric cars, you know, there were precursor electric cars a long time ago. And and back to your other point, electric cars are intrinsically cheaper to manufacture than, internal combustion engines. They're much simpler devices. And so I think that's gonna start to kick in as as they become more and more routine and as batteries keep dropping. Because right now, the batteries are the limiting factor in the cost.
Markham:Well, we'll debate 1958 versus the 19 seventies over a beer in New Mexico sometime.
Doyne:Sounds good.
Markham:But the the this is poignant for me because I'm involved in the debate within Alberta about, how fast the energy transition is going. And Alberta, flies under the radar for many people on oil and gas, but Canada is the 4th largest 4th largest oil producer in the world and the 5th largest gas producer, and all of that is centered in Alberta. Even if it gets done in another province, the companies that do it are headquartered in Calgary. And so this is enormously important to both the energy transition and climate policy and the future of Alberta. I mean, it is in some ways, it could be argued, the engine of the Canadian economy.
Markham:And if it craters, it's hugely, important for workers and governments that rely on tax revenues. And we've been arguing this point that doctor, Ibrahim sorry, doctor Abba made, which is that it needs to begin pivoting towards materials. You know, get away from providing feedstock for fuels and get into feedstock for materials and and build the materials manufacturing. That's a hard sell, And a lot of it has to do with the power of incumbents to impede growth, and and and this is where I'm gonna get back to your systems, it's about information. The information on that we're talking about here, never seems to penetrate the big shield that the incumbents have erected around Alberta.
Markham:Not the media, not the government, the political class. It's it's just a big group think that this kind of information never they never get to to hear it or they just ignore it. They explain it away. The role of information in systems change, your thoughts.
Doyne:Well, it's very important and not just information, understanding, and prediction. You know, Moore's law was important because it allowed organizations to predict what they would be able to do when and and and plan their whole research efforts around it. You know, a remarkable story, you know, the the technology to do Pixar computer animation was basically ready 5 years before they did it. They got it ready, and they said, well, we just have to wait for Moore's Law to catch up, and then we can we can do this. And meanwhile, they got everything all ready.
Doyne:So as soon as they were there, bam, we got Toy Story. And, now in this case, it's really important for the people in Calgary to realize that the, money cows they're they have now is gonna dry up. They're they're in the horse and buggy business. They better find another industry fast. And maybe materials is the right answer.
Doyne:Maybe something else is the answer. I think that requires some explanation. But but they need to really be planning because it it's just not gonna keep going. And CCS, carbon sequestration and storage, is not gonna be the answer. It's too expensive.
Doyne:And the thing is with renewable energy getting cheaper than fossil fuel energy even without CCS, you can't then add CCS and expect it to stay competitive. It just makes it worse.
Markham:Yeah. There's some modeling by the Canadian Energy Regulator that shows that if the oil sands companies in particular are required to pay the full cost of their climate compliance because it's some of the dirtiest oil on the on the planet, that that basically makes them uneconomic.
Doyne:Yeah. And and I would argue that even if they're not required to do that, they're gonna become uneconomical, period. So so I think I think it's one reason why I'm putting a lot of focus these days on predicting technological change because that is such enormous ramifications for society in general. And we need to think ahead to, you know, make sure we're not stranding labor so we can have a a just transition as well as a fast transition and an orderly transition because disorder in the transition is not gonna be good for anybody either.
Markham:Is is, that argument the basis for your book, The Making Sense of Chaos, A Better Economics for a Better World?
Doyne:Well, that's part of it. My book is is more generally about a different way of doing economics. Standard economic models are based on the idea that we're all selfish utility maximizers who figure out the perfect decisions to maximize our utility. And, in contrast, we in complexity economics, you know, model the economy as a dynamical system where the agents make decisions using heuristics or, you know, lot simple logic, simple learning algorithms, which is more the way people really do things. And and furthermore, it allows us to make feasible models where we can really put in all the structural detail that's so important for understanding the economy.
Doyne:So the book's about that more broadly, but this particular topic is a important subset of the book.
Markham:Given the importance of technology change, to your systems thinking, I have a a an explanation, you know, when when I'm talking to people about, okay, why do people adopt an EV or don't adopt an EV? And my point is that anybody looking at any technology basically does a calculation of 4 variables, What it costs you to buy it, what it costs you to operate it, how much risk is attached to it, and how much value non you know, value that you can't measure economically could be status, it could be some other thing that you value, and all of us make our individual calculations depending on our circumstances and our history and all of that. And is that the kind of, decisions that are made in real life decision making process in real life that your model is able to approximate?
Doyne:Certainly, that's an example of something we could throw on and actually throw in a 5th thing, which is that people key off of their peers. They look in what their friends have, they say, hey. I like this car. It's cool. I can I'll buy one for myself.
Doyne:So I think that plays a very big role as well, and actually helps us explain why s curves behave the way they do. So, yeah, we basically try and just to understand how people do things, and we put it in the model. We try for what what I call verisimilitude. You want your model to have the same logical processes in it that the real people and real systems have in them rather than having to make as if arguments. Well, it doesn't work this way, but let's say it's as if it did.
Markham:The, I interview a a a, you know, number of classical economists, we'll call them, about various aspects of energy, and I think some of their heads just exploded. How are your ideas being accepted within the, you know, general economics field?
Doyne:They're seeping their way in. My book is significantly about, trying to make that happen trying to accelerate that process. I was very happy. I I got a great commendation on my book from Larry Summers, who's a pretty mainstream economist. And, so in my experience, some of the best economists are open to these ideas, but many aren't.
Doyne:It's not surprising. It's a fundamentally different way to do economics, requires a different skill set, different knowledge base. They have the incumbent advantage right now. Don't wanna lose the franchise. And
Markham:Shades of Blockbuster.
Doyne:Yeah. So it's it's, it's it's not gonna change easily, but I think change is beginning to happen.
Markham:Is when you say change is beginning to happen, are you referring primarily to North America, or is it the case that outside of North America, the the economics profession is more is more willing to entertain new ideas like yours?
Doyne:Outside, definitely. Europe and Asia are much more open to different ways of doing economics. Economics is a field that's completely dominated now by America. All the top journals are here. All these top top schools.
Doyne:But, you know, this is gonna challenge that because the the the Skunk Works project that we have been is now growing to maturity, and, you know, it takes a model to beat a model. Our models are starting to beat their models, and so I think we're gonna see a lot of change. And it may change the American dominance of the economics profession.
Markham:Where on the s curve would you put your innovation?
Doyne:I would say we're about, a decade ahead of maximum adoption, but plus I mean, there are significant uncertainties in that. I think it's it's gonna happen. The question is when, not if. And, but, you know, I've started a company, and one of my main motivations for that company is to bring things up to scale and reduce them to practice so that we really have practical solutions for the kind of questions that we've been discussing on your program today. And I think we're getting close to providing those.
Doyne:Actually, in some cases, we already are providing those, and I think that there's a huge hunger for that kind of, ability and capacity.
Markham:I'd like to draw our our conversation to a close, doctor Farmer. Well, just give you the opportunity, if there was an idea or 2 that you would like to leave with my audience, what would they be?
Doyne:Well, good question. You've you've done a great job of bringing out, I think, all the main points. You know, I think we we live in interesting times. I think the energy transition is gonna be a very interesting turning point in human history like the industrial revolution was. And I think because it will mean we have cheap, clean, convenient energy, tiny little batteries that can hold a ton of energy, we're gonna have some really sweet technologies, but it will influence the whole progress of civilization on a lot of different fronts, make all of our lives better.
Doyne:And, you know, it's one of many significant changes we're going through right now as we with artificial intelligence and, trying to sort of get control over the planet so that we can it's like our garden. We need to tend it properly.
Markham:If I remember correctly, it was Tony Ciba that made this this argument, but, forgive me if it wasn't. But I believe he made the point that while the technology has the great potential to make all of our lives better and and to herald us into another epoch of of human civilization, we still have to make the right decisions. And if we make the wrong decisions, we can we we can go the other rook the other direction, I guess. What what do you think of that?
Doyne:No. He's right. You know, technology's powerful but dangerous thing, and technologies almost always have negative side effects. Automobiles are great, but look at what they did to cities. Anybody who lives under a freeway can has good right to complain about, and anybody who's been run over by a car knows that there are negative side effects, though we did get rid of horse shit.
Doyne:So each technology is replacing the negative effects of the one before it. There are some side some negative side effects of of renewables too, but I think they're much smaller. We do need to make the right choices, and I think what I'm hoping is that having better economic models will help us make those right choices, help us make them earlier and more clearly so that we can make the transition faster and, stop emitting greenhouse gases earlier.
Markham:Well, on that note, it's a great note to to end our conversations. Doctor Farmer, thank you very much for this.
Doyne:You're welcome. Thank you.