Chris Mailander
So Drew, let's be clear about Omar. Omar died as a result of Hurricane Helene, that he drowned in the Swannanoa River, that his duplex was lifted up, floated away. He was texting until the last minute. He left behind a wife and two children. And the reason is because of decisions that were made or not made. They didn't look at forward data about climate change. They looked at 100-year-old data pertaining to floods. It wasn't part of the building code associated with it. And yet, here we are looking at situations in which we are doing reconstruction. We need to build back better. We're building in other communities that are at a high risk of a flood. We can do better.

Chris Mailander
So, I want to start someplace which is way out there in the macro, which is that we are literally humans on a rock hurtling through space. And man throughout history has used various methods to explain that rationally, whether it is mythology or religion, kings, states, and now science. Science is used to help us understand what is happening in the past as well as forecast what is happening in the future.

We have several instances in which that trajectory, however, of that rock through space, where we as humans try to debate where it's going, what information we trust about it, the decisions we make, the choices that we make about the path going forward.

Fortunately, today that I'm joined by one of the leading thinkers in systemic modeling. His models have been used in over 171 countries. He has briefed Congress and the World Economic Forum. These have been used for the global climate negotiations. He lectures at places like UNC-Chapel Hill and Stanford. He's a graduate of Dartmouth and MIT. He has created the En-ROADS simulation model and is the co-founder and CEO of Climate Interactive.

Welcome, Drew Jones.

Andrew Jones
Thank you, Chris. Happy to be here. Yeah.

Chris Mailander
We are in a place, recording today, which two months ago suffered the most significant hurricane since Katrina in terms of lives lost. It was unexpected. The models didn't forecast it. It was a surprise, leading to significant number of deaths. The realm of damage also is a result of decisions that were made or not made over the past 100 years, knowing that this is a possibility, but overlooking it and choosing not to make those elections.

For you, who work on macro themes and systemic modeling, all of a sudden it became very real and personal. I know that you spent a significant amount of your time on the ground working with the people in need. Tell me about that experience.

Andrew Jones
Just the irony of spending a career trying to prevent extreme weather events caused by climate change. Then ‘boom’, here it hits here in Asheville, North Carolina, where we are today.

And the irony was so stark coming from New York City Climate Week as Helene was gathering strength in the Gulf of Mexico coming up north towards us here in Asheville. I was with the leaders of business and government and civil society in New York City where we gather to prevent Hurricane Helenes, rushed home, and then immediately went to the city center where they give you a list.

They had a list of 15,000 people who were unaccounted for, we couldn't find, and people were looking for them. And I got a list of 10 people, two phone numbers, eight addresses, and just said, go find these people. And there were hundreds of us lined up going around finding people who could have been lost. I got to find everyone on my list.

But my pharmacist, my neighborhood pharmacist, Omar Khan, was just, was lost and it took 11 days to find him. We passed out missing posters and it was heartbreaking and inspiring to see the effort to try to go find people, address the hygiene problems and sanitation. We had the “flush brigade”. People went around with buckets just try to help people who couldn't flush their toilets, flush their toilets because there was no running water for 55 days.

Getting relief services to Swannanoa in these areas. It just became very, very stark about how significant the stakes are, but also the difficulty of learning in these situations.

If it had been that we had made a mistake two weeks earlier, and then here comes Helene, you learn quickly, like, you shouldn't have an energy system that would empower a hurricane like this. You would learn very quickly, like a child touches a hot stove and quickly learns, don't touch the hot stove.

But as you said, the root cause drivers of something like Helene, which we know is strengthened by climate change, by burning coal, oil, and gas, forests being burning, and methane, those things were caused hundreds of years ago. It's so difficult to learn when cause and effect are distant in time. When you make decisions today that don't really rear its ugly head for decades or well into the future.

And that's why we have this field of system dynamics modeling. That's the promise of using simulations to help us experience quickly the long-term delayed implications of actions today, whether it be business or societal decisions like how do we get our energy? How do we handle our forests? How do we use industrial processes well? That's the challenge that we want to face, how we handle complex systems like that.

Chris Mailander
So a lot of the work that I do is with executives and leaders focused on decision-making. And we are quite good, as you mentioned, at making decisions that are a week out, two weeks out, a quarter out, a year out, maybe even up to three years out. There's a fair confidence in our ability to forecast and like that child touching a stove, we learn fairly quickly, adapt and make that. We as a species are very poor at long-term decision making. And that's what you're focused on.

That's it. How do we adjust and make decisions that may reach out 15, 30, 50 years from now?

Andrew Jones
That's right. And societally, it's 15 or 30 years in a business sense. Sometimes it's just two or three or five. And the exercises that you do with your clients is to just imagine just a little bit in the future, but beyond the time horizon that we usually think of. And that's the challenge.

Chris Mailander
Right. It strikes me that we become very discomfortable we become uncomfortable.

We don't trust our ability to forecast or see when the horizon is beyond three years. Certainly not 15, 30, 50.

Andrew Jones
And the discomfort, it's not just intellectual. Sometimes it fails to sink into our bodies and our knowing, our deep knowing in a powerful way. And that's really how I even discovered this idea of using simulation in order to think far ahead.

And I came through it through a really kind of side angle that was surprising to me when I was in college, it bugged me. The problem that bugged me then was the fact that we were filling up landfills, which so much trash and about this is ridiculous. And all we were talking about was recycling. Recycling is the way to solve that. When of course that's really not the way to solve it. We should focus on how much we use in the first place.

And I was that annoying guy at college saying, “Chris, do you really need that water bottle?” You know, disposable water bottle and I was judgy and in your face, no fun. But I realized that, I just had an idea. I said, what if we carried our trash here on campus in clear plastic bags for a week to the dorm, to class, to the gym, to parties, and you had pizza boxes and beer cans and beer bottles and junk mail and junk mail and beer bottles and all that, filling up day-by-day, bigger and bigger.

And it just became impossible not to see the world totally differently because you were carrying the weight of everything you had used. There was no a way that you could throw things to. And it changed your thinking fundamentally through a physical way. You experienced what things would be like in the future and that we were talking about discomfort. There's no discomfort like, I don't know what it would be like three years from now. No, you feel it.

And professor Donella Meadows came to me and she said, “That's amazing. Do you know what you did?” And I said, “No, that was cool.” And I've got in the New York Times and I've got 150 kids on campus to do this.

She said, “That was a simulation and you closed a feedback loop that was open. You feel the feedback. Feel the implications of your actions in a visceral way through a simulation.” And she said, “You should go study simulations on big important issues like business challenges or eventually something as big as climate change that help people viscerally feel what it's like in the future. Experience it right now, so you make decisions today that help you get a sense of how much better it could be in the future as if you could experience what it was like to go through a hurricane.

Like how inspiring would that be if you felt what it would be like to go through what you and I went through with this hurricane now? Would we find the courage to make difficult business decisions, societal decisions about addressing a big persistent but challenging project or problem like climate change if we could feel it today?

to make us feel viscerally the delayed distant implications of our actions in ways that create new possibilities. That's what simulation can bring us.

Chris Mailander
It strikes me. So what you're talking about is decision-making is a product of the intellectual exercise, but to actually make decisions that are effective, it's got to distill down into your physical being and your emotional side in order to have that comprehensive dimension.

We experienced that with climate change when Hurricane Helene hit Asheville and we saw we lost power, we lost telecommunications, we lost water for 55 days. People were dying, the National Guard was activated and FEMA and private citizens came out and actually were part of the recovery effort and actually experiencing.

I would suggest also that we are only two months away from it and it already feels like a distant memory. We're already losing that feeling of a crisis and the challenge and the decisions that we've made. Is that fair?

Andrew Jones
I notice it. I want to get back to normal. And yeah, we're starting to lose some of that urgency that's so critical. And that's why we have to come up with artificial created virtual worlds in order to keep the kind of constant vigilance, the practice of bringing into being a future that we really want, where we can see what we want to create in the future, but make decisions today.

And unfortunately, we have resorted mostly to research, ideas, intellectual, kind of all of that. And the research shows us, we ought to do these things today, and we ought to do these things to keep the urgency. But my colleague at MIT, John Sterman, said it best. He said, “Research shows that showing people research doesn't work.” Research shows that showing people research doesn't work.

That's why we have to do what you said a few minutes ago. Keep it visceral, physical, where you can experience what it would be like. We have to help people learn on their own terms and experience better futures, ideally through simulation.

Chris Mailander
It's a fascinating dynamic because we've talked about in as I led into this which is that man has centered its ideas around through progressively through mythology, religion, the king, the state and now science. Yeah. And but we don't believe the science. We don't believe the research. We are in a place where we say that science is our truth, but we don't believe it.

Andrew Jones
No, new information doesn't change people's minds. New experiences do.

And that's what science misses is like, the information is out there. Here's the facts. Change your mind. Experiences do. That's what I was aiming for with the trash. That is what we could talk about a minute. These climate simulations that help you viscerally feel the future bring new experiences or the facilitation that you do where you've told me about, imagine this company in five years? Five years. Yeah, in five years.

Chris Mailander
Yeah, a lot of the work that we do is to actually disconnect from the realities of today in order to establish an ideal state five years out. And then we walk backwards from there. What has to be true by when in order to achieve that ideal state? What is our trophy and what do we want to accomplish? It completely inverts the cognitive process, the logical process associated with it. And it frees people who are really good at making decisions over the next week, the next few weeks, the next quarter.

All of a sudden they're free to imagine their ideal future. And it does create that experiential state. And by the end of the process, you get a lot of the reactions, are, they come around to, logically we can do this, but I feel clarity. I feel joy, quite frankly, that there is a pathway to achieving this as opposed to the consternation of the difficult road ahead.

And so there's some similar things that we do, but I also think about…

And I want to get into how your simulation models are built and how they work and then the experiences that you create around the world over 171 countries where you've created these experiences. But my mind immediately starts to spin into creating these synthetic experiences which allow people to experience something both good and bad so that we make better decisions and that future that we could create so that we don't have to actually... go through the actual experience of 150 people dead and billions of dollars in losses and an economy setback and lives and futures changed.

Andrew Jones
Yeah. And the big component to add here is when it's not just feeling the trophy of five years, but knowing that the path between here and there has complexity and feedbacks and interactions that our brains can't really handle.

And it's similar, the best analogy is like the pervasive use of say flight simulators. And someone before they're a pilot is gonna have a lot of time handling the mechanics of how an airplane works in that simulated environment…

Chris Mailander
Getting a feel for it.

Andrew Jones
Getting a feel for it along the way. And you just mentioned the trophy of course is that plane that you're flying safely on the ground. So you get to feel that.

But along the way, these complex systems behave in ways that our mental models, the models in our heads that we use every day to make other decisions, don't include what we call the dynamic complexity, the interactions, the ways that delays work and feedbacks work, the way an airplane is going to react, also the way that an economic system, a business system, or the climate will react to our intervention.

So that's why we take the time to build rigorous simulation models that are accessible, but also consistent with the available science that's out there.

And this came to us, it came to me when I was a graduate student at MIT, and it was around the time of the Kyoto Protocol for Climate. And countries had come together, mid-90s, late-90s, and said, let's all make some plan to address climate change. But nobody knew if all these countries did what they said they were gonna do, if it would actually help, nobody could add up given the complexity of the climate system, what it would actually deliver.

And I was knowing that like this was gonna be really important. I wanted the negotiators to both feel the trophy, like, hey, we did it. We prevented a lot of climate change, but also deal with the complexity of how this system was gonna work.

And there was a guy across the hall, Tom Fiddaman, who had taken the models that took two weeks to run one scenario and compressed it into a system dynamics model that could run in 60 milliseconds.

And when I saw that, I realized the negotiators would be able to say, “Well, if China did this and the US did that and Europe did that, India and Russia and Brazil, then we could very quickly help people understand what it would all add up to.”

And it took about 10 years, but build up to the point where the Obama administration and then also the Chinese government used it for 2009 in the big Copenhagen negotiations and then building up to the Paris Agreement in 2015, used these simulators to do real time experimentation that would do exactly what we were talking about with a flight simulator, with carrying your trash, with you talking to your clients about seeing the world in five years to see what would it take to put together a strategy that would add up to, given the complexity, deliver on the goal that there is.

So that new use of simulations, not as research models that deliver ideas, but as, as I said, experiences that help people experiment, engage in play, change assumptions, eventually got us to Congress, where 128 members of Congress with our collaborators at MIT Sloan, at the business school, all those members of Congress use this to test how to do it, which is about electric vehicles and about carbon pricing and about trees and about coal and about methane and about diets, all of the different strategies that would help you deliver.

So it's using the simulations to help people experience the goal they want, given the complexity of the path there.

Chris Mailander
So I see two breakthroughs here. For Kyoto, the negotiators didn't have the ability to add up what is the overall strategy and what would be the implications of it. And you created a model which allowed them to better anticipate or project or forecast what the strategy should be. Exactly.

Secondly, is really about how someone interacts with this complex set of data. Our brains aren't able, even the extraordinarily sophisticated, well-educated, mathematically oriented folks that you work with are not able to understand the cross correlations.

But the objective is not to do what research and science typically does, which is to spit out a graph that says, here's the answer. Exactly. But instead allow them to interact with the data. Yes. To create an experience through the simulation so that they're better able to make decisions and understand those cross correlations.

Andrew Jones
Yeah, that's right. That's right. That experience often comes up from appropriate skepticism.

So often I'm engaging with people who aren't just, they don't like my conclusions. And so when it comes up, then what happens is people will say, “Well, I don't like the fact that you think this set of policies is necessary.”

What they'll say is, “Where did you get your data? Garbage in, garbage out.”

“Hey, no models. The models. Which is basically trust the science, we don't trust. That's it. And what the words that get said are those, but what they're mean is, don't trust your model, why should I believe you?

And so that's when we start engaging on changing assumptions. Well, how do you see the world? What if your assumptions were closer to the truth? Let's test many of these scenarios. And that's when it becomes a conversation. And an experience and is one of the ways where you start to flex with people and explore uncertainty and scenarios that weren't even considered because they're not the standard set of futures that are modeled and put out into the literature that you'll see everywhere where you can explore black swan events and other things that people hadn't imagined, but also start to build on someone own view of the world so that you're having a real conversation. You're not just, hey, here's my truth. Believe me.

Chris Mailander
It strikes me that one of the reasons that we get into these pedantic conversations and divisive black-and-white conversations in which on major policy-related issues is because people feel judged that you have presented a solution that I don't like or is uncomfortable or is adverse to my interests. And therefore I'm going to reject it.

A, B, the means by which I'm going to reject it is by challenging the credibility of the source, the underlying data, garbage in, garbage out. I don't trust it.

What you're talking about is creating simulation models which allow you to run multiple scenarios, including those of the 128 congressmen could run 128 different scenarios, play with those, which is a significant way to create that conversation, that engagement, and to test different theories and ideas.

It strikes me also, there's a third dimension of what you're doing, which is that time between when you put your inputs into a complex system model and the output, you're talking milliseconds, 60 milliseconds of time, so that we then compress that challenge that we've talked about, which is it's hard for me to make decisions that are five years, 15, 30, 50 years out, but what you're doing is being able to allow me to envision a future within 60 milliseconds.

Andrew Jones
Compressing time and space, to let people feel immediately the implications of the actions. But I want to know what you said about trust and judgment.

And that is one of the biggest problems we have in the polarization of these conversations, particularly around something as contentious as climate change, where the stakes are so high financially, there's so much money to be won or lost.

One of the best experiences I had was with Senator John Curtis. I was out at the Aspen Institute, engaging a group. Presented to 15 members of Congress, he said, wake up tomorrow morning, 6 a.m. here at the Aspen Institute. I need an hour and a half with your model before breakfast.

We got up and played with it and explored all these possibilities. He is a Republican and this is seen as a Democratic issue. So we got to play with the things that he was curious about. Nuclear power, carbon capture and storage, carbon dioxide removal, hydrogen, some of the economic development possibilities that are really of interest.

And he said at the end of that, “I've never had a conversation about climate science where I didn't feel judged like this. This is the first time.” Which is just heartbreaking to me that we've polarized ourselves so much that we can't even hear each other on these topics.

So that's partly what we're really trying to do when we say research shows that showing people research doesn't work. Showing research is like, I'm smart, I got it, here's the truth, get in line. And well, we've seen how that's worked in the last 30 years.

Chris Mailander
With the election, there's an abject rejection of that, we're smarter than you, here's the answer, do this. That is a major theme in the election.

So it strikes me, what is your forecast, since you interact in these circles, including with the senator and congressman, et cetera, for creating the context for those conversations?

Do you see the opportunity? Is there the potential for that? Or are we still divided and polarized and have to stake out positions and can't hear each other?

Chris Mailander
Drew, one of the dimensions of what you're talking about is you have breakthroughs when you can create the context for conversations. And that's so much of our policy and economic debates are divided, black and white. We can't hear each other. But you're seeing these opportunities where we create conversations and using simulation model as the vehicle for being able to create that conversation. Do you see opportunity there?

Andrew Jones
Yeah. Particularly in the United States right now, one thing that's really supporting the opportunities is the economic development promise of so many of the solutions that we're seeing.

Here in the US, we passed the Inflation Reduction Act. And it turns out that the biggest beneficiaries in many of the industries are in, quote unquote, red or Republican dominated states. Wind in the Midwest, where you're from, you know, in the plains and remarkable opportunities there or globally.

China's opportunity, what they're investing in clean energy and in batteries and all these possibilities that it's just this engine moving forward that creates an alignment that people are willing to talk more constructively when we have such an alignment of economic interests.

And that's sort of about the US, but internationally is of course where it really matters the most. And that's where the rise of interest and understanding is really leading to better conversations. And we think these simulations can really help.

Chris Mailander
Yeah. It's interesting to me also that our conversations don't allow for the complexity to get back to it.

So you talk about the red states out in the Midwest, which vote extraordinarily on the red, but that's also where ethanol is produced. That's where the wind energy is generated. You have a tremendous interest in alternative sources of energy because it has an economic value.

And so this continuous continuously looking for how you create economic value in the models going forward strikes me as the biggest challenge.

There is a mindset which looks backwards towards historical forms of energy. there are mindsets which look forward to how can we do better and our need for energy is significant and growing. Is there a better way to consume?

Andrew Jones
That's right.

Chris Mailander
How do we create those incentives? How do we create those conversations?

Andrew Jones
The main way that we're seeing is in bringing people together across views in a workshop or sometimes even a game you got to participate years ago in a kind of virtual world, somewhat playful, like even in a workshop setting with members of Congress will say, okay, your job here is to create a world where you get those emissions of greenhouse gases to go down or limit warming to say below two.

So there’s like gamified component and then ask people to play, experiment and talk to each other.

Learning is a social exercise. It's not coming from a simulation. It is people talking to each other.

So creating this virtual space to talk about what might be possible and bring in multiple factors, not just the climate implications, but the economic development implications in the near term and in the long term.

Chris Mailander
It strikes me that the participation element is really strong. You talk about creating a game out of it. So it relieves some of that pressure of a divisive issue, but makes it more of a game. They get to input their opinions. They get to be heard. They get to adjust and evolve. You can play with it in virtually real time. All of that changes how we frame the sets of issues.

Andrew Jones
It does. Like with my business school students, we'll even go the next step with role playing.

In the game and have people play the roles of fossil fuel companies, conventional energy, clean energy technologies, and then people sitting on the floor who represent the developing countries, people sitting on the floor who represent activists who are fighting for this or that.

And what I'll do is I will put people in the opposite role of what they personally lean towards. I'll say, know, and so we'll have the more conservative students playing the climate activists and the obvious environmental activists in my MBA class, they'll go be Rex Tillerson and run conventional energy as the head of Exxon.

Chris Mailander
And what's the implication? Is it acting? Does it become playful as part of that or vindictive or...

Andrew Jones
All of it in Role Playing. Step back. All of it in role playing, there is some theater to it, but it goes beyond it… empathy, people report afterwards.

Like I hadn't seen that with this set of incentives, of course I would see the world this way. And I could imagine if I had that job, which is the opposite of my own view, how I might experience it.

And that kind of empathy creates understanding and patience in my students. And we actually have done it with top decision makers as well. It really helps to walk.

What's the line, you know,”… a mile in someone else's shoes?” That experience.

Chris Mailander
So walk me through the model. How does it work? Take me through the beginning of the journey, going through the model and what you achieve by the end of it.

Andrew Jones
Yeah. And the model, like the model workshop. Yeah.

Chris Mailander
Yeah. So. And the simulation model itself, En-ROADS.

So there is a tremendous amount of data that has been built into the models that you have a technology system which has been architected, which allows you then to do the cross correlations.

So try to hold onto that a little bit. So let's get down into some the deeper layers and understanding the sophistication of developing cross-correlations. Because you indicated previously, this is where our own brains are not very good. So we can use a technology model and architect it over time. It's taking you over a decade to build that to realize.

Andrew Jones
And really, the idea is, again, to supplement the model, the mental models that we use to make 99% of decisions. The principle, of course, is… All decisions are made with models. 99% of those decisions are using the model between our ears. We want to have simulation models, computer models supplement what we do day to day.

And so the way it works that you have to get your arms around in order to really help people with this thinking is it's a simulation that starts in 1990 with just how much energy is being used from coal, oil and gas and what the population is and how many trees there are on earth and how much agriculture and what the methane emissions, all of that initial conditions.

And then every 45 days, it changes things a little bit forward. We have people being born, more people, more energy demand, therefore a little more coal, oil, gas, renewables, nuclear, energy demand, we get a little more energy efficient, agriculture changes in some way, more methane, and then carbon in the atmosphere collects, and then you have more heat being trapped.

And then it plays it all the way out through those 45 days on and on and on, 110 years where you get to see the implications of this.

So how many people like you and me had to experience hurricanes around the world? we, because the science is out there, you can estimate how many hundreds of millions of people are experiencing hurricanes every year over time, but also maps that show extreme heat in Europe and Africa, and in India, wildfire danger days, how many days are lost from outdoor labor? And what is the economic cost of that?

Air quality, because of burning coal, other health considerations like nutrition, biodiversity, what happens with ecosystem changes?

So because the science is amazing, we were able to connect the dots and show people those implications, but also big feedbacks. Like if all that happens, what does that do to economic growth?

There's this big feedback loop from the damages to, hey, think of the $200 billion of damage here from Helene. What does that do to economic growth in this region where you and I now see how many people are leaving because of the damage?

So those feedbacks. So it plays out all these, shows maps, shows graphs, and it's free online.

En-ROADS by Climate Interactive, if you want to go use it, En-ROADS Climate Interactive, 20 languages, because this is not a challenge for the United States. This is mostly going to be won or lost in China, India, Indonesia, Brazil, South Africa, Argentina, Turkey, Mexico, the fast growing emitting countries, the middle income countries.

So it's a tool that people can use out there. And then we actually developed a training program… eight hours of short videos to teach people how to engage their top decision makers. There are 850 people who've used it. Now 1.4 million people. We think, I can't guarantee it, but it's the most widely used climate simulation on earth because it's out there in that form.

Chris Mailander
Yeah, interesting. One of the challenges with our current debate is that people have economic interest. They take up a position. And that has significant financial value to them.

And so they want to become, I mean, we do project financing over 10, 20, 30 year arcs where we're investing in electricity or coal or oil or whatever it might be. And so you want that trajectory, that curve to remain continuous for that lifetime.

What you're saying, however, is that with your model, you can go around and evaluate how the economic interest will be affected going forward.

You could make a case that if you want to be on the forward edge of investing, ensuring, understanding where the implications will be over the arc, your model allows you to get visibility into that.

If I'm managing assets, infrastructure, where am I putting my plants? Where am I putting my people? Where am I building my residential developments? can use the model to get a forecast based on all the data that's been consumed. Where is the best place to put this?

Andrew Jones
Absolutely. Absolutely. And the way that's being framed in the business world, is in these two areas of, the big area is risk.

And more and more regions, Europe is forcing it right now for all countries and companies to evaluate their transition risk and physical risk to climate change. Banks have to do it already.

And the Task Force for Climate-Related Financial Disclosures, TCFD, 10 years ago started sitting down and saying, hey, what should we note? Do we integrate this thinking into our decision making? And it shows up in those two areas.

Physical risk is so clear. And I told you about the maps and graphs of do you have beachfront properties, the most obvious? Are you in agriculture? How is rainfall going to change where you are? Can you evaluate that potential loss physically?

But the transition risk is the one that is more nuanced and more reliant upon our models overall what are called integrated assessment models like En-ROADS, which is if the world got serious about taking action and you have a lot of assets in coal, oil, and gas, are there going to be stranded assets? Are you going to lose money? That is the transition risk question.

If you are in agriculture and you don't change your ways, what happens?

If you are in electric vehicle or in, you are General Motors and you don't get ahead of the curve.

Simulations that are out there, and there are many around the world that publish their findings. They're not set up like En-ROADS, but those are the ones that are informing our thinking about risk and valuing it, integrating those insights into a form where a company can calculate how exposed or not exposed they are in the world of transition risk and in physical risk.

Chris Mailander
So we just had an election. Yeah.

In which it strikes me that we have the effect of shaking the snow globe, that there was a rejection of the existing trajectory of decision making within the government. A large number of the electorate is of the view that the government is out of control. It's making spending decisions. The debt is increasing. We're concerned about our future. We're not seeing the opportunities ourselves, et cetera. We simply want something different. And so we want to shake the snow globe and see what happens on the outside of that.

It strikes me, however, that the people that there will be winners and losers as part of this process, this intentional shaking of the snow globe, and people are lining up to understand the systems and the forecast, what it will look like over the coming four years and what that portends in the next 10, 20, 30 years of that trajectory.

With models like this, it allows you to better anticipate the other side of a snow globe shaking incident that we're about ready to go through. Is that fair?

Andrew Jones
That's fair. And in particular, the world of the models that we work with are all, most of them are optimized and very similar to each other. They all say, “Here are how things are going to play out.”

And what we've been trying to bring in is the possibility of imagining black swan events like we saw with this election. System dynamics, our method can help do that when people are creative about the inputs and say, hey, what if this happens? What if we see coal going away, but natural gas really taking off much more than we ever imagined, which has been happening lately.

But there are also other modeling methods and it's critical. We use system dynamics, but more broadly, other methods are more appropriate to this kind of question. In particular, agent-based modeling. There's the Complexity Institute, the Santa Fe Institute, these groups that are coming up with ways to think about complexity in a way where you get very surprised by events that come together.

And the key here is use modeling methods appropriate to the kind of questions that you have. If you wanna say, hey, I'm curious about a shake the snow globe kind of world, don't use the, they're called CGE, computerized general equilibrium models, that will not help you discover that.

Other approaches. So get away from the world of you have a climate model, which is the best climate model? No, no,

What are the questions that you're asking? What are you particularly curious about? And that's true for climate models, but also for business models. What is the exercise? What is, maybe it's not even the spreadsheet or the model that you need. It's the flip chart exercise that you've designed. What is appropriate to the question that you really have?

And some of these, like taking advantage of uncertainty, requires a different kind of approach than the traditional ones that have gotten us where we've gotten today.

Chris Mailander
I find that all the time. Depending, you know, it's important to identify the problem that you're trying to solve and then develop the model and the method that's most appropriate to that particular problem. If you mismatch it, you'll have a poor outcome and people won't trust it. They'll walk away from it. They'll go back to their, you know, legacy thinking associated with it.

If you can get true alignment between the methodology and the problem that's being solved, that's where you get the breakthroughs associated with it.

And I think it's where some of the most creative thinkers that we see out there, they like the snow globe shaken environment because it creates change. creates opportunities to change the inertia within the decision-making system. And they're going to take advantage of that.

Andrew Jones
Yeah. I'm really curious, Chris, of what you've seen of how to help in, as we look to a future where there are these shake the snow globe kind of opportunities. I've just kind of admitted that my modeling methods are like, they cut, stop short of that. What is the kind of approach that you think is needed for managers who are facing these kinds of possibilities?

Chris Mailander
Yeah. I mean, I think there's a whole range of things that are interesting here, which is your model strikes me as extraordinarily important and interesting in the context of being able to do simulation and creating conversations.

Creating engagement, creating that full body experience between understanding the intellectual side, as well as getting down into my preconceived notions, the emotional reactions.

We've talked about something else in simulation, which is, is there the opportunity to create simulations that would create more experiences, synthetic experiences through virtual reality or whatever that might be, to allow us to explore those dimensions without having to go through actual loss and crisis.

That would be an important dimension of it. Why? Because we're trying to create empathy. And empathy in every setting is the fundamental ingredient. If you can get someone to look at a problem through another set of eyes, you'll create new ideas, new breakthroughs, a conversation, a different trajectory on that arc. That arc that is that globe, that rock that we're floating on and we're trying to shape the trajectory and what the species does with it.

I think that this is where artificial intelligence and the AI is both fear inducing for many people right now because they don't understand it. It feels like a black box. also feels like those who have the tool and get the tool at the top of the hierarchy of wealth and access will have advantage by what it yields. What does AI tell them that's not available to the rest of the public?

There are methodologies that we use in business forecasting and strategic development that use, I mean, there's a dozen different methods that I will deploy depending on the problems trying to be solved. And the way that I choose it is oftentimes by the decision-making apparatus today and what is required to jolt it, to break it. To fit into the slipstream is what 95% of people will do. They will follow in and say, here's the way that we've solved this problem in the past.

What you get is a continuation of the same exercises. It's comfortable to do so. The hard thing is to do is to create a little bit of discomfort in a non-judgmental way, create a bit of empathy, and then work through the problem sets together to create that opening and create new concepts from that. That's the key.

And that's why I think your model is super interesting in terms of the conversation, the creation of empathy, the experience of compressing time also is our ability in all of these different settings to do that forecasting over a longer period of time is really poor. I mean, we think that we're sophisticated and have this ability to project out.

I think it comes back to the way the brain is wired, I'll be honest with you, that the primary, the first reaction that you have, cognitively-speaking, runs through the amygdala, which is fight or flight. And that gets triggered every time. So getting into more intellectual understandings of the future and forecast is difficult.

I think it's why, just to digress more, think it's why neurodivergent thinkers sometimes come up with breakthroughs is because they're going through a patterning, which is distinct from what 99% of the population experiences. They've fallen into those comfortable grooves, the accepted grooves. And somebody from the outside, immigrants, neurodivergent thinkers, come in and look at it and they're like, that doesn't make any sense. Let's do it in a different way.

Andrew Jones
You mentioned along the way, artificial intelligence and where it sits in this world of using simulations and forecasts.

And it's pretty important to make some distinctions here about a component of what I didn't describe about what we're proposing in this with Congress people or anybody. They're seeing a future. They're seeing the pathway, but they're also learning why in a simulation, in the computer model, A leads to B.

They're getting to see the interaction. The reason that if you move this lever, they get to see that economic growth goes up and climate goes down because, and there will be a description, which is more renewables leads to a little bit less coal. Less coal means a little less air quality, but it also is bringing the price down faster because there's this learning curve and there's a reinforcing loop. It's bringing it down. That's why you see the slope doing that.

That explanation along the way is central to the trust building and this process.

So it's such an important distinction of how we use simulations to have people understand. So it is trying to teach and engage people to understand the mechanics of how a complex system works.

And it's so challenging to be in a world where there's so much faith being put into, hey, we're just going to get this answer from this AI tool where it doesn't do any of that. And there's so much faith that that's just gonna give us an answer with a black box model.

Chris Mailander
Very important distinction. Yeah. the interactions versus a modeling system which tells you none of the projections.

I think the other dimension of it is that the common theme across those modeling techniques is that they do forecast what's most predictable based on the inputs associated with it, where all of the models probably struggle the most is the black swan events, random events.

Andrew Jones
And it will never, this kind of approach of just looking entirely to the past and to the knowledge that we have could never come up with those.

Chris Mailander
People need to understand about artificial intelligence to say it in a really dumbed down way. It's telling you the most predictable next word, next sentence, next paragraph, next most likely event in a quantitative system. Not the aberrations, not the randomness. Absolutely. Maybe not even a Hurricane Helene. That was not the most predictable thing to happen. It was supposed to be a 1 in 1,000-year event. And we've had three major floods over the last decade, including the second largest hurricane.

Andrew Jones
And in fact, you know, it's most what's most predictable in a world where some of what we should be able to forecast is is disallowed even like, don't know if we have really recognized the fact that the the flood maps that our neighbors here used to decide is it safe for me to live here, given that I'm close to the Swannanoa River? Is it safe to live here?

Like those maps are created by FEMA, but they're only allowed to use 100 year old data about flooding.

Chris Mailander
Tell me about Oscar Khan. Yeah. Tell me his story.

Andrew Jones
Omar Khan was our neighborhood pharmacist. Westgate shopping center was just the guy who would give flu vaccines, calm with kids, giving a vaccine and just gave my friend Maggie her, just a shot two days before he died.

He was in a house where the flood map said, it's safe. You should be able to stay here right. Next to the Swannanoa River, it's not in a hundred year floodplain.

And when the word came out that, know, floods are coming, we knew we all were supposed to get prepared. Most of us were ready to, you know, bail out our basements, got to stay nearby.

So he was in his apartment building, know, wife, two kids. that river came up so fast that the whole foundation of the house, the duplex was lifted off the foundation, floated down the river, and he was sending texts at the last minute and then was just swept away.

The map said, “It's safe. You are okay here.” Because societally we decide it's not okay or we shouldn't include these forecasts in our estimates of what's safe.

Just in the same way here in North Carolina on the coast, legally, the policies can't include sea level rise into what happens on the outer banks and what bridges get built or don't get built. You may not include it, even at the same time as insurance companies are realizing we can't insure these homes anymore.

We're building in resistance to learning because we don't want the implications of the new maps or the policies in a world where we do have a off of Mexico that's warmer, air that's warmer, and therefore you'd get black swan events like Helene we never thought would have happened.

So that's one reason that AI or other things that just look to the past can't help us as much with the future because we're only looking to the past and we actually are immune to some of the information that will help us into the future because we don't like the implications of it.

Chris Mailander
Just to be clear, Omar Khan died drowned in the Swannanoa River. He did. Passed away, left a wife and kids. And if we trace back the decisions associated with it, it was because the duplex where he was living was built in a place where looked at historical data, which said that you're not in a floodplain. Absolutely. They built there anyway. We did not factor in future forecast about what could happen or any probabilities associated with that. And lives are lost based on those decisions that are made with long range decisions in which we are admittedly very poor at making those decisions.

Andrew Jones
And just to make sure some of the other facts get in there about what happened is Hurricane Helene formed in the Gulf of Mexico.

You probably remember a time when those hurricanes would hit the coast and then die out pretty quickly. But the Gulf of Mexico over the last 100 years is now two to four degrees Fahrenheit warmer over the last century. So you look at the graph, it's just getting warmer and warmer and warmer.

Hurricanes are fueled by hot oceans. And so that warmth fuels what usually would just die at the coast to travel 450 miles. We never thought that it would make it all the way up here and then hit the mountains and then drop an extra amount of rain.

And it was that 31 inches of rain that led that Swannanoa River to rise so fast to surprise all of us and Mr. Khan.

Chris Mailander
So we have significant migrations internal to the United States, to Texas, to Florida, along the coast of the Carolinas, where there are increasing in population, increasing in the development. And yet, with the increasing temperatures in the Gulf of Mexico and storm forecasts, the likelihood of damages, devastation, loss of life is significant and increasing. Correct? Yeah. That strikes me as poor decision making.

Andrew Jones
Yeah. And it's particularly striking. Here where we've topped lists of where you could go to flee climate change. That's one reason it was so surprising is that people have moved here because you think they're getting away. And so it's even that idea that there is a place that you would go flee. Like we now know we're all in this together.

No one, even the wealthiest can't run to somewhere else. And we joke that people are gonna try to run to Mars to get away from it all, but we're in it together.

The good news is, of course, we know what needs to be done. There are ways to avoid the worst case scenarios. And we're advocating for taking the time to get people together across polarizations to talk about what's really needed and experience a better future through simulation to get a sense of what it's going to take and in a model that's complex enough to point to high leverage actions and divert attention from the lower leverage ones that really won't help nearly as much.

Chris Mailander
Are you worried that climate change, which has been a significant international public policy issue over the last decade with significant negotiations and debate and conflict, is taking a second seat with the upcoming election?

That one of the first statements that was made by the press secretary for Donald Trump was our climate policy is “Drill Baby Drill. That there is an embedded viewpoint which is that climate change is not real or I don't believe the science associated with it.

One of the most influential people within the new administration is Elon Musk who has, as you reference, somewhat of a fatalistic notion which is we better hurry up and get to Mars, which almost seems like we've given up on Earth and we move on to an extra, you know, a new planet for the first time ever.

Give me a sense of how you're feeling about the era that we're going into over the next four years, which will affect the next 10 to 20 years and what it means for being able to make these kinds of decisions, the tough decisions that are out there, admittedly tough decisions.

Andrew Jones
The interest and the commitment and the conversation, it ebbs and flows, and it is that kind of cycle.

Twenty years here in North Carolina. I organized the first briefing of the North Carolina State Legislature at the Museum of Science. We brought a bunch of Duke scientists. I didn't know anything about climate science, but I got a bunch of Duke scientists to brief for the first time in North Carolina State Legislature in 2004 to have them understand what's going on.

It was high, it goes down, it goes up, it goes down. We're definitely in the United States at a down, particularly for international negotiations, but the world is engaged and thinking about it. So I'm worried for this next few years and yet it ebbs and flows. So we'll be back.

Chris Mailander
Right. Awesome.

Andrew Jones
Well, I'm curious, Chris, your experience of what it was like in those first weeks and now months after Helene, you do so much work supporting local business people. What was it like?

Chris Mailander
Yeah, it's one of those things where we were surprised, you know, was the, knew that there would be rain.

Our typical pattern of behavior in the mountains, as you've indicated, is that we are the tail end of oftentimes of tropical storms that come up through the Gulf or through the coast, through Charleston and so et cetera. And we will get three to six inches of rain at the end of that process. This was different. It picked up more power and actually hit up here.

So what happened for us is that my wife has several local businesses that support 60 local businesses unto their own right. These tend to be individuals that, you know, they work typically, you know, week to week cashflow wise, probably 70 to 80% are female, I would guess that 70 to 80% are also the primary or sole breadwinner for their families.

On the morning thereafter, as it's quiet, you realize the cashflow has just dried up. The businesses are shuttered. People are stuck in their homes. You can't communicate with them.

All of our systems to manage those businesses are now electronic. So doors, phones, internet, water systems, electricity, et cetera, can be managed from a console. That's all shut down. So the buildings are wide open and there's a fear of looters and bad behaviors. And so we're dealing with that.

So we were scrambling around to be able to close up those businesses and going around flooded out areas, trees. We had power lines that were made the parking lots inaccessible in one of the locations, et cetera.

But the objective is how do we get these back up and running because we support 60 people as quickly as possible. So one of them was able to open within eight, nine days and get people back in. They were fantastic and brought in, enabled their spaces, it's a shared space type business to allow those who were disaffected to come in and share it on the off hours, et cetera.

The sense of community and collaboration and helping each other out really came through extraordinarily strong.

We've had trouble because it's in the business of hairstylists and aestheticians and things of that nature. They are dependent on clean water. We did not have potable water, drinkable water. You do not want to dye somebody's hair with water that is being chemically treated or full of sediment.

So that is a high dollar item that is very difficult to do. So we're bringing in water to support that. We have the same issues with the flush brigades and being able to flush toilets and what have you.

After approximately 30 days, we were able to get that location up and running and make it all work and get people back to work.

But what will happen in this economy, and you mentioned it before, is that Asheville is a significantly a tourist based economy. So a significant amount of our income in the city, in the county comes from tourism. Something like $2 billion comes in the fourth quarter alone projected. That number will shrivel up into a fraction of that amount and downtown is still quite open for business now and the hotels are open and the restaurants are open and we're getting back underway.

But, folks that are at that living wage or less, which tend to be your folks that work at breweries and are waiters and work at the hotels and park cars and all of those sorts of things, will leave. And so our economy over the next six to 12 months will change quite significantly.

And what happens is, those that are labor and at the working wage will go to Charlotte, will go to Greenville, will go to Atlanta, will move somewhere else where they can pay their bills and make things happen.

And again, I think that there's a dimension of this that these are also the people that spoke out during the election and they feel hurt and disaffected and they've got real bills and real challenges and families that are hurting and they've got to make choices and decisions. And so that's the change that we'll see at the working level of our economy.

And I think what will come in is that the Asheville will still be popular with money. And so we have significant amount of tourism and second homes and things, people that retire to Asheville. So it'll grow at the top and you'll get some of the same challenges that you have with Aspen, which is that it's a very expensive place to live. And the economy shifts in dramatic fashion.

It is changing away from the Appalachia that it was, you know, 20 years ago. So we're changing in character as a product of these sorts of shifts.

Chris Mailander
Drew, you've been extremely generous with your time today. This is fascinating conversation. And again, it gets back into how we make long range decisions that affect very short term lives and property laws and our economic interests and the development of our families. And so I want to thank you for joining me and taking us through this.

Tell me again how people can experience your model because that's one of the great differentiators about what you do is that most models are developed, quote, in ivory towers and they spit out a result and here's the graph and it tells you what the right answer is.

People, ordinary people, decision makers, leaders across all stripes and in 20 different languages can go and directly access your model and use it for themselves to experience it.

Andrew Jones
Thank you. Three ways to think about this.

One is very specifically, the simulation is called En-ROADS. The organization that I lead is called Climate Interactive with MIT Sloan. So Google any of that and there it is. And the training course and the game and the workshop and all the different forms, En-ROADS.

More broadly, outside of climate and the economy is the field of system dynamics. We're just one example of this field of system dynamics modeling, which has thousands of practitioners around the world studying and building simulations on other topics, likely in the domains that anybody out there is interested in.

But more broadly, what I'm talking about is really just an Excel spreadsheet away from anybody. It's looking into the future with some grounding in some of the math to envision what things could be, at some point in the future, or it's a flip chart. It's a spreadsheet, it's a flip chart. It is just that process that says, what do I wanna see in the future? Where are we today? What do we think is really driving the change that's going on now? And applying just another level of rigor to the analysis. So it should be accessible to anybody.

Chris Mailander
Right, fantastic, Drew. We'll put all of that in the show notes and so people can access it there.

But that's the key lesson here, which is that your decision is a product of how you think about the problem. And so you're talking about all kinds of different methods which allow us to explore how to think about problems in different ways that we just don't have to shut down. We don't have to step away. There's tremendous opportunity in that. So thank you.

Andrew Jones
All right. Thanks, Chris.