Referring back to episode 4, Kory and Kellan give an update on the scenarios presented in the book "Limits to Growth", with information from updated models, as well as empirical data gained since the original publishing in 1972.
Turner Paper (2012)
The original Limits to Growth (1972)
Episode 39 - Updates to Limits to Growth
Kory: [00:00:00] So Kellan here's a question that I think everybody loves to be asked. did you pay your taxes last year?
Kellan: [00:00:21] Do you want me to answer honestly? Yes.
Kory: [00:00:24] Are you just saying that, pretending that it's your honest answer or is that actually your honest answer?
Kellan: [00:00:27] That's actually honest.
Kory: [00:00:28] Do you think Jeff Bezos paid his taxes last year?
Kellan: [00:00:32] Well, do the ultra wealthy ever pay their fair share?
Kory: [00:00:35] According to ProPublica? They do not.
Kellan: [00:00:37] Oh, let's hear it.
Kory: [00:00:38] this article was released this morning. Uh, this morning when we're recording, obviously by the time this is published, it was probably a week or so ago, but somehow ProPublica came across thousands of tax documents from the nation's wealthiest over the last 15 years. And they won't say how they got them to protect their source. But basically they've over the last few months, been sorting through all this data and checking it and everything just to make sure it all checks out and they put together these profiles of how much taxes, the wealthiest, we're talking like the 0.001% of the U S, paid in taxes.
And then they compared that to what the average Americans pay in taxes. And it's just insane. Like there was years in the last 15 years, two or three years that Jeff Bezos didn't pay any taxes. George Soros, Elon Musk, Michael Bloomberg, other billionaires I've never heard of cause I don't care, they were not paying anywhere near their fair share of taxes. In fact, warren buffet based on the amount of wealth that he acquired over that 15 year period, he only paid 0.1% in taxes. So that's not necessarily his wage, right. And they have their loopholes in their ways that they get around it by claiming losses and deductions on other things and all these weird loopholes. But to think he paid 0.1%.
So they added everything together and basically said, by the end of 2018, the top 25 wealthiest in the nation were worth $1.1 trillion. And that for comparison, it would take 14.3 million ordinary American wage-earners put together to equal that same amount of wealth. That paragraph is directly from the article. So 25 people are making the same as 14.3 million average Americans.
The personal federal tax bill for the top 25 in 2018 was 1.9 billion. And for those same 14.3 million wage earners, it was 143 billion. So the average Americans are paying around a hundred times more for the same amount of wealth in taxes.
Kellan: [00:02:31] I guess I'm not surprised because you hear things like that all the time, but it doesn't make me any less frustrated. it's a reminder of just how unfair things are and if you have that much money, you have a whole lot of sway and a whole lot of power. And why would anybody without much money be motivated to do anything other than ensure that they continue to pay the smallest amount of taxes possible.
Kory: [00:02:51] Exactly. And that's the positive feedback loop of corruption in our political system. And it's especially frustrating because we're watching as catabolic collapse sort of takes place and how the federal budget keeps shrinking. And yet we're missing out on all these taxes from the people who need it least. Meanwhile, the people who are just getting by paycheck to paycheck, your average American, who may not have much in savings, they are paying a significantly higher amount in taxes.
Kellan: [00:03:18] You know, another thing that makes me think of, the fact that we've had these stimuluses in the last year and a half has made it really apparent to people that the government can just print as much money as they want. And I think a lot of people kind of knew that before, but it was just such a drastic example that from what I've seen, it's making a lot of people question things. And in some personal conversations, some group conversations that I've been a part of, I've heard people asking questions, like, why do I have to pay taxes? Why can't the government just print all that money instead of requiring those taxes from all of us, who in some cases are really struggling to pay those taxes.
and I'm sure we could give plenty of answers for that. I feel like I'm seeing this shift in people where they feel more entitled but they also, I strongly feel that it's unfair and they feel like what the government has done with our economic system is unjustified. And you know, the experts out there don't seem to agree either for every economist that says. Pumping trillions into the economy is exactly what we needed and probably still what we need, there's some other leading economists who says we made a huge mistake.
But when you talk about trillions being pumped into the economy by the government, or you talk about the billions that are being saved in taxes by the nation's most wealthy I feel like I see a trend that people getting more skeptical and more confused about what money even is and why it works the way it does.
Kory: [00:04:40] Yeah. And it feels like if this article had come out in a different country or in a different time period, this would be something that would spark so much anger. It would be revalatory. Right. And this is sparking a lot of anger, but I mean, you hadn't heard about this article and I don't know how many of our listeners will have heard of it. It didn't make mainstream national news. And yet it's absolutely disgusting to read, honestly.
And I think people for the most part have just kind of been brainwashed over time into thinking that it's okay, those people earn their money. And if they're smart enough to be able to go around the loopholes or whatever to avoid paying taxes and it's legal then good for them. They're smart. They're not greedy. They're smart.
Kellan: [00:05:17] And I also hear the argument that, you know, big companies shouldn't have to pay taxes or the ultra wealthy individuals shouldn't have to pay taxes because that would make it more difficult for them to provide all the jobs that they're providing and to provide all the production that they're producing for our country.
Kory: [00:05:34] Heaven forbid that there'd be less people peeing in bottles for Amazon on their truck routes and, you know, minimum wage earners pushed into a job that has no benefits and no future for them. I get it that jobs are important, they pay people, but for companies who are extracting our resources, for the main players in industries that are creating waste and pollution, using water, all of these different things, they should be the ones that are paying the taxes.
We've talked before about how our personal contributions or personal footprints are relatively tiny compared to those of giant corporations and the ultra wealthy whose carbon footprint are just massive. So I think, especially in regards to that tax money, going towards trying to give us a better future, that's where it should be coming from, but everyone's entitled to their opinion.
Kellan: [00:06:21] Yeah, that's true. You know, I don't know anybody that's ultra wealthy, but I feel like I have close acquaintances that are under the poverty level and I have close acquaintances that I would consider wealthy. And one thing I do notice about those that I consider wealthy are that they are very skilled at dodging taxes. In fact, that's one of the things they're best at right, is understanding, " Hey, here's exactly the point in time that I can do this with my money to avoid paying this level of capital gains tax." you know, you can't blame them because nobody wants to pay more taxes. But from my perspective, typically they see it kind of as a game. And it's like, here's the rules of the game. And if I can find my way around this rule, or if I can count this as an expense so that I don't show as much profit, so I don't have to pay as much taxes then of course I'm going to do that.
Kory: [00:07:06] Yeah. And I think to clarify when we talk about ultra wealthy. I mean, we're talking about like, like I said, the 0.001%, right? I don't find any fault with someone upper middle class or even, you know, the top 10% who, you know, have worked hard for their wealth. They've been smart. There's nothing wrong with having money. But when you're talking about hundreds of millions to billions of dollars or tens or hundreds of billions of dollars, I mean to then skip out on your taxes, what's the point like that is money you are never going to see never going to use. There's just so much potential for that to help the nation. But it feels like out of greed, it's just hoarded.
Kellan: [00:07:41] Yeah, I agree. Kory I'm excited for today's conversation because when you first started introducing me to collapse those first handful of conversations, you know, the first, what, seven or eight episodes of this podcast, were focused on the fundamentals and kind of laying the foundation of what collapse is and making the case for somebody like me, who had never heard of it and who was highly skeptical, of why it's something I should be paying attention to and thinking about. And in one of those early episodes, we talked about Limits to Growth. And I'll ask you to give just a real brief recap but before I do, I'll mention that I'm really excited to share some of what I've learned since that conversation, as it relates to limits to growth specifically. So maybe just give us a really high level overview of what limits to growth is all about.
Kory: [00:08:29] Yeah. So Limits to Growth was a book that was written in 1972, and it was based off of some computer modeling called the World3 model. It was one of the first computational models that looked at things as a system.
And so basically they plugged in all these different variables based on historic records. So population natural resources, mortality rate, birth rate, that type of thing, and then extrapolated based on how those things interact with each other, through a very complex web of interactions, what would happen in a various number of scenarios based on future growth, basically.
And in the end, they came up with several scenarios, ranging from a fairly rapid and intense collapse, all the way to a scenario that was a sustainability scenario. And then they extrapolated based on, you know, business as usual where we're currently going versus all these different things. Like if we doubled our resources, if we were able to control birth rates and make families smaller. And that was how they came up with all the different scenarios. The business as usual scenario was the one that said we will collapse. And it looked like the timeframe was somewhere around 2020 to 2050 in that time range.
Kellan: [00:09:34] Yeah, that's a great summary. I remember walking away from that conversation, thinking, whoa, like scientists have plugged in the data and just based on the trends that we were on at the time. We were headed toward almost certain collapse. And I remember as you talked me through the different scenarios that they ran, it was almost like they were trying to find any sort of solution. Right? If we had twice as many resources, how far could we make it? Or if we didn't pollute at all, or if we didn't grow our population anymore. Things that were totally unrealistic, but they were still trying to see if we could get to these solutions, would we be saved?
So you mentioned those variables and what they looked at was population food, production, industrialization, pollution, and consumption of non-renewable natural resources. And they were seeing that all of these were increasing exponentially, but they also realized, Hey, we're on a finite planet, and they ran a dozen scenarios. And basically through all that came to that conclusion that. We're all eventually doomed unless we make some serious changes and we'll have to make them very quickly.
Now at the time, this was pretty groundbreaking and just like any big, new area of research, it was suddenly met with a bunch of criticism, a lot of skeptics, a lot of people challenging what was said. In fact, there were some coauthors in a New York times article in 1972 who said limits to growth was, and I quote "an empty and misleading work best summarized as a rediscovery of the oldest Maxim of computer science, garbage in garbage out."
And they're trying to make the point, that you plug in bad data or you make bad assumptions in your modeling and of course, what you get out is going to be something that's garbage. And since that time, there have been all sorts of updates from the original researchers and from other researchers. And there's all sorts of articles and books that argue both sides of it.
But now we're talking about something that took place 49 years ago. and we're starting to see some people in recent years that are saying, let's test it. Let's see if everything they predicted up to this point has been accurate. And if that's the case, we can probably assume that what they're predicted for the future will continue to be accurate.
Kory: [00:11:37] yeah. Basically being able to take the actual pass data over the 50 years, plug that into the same model, or that model updated. And just say, which one of those scenarios they created are we most closely tracking to? And what does that tell us about the future? If we continue on that trajectory, what can we expect?
And I think it's really important to note that the authors of the book: Randers, Meadows and the others basically said that the data given wasn't meant to be specific timeframes. It wasn't meant to be a specific prediction of what was going to happen and how it was going to happen. More, the idea of the model was to get an overall general idea of the ups and the downs and the directions that these different variables would take over time. And they said that lots of times: "don't take this as a prediction of certain years" and that sort of thing. But by doing these continual updates to it, like you said, it is easier to see not only was their assumptions, correct up to this point, but again, what does that mean possibly about our future?
Kellan: [00:12:37] Yeah. So this is a point where I want to pause and just give a lot of credit to one of our listeners. We probably would have just left it at that initial conversation when you taught me about limits to growth. But you know, we frequently get messages from those that listened to the podcast, oftentimes telling us what they appreciate about it at other times, making suggestions. In this case, one of our listeners from across the pond.
Kory: [00:12:59] Great accent.
Kellan: [00:13:00] Across the pond.
Kory: [00:13:02] That's terrible.
Kellan: [00:13:05] And I don't know if he would want his full name used, but his first name is Sonny.
And we just really appreciate the, he reached out and shared a lot of awesome information. He pointed us toward a couple of articles in which researchers have kind of done an update to the limits, to growth testing, how true it's been over the last few decades, and beyond just sending us articles and saying, Hey, read this, he even wrote up an entire summary for us and also gave some additional insight. And so, you know the credit goes to him for the further information we're getting in this episode.
Kory: [00:13:38] Yeah and I wanna point out that we have quite a few people who reach out and send us episodes suggestions, and even send sources and articles and books to read. And that is always really appreciated. Um, you know, I have a whiteboard with all the ideas that have been sent to us written down that I do intend to eventually get to. So I want people to know who have already reached out that we appreciate it, that we take those suggestions seriously, that many of them will likely end up being a show in the future. And so if you do have suggestions for future shows and ideas, please feel free to reach out. We can't promise that we'll use every suggestion, but it does definitely help us to know what people are interested in listening to and helps us find sources that we may not be familiar with already.
Kellan: [00:14:17] Perfect. So we were sent in these couple of articles and I'm so excited to share some of this because as you know, Kory, I'm naturally pretty skeptical and it's easy for me to say, yeah, back in 1972, researchers said, blah, blah, blah. But the proof is in the pudding, right? So it's time to determine, was it totally bogus? Were they just crazy or did they make an accurate prediction and of all the different scenarios that they threw out there which one have we most closely aligned to?
So the first article is from nine years ago, a guy by the name of Graham Turner from the university of Melbourne. And it's titled "On the cusp of global collapse? Updated comparison of limits to growth with historical data".
So Graham Turner takes a look at the original model and wants to test empirical data from the last 40 years to see if we align up to any of these three scenarios from the original report. He tested the standard run, which is what you mentioned, kind of business as usual. If nothing changes, what can we expect and originally, and limits to growth they said, Global welfare levels would kind of top out around 2020, and we'd start to see a collapse around 2030.
Another one of the scenarios was called stabilized world in which we avoid any major issues because we take immediate action and global welfare remains high.
Kory: [00:15:37] And those are basically the two extremes. Right? You had the worst case scenario, which was BAU and the best case scenario, which was stabilized world.
Kellan: [00:15:44] Yup. That's right. And then there was something called comprehensive technology. Which just means it will be delayed, right. Technology is going to help us to not have this sudden collapse, but will instead make it kind of a, a more gradual outcome.
Okay. So as Graham Turner, again, wanted to compare what has actually happened over the last 40 years at that point to what had been predicted by limits to growth, he looked at population birth rates, death rates, industrial output per capita, food per capita, services per capita, global pollution and non-renewable resources. And with each one of those variables, Tried to chart out how much did it line up to each of those three scenarios that we talked about?
And I'll just mention, as I read through it, it was kind of fun to see, you know, terms like energy return on energy invested a fraction of capital allocated to obtaining resources. Catabolic collapse was mentioned in there. There were some mentions of Diamond and Tainter and Greer, and I would not have understood any of that before. So it was fun to see a lot of what we've talked about, show up in a paper like this.
Kory: [00:16:49] I'm just glad, you know, I'm not making it up.
Kellan: [00:16:50] Well, I wasn't sure until I read this paper. But early on in the paper, it's really not that long of a paper, but there's a paragraph and I just want to read it to you Kory and get your thoughts on it. It says, we found that 30 years of historical data compared very well with the limits to growth baseline or standard run scenario. The standard run scenario embodies the business as usual social and economic practices of this historical period of the model calibration 1900 to 1970 with the scenario model from 1970 onwards.
So if you followed that early on, they state things stuck really close to business as usual
Kory: [00:17:27] Which I think having done the podcast now for as long as we have and gone going through the episodes that we have, that seems right. You know, looking back at growth and everything that's been happening over the last five decades, it does certainly seem like we have not slowed down at all. That being said, it's still tragic and scary to hear that, that business as usual scenario in which things started to slow down, downturn in the 2020s and in the 2030s really started to collapse is pretty frightening.
Kellan: [00:17:54] Yeah, I agree. Frankly, it would have been nice for him to say, Hey, I looked at all the data and it turns out they were crazy.
Kory: [00:18:01] Congratulations everybody. We're fine.
Kellan: [00:18:03] Yeah. Um, but he kind of restates it in the conclusion. He says this, " the data review continues to confirm that the standard run scenario represents real-world outcomes considerably well. This scenario results in collapse of the global economy and population in the near future. It begins in about 2015 with industrial output per capita falling precipitously followed by food and services. Consequently death rates increase from about 2020 and population falls from about 2030 as death rates, overtake birth rate." does that make you feel warm and fuzzy?
Kory: [00:18:38] Makes me feel something I'm not sure that warm and fuzzies, the words I'd use.
Kellan: [00:18:41] Okay. So that was 2012, right? Which now we're in 2021, we've got nine more years of data. And so we're not going to stop there. We're going to take a look at a thesis from a master student named Gaya Branderhorst. And this was really quite recent. It was just in March of 2020 at Harvard university. It's called "a thesis in the field of sustainability for the degree of master of liberal arts and extension studies."
And I'll just say that I completed a master's degree. In my degree I didn't have to complete a thesis, but my wife, when she did her master's degree, she did have to do a thesis and it was awful.
Kory: [00:19:15] Her thesis was awful? Dude she listens to this podcast?
Kellan: [00:19:19] Her thesis was very well done, but the process was terrible. It was a lot of work, so much research. You know, so much pressure to make sure everything's very accurate. It's reviewed by high profile people. I helped her along the way here and there. And I just got to say congratulations to Gaya for completing a thesis which is a hundred pages long.
Like I said, this was at Harvard. And I'm not sure exactly how this works, because if you'll remember Graham Turner was at the university of Melbourne, but Graham Turner was the thesis director for Gaya on this thesis. So you can imagine where he did his research and report in 2012, he probably had a very strong interest in knowing has this continued to hold true. And he was able to help this master's student to complete her thesis and give us the updated information.
So the difference with this one is that Gaya used an updated model. You talked about the model before, Kory, that was used in running these scenarios. It's called world3. Since they updated it a couple of times since then, that first one is world three dash zero one. And there has since been a world three dash zero two, and a world three dash zero three. She used the most updated model.
And frankly, I don't know all the differences between the updates in the models themselves. Obviously there have been updates to make those more accurate and more relevant. But Gaya also didn't just look at three of the scenarios. She looked at four of them. She looked at business as usual, like we talked about and stabilize world and comprehensive technology, the same ones that Turner looked at, but she also looked at one called business as usual two in which there was an assumption that we had double the resources. And the original limits to growth researchers concluded under business as usual two that we still hit collapse as a result of pollution.
Kory: [00:21:05] Yeah. So instead of running out of natural resources, we use those natural resources to agree that we polluted the planet too much. And that pollution caused collapse.
Kellan: [00:21:14] Yeah, exactly. so you might not be surprised to find that of the four, the one that least aligned with what's actually happened over the last 49 years was stabilized world.
Kory: [00:21:25] They were basically like, yeah, just throw that one out. Not going to happen.
Kellan: [00:21:28] Yeah. It's kind of interesting because they've kind of shown the trajectory of each variable on these charts. And so you can see a line for each scenario and you can see the line of the actual empirical data to see how closely it aligns. And yeah, we missed the mark on reaching the stabilize world outcome. It was the least, the next least was actually business as usual and then business as usual two. And then the one that actually most aligned was comprehensive technology.
And Gaya went into it thinking that, you know, she'd see the exact same thing that Turner saw eight years before, but she said this, this is a quote from her paper. " My hypothesis was rejected. But this could change with an update of the comparison because for several variables, the scenarios only diverge significantly after 2020. This is especially so for business as usual two and comprehensive technology, which is why it was not possible to differentiate between them. It's thus unclear whether a future decline can be expected to be moderate or sharp, but both scenarios indicate society will run into limits in the medium term.
So then she goes on to explain that a little bit further but it's so interesting. Cause again, looking at the charts, going back to those lines, business as usual two and comprehensive technology basically follow the same course. They hug each other right up until a little bit after 2020, and that's when they start to diverge.
So she's saying according to what we've seen over these last few decades, we're following really closely what was predicted under a couple of these scenarios. And those scenarios, both indicate there will be collapse but one of them indicates it'll be more long-term, right. It'll be gradual. The other indicates it's going to happen really soon in the next couple of decades.
And at least according to the models, it's going to be within the next five years or so that we'll start to see which of those two paths we take.
Kory: [00:23:20] And it's interesting because she noted that while it most closely tracked to BAU2 and CT, being comprehensive technology, she still noted there is a possibility because of how close those lines generally are that with data over the next five to 10 years, we could see that we're actually still tracking closer to BAU, to business as usual.
And what's really interesting is that she mentioned that there is every possibility that it could be a mixture of the two, right? It could be somewhere between comprehensive technology and business as usual two, and even business as usual. And just to clarify a little bit what these graphs look like as far as what happens in the future, comprehensive technology is basically them saying we're going to come up with all of these technologies that prevents us from collapsing. We're going to work really hard to fix pollution and lower our footprint, and we're going to be able to increase our resources and that that's going to continue exponentially. I think she said that for it to be possible, we would have to increase our technological advancements by 4% per year, which would also mean that we would decline our pollution by 4% per year. And we'll talk about what they considered when they talked about pollution here in just a second, because they aren't able to capture everything obviously involved with that. But what she did say was we have no way shown that we are going to reduce our fossil fuel emissions, at least not in the very near future. And so over the next five to 10 years, it could be very telling which path we're going to follow.
In that scenario, the comprehensive technology, it showed that we continued to increase in industrial capital. So we continue to grow economically and we continue to grow in human welfare until it hits a point around, I think it was like 2040s, 2050s when it takes a big bump and welfare goes down. So basically our standard of living decreases and I think it was a decently significant amount. It wasn't probably what we all picture when we think of a full-on collapse, but our standard of living does decrease and then it flattens out and kind of just waves back and forth through 2100. And so she says, you know, that doesn't necessarily constitute a collapse, perhaps. I think it could still represent very large scale changes, right? Because the economy also stops growing. So everything that would happen to the financial system in that scenario, it is in no way, an easy road. And like you said, Kellan it does still eventually lead to collapse. Whereas the business as usual two model. It is full on kind of what we picture is collapse.
The population tanks, the standard of living tanks, and they all bottom out. You know, it would be a regression quite a bit from our current standards of living.
Kellan: [00:25:48] So fascinating to me in a lot of the conversations we've had, because we've done a kind of a mini series within this podcast of "can technology save us" and over and over and over again, the conclusion seems to be, gosh, this technology that we're taking a look at. Yeah. Very, very unlikely that it's going to save us. It's still important because it's going to help mitigate some of the issues, but it's not going to prevent collapse. And this thesis is essentially backing that up. Right? So to me, it's kind of alarming to think, hey, this was just kind of an idea thrown out there based on trends at the time, almost 50 years ago. And yet now look, Hey with 50 years of data, since then, according to this model, we are headed toward collapse one way or another, and either we're going to collapse in the next couple of decades or, you know, we'll make it to 2100.
But there's one caveat on all of this, because you might be thinking, oh nice. We were following comprehensive technology. You know, that means we've got more time. That means to some degree technology is going to save us, but the model doesn't fully take into account climate change. You know, they, they kind of do, they label it under pollution and in the paper Gaya, you know, here's another quote. She says "we use two proxies, CO2 and plastics." So they do look at CO2 and plastics and what those levels are at, but they're not factoring in all of the feedback loops that we've talked about. And a lot of the other kind of escalating outcomes that we've mentioned as it relates to climate change.
Kory: [00:27:11] Yeah, since the very beginning, 1972, when they first release the book, they said, this is a very simple model, there's so much that we cannot calculate here. And back in 1972, they didn't really even know the full effects of climate change.
Now, when I, I say simple, I mean, if you look at the feedbacks that they have listed, they have a, basically a chart showing how each thing connects to each other and it takes up two full pages and there's like a hundred different things on there that all have arrows pointing in different directions. I mean, it's, it's complicated, it's complex, but.
There's no way it can match the true complexity of ecosystems and biodiversity and climate change and the way that feedback loops work and tipping points. So just looking at plastics and just looking at CO2, it does not give a full picture. You know, within the model they're not able to see the full effects of sea level rise. And all of these things are going to have drastic effects on our resources, on where our resources are allocated on how much we're able to put towards industrial output and human welfare and how much we're going to have to put towards just fixing these continued problems that come about.
And while it is, you could say a flaw in the model, it's a flaw that's been admitted from the very beginning. But for that reason, and Gaya talks about this in her paper. It's very important to understand that these models are conservative. We're talking about best case scenarios in comprehensive technology and best case scenarios in business as usual two.
Kellan: [00:28:34] Yeah. And going back to just how complicated it all is. Even outside of climate change itself. When you talk about these different variables that they were looking at in these reports, you know, in none of them are we exactly on the line of what was predicted. Generally we're close depending on which scenario we're talking about, but on you know, population, resources or any of the other variables, you know, on some we're a little bit below, on some we're a little bit above. And so trying to compile that all into one line graph that shows yeah here's exactly overall how close we are to what was predicted is a challenge. So there's still a lot that's unknown, but you know, for me personally, because perhaps I'm as skeptical as I am of everything that I hear, I tend to think anybody that's stating something bad is going to happen is probably overreacting. That yeah, things might get bad, but they're not going to be as bad as you're talking about. So for example, as we were approaching the most recent US presidential election, I remember at one point telling you Kory like, man, I just don't see any way that it's not going to go totally crazy. And that the whole nation is going to erupt into pockets of violence. Like the tensions were so high, we were seeing violence and I kind of thought, Hey, on election day we're just going to see riots breaking out in the streets.
Now I was wrong on that, but I also didn't predict, you know, the capital riot. But my point is, you know, I thought everything I'm seeing indicates things are going to be really bad at this point. And in the end there was some craziness, but it wasn't as bad as I thought. And I've often wondered that during our conversations about collapse, like we talked about all these awful things that it looks like are going to happen. But I just keep thinking yeah, I probably need to dial that back a little bit. I do think it'll get bad, but I don't think it will get that bad, but then I see all these updates to limits to growth, and I see how closely we have actually followed over roughly 50 years what was predicted clear back in 1972. And I see where those trend lines are forecasted to take us. And I guess it just really makes, you know, reality set in for me that this isn't all crazy. It's not just garbage in garbage out flawed data in a flawed model. Clearly it's proven to be correct up to this point. And it's just one more layer on this whole story that I'm starting to really believe.
Kory: [00:30:51] Yeah. You know, it's interesting. One of the things you mentioned is the different perspectives that people have on collapse. Um, you know, you talked about this idea that when things were really high intensity and high tension. There was this thought that things are about to get really crazy and then it kind of chilled out for a little bit and then it got crazy and then it chilled out again. And, you know, you see on, for example, on the collapse subreddit, it can be quite like doomery, right? There's a lot of people who are really like, we're gonna all die in the next five years, the next decade. And people get very into the hype of it.
You start to get in over sensationalized stuff and. And it actually takes away it discredits the idea of collapse because every time somebody says a BOE is going to happen this year and then the world's gonna explode, you know, and then it doesn't happen. It takes away from that credibility a little bit. But what I was going to say is there are so many different ideas of collapse and Gaya actually had some really interesting things to say about what she thought, uh, could potentially happen based on her extrapolation of the data. And I'm just going to read this part of the paper.
She says " therefore, we will see unprecedented innovation in fields like renewable energy pollution, abatement, resource efficiency, agricultural practices, and disaster resiliency. Although not as much as in the assumptions underlying comprehensive technology." So she's saying we're going to see a ton of technological advancement. Maybe not as much as projected in this optimistic scenario. She says, "these technologies will come at major costs. It is these costs that caused declines in comprehensive technology. But because world three, (the model they used) lacks a distributional factor in this scenario, they are born equally by every person."
So this was something that was super interesting to me is that she said there are going to be high costs for all this technology we come up with. But guess what? This model does not take into account who bears those costs. The model doesn't care about wealthy or poor, but the real world does.
So she goes on to say, " in this scenario, they are born equally by every person. I do not think this will happen in the real world. Amidst major income and wealth inequality, a mix of comprehensive technology and business as usual two will mean that negative impacts from pollution on water and food supply, human health and weather patterns will be largely spared from those that can afford the technological solutions and born mostly by those that cannot. Basically, when I say that I expect a mix of the two scenarios I mean that some of us will experience a comprehensive technology future while others will experience the BAU two.
So that impacted me pretty hard realizing that yeah, you know what, for the wealthy, the ones who can continue to afford this technology, they may continue to have a somewhat comfortable future. Their standard of living may decline a little bit. But it will level off because they will have these technologies that keep them going. Meanwhile, the poor, they will bear the costs of not just that technology that will be required to keep the wealthy comfortable, but they'll also bear all the costs of increasing pollution and lack of resources and climate change and all of the things that we've talked about in this podcast. And to me, I know we brought this up before, but it brought back the whole idea of what a future looks like in the book, the hunger games. Some people hate when we do this, bring up fictional stories, but I think it just, it captures a really quick image in your mind if you've read the book or seen the movies of this world, where the wealthy have these crazy technologies.
And, you know, in that book, their lifestyles are so lavish, but at the same time, their standard of living still seems less than ours today. Like they're still in kind of a ratty like dirty world, but the technologies that they take advantage of help them to stay more comfortable. Meanwhile, the entire rest of the population is just dirt poor, barely scraping by living in the streets, in the outskirts, away from the wealthy. And that seems to be the type of scenario that Gaya is describing here.
Kellan: [00:34:33] I'm so glad you bring that up because you know, of all the variables that were considered in these models, one of them had to do with food output, right? How much food is being produced. And that's one of those areas where when you look at what has actually happened over the last few decades, it didn't go as predicted. You know, in reality food per capita has remained pretty steady. And yet, despite that, the number of undernourished people in the world is going up. And so it just proves that point, that things aren't distributed equally. We can expect to see ya know collapse of poorer nations, probably first or poor people in rich nations.
and it's sad, right? We, we talked about in a previous episode, how more people are dying of obesity than people who are dying of starvation. And when we talk about the way any of our resources are being distributed, it's very unfair. And even as we've discussed, you know, overpopulation versus over consumption and really what it comes down to is how much are the people that are here consuming. Frankly, we have plenty to go around. And yet that's not the case and based on our trajectory, that will be even less and less the case going forward.
Kory: [00:35:42] Yeah. She had some really good insights in the paper. And one of the questions that she brought up that I actually really liked was she said, if comprehensive technology is sort of the optimistic scenario, she said, should we even be aiming for that? Like, do we really want that? Because all that is is us finding ways to allow ourselves to continue to grow. We're just continually putting more band-aids, finding new solutions that allow us to keep the growth rate up. She said, shouldn't we just care about taking care of our resources and taking care of the earth.
You know what good does it do us? If we have little robot honeybees going around pollinating all the plants if we've lost that valuable part of nature, and she puts it like this, she says, " this illustrates one of the major reasons that humanity cannot be expected to technologically innovate itself out of an environmental crisis. As long as the goal of economic system is perpetual growth, technological developments will mostly serve to sustain growth, not life. And as long as growth continues, new limits will be met." So she's basically pointing out that we're valuing growth over life. And as we continue to grow, we'll meet new restraints. There will always be limits to growth.
So it will be interesting in the next few years to see as more of these updates come out, especially because they said 2020s is where it really starts to diverge, to see which path we're on. And so we'll continue to do updates. I think, as they come out.
In the end, we want to thank again Sonny who sent us the sources and the suggestion for this episode. We also wanted to make a special request this week. If you have apple podcasts, if you could subscribe to the podcast there, it really helps boost our ratings. It helps us be more visible to others. This last week we realized that we almost breached the top 50 documentary podcasts in the U S in apple, which once you do that, you become visible on the main screen of the documentary podcasts when people are browsing. So it's just another way for us to get out there more. Help more people learn about these important topics. So leaving a review, subscribing on apple podcasts, downloaded on apple podcasts does us a great service.
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