The model that ate Europe

arXiv covers modeling on an epic scale in Europe’s Plan to Simulate the Entire Earth: a billion dollar plan to build a huge infrastructure for global multiagent models. The core is a massive exaflop “Living Earth Simulator” – essentially the socioeconomic version of the Earth Simulator.


I admire the audacity of this proposal, and there are many good ideas captured in one place:

  • The goal is to take on emergent phenomena like financial crises (getting away from the paradigm of incremental optimization of stable systems).
  • It embraces uncertainty and robustness through scenario analysis and Monte Carlo simulation.
  • It mixes modeling with data mining and visualization.
  • The general emphasis is on networks and multiagent simulations.

I have no doubt that there might be many interesting spinoffs from such a project. However, I suspect that the core goal of creating a realistic global model will be an epic failure, for three reasons. Continue reading “The model that ate Europe”

Faking fitness

Geoffrey Miller wonders why we haven’t met aliens. I think his proposed answer has a lot to do with the state of the world and why it’s hard to sell good modeling.

I don’t know why this 2006 Seed article bubbled to the top of my reader, but here’s an excerpt:

The story goes like this: Sometime in the 1940s, Enrico Fermi was talking about the possibility of extraterrestrial intelligence with some other physicists. … Fermi listened patiently, then asked, simply, “So, where is everybody?” That is, if extraterrestrial intelligence is common, why haven’t we met any bright aliens yet? This conundrum became known as Fermi’s Paradox.

It looks, then, as if we can answer Fermi in two ways. Perhaps our current science over-estimates the likelihood of extraterrestrial intelligence evolving. Or, perhaps evolved technical intelligence has some deep tendency to be self-limiting, even self-exterminating. …

I suggest a different, even darker solution to the Paradox. Basically, I think the aliens don’t blow themselves up; they just get addicted to computer games. They forget to send radio signals or colonize space because they’re too busy with runaway consumerism and virtual-reality narcissism. …

The fundamental problem is that an evolved mind must pay attention to indirect cues of biological fitness, rather than tracking fitness itself. This was a key insight of evolutionary psychology in the early 1990s; although evolution favors brains that tend to maximize fitness (as measured by numbers of great-grandkids), no brain has capacity enough to do so under every possible circumstance. … As a result, brains must evolve short-cuts: fitness-promoting tricks, cons, recipes and heuristics that work, on average, under ancestrally normal conditions.

The result is that we don’t seek reproductive success directly; we seek tasty foods that have tended to promote survival, and luscious mates who have tended to produce bright, healthy babies. … Technology is fairly good at controlling external reality to promote real biological fitness, but it’s even better at delivering fake fitness—subjective cues of survival and reproduction without the real-world effects.

Fitness-faking technology tends to evolve much faster than our psychological resistance to it.

… I suspect that a certain period of fitness-faking narcissism is inevitable after any intelligent life evolves. This is the Great Temptation for any technological species—to shape their subjective reality to provide the cues of survival and reproductive success without the substance. Most bright alien species probably go extinct gradually, allocating more time and resources to their pleasures, and less to their children. They eventually die out when the game behind all games—the Game of Life—says “Game Over; you are out of lives and you forgot to reproduce.”

I think the shorter version might be,

The secret of life is honesty and fair dealing… if you can fake that, you’ve got it made. – Attributed to Groucho Marx

The general problem for corporations and countries is that there’s a big problem attributing success to individuals. People rise in power, prestige and wealth by creating the impression of fitness, rather than creating any actual fitness, as long as there are large stocks that separate action and result in time and space and causality remains unclear. That means that there are two paths to oblivion. Miller’s descent into a self-referential virtual reality could be one. More likely, I think, is sinking into a self-deluded reality that erodes key resource stocks, until catastrophe follows – nukes optional.

The antidote for the attribution problem is good predictive modeling. The trouble is, the truth isn’t selling very well. I suspect that’s partly because we have less of it than we typically think. More importantly, though, leaders who succeeded on BS and propaganda are threatened by real predictive power. The ultimate challenge for humanity, then, is to figure out how to make insight about complex systems evolutionarily successful.


This is the latest instance of the WORLD3 model, as in Limits to Growth – the 30 year update, from the standard Vensim distribution. It’s not much changed from the 1972 original used in Limits to Growth, which is documented in great detail in Dynamics of Growth in a Finite World (half off at Pegasus as of this moment).

There have been many critiques of this model, including the fairly famous Models of Doom. Most are ideological screeds that miss the point, and many modern critics do not appear to even have read the book. The only good, comprehensive technical critique of World3 that I’m aware of is Wil Thissen’s thesis, Investigations into the Club of Rome’s WORLD3 model: lessons for understanding complicated models (Eindhoven, 1978). Portions appeared in IEEE Transactions.

My take on the more sensible critiques is that they show two things:

  • WORLD3 is an imperfect expression of the underlying ideas in Limits to Growth.
  • WORLD3 doesn’t have the policy space to capture competing viewpoints about the global situation; in particular it does not represent markets and technology as many see them.

It doesn’t necessarily follow from those facts that the underlying ideas of Limits are wrong. We still have to grapple with the consequences of exponential growth confronting finite planetary boundaries with long perception and action delays.

I’ve written some other material on limits here.

Files: WORLD3-03 (zipped archive of Vensim models and constant changes)

Maya fall to positive feedback

NASA has an interesting article on the fall of the Maya. NASA-sponsored authors used climate models to simulate the effects of deforestation on local conditions. The result: evidence for a positive feedback cycle of lower yields, requiring greater deforestation to increase cultivated area, causing drought and increased temperatures, further lowering yields.

Mayan vicious cycle


“They did it to themselves,” says veteran archeologist Tom Sever.

A major drought occurred about the time the Maya began to disappear. And at the time of their collapse, the Maya had cut down most of the trees across large swaths of the land to clear fields for growing corn to feed their burgeoning population. They also cut trees for firewood and for making building materials.

“They had to burn 20 trees to heat the limestone for making just 1 square meter of the lime plaster they used to build their tremendous temples, reservoirs, and monuments,” explains Sever.

“In some of the Maya city-states, mass graves have been found containing groups of skeletons with jade inlays in their teeth – something they reserved for Maya elites – perhaps in this case murdered aristocracy,” [Griffin] speculates.

No single factor brings a civilization to its knees, but the deforestation that helped bring on drought could easily have exacerbated other problems such as civil unrest, war, starvation and disease.

An SD Conference article by Tom Forest fills in some of the blanks on the other problems:

… this paper illustrates how humans can politically intensify resource shortages into universal disaster.

In the current model, the land sector has two variables. One is productivity, which is exhausted by people but regenerates over a period of time. The other… is Available Land. When population exceeds carrying capacity, warfare frequency and intensity increase enough to depopulate land. In the archaeological record this is reflected by the construction of walls around cities and the abandonment of farmlands outside the walls. Some land becomes unsafe to use because of conflict, which then reduces the carrying capacity and intensifies warfare. This is an archetypal death spiral. Land is eventually reoccupied, but more slowly than the abandonment. A population collapse eventually hastens the recovery of productivity, so after the brief but severe collapse growth resumes from a much lower level.

The key dynamic is that people do not account for the future impact of their numbers on productivity, and therefore production, when they have children. Nor does death by malnutrition and starvation have an immediate effect. This leads to an overshoot, as in the Limits to Growth, but the policy response is warfare proportionate to the shortfall, which takes more land out of production and worsens the shortfall.

Put another way, in the growth phase people are in a positive-sum game. There is more to go around, more wealth to share, and population increase is unhindered by policy or production. But once the limits are reached, people are in a zero-sum game, or even slightly negative-sum. Rather than share the pain, people turn on each other to increase their personal share of a shrinking pie at the expense of others. The unintended consequence-the fatal irony-is that by doing so, the pie shrinks much faster than it would otherwise. Apocalypse is the result.

Making climate endogenous in Forest’s model would add another positive feedback loop, deepening the trap for a civilization that crosses the line from resource abundance to scarcity and degradation.

Another Look at Limits to Growth

I was just trying to decide whether I believed what I said recently, that the current economic crisis is difficult to attribute to environmental unsustainability. While I was pondering, I ran across this article by Graham Turner on the LtG wiki entry, which formally compares the original Limits runs to history over the last 30+ years. A sample:

Industrial output in Limits to Growth runs vs. history

The report basically finds what I’ve argued before: that history does not discredit Limits.

The Growth Bubble

I caught up with my email just after my last post, which questioned the role of the real economy in the current financial crisis. I found this in my inbox, by Thomas Friedman, currently the most-emailed article in the NYT:

Let’s today step out of the normal boundaries of analysis of our economic crisis and ask a radical question: What if the crisis of 2008 represents something much more fundamental than a deep recession? What if it’s telling us that the whole growth model we created over the last 50 years is simply unsustainable economically and ecologically and that 2008 was when we hit the wall ’” when Mother Nature and the market both said: ‘No more.’

Certainly there are some parallels between the housing bubble and environment/growth issues. You have your eternal growth enthusiasts with plausible-sounding theories, cheered on by people in industry who stand to profit.

There’s plenty of speculation about the problem ahead of time:
Google news timeline - housing bubble

Google news timeline – housing bubble

People in authority doubt that there’s a problem, and envision a soft landing. In any case, nobody does anything about it.

Sound familiar so far?

However, I think it’s a bit of a leap to attribute our current mess to unsustainability in the real economy. For one thing, in hindsight, it’s clear that we weren’t overshooting natural carrying capacity in 1929, so it’s clearly possible to have a depression without an underlying resource problem. For another, we had ridiculously high commodity prices, but not many other direct impacts of environmental catastrophe (other than all the ones that have been slowly worsening for decades). My guess is that environmental overshoot has a lot longer time constant than housing or tech stock markets, both on the way up and the way down, so overshoot will evolve in more gradual and diverse ways at first. I think at best you can say that detecting the role of unsustainable resource management is like the tropical storm attribution problem. There are good theoretical reasons to think that higher sea surface temperatures contribute to tropical storm intensity, but there’s little hope of pinning Katrina on global warming specifically.

Personally, I think it’s possible that EIA is right, and peak oil is a little further down the road. With a little luck, asset prices might stabilize, and we could get another run of growth, at least from the perspective of those who benefit most from globalization. If so, will we learn from this bubble, and take corrective action before the next? I hope so.

I think the most important lesson could be the ending of the housing bubble, as we know it so far. It’s not a soft landing; positive feedbacks have taken over, as with a spark in a dry forest. That seems like a really good reason to step back and think, not just how to save big banks, but how to turn our current situation into a storm of creative destruction that mitigates the bigger one coming.

On Limits to Growth

It’s a good idea to read things you criticize; checking your sources doesn’t hurt either. One of the most frequent targets of uninformed criticism, passed down from teacher to student with nary a reference to the actual text, must be The Limits to Growth. In writing my recent review of Green & Armstrong (2007), I ran across this tidbit:

Complex models (those involving nonlinearities and interactions) harm accuracy because their errors multiply. Ascher (1978), refers to the Club of Rome’s 1972 forecasts where, unaware of the research on forecasting, the developers proudly proclaimed, “in our model about 100,000 relationships are stored in the computer.” (page 999)

Setting aside the erroneous attributions about complexity, I found the statement that the MIT world models contained 100,000 relationships surprising, as both can be diagrammed on a single large page. I looked up electronic copies of World Dynamics and World3, which have 123 and 373 equations respectively. A third or more of those are inconsequential coefficients or switches for policy experiments. So how did Ascher, or Ascher’s source, get to 100,000? Perhaps by multiplying by the number of time steps over the 200 year simulation period – hardly a relevant measure of complexity.

Meadows et al. tried to steer the reader away from focusing on point forecasts. The introduction to the simulation results reads,

Each of these variables is plotted on a different vertical scale. We have deliberately omitted the vertical scales and we have made the horizontal time scale somewhat vague because we want to emphasize the general behavior modes of these computer outputs, not the numerical values, which are only approximately known. (page 123)

Many critics have blithely ignored such admonitions, and other comments to the effect of, “this is a choice, not a forecast” or “more study is needed.” Often, critics don’t even refer to the World3 runs, which are inconvenient in that none reaches overshoot in the 20th century, making it hard to establish that “LTG predicted the end of the world in year XXXX, and it didn’t happen.” Instead, critics choose the year XXXX from a table of resource lifetime indices in the chapter on nonrenewable resources (page 56), which were not forecasts at all. Continue reading “On Limits to Growth”