# Locklin on science

## Cybersyn and Allende’s Semi-Automated Luxury Socialism

Posted in econo-blasphemy by Scott Locklin on February 26, 2019

One of the interesting “what ifs” of history is “what if the 70s-80s commies used computers to do their planned economy.” Men like KantorovichNikolay Fedorenko and Victor Glushkov helped develop some of the mathematical tools and computer systems which would have made this possible.There were abortive attempts to build this in East Germany (pdf link), the Soviet Union and Allende’s Chile. As far as I can tell, the Soviet and German efforts were crushed by old guard party rednecks who feared losing control to technocrats. Oddly, Allende’s attempt at this, which would have been constructed of bone knives and bearskins, seemed to come closest to being deployed.

The visionary behind this was Fernando Flores, who is still alive despite being Allende’s minister of finance and later “General Secretary” back in the early 1970s. Flores was inspired by a sort of futurist “cyberneticist” operations research proponent named Stafford Beer. Operations research is generally now thought of as the field of applied work involving optimization; linear programming and all that. In those days  it was something more general: mathematics applied to the problem of management. Guys like Beer with this sort of training ended up running large parts of the war economy.

It’s difficult for me to characterize what “cybernetics” is, probably because it doesn’t really mean anything. Norbert Wiener, who I respect, coined the phrase, and more or less defined as a hand wavey general study of systems of feedback and control mechanisms. As far as I can tell, “cybernetics” was a complete bullshit field, and what it really meant was “I know futuristic looking words and have Wiener’s book on my shelf; pay me more.”  Stafford Beer was a proponent of “management cybernetics” which, as far as I can tell, meant “using data to make business decisions.”  The books are hysterical; you can go look at them on filesharing sites. They appear to be total horse shit. FWIIW the Soviets more or less agreed with me, at least in 1947; the field of cybernetics was condemned as “a science of obscurantists, a pseudoscience wedded to obscurantist epistomology.”

This looks like it pertains to something real; nope

Flores hired Beer. Beer cut his rates to $500 a day (about$2500 in today’s money) along with unlimited cigars, chocolate and wine; items the Chilean government had a surplus of. Mind you the Chilean government was being starved of dollars at the time as a form of colonial pressure, just as the Venezuelan government is now in 2019. The results were hilarious.

The thing Beer built for the Chilean government is most famous for its control room, so we’ll start there. It had a bunch of cool chairs where powerful human intelligences would examine data on the walls and vote on the cybernetically optimal next steps. The chairs are TOTALLY not based on Captain Kirk’s control chair from Star Trek; every account of the thing makes certain to mention this. I assume Beer got a lot of shit over it, and rightly so, because he totally copied this from Star Trek. Or, if he didn’t, his designer did.

The chairs come equipped with ash trays (men of power always smoked in those days) and a place for a whiskey glass, presumably in case Castro or Beer wanted to relax while making important decisions. There are 7 of the chairs to make sure they can always achieve consensus when they vote. They use ridiculous glowing geometric buttons (like on Star Trek) instead of keyboards. The main reason is because they’re all hardwired to physical mechanisms; the images and graphs on the wall are not computer generated or directly interfaced with a computer at all. They’re slides and viewgraphs that are manually put in there by human helpers behind the walls. The lack of keyboard has also attributed to keyboards being “feminine” or confusing to men, which may be true in some way, but which doesn’t make any sense, as male factory workers used the teletypes to communicate factory data with home base.

The important pieces in the background, besides the workers behind the curtain, were the computer, an antique that they had on hand, and dozens of teletype machines they distributed to factories and control points to relay important metrics and data back to home base. These metrics would be entered into the computer (by hand), which would presumably generate reports (it’s not clear this ever happened) which would be manually turned into viewgraphs and slides by artists. The display of these slides would then be controlled by heavy drinking/smoking men in Captain Kirk Star Trek chairs, just like when they show you their vacation photos on a carousel slide projector. Except it was 7 people controlling the projector and arguing about what it all means.

People go on about how futuristic this was, because … I dunno, muh internet and muh powerpoint is used to make business decisions now. The reality is, Beer built the Allende government the economic equivalent of one of those WW-2 era RAF air defence sector station operation rooms with a little futuristic woo slapped onto it. It has some trappings of high technology with the Star Trek like buttons, but those buttons really didn’t do much of anything. The data allegedly eventually feeding  back to the computer could have been more effectively gathered by people on the telephone with yellow legal pads rather than the teletype, just like it was in a WW-2 era RAF air defence command center. In fact, factory managers ended up routing around the central command center and teletype process by calling up other factory managers and working out potential supply issues.

The one time it was allegedly useful was during a CIA organized truckers strike. You’d expect any central data/controll station to be useful in a crisis situation, more for putting decision makers in a room where all the data is available than anything else. Pretty sure the slides, assuming any were made for the event, and the computer, assuming any data was entered into it, were not helpful here.

It may have eventually been a helpful tool if Pinochet hadn’t taken over, thrown many of those involved out a helicopter, and destroyed the room of socialist power. The fancy appearance of it was almost entirely Potemkin village though. It relied on people entering stuff into the system at the collection end. It relied on “data science” people writing code. And it relied on artists marshalling the data into useful and insightful visual reports. It also relied on people who managed the factories to obey, and in a timely fashion; presumably once you finished your whiskey and cigars, you summoned a telephone to tell the factory workers what to do. All of these things are guaranteed to more or less fail.

Even small design decisions were foolish. The controls; why should everyone in the room be able to control the view? How could everyone in the room control the view? We don’t give everyone a remote when we do powerpoint now. Beyond that, how does the cigar smoking drunk in the chair know what slides are where when he’s pressing his buttons? It changes every meeting, and some boob in the background could screw up the order of the things. Who sets the agenda? I strongly suspect the guys in the chairs would be shouting through the walls to get the secretaries to pull up different slides. Also the voting buttons. Seems very scientific and futuristic to have the seven cigar puffing drunks in the Captain Kirk chairs voting by some kind of electrical secret ballot to make decisions. Why wouldn’t they just say “dude this sucks?” How would it make a difference? And of course, there was no way to actually transmit decisions using all this fancy electronics, besides the telephones they should have used in the first place.

The SAGE system was a real world embodiment of this sort of thing, built 15 years earlier. Unlike Cybersym, it was a real time system, with real time data flowing into a central processing unit, and real time commands being sent out to remote bases. SAGE also had human operators who helped the computer make the right decisions. SAGE worked (we think) because it actually was entirely networked, and the data flowed quickly, and split second decisions were absolutely necessary. SAGE also didn’t have any goofy fake control panels with a place to put your liquor, or LARPY telex stuff where secretaries had to do data entry to put the data into a computer. But, at the time, it was probably fairly difficult to see this, and people who watched a lot of Star Trek were probably impressed.

I’m not sure how the detailed history of this played out. It’s entirely possible American spooks ramped up their efforts to depose Allende in part because of fear of this. US economists and analysts almost always overrated Soviet and communist efficiencies. In part this happened because the Soviets would occasionally surprise people with things like Sputnik. In part it was rice bowl politics; you get a bigger budget for the scary threat rather than the third world threats made of coconuts and rubber band slingshots. But mostly it was because the technocrats and economists who purported to study Soviet economics thought their own farts smelled of roses. Western economists in those days were not the mere bean counters and toadies for capital they are today: they had vast powers to regulate the economy, set prices and so on. They just assumed more regulation of the economy would cause it to run more efficiently. They believed their own bullshit.

The threat of a more efficient civil service is taken very seriously by governments. For examples from history, the late Imperial government of Russia was seen as a great threat by Germany as it had developed an efficient and productive civil service. One which was rapidly industrializing the country and improving its logistics with a fraction of the per capita civil service manpower of Germany. WW-1 may have been partially a result of this fear. I can’t  prove any of this without access to spook internal documents and reports on Cybersyn. But I do have the example of an article in New Scientist who described Cybersyn as potentially “one of the most powerful weapons in history.” I mean, it very obviously wasn’t and probably couldn’t have been with the approach they took. But the CIA had no real way of knowing this.

As a sort of weird coda to all this, apparently Brian Eno and later David Bowie and David Byrne befriended Beer. I kind of wonder what they talked about, or if they just partied. As mountebanks go Beer seemed like a fun guy. Any proto data scientist who puts ashtrays and whiskey cup holders in a Captain Kirk control chair can’t be all bad, even if he was full of shit.

Bones send whiskey and smokes, stat

https://www.newstatesman.com/world/2018/08/project-cybersyn-afterlife-chile-s-socialist-internet

https://www.newyorker.com/magazine/2014/10/13/planning-machine

https://mitpress.mit.edu/books/cybernetic-revolutionaries

https://www.jacobinmag.com/2015/04/allende-chile-beer-medina-cybersyn/

http://www.guardian.co.uk/technology/2003/sep/08/sciencenews.chile

https://en.wikipedia.org/wiki/Project_Cybersyn

## AI is not eliminating jobs

Posted in econo-blasphemy, machine learning by Scott Locklin on February 9, 2019

Midwits keep asserting that “AI” is going to eliminate jobs. They say things like “those jobs aren’t coming back because of AI” (or screws or whatever other dumb excuse: but they’re real sure about those jobs not coming back).  These are not statements of scientific or technological fact, or even a reasonable prediction based on present trends. These are ideological political statements. “AI” is a soundbite/fnord excuse for not doing anything about the policy problems of the present.

The ruling caste of American tech and FIRE lizard people continue to make these statements, not because they are inevitable, but because this is their desired future. Their preferred future is a population consisting of powerless, preferably drugged up serfs on the “universal basic income” dole, ruled over by our present ruling class of grifters, rentiers, pyramid scheme salesmen, watched over by a surveillance hellscape.  The lizard people would like to continue our present policy of de-industrializing the country, breaking what little labor negotiating power US citizens have, and atomizing people to their raw protoplasm. It’s almost like a Freudian slip. Don’t bother agitating for any rights, slave, we soon will have electric Golems and won’t need you!

The most murderous drug dealers who ever existed … Google’s AI dude thinks they’re great! https://twitter.com/JeffDean/status/1093953731756867584

Oh I am sure the Google doofs would like to develop and control some strong AI, and perhaps a robot maid to replace Juanita. I, too, would like to have a magic technology which gives me infinite power, and a robot maid to iron my shirts. If I were a Silicon Valley oligarch rather than a humble nerd, I might develop delusions the pile of C++, Javascript and tech drones which made me rich could become a Golem of infinite power. Personally,  I would build rockets. At least I could get away from lizard people who want to turn the world into a soy dystopia.

If these clowns really believed that “AI” were something actually like an “AI” which could replace humans in general tasks, they’d use it to replace computer programmers. At one point in history, people believed CASE tools would eliminate most programmer jobs. How’s that working out for the AI geniuses at Google? They can’t even automate devops jobs; devops being one of the most automatable roles in tech companies. Devops tasks don’t seem much different from a computer strategy game.

Google’s “AI” team can’t do this useful thing, which, even by my lights, actually seems  achievable. Yet somehow, google boobs think they’re going to violate Moravec’s paradox and replace drivers. Think about that for a minute. It’s becoming clear that autonomous vehicle “technology” as sold to people for the last 10 years is basically fraud, and is still stuck in the 1980s when Ernst Dickmanns was driving around the autobahn with Sun Workstations in his back seat. Demonstrations of this tech always have a human in the loop (remote or in vehicle), because moving automobiles without human control are death machines under most circumstances.

Inside of the UniBwM autonomous experimental vehicle VaMP, at the rear bench where the computing system was installed for easy access and monitoring. This was at the PROMETHEUS demonstration in Paris in October 1994 | Photo by Reinhold Behringer

Even assuming I’m wrong and the media hyperbole is right and full level 5 autonomous vehicles are “right around the corner” Google also has zero business interest in “disrupting” driving. Google is a tech driven advertising company with a  collection of loss leaders. Yet they go after this preposterously difficult, possibly impossible task. Why not disrupt a business they presumably know how to disrupt, like that of the lowly ops engineer? At least this would be good for their bottom line, and it would be a real step forward in “AI” rather than a parlour trick perpetuated by marketing nerds and started by obvious mountebanks.

From a semiotics point of view, this shows astounding hostility to the types of people who drive cars and trucks for a living. Drivers are … ordinary, usually uneducated, salt of the earth people who have a fairly independent lifestyle and make a decent living. Google overlords must really hate such people, since they’re dumping all this skrilla into ruining their lives for no sane business reason. They will almost certainly fail, but man, why would you try to blow up those people’s lives? If this country really wanted to get rid of driving, or considered it a serious problem that there are too many cars on the road, or thought that people now employed as drivers should do something else, we had a solution to this problem invented in the late 1800s.

The other professions  people “think” will be replaced always seem to be low caste irritations or lawyers (lol). You regularly hear “experts” talking about how presently common jobs won’t exist in 20 years because of “AI.”  I’ve said multiple times now that all estimates for delivery of something in 20 years are bullshit. A prediction that a technology will do X in 20 years means “we don’t know how to do this, but we want your money to fool around with anyway.” Controlled nuclear fusion researchers being the most amusing case of the perpetual 20 year rice bowl. 20 years is a magic number, as it’s plenty of time for a technological mountebank to retire; and it’s at least 2-3 generations of tenured academics, which is enough to turn a scam subject like “quantum computing” or “nanotech” into an actual field.

“AI” doesn’t exist. Machine learning is a force multiplier and productivity enhancer for statisticians. If you believe the “automation”=”no more jobs” ding dongs, machine learning should have at least automated away the job of statistician. Yet somehow, the  statistician (aka “data scientist”) jobs are among the best paid and most in-demand jobs out there at present.

The last job category I can think of which was automated away is Flight Engineer on airliners. It mostly went away because of automation of airliners, but it wasn’t even computer related; just normal improvements of systems monitoring and reliability; good old mechanical and systems engineering. Despite 1/3 fewer seats in airliner cockpits, there are now more people with airline flight officer jobs now than ever before. Planes got cheaper and there are more of them servicing vastly more people.

The example of Flight Engineer is how the world works. Technological advances increase human power over nature and makes more things possible. Actual “AI” advances, should any eventually materialize, will work exactly like this.

AI has eliminated exactly zero professions, and essentially no jobs. Since the best prediction tool for a market is generally a random walk, my forecast is, barring giant breakthroughs, this trend of “nothing important actually happened” regarding AI job destruction will continue. If you disagree with me and have an alternate prediction on a normal human (aka 5 or 10 year) timescale, I am happy to entertain any long bets on whatever platform you care to use.

## On beating roulette: part 3

Posted in econo-blasphemy, Gambling systems by Scott Locklin on March 14, 2016

This is third in a four part series. Part 1 here, part 2 here.

To my mind, the most mathematically interesting thing about roulette is the betting system you should use to maximize your wins. Bet sizing systems are important in all probabilistic games, and the types of lessons learned from a winning game of roulette are the same types of lessons you need to learn in betting on other things, like success in trading, or having an edge on the wiener dog races. The nice thing about a game of roulette is it is relatively easy to characterize your edge. Most people’s edge over the roulette wheel is negative, so you should not bet. If you built one of the computer gizmos I went over in part 2, you have a positive edge over the roulette wheel.

We know from results in information theory, that sequential bets in the presence of an edge should be sized according to the Kelly Criterion to maximize bankroll growth rate.

$betsize = \frac{bankroll * edge}{house odds}$

or, in more probabilistic terms;

$betsize = \frac{p * odds + p -1}{odds}$

where $p$ is probability of success.

It’s probably not immediately obvious why this is so, but consider a biased coin toss at even odds ($1 payoff for$1 bet). If your coin’s edge is 100%, you gain money fastest by betting your whole bankroll. If you have 0% edge, you shouldn’t bet anything. If you have a 1% edge, you should bet 1% of your bankroll.

Daniel Bernoulli came up with the same fraction a long time before by maximizing the geometric mean.

Kelly’s original paper figured this out by modeling how a better would place bets assuming he had insider information transmitted over a noisy wire transmitting a binary code; a beautiful way of thinking about predictions in the presence of noise. Kelly is a guy I wish had lived longer. He dropped dead at the young age of 41; in his short life he was a Naval aviator in WW-2, invented computer speech synthesis, made huge contributions to information theory, mentored important mathematicians (Elwyn Berlekamp, who went on to found Axcom/Rentech, based in part on Kelly’s insights) and had the kind of life that would be considered hyperbole if he was in a science fiction novel.  They make big men in Texas. Kelly was a giant.

I’m pretty sure his testicles smoked unfiltered camels

I’ve been known to take sadistic glee in making fun of economists. One of the most mockable economists in American history is (Nobelist -the Swedes have dry humor) Paul Samuelson.  One could write entire books on the ways in which Samuelson was a scoundrel and a numskull who set back human knowledge by decades. One fact will suffice for this essay: Samuelson didn’t believe in Kelly betting. Explaining why he thought this, and why he’s wrong would be pointless; debugging an economist’s faulty thought processes is as pointless as explaining why a crazy lady is breaking dishes in the kitchen. If you’re interested, Ed Thorp is your man here also.

Ed Thorp is the man, period

Following Ed Thorp’s original essay in the Gambling Times, as good little experimental physicists, we need to build up an error budget to figure out our edge.  Thorp breaks down the errors in his and Shannon’s Roulette system into several kinds.

1. E1 Rotor speed measurement error
2. E2 Ball speed measurement error
3. E3 Ball rotor path randomness
4. E4 Ball stator path randomness
5. E5 Fret scatter
6. E6 Rotor tilt (discovered by Shannon and Thorp)

Uncorrelated errors add up as the sum of squares, so the total error budget is

$Error = \sqrt{\sum_{n=1}^{n=6}{E_n^2} }$

The Thorp/Shannon roulette system had a 44% edge on the most favored number; single number payouts in Vegas are 35:1, making the correct bet on one number 0.44/ 35 = 0.01256. Since nobody in 1960s Vegas suspected the mathematical machinators of having a physics edge on the wheel, they were able to place larger bets on parts of the quadrant. While Thorp describes it as “diversification” in his exposition. Another way of thinking about it: he’s just playing more games at once. A friend and former customer explained his trend following method as working in much the same way. The more bets you place, the more likely you’ll hit a winning trend.

Kelly betting isn’t a perfect solution in all cases; fixed fraction betting has certain disadvantages when you can’t exactly characterize your edge, or the payout odds, or you have a limited number of bets before you have to cash in your chips. However, in the case of a machine to beat Roulette, it’s difficult to think of a better technique.

Of course, Kelly betting and things like it figure in other sorts of betting; people do use it in Markets where it is appropriate. Supposedly it was part of Axcom/Rentech’s early secret sauce, and certainly folks who have thought about trading need a bet sizing and risk management strategy that makes sense. Kelly is often a good place to start, depending on your situation. But that’s a topic for another blog post. One more coming on modern techniques to beat Roulette, including the one I came up with in 2010 (which, in case you were holding your breath, didn’t really work, which is why I have to work, and am willing to talk about such things in blogs).

Kelly criterion resources

Kelly’s original paper:

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6771227

Thorp’s explanation:

http://edwardothorp.com/sitebuildercontent/sitebuilderfiles/TheKellyMoneyManagementSystem.pdf

Thorp’s website:

http://edwardothorp.com/id10.html

## Bad models and the end of the world

Posted in econo-blasphemy, stats jackass of the month by Scott Locklin on March 23, 2014

I loathe journalism as a profession: a claque of careerist whores, half-educated back-slappers and propagandists for the oligarchical lizard people who are ruining civilization. I loathe “science journalism” particularly, as they’re generally talking about something I know about, and so their numerous impostures are more obvious.

Journalists: they’re mostly like this

Today’s exhibit, the “NASA study predicting the end of Western Civilization.” The actual study can be found in PDF format here. If you read the “journalism” about this in the guardian, cnet, or wherever else, it’s all about our impending doom. Not only do scientists tell us we are doomed, fookin’ NASA scientists tell us we are doomed.

The authors of the study are not NASA scientists. The NASA subcontractor  associated with this paper would like you to know this; probably because NASA was annoyed their name was associated with this paper. The only contribution NASA made was in partially supporting an institution which partially supported one of the three authors for one semester. The author in question,  Safa Motesharrei is a grad student in “public policy” and “mathematics” at U Maryland. The other two authors are also not NASA scientists. One is allegedly a professor of … political science in Minnesota -and more recently some cranky looking outfit called “Institute of Global Environment and Society.” The other one is a professor of the U Maryland department of Oceanic and Atmospheric sciences. Unless you consider the partial ramen noodle stipend one grad student received for one semester to be “funding,” or you consider NASA’s subcontractor to be liars, NASA did not fund or endorse this study in any meaningful way. Journalism 101, failed before even getting to the content of the article.

The three authors of this study

For what it is worth, had I published anything my sophomore year of grad school instead of trying to build a crazy vacuum chamber and catch a venereal disease, I’d have had some words in my paper thanking NASA for their support as well. This is despite the fact that most of my money came from the NSF and the University I was attending. I wasn’t in any way a NASA scientist. My institution wasn’t NASA affiliated. But we did get a NASA grant that paid for at least a month’s salary for me over the course of a year. When you get those grants, you say “thank you.”

Nafeez Ahmed, the imbecile at the Guardian who broke the story, continues to insist that NASA funded this study, despite the fact that they didn’t. I guess when someone Discovers you are a shoddy journalist, the accepted thing to do these days is doltishly double down on your error. Ahmed, of course, works for some preposterous save-the-world outfit, which apparently means he can pretend he is a journalist and doesn’t have to tell the truth about anything.

Journalistic failure is to be expected these days, and NASA scientists say stupid things all the goddamned time. Still, reading the paper itself was informative. Had anybody bothered to do so, the story would have been murdered in infancy. It’s one of the godawful silliest things I have ever read.

There is a fairly standard model from ecology called the “predator prey” model. Predator/prey models were  mostly developed to model exactly what it sounds like: things like wolf and moose populations in a National Park. The model makes assumptions (that predators are always hungry,  the prey will never die of old age, and  there are no other predators or prey available, for just a few examples of the limitations of the model), but if you set these equations up right, and the parameters and conditions are non-degenerate, it can model reality reasonably well. It’s really no good for predicting things, but it’s OK for modeling things and understanding how nature works.  The equations look like this, where $x(t)$ is the predator population, $y(t)$ is the prey population and $a$ is predator birth rate, $b$ is the predator death rate, $c$ is the prey’s birth rate, and $k$ is the predation rate; all rates are constant.

$\frac{dy}{dt} = ay(t)x(t) -bx(t)$

$\frac{dx}{dt} = cy(t) -kx(t)y(t)$

The predator/prey model is elegant, concise, and in some limited circumstances, occasionally maps onto reality. It is, of course, a model; there is no real reason to model things using this set of differential equations, and a lot of reasons not to. But sometimes it is useful. Like most good models, it is simple and doesn’t have too many parameters. Everything can be measured, and interesting dynamics result; dynamics that we can observe in nature.

The authors of this doom-mongering paper  have  transformed that relatively simple set of equations; a set of equations which, mind you, produces some fairly complicated nonlinear dynamics, into this rather un-handy mess, known as HANDY (for “Human And Nature DYnamics”):

$\frac{dx_c}{dt} = \beta_c x_c(t) - \alpha_c x_c(t)$

$\frac{dx_e}{dt} = \beta_e x_e(t) - \alpha_e x_e(t)$

$\frac{dy}{dt} = \gamma (\lambda -y(t)) y(t) - \delta x_c(t) y(t)$

$\frac{d \omega}{dt} = \delta y(t) x_c(t) - C_c(t) - C_e(t)$

In this set of equations, $x_c(t)$ is the productive peasant population, $x_e(t)$ are the population of parasitic elites, $y(t)$ is “natural resources” and $w(t)$ is “wealth.” $\lambda$ is a “saturation of regrowth of nature rate.” $\gamma$ is an “exponential growth of nature rate.” $\delta$ is a “depletion of nature” rate term. $C_c(t), C_e(t)$ are wealth consumption rates.

to make it even more complex: $\alpha_c(t), \alpha_e(t), C_c(t), C_e(t)$ are all functions of $\omega(t), x_c(t), x_e(t)$

$C_c(t) = min(1,\frac{\omega(t)}{poor(t)}) s x_c(t)$

$C_e(t) = min(1,\frac{\omega(t)}{poor(t)}) \kappa x_e(t)$

$poor(t) = \rho x_c(t) + \kappa \rho x_e(t)$

$poor(t)$ is some threshhold wealth function, below which you starve, and allegedly $\rho$ is supposed to be a minimum consumption per capita, but it really makes no sense based on the equations. $s$ is some kind of subsistence level of wealth and $\kappa$ is the multiple of subsistence that elites take.

Instead of contenting themselves with constant predation or death rates, this train-wreck insists on making them the following:

$\alpha_c(t) = \alpha_m + max(0,1-\frac{C_c(t)}{s x_c(t)}) (\alpha_M - \alpha_m)$

$\alpha_e(t) = \alpha_m + max(0,1-\frac{C_e(t)}{s x_e(t)}) (\alpha_M - \alpha_m)$

Where $\alpha_m, \alpha_M$ are constants for a normal death rate and a death rate where you have a high death rate, where, and I quote the paper directly: “when the accumulated wealth has been used up and the population starves.”

It’s worth a look at what they’re implicitly modeling here by adding all this obfuscatory complexity. All of the following assumptions are made by this model. Very few of them are true in reality. Most of these assumptions are designed to get the answer they did.

1. The natural resources of the earth is well modeled by the prey equation
2. The natural resources of the earth regenerate themselves via a logistic function
3. There are two classes of humans
4. There is a thing called “wealth” that is consumed by the two classes of humans at different rates
5. The elite class of humans preys on the peasants and produces nothing
6. The peasant class is all equally productive
7. Wealth comes from peasants exploiting nature
8. Elites all have $\kappa$ times a subsistence income, rather than a smooth distribution of incomes
9. Peasants all have $s$, a subsistence income, rather than a smooth distribution of incomes
10. An extra variable called “wealth” is needed to make sense of these dynamics, and this variable maps onto the thing known in common parlance as “wealth.”
11. The wealth factor could sustain a human society for centuries after ecological collapse (page 18)
12. Death rates increase as natural resources are consumed at a faster rate (everything about modern civilization indicates the exact opposite is true)
13. The peasants get nothing from the elites except population control
14. Technological change is irrelevant (yes, they argue this; page 7)
15. This ridiculous spaghetti of differential equations actually models something corresponding to Human Civilization

There are more assumptions than this, but you get the idea: this model is ridiculous, over parameterized, and designed to get the answers that they did. If you assume parasitic non-productive elites, you get the situation where social stratification can help “cause” collapse. Of course, if you assume parasitic non-productive elites, you’re assuming all kinds of ideological nonsense that doesn’t map well onto reality.

If you assume natural resources also act like prey, you can get situations where the natural resources collapse, then the society collapses. This is no big surprise, and you don’t need these obfuscatory complications to say this: it’s in the predator-prey equations already. Why didn’t they just model humanity and nature as simple “predator/prey” above? I am guessing, because nobody would buy it if you say things that simply, and it wouldn’t be an original paper. It also doesn’t allow them to pontificate on egalitarian societies.

As for the additional “wealth” factor these clowns use to distinguish themselves from an earlier bad model; as far as I can tell, the only purpose served by this degree of freedom is making it easier to mine way more natural resources than we actually need to support a population (something that wouldn’t happen in a standard predator-prey model). It also doesn’t make any sense, modeled in this way, unless you believe grain silos contain centuries worth of corn, or that people can eat skyscrapers. That’s how their wealth equations work; they actually assume you can eat wealth.

Dr. Nafeez Ahmed: Guardian columnist who broke this story

I actually feel a bit sorry for these guys, even though they are unashamed quacks. They didn’t ask to become this famous. Somehow the zeitgeist and some imbecile activist newspaper reporter decided to make them famous as people who are really bad at modeling anything. God help these people if they attempt to model something real, like chemical reaction dynamics, or, say, the earth’s atmosphere.

Returning to the mendacious loon, Ahmed, who brought this paper to world fame and attention. He asserts that the paper actually compares historical civilizations using this model. It does nothing of the sort. The paper mentions historical civilizations, but they don’t even make legalistic arguments that, say, the ancient Egyptians, whose civilization lasted for thousands of years, somehow follow these equations.  All they say is, ancient cultures were cyclical; they rise and fall; something everyone has known from the time of Heraclitus. Cyclical behavior does not imply this complex pastiche of differential equations; there are cyclical behaviors in nature which can’t be modeled by any differential equations. Finally, Ahmed asserts that the model predicts things. It doesn’t; nor does it claim to. It claims to model things. Modeling things and predicting things are very different.

The model itself was bad enough. What the activist-reporter said about it is inexcusable. The fact that everyone credulously picked up on this nonsense without questioning how Nafeez Ahmed made his living is even worse. Science by activist press release. Yeah, thanks a lot, “science journalists.” Nobody even noticed the clown who broke this story is a goddamned 911 truther.

A more reliable narrator than the Ahmed bozo who broke this story

I find all this intensely sad. I’m sad for the boobs who wasted their lives cranking out a model this useless. I’m sad for our civilization that it is possible to make a living publishing rubbish, and that talented people can’t make a living doing interesting and correct research which will benefit humanity. I’m also sad that journalists aren’t fired over their credulity regarding this fraud. I’m sad that ideological hogwash is published in all the papers as some kind of scientific truth, while nobody notices simple things, like the fact that the world fisheries are presently undergoing collapse, or the fact that there are no more rhinos because Chinese people haven’t discovered viagra yet.

I’m also sad that people are so obsessed with the end of the world. Maybe some day we’ll experience some kind of ecological apocalypse, or the imbeciles in the White House will nuke the slightly less stupid cavemen in the Kremlin. Chances are pretty good though, that before these things happen, we will all be dead. Wiser men than me have pointed out that anxiety about the end of the world is a sort of transference for anxiety about their own impending demise. As Spengler put it, “perhaps it is not the end of the world, but just the end of you.”