Locklin on science

“AI” and the human informational centipede

Posted in fraud, stats jackass of the month by Scott Locklin on September 2, 2017

Useful journalism about technology is virtually nonexistent in the present day. It is a fact little commented on, but easily understood. In some not too distant past, there were actually competent science and technology journalists who were paid to be good at their jobs. There are still science and technology journalists, but for the most part, there are no competent ones actually investigating things. The wretches we have now mostly assist with press releases. Everyone capable of doing such work well is either too busy, too well paid doing something else, or too cowardly to speak up and notice the emperor has no clothes.

Consider: there are now 5 PR people for every reporter in America.  Reporters are an endangered species. Even the most ethical and well intentioned PR people are supposed to put the happy face on the soap powder, but when they don’t understand a technology, outright deception is inevitable. Modern “reporters” mostly regurgitate what the PR person tells them without any quality control.

The lack of useful reporting is a difficulty presently confronting Western Civilization as a whole; the examples are obvious and not worth enumerating. Competent full time reporters who are capable of actually debunking fraudulent tech PR bullshit and a mandate to do so: I estimate that there are approximately zero of these existing in these United States at the moment.

What happens when marketing people at a company talk to some engineers? Even the most honest marketing people hear what they want to hear, and try to spin it in the best possible way to win the PR war, and make their execs happy.  Execs read the “news” which is basically marketing releases from their competitors. They think this is actual information, rather than someone else’s press release.  Hell, I’ve even seen executives ask engineers for capabilities they heard about from reading their own marketing press releases, and being confused as to why these capabilities were actually science fiction. So, when your read some cool article in tech crunch on the latest woo, you aren’t actually reading anything real or accurate. You’re reading the result of a human informational centipede where a CEO orders a marketing guy to publish bullshit which is then consumed by decision makers who pay for investments in technology which doesn’t do what they think it does.

Machine learning and its relatives are the statistics of the future: the way we learn about the way the world works. Of course, machines aren’t actually “learning” anything. They’re just doing statistics. Very beautiful, complex, and sometimes mysterious statistics, but it’s still statistics. Nobody really knows how people learn things and infer new things from abstract or practical knowledge. When someone starts talking about “AI,” based on some machine learning technique, the Berzerker rage comes upon me. There is no such thing as “AI” as a science or a technology. Anyone who uses that phrase is a dreamer, a liar or a fool.

You can tell when a nebulous buzzword like “AI” has reached peak “human information centipede;” when oligarchs start being afraid of it. You have the famous example of Bill Joy being deathly afraid of “nanotech,” a previously hyped “technology” which persists in not existing in the corporeal world. Charlatan thinktanks like the “center for responsible nanotechnology” popped up to relieve oligarchs of their easy money, and these responsible nanotech assclowns went on to … post nifty articles on things that don’t exist.

These days, we have Elon Musk petrified that a near relative of logistic regression is going to achieve sentience and render him unable to enjoy the usufructs of his toils. Charlatan “thinktanks” dedicated to “friendly AI” (and Harry Potter slashfic) have sprung up. Goofball non-profits designed to make “AI” more “safe” by making it available as open source (think about that for a minute) actually exist. Funded, of course, by the paranoid oligarchs who would be better off reading a book, adjusting their exercise program or having their doctor adjust their meds.

Chemists used nanotech hype to drum up funding for research they were interested in. I don’t know of anything useful or interesting which came out of it, but in our declining civilization, I have no real problem with chemists using such swindles to improve their funding. Since there are few to no actual “AI” researchers existing in the world, I suppose the “OpenAI” institute will use their ill gotten gainz to fund machine learning researchers of some kind; maybe even something potentially useful. But, like the chemists, they’re just using it to fund things which are presently popular. How did the popular things get popular? The human information centipede, which is now touting deep reinforcement networks as the latest hotness.

My copy of Sutton and Barto was published in 1998. It’s a tremendous and interesting bunch of techniques, and the TD-gammon solution to Backgammon is a beautiful result for the ages. It is also nothing like “artificial intelligence.” No reinforcement learning gizmo is going to achieve sentience any more than an Unscented Kalman filter is going to achieve sentience. Neural approaches to reinforcement learning are among the least interesting applications of RL, mostly because it’s been done for so long. Why not use RL on other kinds of models? Example, this guy used Nash Equilibrium equations to build a pokerbot using RL. There are also interesting problems where RL with neural nets could be used successfully, and where an open source version would be valuable: natural language, anomaly detection. RL frameworks would also help matters. There are numerous other online approaches which are not reinforcement learning, but potentially even more interesting. No, no, we need to use RL to teach a neural net to play freaking vidya games and call it “AI.” I vaguely recall in the 1980s, when you needed to put a quarter into a machine to play vidya on an 8-bit CPU, the machines had pretty good “AI” which was able to eventually beat even the best players. Great work guys. You’ve worked really hard to do something which was doable in the 1980s.

“The bot learned the game from scratch by self-play, and does not use imitation learning or tree search. This is a step towards building AI systems which accomplish well-defined goals in messy, complicated situations involving real humans.”

No, you’ve basically just reproduced TD-gammon on a stupid video game.  “AI systems which accomplish well-defined goals in messy … situations” need to have human-like judgment and use experience from unrelated tasks to do well at new tasks. This thing does nothing of the sort.  This is a pedestrian exercise in what reinforcement learning is designed to do. The fact that it comes with accompanying marketing video (one which probably cost as much as a half year grad student salary, where it would have been better spent) ought to indicate what manner of “achievement” this is.

Unironic use of the word “AI” is a sure tell of dopey credulity, but the stupid is everywhere, unchecked and rampaging like the ending of Tetsuo the Iron Man.

Imagine someone from smurftown took a data set relating spurious correlations in the periodic table of the elements to stock prices, ran k-means on it, and declared himself a hedge fund manager for beating the S&P by 10%. Would you be impressed? Would you you tout this in a public place? Well, somebody did, and it is the thing which finally caused me to chimp out. This is classic Price of Butter in Bangladesh stupid data mining tricks. Actually, price of butter in Bangladesh makes considerably more sense than this. At least butter prices are meaningful, unlike spurious periodic element correlations to stock returns.

This is so transparently absurd, I had thought it was a clever troll. So I looked around the rest of the website, and found a heart felt declaration that VC investments are not bets. Because VCs really caaaare, man. As if high rollers at the horse races never took an interest in the digestion of their favorite horses and superfluous flesh on their jockeys. Russians know what the phrase “VC” means (туалет). I suppose with this piece of information it still could be a clever Onionesque parody, but I have it on two degrees of Erdős and Kevin Bacon that the author of this piece is a real Venture Capitalist, and he’s not kidding. More recently how “Superintelligent AI will kick ass” and “please buy my stacked LSTMs because I said AI.” Further scrolling on the website reveals one of the organizers of OpenAI is also involved. So, I assume we’re supposed to take it seriously. I don’t; this website is unadulterated bullshit.

Gartner: they’re pretty good at spotting things which are +10 years away (aka probably never happen)

A winter is coming; another AI winter. Mostly because sharpers, incompetents and frauds are touting things which are not even vaguely true. This is tragic, as there has been some progress in machine learning and potentially lucrative and innovative companies based on it will never happen. As in the first AI winter, it’s because research is being driven by marketing departments and irresponsible people.

But hey, I’m just some bozo writing in his underpants, don’t listen to me, listen to some experts:

http://thinkingmachines.mit.edu/blog/unreasonable-reputation-neural-networks

https://medium.com/project-juno/how-to-avoid-another-ai-winter-d0915f1e4798#.uwo31nggc

https://www.researchgate.net/publication/3454567_Avoiding_Another_AI_Winter

Congress is presently in hearings on “AI”. It’s worth remembering congress had hearings on “nanotech” in 2006.

http://www.nanotechproject.org/news/archive/congressional_hearing_on_nanotechnology/

“By 2014, it is estimated that there could be $2.6 trillion worth of products in the global marketplace which have incorporated nanotechnology. There is significant concern in industry, however, that the projected economic growth of nanotechnology could be undermined by either real environmental and safety risks of nanotechnology or the public’s perception that such risks exist.” Edit Add (Sept 10, 2017) (Taken from Mark Ames): Advertisements My favorite photo of this wacky election Posted in stats jackass of the month, Uncategorized by Scott Locklin on November 9, 2016 This dope got lucky in 2012, essentially using “take the mean” and was hailed as a prophet. He was wrong about virtually everything, and if someone were to make a table of his predictions over time and calculate Brier scores, I’m pretty sure he’ll get a higher score than Magic-8 ball (Brier scores, lower is better). Prediction is difficult, as the sage said, especially regarding the future. Claiming you can do prediction when you can’t is irresponsible and can actually be dangerous. While he richly deserves to find his proper station in life as an opinionated taxi driver, this clown is unfortunately likely to be with us for years to come, bringing shame on the profession of quantitative analysis of data. We’ll be watching, Nate. Michael Lewis: shilling for the buyside Posted in finance journalism, microstructure by Scott Locklin on April 4, 2014 Journalism, in the ideal world, is supposed to inform the citizenry of facts important to their well being. Modern journalism seems to involve issuing press releases from the oligarchical reptiles who are destroying Western Civilization. Maybe I am a naive fool, and it was always thus. Either way, Michael Lewis’s latest book lends credence to the view that he is a very modern journalist. lookin a bit scaly, bub Lewis’s book purports to be about high frequency trading. He manages to write several hundred pages of gobbledeygook without actually speaking to a High Frequency Trader (unless you count his incongruous encounter with poor Sergey Aleynikov ). The story Lewis actually tells is one of incompetent sell side traders who started an exchange which serves the interests of wealthy buy siders and shady brokers. Brad Katsuyama is the hero of the book. Lewis’s recent books use the dreary trope: the band of clever and plucky outsider misfits who take on the establishment. Katsuyama’s misfittery is he’s an Asian who is good at sports, bad at math and computers; and even though he worked for a Wall Street bank, he went to a crappy Canadian school instead of Yale-vard. Among his misfit sidekicks are a potato-wog who is good at network ops, but who could never get a break on the street (I can relate). Also, a fat grouch from Brooklyn, a computer genius, a puzzle wizard and a few other guys who fade into the woodwork. They worked for RBC: a Canook bank which is supposedly the least Wall Streety place on the Street. The plucky outsiders in this story are not portrayed in a particularly flattering way. In fact, they come off as dimwitted incompetents. Katsuyama was an old school block shopping sell side trader. If you remember my previous pieces on HFT nay sayers: Joe Saluzzi was also a sell side block shopper. Old fashioned sell side guys have obsolete jobs. Their jobs are to find liquidity for “buy side” customers buying into or liquidating a large position. Katsuyama’s anger at the idea that “the market is rigged” seems the simple rage of a man who has been assigned a task he is not qualified for. There are tales of he and his team wasting hundreds of thousands in RBC money executing bad trades to see what happens. They seemed shocked, shocked, that the market would move away from their ham-fisted dumpings of huge blocks of shares to someone else’s routing system. Lewis keeps going on about how “nobody understood” any of this back in 2009, except for his plucky outsider heroes. If “nobody” understood it, how was I was able to write about it on my blog in 2009? Over 100,000 people read my various blogs on HFT that year. If you were not among the elite group of more than 100,000 insiders who read blogs, any punter could have purchased the Larry Harris book “Trading and Exchanges” available on Amazon.com for$71.58 + tax. This is how I originally clued myself in (thanks FDAX-H). Larry’s book was published in 2002.  In early 2010 Barry Johnson published the book, “Algorithmic Trading and DMA” which explains the profession dedicated to getting a good fill on the modern electronic trading landscape. So, in 2010, there was not only a  job description, “algorithmic trader,” for getting a good buy-side fill, there was also a “how to” book on the subject.  Such people perform the function that used to be done by sell side people like Katsuyama and Joe Saluzzi. Lewis repeatedly states that this was a mysterious topic and nobody was talking. Actually, it is an extremely well understood topic;  library shelves groan with volumes dedicated to the subject.

No books were really needed; history and experience should suffice. Back in the days of pit traders, if you threw a huge order at the pit, you might get a fill on a couple of round lots. The rest of the pit is going to change their prices, because they figure anyone swinging 10,000 or 100,000 share orders around must be informed traders. If they’re informed traders, they need to pay for their immediacy. Informed traders may be criminal insider-trader creeps,  they may be people with really good trading strategies; it doesn’t matter -they’re informed somehow: they know stuff. If the market maker doesn’t adjust their prices in front of an informed trader, the market maker will go bankrupt. That’s market economics 101. As I previously described it in 2009 in the Three Stooges of the High Frequency Apocalypse;

What happens when you buy something? …  If you want it for cheap, you sit around and look at different markets (ebay, amazon, craigslist) until someone displays a price you find acceptable. If you want that “something” right now, you drive to a store and buy it. You’ll almost certainly pay a little more at the store, because they need to make enough money to pay employees to prevent barbarians from stealing everything, and to keep the lights on and other such things for your convenience. You can also generally return what you bought to the store much easier than to ebay or amazon. You’re paying for the immediacy (buy it now!) and liquidity (buy as many as you want!) provided by the store. This is a service which costs money.

Immediacy costs money. Markets have always moved prices away from large orders. Market participants  have always been able to cancel or move a limit order. That’s one of the features of the limit order. If  Katsuyama didn’t understand these simple facts, he had no business collecting a $2 million a year paycheck shopping blocks for his customers, because he didn’t understand the basics of his profession. It’s possible that Lewis simply misunderstood something Katsuyama explained to him. It’s also possible that Katsuyama is a shark who told Lewis a lot of bullshit to get good press for IEX. This leaves only two possibilities: either Lewis is a credulous idiot who is not competent as a journalist, or Katsuyama is an idiot who was not competent as a trader. Take your pick. They made their money trading flow as well Where it gets interesting is where Lewis claims bigshot buysider crybabies like Loeb and Einhorn never heard of any of this. They made it sound as if, back in the day when Loeb and Einhorn were paying 1/8 of a dollar spreads to knuckle-dragging pit orcs, no rock-ribbed he-man trader with 10lbs of undigested beef in his lower intestine would would dare move his price away from where Loeb and Einhorn wanted it. Why, moving the price away from a big order: that’s un-American! So … these “plucky underdogs” helped Katsuyama form a new stock exchange, IEX. They claim that no sort of nefarious activity is possible on IEX, because, well, “trust us!” Liquidnet’s average cross is 45,000 shares; over 100 times the vaunted liquidity figures provided by IEX. If I traded stocks, why should I trust IEX over Liquidnet? Because Michael Lewis says they’re honest guys? If I believe the tales of Michael Lewis, the founders of IEX are a collection of “traders” who do not know how to trade, and the market itself is owned by … buy side traders. He seems to give IEX sloppy wet kisses for honesty, yet sees nothing wrong with the fact that they’re owned by a bunch of buy side guys. They’re also owned by some unknown buy side guys, which does not inspire confidence. Buy side guys, if they’re good at their jobs are informed traders. Nobody wants to trade against informed traders. Everyone wants to trade against noise traders. IEX has simple order types; limit, midpoint, fill or kill and market: I approve of this. On the other hand: “IEX follows a price-priority model first, then by displayed order second. Then comes broker priority, which means a broker will always trade with itself first, which Katsuyama described as “free internalization.” He explained that brokers do not pay IEX to trade should an order be matched against another order from that same broker. This, he added, offers brokers incentive to trade in IEX.” Hey now, wait a minute. Internalization and broker priority is pretty much the same thing as dark crossing, which Lewis was trying to tell us was bad. Now it’s supposed to be OK when Goldman does it? Later, Lewis actually quotes Katsuyama saying there were only a few brokers acting in their customer’s interests: “Ten,” Katsuyama said. (IEX had dealings with 94.) The 10 included RBC, Bernstein and a bunch of even smaller outfits that seemed to be acting in the best interests of their investors. “Three are meaningful,” he added: Morgan Stanley, J. P. Morgan and Goldman Sachs. I think this is the crux of this story: according to Michael Lewis and Katsuyama, we’re supposed to trust people like Einhorn who have been convicted of insider trading, people who are suspected of insider trading (buy side is by definition rife with this; particularly firms that do merger arb and special events), J.P. Morgan, Goldman and Morgan Stanley: we’re supposed to trust these guys more than we’re supposed to trust a bunch of tiny little market making firms who had been inconveniencing them by taking away some of their flow. Lewis tries to make this seem like a battle between the underdog “good guys” and the evil establishment. To believe this, you’d have to believe that Goldman Sachs and people like Einhorn are underdogs, rather than the actual establishment. To believe this, you’d have to believe the tiny industry of HFT traders actually rules the world and buys off congressmen and the SEC more than … J.P. Morgan and Goldman. To give you a sense of scale: the largest HFT firm I know of, KCG, has operating cash flows of$140 million a year and a  modest market cap of $1.4 billion (betcha didn’t know it was a publicly traded company: Lewis certainly doesn’t mention it). JPM has operating cash flows of$100 billion a year, almost a trillion on the balance sheets, and a quarter trillion or so in market cap. David Einhorn is personally worth $1.25 billion dollars. KCG’s entire market cap is only slightly more than that, and it employs 1200 people. Yet, somehow the HFT firms are the evil establishment, and JPM and Einhorn are … the plucky underdogs standing up for truth, justice and market makers not changing their quotes when some reptilian oligarch dumps 200,000 shares of YoyoDyne on the market. Yeah, I might believe that. I might believe that if I were a dribbling retard. Put down Lewis’s book; read one by Bernays Doing a bit of investigation into who owns IEX: we have the$13.2 billion  activist shareholder fund Pershing Square, owned by Bill Ackman, another “underdog” worth $1.2 billion. We have the$6.7 billion Senator Investment Group. Scoggin Capital is only worth $1.8 billion; they do distressed debt and mergers, and have managed to only have one down year in 25. Another investor is venture capitalist Jim Clark, net worth$1.4 billion. He is particularly noteworthy as being a pal of Michael Lewis, and almost certainly the guy who made the introductions to the “flash boys” at IEX. Brandes Investment Partners is an old $29 billion AUM politically influential money management firm doing value investments, and is run by another billionaire. Third point, a hedge fund with$15 billion, also working in special situations aka “distressed debt and mergers,” run by  Danny Loeb (who also miraculously has only one down year). Another investor in IEX is a little place called  Capital Group Companies, one of the biggest buy side investors in the world, with \$1.15 trillion AUM. Capital Group has been more or less scientifically proven to be one of the most powerful and influential corporations in the world.

You get the idea: IEX is not owned by plucky underdogs. It is owned by very rich and powerful “buy side” people. People who find the present system of liquidity provision inconvenient.  Buy side has always found liquidity providers inconvenient; they had to pay old school “sell side” traders like Katusyama to work the trades for them at the very least. There wasn’t much they could do about it until now. Now that they own  almost everything, they can open their own damn stock exchange and buy some cheap brokerage flow. That and unleash Michael Lewis, the FBI and New York Attourney General on the peasants who make them pay for liquidity.

IEX … little investor… blah blah blah

I  don’t think IEX and their investors represent the interests of “the little guy” at all. The actual little guy (aka people like me) does pretty well making small orders with the present system. If you  believe Lewis’s book, the thing we’re supposed to be worried about is telegraphing a big buy or sell by routing  your order to several different exchanges. The thing is, “the little guy” doesn’t make large buy or sell orders, and unless he does, what Lewis describes is impossible. The people IEX benefits are exclusively preposterously wealthy buy side people. That and the brokerages who get to trade against the pieces of their flow that they want. Pardon me if I notice that such people aren’t exactly tribunes of the people. What’s actually going on here is the brokers are, as usual, taking the flow. They’re giving up some of the leftovers to the buy side guys, who also pocket the exchange fees. If you’re worried about flow or think the present system of liquidity provision is somehow predatory: this is a buzzard and a hyena sharing a carcass.

I know a few HFT type people. One of ’em might be even be as rich as Michael Lewis.  So far, all the ones I have met are clever and decent people, and I figure whatever they’ve managed to earn by the sweat of their brows, they deserve it. I’m not real pleased with the idea of a small group of decently paid, politically helpless nerds being the fall guys for a bunch of crooked oligarchs who don’t want to pay for their liquidity.

Speaking of which: FREE SERGEY

despite the awesomeness of his pantaloons, this man’s legal problems are a bad sign for America

This review by a trader lists 15 more technical inaccuracies in the book. He also noticed that broker priority is shady business if we’re talking about helping “the little guy” here.

This trader gives a really great review.

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.”