Ludic Fallacy

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

by rfreytag • 6 years ago

119 71 6 years ago

en.wikipedia.org

ak39• 6 years ago

Interesting. I see the examples don’t cite “technical analysis” of price action of stocks. Is that also an example of Ludic fallacy?

gcc_programmer• 6 years ago

If the person went bust, it is. If he didn't, it's not.

cjfd• 6 years ago

The ludic fallacy could apply here as well. If you calculate that on average you will make a profit but in actuality this profit fluctuates so wildly that you will almost certainly go bankrupt in the process the ludic fallacy could apply.

Another criticism by Nassim Taleb to this field is the use of the normal distribution to distributions that are not normal at all. This could lead to the problem that I described in the previous paragraph.

Ambol3• 6 years ago

Also the fact that many market players got bailed out by governments when things went south. They may have been aware that this would happen all along, which would mean the explicit market game and the real market game are 2 very different things with very different rules.

sgt101• 6 years ago

Yes and no - mostly the market is a game, like foxes and rabbits where the "rabbits" are forced into behaviours that the foxes can exploit. The dominant strategy for the rabbits is created by policy and regulation and also business success - all that money has to go somewhere. The foxes know that Mr. Rabbit will come back from the veg garden at 6pm and so wait at the hole. All is well as the rabbits grow in number, fatten and prosper, and so do the foxes. So in this situation its all games and you can get rich if you play well.

Good examples are carry trades and insurance market punts - people know that the central bank of Japan has to do X, they know that people are getting old in the developed world... betting on this happening is mostly a clever thing to do.

Every so often at random along comes an event that throws all this into the air - this might be something massive or something small but when it happens people go bust. For example, well look around.

There is a lot of talk that "oh we will know when we are in trouble and we will just change strategy" but sometimes that just proves not to be so. The point is that getting to play the game well for long enough to prosper is just luck, getting out at the right time is just luck. You can be stupid and get taken to the cleaners at any time, and you can play well and just be "the fat rabbit" at any time as well. So, be lucky and play well.

sudhirj• 6 years ago

The nicest example of this I've seen is that Tim Ferris won a kickboxing championship without being a kickboxer, https://www.martialdevelopment.com/how-to-win-kickboxing-wro...

The fallacy is that winning a world championship at kickboxing must mean that you're an excellent kickboxer, but nope.

FeepingCreature5• 6 years ago

Istm he was an excellent kickboxer to exactly the extent the world championship was one of kickboxing.

pmoriarty• 6 years ago

This reminds me of Derren Brown (a magician) winning simultaneous chess games against grandmasters...

https://www.youtube.com/watch?v=rIAXIubSTkc

thom2• 6 years ago

As in, he got another kickboxer to pretend to be him and fight in his place?

buran774• 6 years ago

I'm not sure what kind of championship that was but for an experienced fighter having a 30 pound "handicap" versus an inexperienced one should amount to no real life disadvantage. Don't underestimate what a 165 lbs person's tibia can do to a 195 lbs person's head on even thigh. There's no "hack" to not getting your lights knocked out with one punch/kick from a good fighter 30 lbs lighter than you. And tricking the weigh in is something that has been done since the second ever weigh-in.

The fact that he was able to hold off experienced fighters, even if they were below his weight class, means he was plenty qualified to be there despite his very modest self assessment.

[Edited from here] He seems to be an actual fighter under Dave Camarillo but the framing of this story, that he's just an average "stuff my face with peanut butter sandwiches, tricked the weigh-in" kind of guy, is just in order to sell his "life hacks" books.

All I can find is that 1999 was the second year for the championship which could mean not very strong competition. But there's no mention of him in any Wushu/Sanda/Sanshou championship. He also used to claim that he is a "Cage fighter in Japan, vanquisher of four world champions (MMA)" (since removed from his page). Being a 4 time world champion would have contradicted his "just a regular guy using life hacks" premise. Without an actual record of him winning that "Chinese Kickboxing National Championships 1999" I guess he's just peddling the same "tricks" from his book. One of them might be "just say you did it".

aspenmayer2• 6 years ago

Thai kickboxing and BJJ isn’t a joke. Neither is physics and bone density increases through training, same with muscle fiber density and reaction time. I can go on. Training matters.

yesenadam2• 6 years ago

an actual record of him winning that "Chinese Kickboxing National Championships 1999"

There appears to be some footage of it in this video.

https://www.youtube.com/watch?v=ODoVqXgblyw

louwrentius• 6 years ago

Tim Ferris really became rich and famous by peddling bullshit pills (I call it fraudulent) and then writing an 'empty' book about it.

SuoDuanDao• 6 years ago

According to him, he didn't just kickbox with a 30 pound weight advantage, he also won entirely by forcing ring-outs. He essentially treated the competitions like a sumo match, something other competitors didn't typically try for or practice defending against all that much.

amelius• 6 years ago

I think this is an example of a "N=1 fallacy".

thih92• 6 years ago

Is this verifiable? I saw a comment on that page saying:

I’m not saying you couldn’t win a kickboxing tournament like that. I just think it’d be nice if he at least gave the year and location of the tournament so interested parties could look into it.

FeepingCreature5• 6 years ago

Isn't the first example extremely bullshit?

A third party asks them to "assume that a coin is fair, i.e., has an equal probability of coming up heads or tails when flipped. I flip it ninety-nine times and get heads each time. What are the odds of my getting tails on my next throw?"

Istm that Fat Tony here gets the right answer to the wrong question. Whether we should assume this is not part of the question. That this is a useful thing to ask IRL doesn't change the fact that if you posed this to me IRL and smugly quoted the ludic fallacy at me for correctly answering your question I'd be strongly tempted to deck you.

https://xkcd.com/169/ comes to mind.

baxtr• 6 years ago

That’s actually exactly what I was going to say. Of course you should update your priors continuously and thus evolve your model. A model is never perfect but it’s the best approximation to reality we have. In the end, Fat Tony has a model in his head, too.

FeepingCreature5• 6 years ago

Right - "assume at the start that the coin is fair - you are free to update the assumption as you go" is a different thing than they said. Usually "assume that" assumptions are meant to hold throughout the question.

As Randall says, "communicating badly and then acting smug when you're misunderstood is not cleverness."

gwd• 6 years ago

I think the Ludic Fallacy would be better described as, "A tendency to be overconfident that you know what the game is." If you read the Black Swan, what Taleb is mainly railing against are people who are completely confident that because they have a model, that it must therefore be correct, and refuse to remember all the caveats, and what could happen if their model is wrong.

l0b0• 6 years ago

Yeah, the only thing it proves is that when a scientist says "assume X" to another scientist the common understanding is that it means "in a situation where it is given that X is true, no matter how ridiculous that might be in real life."

As for more reasons why this is bullshit, see the gambler's fallacy and the Monty Hall problem – intuition is often terrible at arriving at the right prediction.

TheOtherHobbes• 6 years ago

But the assumption is the point. When you have enough data to suggest your model is wrong, you should throw away the model and the assumptions it's based on, not the data.

The fact that your model can be justified as technically correct is irrelevant. When the data doesn't fit the model any more, the supposed absolute correctness of the textbook model blocks your ability to understand what's happening.

This isn't even about games, but about whether it's possible to be open-minded enough to consider that simple textbook "solutions" are not guaranteed to be a good fit for real problems - especially if you don't understand their limitations or the assumptions they're based on.

And it doesn't just apply to statistics.

Hitton• 6 years ago

I remember reading some kind of fantasy anthology of Sherlock Holmes pastiches. In one story there was interesting twist on the famous quote "Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.". It was changed to the effect that "once whatever remains is ridiculously improbable, you should probably reconsider what is actually impossible".

leereeves• 6 years ago

But the example is poorly communicated. It's not clear whether the entire quoted portion is:

A) a hypothetical introduced by the idiom "Assume that..." (which introduces a statement of fact in the hypothetical situation), and we are discussing a scenario in which the coin is in fact fair, in which case Dr. John is correct and Fat Tony is committing the gambler's fallacy, or

B) a scenario in which a third-party tells someone that the coin is fair, but that is simply an assumption that should be updated by new evidence, in which case Dr. John would be committing the ludic fallacy.

The example isn't instructive because anyone reading this and thinking of scenario A isn't disputing the idea that, if this happened in reality, you should throw away the model. They're just interpreting the phrase "assume that" differently.

moring• 6 years ago

When you have enough data to suggest your model is wrong, you should throw away the model and the assumptions it's based on, not the data.

In the example, you agreed to assume the coin is fair. That is, you agreed to stick to the model even if it turns out to be wrong. Throwing the model away, however suggested by the evidence, is just violating the rules you agreed to.

aaron695• 6 years ago

I think The Emperor Wears No Clothes.

This has no meaning.

But it's vague and meaningless enough you can pull it out when you want to prove something involving statistics or models not working, which they mostly don't.

raxxorrax• 6 years ago

A case against hubris but also the next step to declare every written word as fallacious.

quickthrower26• 6 years ago

And yet companies make a fortune betting on markets or sports using those exact "Ludic Fallacy" models - like linear regressions, probability etc. They know it's real life, and many someone else is fixing the coin toss, but they can still get an advantage. In any real casino, 99 blacks in a row and they'd shut down the table.

Reimersholme2• 6 years ago

...and then a financial crisis hits and suddenly they expect the government to bail them out because they didn't account for that risk in their models.

Ambol3• 6 years ago

Or they knew all along that the government would bail them out, so they were playing a very different game than everybody else.

quickthrower26• 6 years ago

Ha ha well that’s a different story more to do with bonus culture. An example of where the street smarts might come into play in modelling the modellers and predicting 2008

PhantomGremlin• 6 years ago

And yet companies make a fortune betting on markets

Until they don't.

This happened in March, and I just love the Reddit headline:

   Someone yolo’d a pension fund

The trade was easy money until fat tails caught up with it. I think Matt Levine also discussed this, as did HN.

https://old.reddit.com/r/wallstreetbets/comments/g5r5n6/some...

everybodyknows• 6 years ago

Ah ha! Thank you so much -- been wondering for months who might have been on the other side of this trade:

https://www.forbes.com/sites/antoinegara/2020/03/25/billiona...

The tragedy of it of course is that the incompetent pension managers will keep their last ten years of performance bonuses, and the citizens of Alberta will get ... tax increases.

stared• 6 years ago

One core example of modeling something as a game is dating (as in "The Game" by Neil Strauss).

Two literal takes on that are:

- "Super Seducer: How to Talk to Grils" a (somewhat controversial) game on Steam by Richard La Ruina, a Pick-Up Artist - https://store.steampowered.com/app/695920/Super_Seducer__How...

- "If Dating was like Who Wants to be a Millionaire" - https://www.youtube.com/watch?v=7E33j3gQg98

While some analogies of a game are in place (depending on someone's action, it's "fail" or "progress"), I think that the worst fallacy is that one always can, and should, "win". Depending on the attitude, it is anything from frustrating (obsessing why one has failed despite the effort, or ending in a relationship with a wrong person) to outright dangerous.

sradman• 6 years ago

All models are simplifications of real-world phenomena, the question is how useful they are. Taleb’s Ludic Fallacy is a useful prod to remind us to consider our core assumptions.

throwaway2245• 6 years ago

I haven't understood this as a fallacy.

In the "suspicious coin" example, there is an opening assumption that the coin is fair, but it transpires clear evidence to the contrary.

It isn't a fallacy to continue to treat this as a game: it has just become sensible to drop the assumption and treat it as a game where you are unsure about whether the coin is fair (as the second player in the example, in fact, does).

thih92• 6 years ago

In the "suspicious coin" example, there is an opening assumption

I understood it differently: there are no assumptions per se, just a request to make an assumption. The request is made by a third party and all this is part of the thought experiment.

It isn't a fallacy to continue to treat this as a game

True. The article states that “The ludic fallacy here is to assume that in real life the rules from the purely hypothetical model (where Dr. John is correct) apply.”.

treat it as a game where you are unsure about whether the coin is fair

This significantly modifies the scope of the original game.

I understood this as an example of how simplified models might easily stop being useful because of real life conditions.

gmuslera2• 6 years ago

That is the difference between a model and the reality. It "should" be fair, but in reality (with all the factors you see, and maybe several others that you don't) it seem to not be working that way.

dtjohnnyb• 6 years ago

The book Range talks about a similar idea, the idea of "kind" and "wicked" learning environments.

In kind environments (most games) "patterns recur, situations are constrained, and importantly, every time you do something you get feedback that is totally obvious, all the information is available, the feedback is quick, and it is 100% accurate"

In contrast, wicked environments (most of the rest of life!!!) none of the properties of kind environments hold, and in some extreme cases the feedback teaches you the exact wrong lesson.

In the book, he similarly warns against taking the lessons from successful people in chess or golf and applying them to our own wicked lives.

misiti3780• 6 years ago

What did people think about that book ?

I enjoyed it but felt like it was a bunch of other peoples ideas (Taleb, Kahneman, Levitin, etc) strung together.

rogerclark• 6 years ago

that's every book

Emphere• 6 years ago

Can't help but feel that people here are missing the point and perhaps too hung up on the specific example in the wikipedia article. The broader point is about the misuse and misapplication of technical/"rational" methods in real life i.e. not thinking about whether the model can actually be usefully applied in a certain real world situation. For example, blindly following rote statistical methods/not understanding their assumptions is what got us into the whole psychology replication crisis mess.

Reimersholme2• 6 years ago

Yes. One of the key points Taleb likes to make is that many real life situations are fat tailed, i.e. extreme events are much more likely than what someone assuming a normal distribution would account for, which might help explain why the financial system turns out to be so extremely fragile over and over again every time a major event/crisis occurs.

bezmenov• 6 years ago

Yes, it’s just a variation of don’t confuse the map for the territory, or the more general, don’t confuse the model for reality.

xondono• 6 years ago

I get the idea (although I’m not sure I’d call it a ‘fallacy’), but the examples are horrible.

kwhitefoot• 6 years ago

Seems like a long winded and sanctimonious way of saying that models are simpler than the reality that they mimic.

Bears in woods and catholic popes come to mind.

karmakaze• 6 years ago

or spherical cows.

briankelly• 6 years ago

"Map is not the territory." Straightforward, succinct, and no need to use latin or invoke Plato.

ajross• 6 years ago

It sounds obvious, but in practice it's not. It's an election year, so take polling as a great example:

Every poll of a race comes with two numbers, one a fraction of support for whatever issue or candidate is being measured, and the other a "margin of error" (which in the industry is a 95% confidence interval, I believe). This is just a statistical measure based on sample size. It's backed by two centuries of math and no one interestingly disputes the way the number is calculated or whate it means.

And there are a LOT of these polls taken. So take all those polls, check their variance, and you'll find that it's much higher than the value you'd expect given the margins of error they reported. This is a routine effect. So square that: why are the MoE numbers "wrong", given that multiple measurements of the same number are giving values with more noise than expected?

The answer is exactly this paradox. The model, that all these polls are measuring the same thing, is wrong. They aren't measuring the same thing. The different polls use different sampling methods, they weight their data using different algorithms, with opinion polls they phrase the questions slightly differently (or just ask the same questions in a different order), all of which affect the results.

And this happens everywhere in science. It's a frightenly easy mistake to make, especially as data sets get large.

jayd16• 6 years ago

Hmm this is a surely a common mistake to make but what does it have to do with games? If you sampled poker plays with similar differences you'd get similar errors.

gmuslera2• 6 years ago

"different", but not in decimal points. Sometimes what you interpret as noise could give you vastly different results. And it can be bigger than just positive feedback loops.

Animats• 6 years ago

That's Taleb. Taleb ran a fund that bought options way out of the money. This loses money every year, unless there's a big crash. His fund happened to be active in 2008, and made a ton of money that year. He doesn't release the numbers for other years. Not clear if this is a net win over a full business cycle.

Taleb is sort of a counter to Black-Sholes option pricing. Black-Sholes assumes a Gaussian distribution. Given that assumption, a few numbers let you quantify risk. That's convenient, but somewhat unrealistic, and was taken way too seriously by the bond market from the 1980s to 2008. It provided a philosophical underpinning for the junk bond market. (They can't possibly all go bad at the same time, can they?)

Ludic Fallacy

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