ludig-fallacy-explained

The Ludic Fallacy – Nassim Taleb & The Incerto

What Is The Ludic Fallacy | Coined By Nassim Taleb In The Black Swan

The Ludic Fallacy is a term originally coined by Nassim Taleb in his second instalment of the ‘Incerto‘ – The Black Swan.

Ludic comes from Latin – no-one should be surprised Taleb is leaning on an ancient reference – and the word means to refer to games. Taleb is writing in the content of probability, randomness, uncertainty, statistics and as such the Ludic Fallacy quite neatly fits into his worldview that life is not a series of games.

The Ludic Fallacy can be thought of otherwise as the fallacy of thinking about life in terms of games. Games have fixed and pre-determined rules – life does not. And it is in this narrow but nonetheless trench deep difference where much of the ‘Incerto‘ operates.

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Explaining The Ludic Fallacy

The Ludic Fallacy is the misuse of measuring games to model real-life situations. The fallacy comes from the idea that much of our probability modelling is either proven or disproven through the narrow world of games of dice.

This idea goes to complement and reinforce Taleb’s ‘Bed Of Procrustes‘ metaphor – do not try to fit life into a model, allow a model to ebb and flow with life.

The Black Swan can prove some model based on an understanding of dice to be an eventual victim to the Ludic Fallacy. Taleb argues that the study of statistics is only actually applicable in certain domains such as casinos and games where all the variables are visible and defined.

The problem is that as soon as you enter real life and leave behind the realm of defined variables most statistical and therefore predictive models become victim to the Ludic Fallacy.

Why?

Because in real life we are not in possession of all the variables. This point is so blatantly obvious to me but seems to be too abstract of an input to compute for most. I really don’t understand why.

The future of infinite possibilities contains far too many variables for even all of the world’s supercomputers working together to take into account. Black Swans exist – and Black Swans prove the Ludic Fallacy – therefore the Ludic Fallacy exists. When not playing Ludic games, It is impossible to be in possession of all available information.

Small unknown variations in the data could have a huge impact. I will explain with examples.

When you are playing roulette, blackjack or poker – you will struggle to prove the Ludic Fallacy because each variable is visible and accounted for. Add one card to the deck however, or one crack to the wheel – and all of a sudden each variable is not visible and accounted for… now you could fall victim to the Ludic Fallacy.

Think along the lines of whether all the information is accounted for or not.

Example Of The Ludic Fallacy | Professional Fighting

Professional boxing, Jiu-Jitsu, MMA etc, trains fighters to focus on the game and to ignore the possibility of what is not specifically allowed by the rules. This includes things such as kicks to the groin, a surprise knife, eye-gouging, etc.

Those who win the belt in the UFC or win the gold medal at the Olympics might therefore be precisely those who will be most vulnerable in real life. Now it might not be true that a gold medal boxer is going to vulnerable on the streets – but this is because a person lives in the real world and knows how to adapt to new information. Walking home from the gold medal ceremony if the boxer is mugged he knows to be aware for a knife, a gun, a groin attack and eye gouge etc. 

A predictive model that could somehow program a robot to win gold at the Olympics, on the other hand, would fall victim to variables outside of the pre-determined rules. The robot is now a victim of the Ludic Fallacy because his statistical understanding of the world was brought down by the EMP attack Black Swan event that fell outside of his pre-determined rules

Example Of The Ludic Fallacy | Fat Tony & The Loaded Coin.

Taken straight from the book – Taleb’s infamous Fat Tony.

  • Dr. John is regarded as a man of science and logical thinking. Likes models.
  • Fat Tony is regarded as a man who lives by his wits. Prefers instincts.

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?”

  • Dr. John says that the odds are not affected by the previous outcomes so the odds must still be 50-50.
  • Fat Tony says that the odds of the coin coming up heads 99 times in a row are so low that the initial assumption that the coin had a 50-50 chance of coming up heads is most likely incorrect. “The coin gotta be loaded. It can’t be a fair game.”

Be aware of the Ludic Fallacy. You almost never know all the variables – stay sharp – and most importantly, apply mounds of salt to predictive models.

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