All or None
The all-or-none fallacy is the tendency to think in binary terms, misinterpreting probabilistic statements as absolute. It also involves confusing necessary conditions with sufficient causes, and committing the fallacy of affirming the consequent.
THE IDEA
All or None
A few confusions with the message in this book. Just as our brain does not easily make out probabilistic shades (it goes for the oversimplifying “all-or-none”), it was hard to explain that the idea here was that “it is more random than we think” rather than “it is all random.” I had to face the “Taleb, as a skeptic, thinks everything is random and successful people are just lucky.” The Fooled by Randomness symptom even affected a well-publicized Cambridge Union Debate as my argument “Most City Hotshots are Lucky Fools” became “All City Hotshots are Lucky Fools” (clearly I lost the debate to the formidable Desmond Fitzgerald in one of the most entertaining discussions in my life—I was even tempted to switch sides!). The same delusion of mistaking irreverence for arrogance (as I noticed with my message) makes people confuse skepticism for nihilism.
Let me make it clear here: Of course chance favors the prepared! Hard work, showing up on time, wearing a clean (preferably white) shirt, using deodorant, and some such conventional things contribute to success—they are certainly necessary but may be insufficient as they do not cause success. The same applies to the conventional values of persistence, doggedness and perseverance: necessary, very necessary. One needs to go out and buy a lottery ticket in order to win. Does it mean that the work involved in the trip to the store caused the winning? Of course skills count, but they do count less in highly random environments than they do in dentistry.
No, I am not saying that what your grandmother told you about the value of work ethics is wrong! Furthermore, as most successes are caused by very few “windows of opportunity,” failing to grab one can be deadly for one’s career. Take your luck!
Notice how our brain sometimes gets the arrow of causality backward. Assume that good qualities cause success; based on that assumption, even though it seems intuitively correct to think so, the fact that every intelligent, hardworking, persevering person becomes successful does not imply that every successful person is necessarily an intelligent, hardworking, persevering person (it is remarkable how such a primitive logical fallacy —affirming the consequent— can be made by otherwise very intelligent people, a point I discuss in this edition as the “two systems of reasoning” problem).
There is a twist in research on success that has found its way into the bookstores under the banner of advice on: “these are the millionaires’ traits that you need to have if you want to be just like those successful people.” One of the authors of the misguided The Millionaire Next Door (that I discuss in Chapter 8) wrote another even more foolish book called The Millionaire Mind. He observes that in the representative cohort of more than a thousand millionaires whom he studied most did not exhibit high intelligence in their childhood and infers that it is not your endowment that makes you rich—but rather hard work. From this, one can naively infer that chance plays no part in success. My intuition is that if millionaires are close in attributes to the average population, then I would make the more disturbing interpretation that it is because luck played a part. Luck is democratic and hits everyone regardless of original skills. The author notices variations from the general population in a few traits like tenacity and hard work: another confusion of the necessary and the causal. That all millionaires were persistent, hardworking people does not make persistent hard workers become millionaires: Plenty of unsuccessful entrepreneurs were persistent, hardworking people. In a textbook case of naive empiricism, the author also looked for traits these millionaires had in common and figured out that they shared a taste for risk taking. Clearly risk taking is necessary for large success—but it is also necessary for failure. Had the author done the same study on bankrupt citizens he would certainly have found a predilection for risk taking.
I was asked to “back up the claims” in the book with the “supply of data,” graphs, charts, diagrams, plots, tables, numbers, recommendations, time series, etc., by some readers (and by me-too publishers before I was lucky to find Texere). This text is a series of logical thought experiments, not an economics term paper; logic does not require empirical verification (again there is what I call a “round-trip fallacy”: It is a mistake to use, as journalists and some economists do, statistics without logic, but the reverse does not hold: It is not a mistake to use logic without statistics). If I write that I doubt that my neighbor’s success is devoid of some measure, small or large, of luck, owing to the randomness in his profession, I do not need to “test” it—the Russian roulette thought experiment suffices. All I need is to show that there exists an alternative explanation to the theory that he is a genius. My approach is to manufacture a cohort of intellectually challenged persons and show how a small minority can evolve into successful businessmen—but these are the ones who will be visible. I am not saying that Warren Buffett is not skilled; only that a large population of random investors will almost necessarily produce someone with his track records just by luck.
When to use it
In business, when evaluating a startup's success, avoid assuming that because successful founders have certain traits, those traits guarantee success.
In sports, when a team wins a championship, fans often attribute it to the coach's strategy, ignoring the role of luck in key plays.
In personal finance, when reading investment success stories, remember that survivorship bias and randomness play a role; not all strategies that worked in the past will work in the future.
In academic research, when interpreting studies that find common traits among high achievers, be cautious of affirming the consequent.
FROM THEORY TO EVERYDAY LIFE
In practice
Debate Misinterpretation
In a Cambridge Union debate, the author's argument that 'most City Hotshots are Lucky Fools' was misconstrued as 'all City Hotshots are Lucky Fools', leading to a loss in the debate. In the all-or-none fallacy, a probabilistic statement is taken as absolute.
Millionaire Studies
Studies of millionaires often find common traits like hard work and risk-taking, but these are necessary conditions for success, not sufficient. The fallacy is to infer that these traits cause success, ignoring the role of luck. This is an example of confusing necessary with sufficient and affirming the consequent.
A MOMENT TO REFLECT
Put it to work.
Think of a recent news story where a probabilistic claim was misinterpreted as absolute. How does the all-or-none fallacy apply?
Consider a successful person you admire. List traits that are necessary for success but not sufficient. How might luck have played a role?
When someone argues that 'all millionaires are hard workers, therefore hard work leads to millionaire status,' what logical fallacy are they committing?
Often confused with
References
- The Millionaire Next Door — Thomas J. Stanley and William D. Danko (1996)
- The Millionaire Mind — Thomas J. Stanley (2000)
CONTINUE THE CONVERSATION
Source texts
- Fooled by Randomness The Hidden Role of Chance in the Markets and in Life (Nassim Nicholas Taleb)