Insecurity and Probability
This concept advocates for cultivating intellectual insecurity over confidence, treating probability as a branch of applied skepticism that accepts uncertainty and develops methods for dealing with ignorance rather than mere computation.
THE IDEA
Insecurity and Probability
I believe that the principal asset I need to protect and cultivate is my deep-seated intellectual insecurity. My motto is “my principal activity is to tease those who take themselves and the quality of their knowledge too seriously.” Cultivating such insecurity in place of intellectual confidence may be a strange aim—and one that is not easy to implement. To do so we need to purge our minds of the recent tradition of intellectual certainties. A reader turned pen pal made me rediscover the sixteenth-century French essayist and professional introspector Montaigne. I got sucked into the implications of the difference between Montaigne and Descartes—and how we strayed by following the latter’s quest for certitudes. We surely closed our minds by following Descartes’ model of formal thinking rather than Montaigne’s brand of vague and informal (but critical) judgment. Half a millennium later the severely introspecting and insecure Montaigne stands tall as a role model for the modern thinker. In addition, the man had exceptional courage: It certainly takes bravery to remain skeptical; it takes inordinate courage to introspect, to confront oneself, to accept one’s limitations—scientists are seeing more and more evidence that we are specifically designed by mother nature to fool ourselves.
There are many intellectual approaches to probability and risk—“probability” means slightly different things to people in different disciplines. In this book it is tenaciously qualitative and literary as opposed to quantitative and “scientific” (which explains the warnings against economists and finance professors as they tend to firmly believe that they know something, and something useful at that). It is presented as flowing from Hume’s Problem of Induction (or Aristotle’s inference to the general) as opposed to the paradigm of the gambling literature. In this book probability is principally a branch of applied skepticism, not an engineering discipline (in spite of all the self-important mathematical treatment of the subject matter, problems related to the calculus of probability rarely merit to transcend the footnote).
How? Probability is not a mere computation of odds on the dice or more complicated variants; it is the acceptance of the lack of certainty in our knowledge and the development of methods for dealing with our ignorance. Outside of textbooks and casinos, probability almost never presents itself as a mathematical problem or a brain teaser. Mother nature does not tell you how many holes there are on the roulette table, nor does she deliver problems in a textbook way (in the real world one has to guess the problem more than the solution). In this book, considering that alternative outcomes could have taken place, that the world could have been different, is the core of probabilistic thinking. As a matter of fact, I spent all my career attacking the quantitative use of probability. While Chapters 13 and 14 (dealing with skepticism and stoicism) are to me the central ideas of the book, most people focused on the examples of miscomputation of probability in Chapter 11 (clearly and by far the least original chapter of the book, one in which I compressed all the literature on probability biases). In addition, while we may have some understanding of the probabilities in the hard sciences, particularly in physics, we don’t have much of a clue in the social “sciences” like economics, in spite of the fanfares of experts.
When to use it
When evaluating investment strategies, maintain a skeptical outlook and consider that past performance does not guarantee future results.
In scientific research, acknowledge the limitations of inductive reasoning and consider alternative explanations for observed data.
When making major life decisions (e.g., career changes, moving), actively seek out disconfirming evidence to challenge your assumptions.
In business risk management, adopt a qualitative approach that emphasizes uncertainty and fat-tailed risks rather than relying solely on quantitative models.
FROM THEORY TO EVERYDAY LIFE
In practice
Applying Intellectual Insecurity in Investing
An investor who cultivates intellectual insecurity will not rely on past performance as a guarantee of future returns. Instead, they will consider the possibility of rare, unpredictable events (black swans) and diversify their portfolio to hedge against unknown risks. They actively seek out disconfirming evidence about their investment thesis and remain open to changing their mind when new information arises.
Scientific Research and Inductive Skepticism
A scientist who embraces this concept acknowledges that all empirical knowledge is provisional. When interpreting experimental results, they consider the limits of induction and the possibility that future observations may overturn current theories. They use Bayesian reasoning to update beliefs and are wary of overconfidence in statistical significance, especially in fields with low replicability.
A MOMENT TO REFLECT
Put it to work.
How can you cultivate intellectual insecurity in your own decision-making process?
What are the dangers of overconfidence in probabilistic judgments, and how can you guard against them?
In what areas of your life do you most need to apply the Problem of Induction to avoid false certainty?
Often confused with
CONTINUE THE CONVERSATION
Source texts
- Fooled by Randomness The Hidden Role of Chance in the Markets and in Life (Nassim Nicholas Taleb)