[The Theory That Would Not Die 01] • The Theory That Would Not Die

What it’s about

Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes’ rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s, its independent development by the French scientist Pierre-Simon Laplace, and its 150-year suppression by statisticians who championed a rigid, 'objective' view of science. The book reveals how, even while it was professionally taboo, practitioners secretly relied on it to solve crises involving great uncertainty, from breaking Germany’s Enigma code in World War II to hunting for lost H-bombs and Soviet submarines during the Cold War. It's a riveting story of how a small group of beleaguered believers, empowered by the advent of computer technology, finally brought Bayes' rule to the forefront, making it the engine behind everything from DNA decoding and machine learning to Google searches and AI.

The through-line

Who it’s for

An intellectually curious person, professional, scientist, or leader who grapples with uncertainty and wants a better framework for making rational decisions and predictions based on evolving evidence.

The problem

Lacking a formal, logical system for combining prior knowledge with new data to make judgments in complex situations with incomplete information. Feeling frustrated by rigid, conventional statistical methods that seem ill-suited for real-world problems, and suspecting there must be a more intuitive way to think about evidence and update one's views.

The plan

1. Learn the dramatic history of the theorem's discovery by Bayes and its powerful development by Laplace.
2. Understand the philosophical conflicts that led to its rejection by mainstream statisticians like R.A. Fisher.
3. Discover its secret, high-stakes applications during World War II and the Cold War.
4. Witness its modern revival and triumph, enabled by the dawn of the computer age.

The payoff

Gaining a powerful mental framework for making sense of an uncertain world. · Thinking more clearly and rationally about evidence, risk, and probability. · Understanding the statistical revolution that underpins much of modern science and technology, from AI to genetics.

See our guide

• Update Your Beliefs With Evidence →