Bayes and Base Rates 2.0: How History Can Guide Our Assessment of the Future

13 MAI 2026

The Authors

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This is a follow up to our recent report, “Bayes and Base Rates,” which argued that to anticipate what is going to happen, it is useful to start with base rates as a prior probability distribution and to update your view based on new information.
That report sparked interest and some questions that we address, including how to handle inflation, the appropriate reference class, and groundbreaking technologies.
Comparing the projected sales growth rates of a couple of companies, including OpenAI, to base rates revealed that these forecasts are highly improbable in the context of history.
Base rates are dynamic distributions, and nothing in past results says OpenAI's projected rates of growth are unachievable.
Factors working in favor of OpenAI are rapid adoption of the product, high one-year sales growth, and the fact that intangible-intensive businesses have proven they can grow fast.
On the other hand, there have been numerous disruptive innovations since 1950, and most of the all-time leaders in sales growth have done so through M&A rather than organically.

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Bayes and Base Rates 2.0: How History Can Guide Our Assessment of the Future

We follow up on our recent report that argued that forecasters should start with base rates and update views over time. We got questions about inflation, reference classes, and groundbreaking technologies. Comparing projections for OpenAI to base rates revealed they are highly improbable. Factors in their favor are rapid adoption, high one-year growth, and the past growth of intangible-heavy firms. But there have been other disruptive innovations, and most of the top growers did so through M&A.

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