Gerd Gigerenzer (born 3 September 1947) is a German psychologist who has studied the use of bounded rationality and heuristics in decision making.

Similarly, decisions by experienced experts (e.g., police, professional burglars, airport security) were found to follow the take-the-best heuristic rather than weight and add all information, while inexperienced students tend to do the latter.

A third class of heuristics, fast-and-frugal trees, are designed for categorization and are used for instance in emergency units to predict heart attacks or to model bail decisions made by magistrates in London courts.

The short book Classification in the Wild (2020, MIT Press),[7] uses examples such as how American citizens decide to vote for their president or how paramedics prioritise treatments at a medical emergency to show how to build heuristics such as fast-and-frugal trees and tallying models.

The book also shows how to test and compare these simple heuristics' accuracy and transparency with state-of-the art algorithms from other fields, including machine learning.

The basic idea of the adaptive toolbox is that different domains of thought require different specialized cognitive mechanisms instead of one universal strategy.

For instance, lay people as well as professionals often have problems making Bayesian inferences, typically committing what has been called the base-rate fallacy in the cognitive illusions literature.

Gigerenzer has taught risk literacy to some 1,000 doctors in their CMU and some 50 US federal judges, and natural frequencies has now entered the vocabulary of evidence-based medicine.

In recent years, medical schools around the world have begun to teach tools such as natural frequencies to help young doctors understand test results.

Gigerenzer and colleagues write of the mid-17th century "probabilistic revolution", "the demise of the dream of certainty and the rise of a calculus of uncertainty – probability theory".