In the 18th century, the philosopher David Hume observed that induction — inferring the future based on what’s happened in the past — can never be reliable. In 1997, SFI Professor David Wolpert with his colleague Bill Macready made Hume’s observation mathematically precise, showing that it’s impossible for any inference algorithm (such as machine learning or genetic algorithms) to be consistently better than any other for every possible real-world situation.
Over the next decade, the pair proved a series of theorems about this that were dubbed the “no-free-lunch” theorems. These proved that one algorithm could, in fact, be a bit better than another in most circumstances — but only at the cost of being far worse in the remaining circumstances.
These theorems have been extremely controversial since their inception, since they punctured the claims of many researchers that the algorithms they had developed were superior to other algorithms. As part of the controversy, in 2019, the philosopher Gerhard Schulz wrote a book wrestling with the implications of Hume’s and Wolpert’s work. A special issue of the Journal for General Philosophy of Science was devoted to Schulz’s book, and included an article by Wolpert himself.
Read the study “The Implications of the No-Free-Lunch Theorems for Meta-induction” at doi.org/10.1007/s10838-022-09609-2