Scientists are getting better at predicting the future, but prediction remains an inherently difficult problem. Indeed, there’s good reason to believe we will eventually bump against some fundamental limits. What are those limits?

During a recent workshop at SFI, experts attempted to get a handle on this most fundamental of questions. 

The question isn’t just about how well we can predict things today using current ideas and technologies, says SFI Omidyar Fellow Josh Grochow, who co-organized the workshop with SFI President David Krakauer.

“The idea is that there are limits to prediction – practical, theoretical, and fundamental – and we want to understand what goes into those,” Grochow says.

A classic example of where prediction faces fundamental challenges is in chaotic systems. By definition, the future of a chaotic system depends very sensitively on its initial conditions. Inherent limits on our ability to measure those starting points make prediction more difficult.

But even that is a fairly mild challenge compared to situations where evolution, adaptation, and innovation come into play. How, for example, would biologists predict the future evolution of species, where mutation and natural selection combine to produce...what, we don’t really know. Likewise, predicting the future of technology even five to ten years out is often little more than a guessing game.

The workshop was a first attempt to understand how much better we might be able to do. “We think that getting at the core issues of prediction in complex adaptive systems will benefit from and possibly require every tool in the tool chest we have for prediction, in every field,” he says. “So we want to bring people together, to see what those tools are, where they’re going, and how they might be combined to get a better understanding of the limits of prediction.”

More about the workshop.