Anthropic-backed researchers argue AI should interpret scientific models

In a post published by Anthropic, the company’s supported researchers Jakob Macke, Daniel Gedon and Stefan Wahl explain how AI could change the construction and interpretation of scientific models. They use the Hodgkin-Huxley model, created in 1951 to describe the electrical activity of a squid nerve cell, to show how a choice that fit the data—raising a variable to the fourth power—could later help explain the structure of related potassium channels.

The post says an AI system could find a similar equation quickly, perhaps with an even closer fit, but that reproducing the data is not enough: multiple models can do so without revealing which features correspond to the real-world system. The authors divide modeling into steps, including building a model and tuning its parameters to real measurements, and argue that AI should also contribute to understanding the phenomena being studied.