Eric Holloway: How can we measure meaningful information?

toothpicks/Superbass (CC BY-SA 4.0)

Neither randomness nor order alone create meaning. So how can we identify communications in a scientifically meaningful way?

Dropping a handful of toothpicks on the table seems to produce a different sort of pattern than spelling out a word with toothpicks. Surprisingly, this intuitive distinction is harder to make in math and the sciences. Algorithmic specified complexity (ASC) enables us to distinguish them.

Neither Shannon information nor Kolmogorov complexity work well for this purpose.

This leads us to a third concept, algorithmic specified complexity (ASC). ASC solves the problem by combining the two measures. ASC states that an event has a high amount of information if it has both low probability and a concise description. This matches our intuition much better.
More.

Eric Holloway has a Ph.D. in Electrical & Computer Engineering from Baylor University. He is a current Captain in the United States Air Force where he served in the US and Afghanistan He is the co-editor of the book Naturalism and Its Alternatives in Scientific Methodologies. Dr. Holloway is an Associate Fellow of the Walter Bradley Center for Natural and Artificial Intelligence.

Also by Eric Holloway: Human intelligence as a halting oracle

and

Does information theory support design in nature?

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