Max Tegmark (MIT physics dept.) : “Integrated Information Theory of consciousness (IIT) [. It] says that information being processed is conscious if a mathematical quantity called Φ (“Phi”) is large. Phi quantifies integration, the extent to which information is interconnected into a unified whole rather than split into disconnected parts. The theory has generated interest from the neuroscience community, but also controversy, including recent critique from Scott Aaronson.

I want to see the question of whether IIT is correct or not resolved by experimental tests. Unfortunately, Tononi’s proposed measure of integration is too slow to compute in practice from state-of-the-art patient data, requiring longer than the age of our universe, let alone the lifetime of the patient. I’ve therefore worked hard over the last year in search of a faster way to compute integration, and I’m happy report that I’ve found one — in fact, several. In a paper I just posted, I explore and classify existing and novel integration measures by various desirable properties, finding that although there at first seem to be a few hundred options, there are in fact only a handful if attractive ones. I was happy to discover that there’s an approximation based on graph theory that let’s you dramatically speed up the exact formulas, so that they can be applied to real-world data from laboratory experiments without posing unreasonable computational demands. Let’s try to shed more light on the fascinating questions and theories about consciousness my making experimental tests!”

The digest summary: Let’s Measure Consciousness!

The hardcore original physics paper: Improved Measures of Integrated Information