Sean Carroll from preposterousuniverse.comMaxwell’s Demon is a famous thought experiment in which a mischievous imp uses knowledge of the velocities of gas molecules in a box to decrease the entropy of the gas, which could then be used to do useful work such as pushing a piston. This is a classic example of converting information (what the gas molecules are doing) into work. But of course that kind of phenomenon is much more widespread — it happens any time a company or organization hires someone in order to take advantage of their know-how. César Hidalgo has become an expert in this relationship between information and work, both at the level of physics and how it bubbles up into economies and societies. Looking at the world through the lens of information brings new insights into how we learn things, how economies are structured, and how novel uses of data will transform how we live.
César Hidalgo received his Ph.D. in physics from the University of Notre Dame. He currently holds an ANITI Chair at the University of Toulouse, an Honorary Professorship at the University of Manchester, and a Visiting Professorship at Harvard’s School of Engineering and Applied Sciences. From 2010 to 2019, he led MIT’s Collective Learning group. He is the author of Why Information Grows and co-author of The Atlas of Economic Complexity. He is a co-founder of Datawheel, a data visualization company whose products include the Observatory of Economic Complexity.
I was also piqued at the mention of Lynne Kelly’s work, which I’m now knee deep into. I suspect it could dramatically expand on what we think of as the capacity of a personbyte, though the limit of knowledge there still exists. The idea of mnemotechniques within indigenous cultures certainly expands on the way knowledge worked in prehistory and what we classically think of and frame collective knowledge or collective learning.
I also think there are some interesting connections with Dr. Kelly’s mentions of social equity in prehistorical cultures and the work that Hidalgo mentions in the middle of the episode.
There are a small handful of references I’ll want to delve into after hearing this, though it may take time to pull them up unless they’re linked in the show notes.
hat-tip: Complexity Digest for the reminder that this is in my podcatcher. 🔖 November 22, 2019 at 03:28PM
