Striving for Expansion
Survival within a niche is less about the will to power and more about taming entropy.
Why, man, he doth bestride the narrow world
Like a Colossus, and we petty men
Walk under his huge legs and peep about…
The fault, dear Brutus, is not in our stars,
But in ourselves.
— Julius Caesar, Act 1, Scene 2
There is a tendency to look towards artificial intelligence — and particularly Artificial General Intelligence (AGI), not just ChatBots — as some kind of savior that will yank us out of our omnidirectional existential crisis and pull us back from the brink of human extinction. This logic, or deep-seated fantasy, flows neatly from the historical themes of Abrahamic desert religions that guide so much of Western popular culture, from action films to sporting events to current politics. But saviors are implausible, if not impossible, and AGI is no different.
Earlier this year the elderly gent who coined the term, EROIE (energy return on invested energy) and later inaugurated the scientific discipline of biophysical economics, the venerable 80-year-old Charles A.S. Hall, coauthored a paper in the Philosophical Transactions of the Royal Society (I read it for the Sunday funnies) entitled, “Maximum power in evolution, ecology and economics.”
Hall’s paper recounted the progression of science’s understanding of the role of energy in biological and physical systems from Darwin’s finches to the formation of galaxies. The essay reminded us that the human species, like every other organizational unit in the universe, is governed by a drive to acquire power. The nineteenth-century German philosopher Friedrich Nietzsche called this drive, “Streben nach Entfaltung” (striving for expansion). As Hall relates, later biophysicists like Boltzmann, Lotka, Odum and Pinkerton would show how survival within a niche is less about the will to power and more about the taming of entropy — reducing the dissipation of captured energy. Lotka, in 1922, said that organisms that capture and use energy more rapidly and effectively have a selective advantage but in the context of ecosystems, the maximum is not always the optimum — there is a sweet spot where…