Motivation, Entropy, and IntelligencePosted: February 17, 2014
The February doldrums play havoc in the best of times. Unfortunately, this year’s extraordinary weather events have weighed heavily on the minds of everyone in the USA, the UK, and beyond. Mother Nature’s shenanigans have us all yearning for summer’s freedom and flowers. We want a change of pace, a change of place, and perhaps even a change of heart beyond that supplied by the purveyors of Valentine’s Day chocolates and cards.
Schools of all types feel the February doldrums. Children serve as canaries in the cold mines of winter. Their academic motivations often wane before educators feel their own motivation lows.
What’s the secret to staying motivated?
Instead of fabricating motivation out of cold air, why not embrace chaos, randomness, and disorder? Why not let go of all notions that X academic unit must be completed by Y arbitrary time, and instead use times of low motivation as opportunities to increase student choices and explore student passions? Why not throw curricular caution to the prevailing winds and instead jump-start new interests and motivations?
Intelligence as Entropy
I jump-started my own interests and motivations earlier this month by watching a fascinating TEDx talk that defines intelligence as entropy. In Alex Wissner-Gross: A new equation for intelligence, Wissner-Gross explains that “intelligence is a force that acts to maximize future freedom of action and keep options open. . . intelligence emerges from long-term entropy.”
By “intelligence” Wissner-Gross means all kinds of intelligence—that of humans, animals, and machines. Yes, he’s comparing our own intelligence to that of machines. And, remarkably, he has written software with intelligence approximating that of tool-using animals and stock-trading humans.
Wissner-Gross’s equation for intelligence is that intelligence is a force (f) that acts to maximize future freedom of action (or keep options open) with some strength (t) with the diversity of possible accessible futures (s) up to some future time horizon (tau). He explains, in short, that intelligence doesn’t like to be trapped. Intelligence instead prefers to keep options open.
(Screen shot from the TEDx talk by Wissner-Gross)
Why Listen to Wissner-Gross?
I first watched Wissner-Gross’s TEDx talk late one evening in early February. I went to bed thinking, “This guy might be a fruitcake.” At the time, I knew nothing about Wissner-Gross or his work. I knew that a few fruitcakes have slipped through the careful TEDx vetting process. During my night-thoughts, I tossed and turned Wissner-Gross’s ideas about intelligence being a maximization of future freedom of action.
In the morning, I learned online that Wissner-Gross has impressively maximized his own future freedom of action. He’s a young Harvard physicist who serves both as an Institute Fellow at the Harvard University Institute for Applied Computational Science and as a Research Affiliate at the MIT Media Laboratory. He has a triple major from MIT, a physics Ph.D. from Harvard, and an impressive number of distinctions, publications, and patents. His TED speaker profile calls him a “serial big-picture thinker.” Wow.
Wissner-Gross has smarts, for sure, but how might he convince others that his equation works? He explains, “We developed a software engine called ENTROPIC designed to maximize the long-term entropy of any system that it finds itself in. ENTROPIC was able to pass multiple animal intelligence tests, play human games and even earn money trading stocks, all without being instructed to do so.” The TEDx talk includes video footage of the computer program figuring out tool use, social cooperation, gaming, network organization, problem-solving, and risk-managing.
In their 2013 research article, “Causal Entropic Forces,” Wissner-Gross and MIT researcher C.E. Freer mention the application of their work to various fields including condensed matter physics, particle theory, econophysics, cosmology, and biophysics. Although they do not mention any educational implications of their work, they note: “We found that some of these systems exhibited sophisticated spontaneous behaviors associated with the human ‘‘cognitive niche,’’ including tool use and social cooperation * * * .”
Implications for Education and Motivation
Although Wissner-Gross’s and Freer’s work has not yet entered education circles, I believe their work bears relevance not only to the intelligence of machines, but also to the education, motivation, and intelligence of human beings. At least one writer agrees that Wissner-Gross’s work has human implications: “With broad implications for fields ranging from management and investing to artificial intelligence, Wissner-Gross’s message reveals a profound new connection between intelligence and freedom.” From Kurzweil Accelerating Intelligence.
I love the notion that intelligence “prefers to keep options open.” I love thinking that education might someday be less of a mechanism for producing educated adults, and more of a mechanism for helping children keep their options open.
I love to think of academic motivation not as “finish this unit and you’ll win X grade or reward,” but rather as “how do we keep your options open so you don’t feel trapped?” Why not cure low educational motivation not with rewards external to the child, but rather with new sparks of option-opening?
Perhaps the core mission of education should be to maximize the future choices of children? By maximizing the future choices of children, might we automatically maximize the intelligence of society as a whole?
Wissner-Gross notes a profound irony stemming from his work. Rather than the fictional scenario of robots gaining intelligence and then using that intelligence to take control of human society, the reverse may be true: intelligence might arise from control-taking. He explains, “It’s not that machines first become intelligent and then megalomaniacal and try to take over the world. It’s quite the opposite. That the urge to take control of all possible futures is a more fundamental principal than that of intelligence. General intelligence may in fact emerge directly from this sort of control-grabbing, rather than vice versa.”
Just in case Wissner-Gross is correct, and just because children really do love grabbing control from adults and experiencing the world on their own terms, here’s my advice to children and educators:
During times of low motivation, (1) embrace chaos, randomness, and disorder, (2) let go of all notions that X academic unit must be completed by Y arbitrary time, and (3) jump-start new interests and motivations.
If Wissner-Gross is correct, increasing children’s chaos and choices might just increase their intelligence.