Adonis Diaries

Could anyone have predicted his own trajectory? It began in quiet New Zealand — first in Christchurch and then a small town nearby — with an idyllic beach and two parents who knew they had a smart kid.

While young Sean was good at math, his parents happily left him to his own devices instead of putting him in advanced tutoring classes. The boy ran, studied the humanities, did law and philosophy at university.

Math “was sort of on the side,” he recalls. The future Rhodes Scholar, physicist and AI expert might have ended up an attorney with a head for numbers.

Thank goodness he got B’s in the law classes — math and physics came a-calling (A big difference between man-made rules as in law and accounting, and axioms and theorems)

Fast-forward to roughly 2004, when Gourley was at Oxford.

Among those scholars, all the talk was about the war in Iraq, and Chelsea Clinton was around, waving American flags at protests against the war.

Though he was “nominally there” to do a Ph.D. on nanotechnology, the war caught his attention. Few quants outside intelligence communities used data, and defense agencies like the Pentagon weren’t exactly eager to part with it.

Gourley’s real catalyst came when he started to notice signals, or usable data, in the noise — in blogs, on newscasts, in NGO reports (130 sources in all). Now that was a big “wow.”

Over the next four years, Gourley and an interdisciplinary team began tackling a problem that didn’t fit anywhere obvious within academia: the mathematics of insurgency.

Gourley spent about a month in Iraq itself, where, he says, life “was pretty normal … except suddenly you’d have an explosion around the corner, or AK fire all of a sudden.” He witnessed the messiness of war not just in the cities but also in the people themselves — “the kid straight out of Iowa, the grizzled CIA operative, the people there for profit,” and even the faces of human trafficking.

How strange to discover that amid blood and destruction lay something predictable, something you could even model.

Remember the interdisciplinary thing? It turned out to be both the biggest flaw and biggest stroke of luck for Gourley.

“You find yourself berated by your own discipline for not doing ‘real work’ and by the discipline you’re entering into for not knowing enough,” he says.

“I never expected a new idea would encounter so much friction.” So it took some creativity to find a home for the whole thing. The researchers framed the study on war and math as an ecological argument. Huh?

They needed a discipline that studied systems, Gourley explains, and ecology is one of the few that studies mathematical interactions between objects. The big idea was suddenly deemed a study of “synthetic ecology.” In went the paper to one of the most prestigious journals around, Nature.

And then, for six months — nothing. Somewhere in there, Gourley got a call from TED. “It was really a gamble,” allowing him to speak, he says. The vindication came later, when, at 30, Gourley saw his research land on the cover of Nature.

Ironically enough, that long wait time “saved” Gourley from academia, he says now. Because he couldn’t win the academics over so easily, he began to think about applying his big theories to the real world. Without the frustration, he could very well have continued along the tenure-track path. And he’s glad to be outside of that.

Today, Gourley’s idea is still running around out there. Unfortunately, it hasn’t yet changed the face of diplomacy as we know it, says Carne Ross, a former British diplomat who runs a nonprofit advisory group called the Independent Diplomat.

“Diplomacy is seeing remarkably little technological tools,” he says. “This community is very ideologically resistant to technology.” In intelligence and the military, though, he ventures that might not be the case.

As for Gourley himself? He’s no longer studying war anymore. Today finds him a couple of months into his second company; the first, Quid, helps companies do what Gourley did for war — crunch data, turn it into something visual and comprehensible, and act on it.

He’s worked with the Department of Defense, Hollywood types, Rupert Murdoch (who, he says, learned from the data that vampire movies are, in fact, still hot).

The second venture is a bit under wraps, but he tells me it’s tackling some tough AI problems.

“You can’t convince anyone with just math,” Gourley says now. “You have to build something.”

(The illusion that colored graphs from crunched data that fit a model is reality? I which I can get a copy of the war math paper to discuss it)