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Sean Gourley is founder and former CEO of Primer. Previously, he was CTO of Quid, an augmented-intelligence company he co-founded in 2009. Prior to Quid, Gourley worked on self-repairing nano-circuits at NASA Ames.
He holds a PhD in physics from Oxford, where his research as a Rhodes Scholar focused on complex systems and the mathematical patterns underlying modern war. This research was published on the cover of Nature.
He has served as a political advisor, briefed USCENTCOM at the Pentagon and addressed the United Nations in Vienna. He is a two-time New Zealand track and field champion. Gourley sits on the Knight Commission, serves on the Board of Directors at Anadarko (NYSE:APC), and is a TED Fellow.
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The New Corporate Intelligence
Disruptive technology shapes the world, defining political, military, financial, and commercial opportunities and threats. Whether originating in academic research, in National Labs, or in privately held or public companies, these technologies can emerge with explosive impact, creating and destroying value. Yet there are few tools to track these innovationsat a global scale and at a pace that keeps up with the rate of change.
What if corporate strategists could literally draw a map to find growth opportunities? A technique called semantic clustering analysis makes this possible. When applied to technology entities worldwide, this analysis can reveal not only which innovation areas are thick with competition, but also where in the market there are opportunities, or white spaces, ripe for innovation. The result is a data-driven visual tool that can be used to drive corporate innovation strategy.
Augmenting Humans to Make Better Policy Decisions
What's smarter? A person, or a computer? Today, at least, the answer is both. Computers can't simply print out the answers to complex problems. Plenty of problems are opaque to raw computing power. From corporate strategy to geopolitics, a purely algorithmic or data-driven approach wont work. In this talk, Sean Gourley will look at ways to combine humans and machines to make better decisions. Well look at some specific examples, such as global space policy, to show how a blended approach improves results and adds to the cognitive ability of decision-makers involved in big, complex, seemingly intractable questions.
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