Exponentials • Future of Work • Moderator • Future Forecasting
Paul is a Silicon Valley-based forecaster with over three decades of experience helping corporate and governmental clients understand and respond to the dynamics of large-scale, long-term change. He teaches at Stanford, where he is a Consulting Associate Professor in the School of Engineering, and a Distinguished Visiting Scholar in the Stanford Media-X network. Paul is also a non-resident Senior Fellow at the Atlantic Council, a Fellow of the Royal Swedish Academy of Engineering Sciences, and serves on the boards of the Long Now Foundation, and the Bay Area Council Economic Institute.
Previously, Paul was the founding chair of the Samsung Science Board and a member of the AT&T Technical Advisory Board. His essays have appeared in a wide range of publications, including The Harvard Business Review, Foreign Policy, Fortune, Wired, the Los Angeles Times, Newsweek, the New York Times, and the Washington Post. Paul holds degrees from Harvard College, Cambridge University, and Stanford University.
Are robots stealing our jobs? Wrong question! A better question is what does “work” mean – and what gives us meaning in work – amidst a storm of turbulent exponentials. But even that question fails to fully capture what really is afoot. The deepest question is this: how will the relentless exponential advance of digital technologies reshape the global economy. There is more to this question than a mere answer. Understanding the digital forces afoot positions us to not merely foresee the next economy – it allows us to determine how to shape it in a manner that ensures that all share in its abundance.
The exponentials that so fascinate us are merely the artifacts of deeper patterns of change and innovation. Understanding the interplay between visible shifts like Moore’s Law and these deeper forces is essential to making sense of the challenges – and opportunities – that lie ahead. The good news is that one need not launch an elaborate research effort in order to look ahead; a few simple heuristics are all that is needed to quickly develop a practical first draft forecast.
Examine the uses of forecasting as well as some of the perils and pitfalls associated with long-term planning and assumptions. Learn to question your own assumptions about the way things are and to narrow down the “cone of uncertainty” found in every prediction.
In 1999, “Pace Layers” made its debut in the book The Clock of Long Now by Stewart Brand. It appeared as a deceptively simple diagram with the caption: “The order of civilization. The fast layers innovate; the slow layers stabilize. The whole combines learning with continuity.”
Prominent designers and tech company executives have cited this diagram as the catalyst for change.
Learn how Pace Layers can be used as a tool to analyze our past, present, and future.