The Stuff of Forecasting

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Topics: Education Policy, ESSA, Future of Learning

A colleague likes to joke that forecasting is akin to sausage making: the end products are great, but he doesn’t necessarily need to see the full process. With KnowledgeWorks’ fourth full forecast on the future of learning coming out this fall, Jason Swanson and I have begun rolling up our sleeves to do the messy work of looking ahead ten years and imagining what the emerging landscape might mean for education.

At a work session with collaborator Andrea Saveri earlier this month, we began solidifying our list of big shifts outside education that could change not just how people approach learning, but also the reasons why and the purposes for which people pursue it. The changes on the horizon look really big this time: the fundamental substrate of the economy appears to be changing in ways that could shift education’s very foundations. We titled our last forecast Recombinant Education. Now it looks as if we could be moving toward a recombinant society in which many of our traditional structures and interrelationships are taking multiple new forms as a result of exponential changes in technology and society, not the least of which is the changing nature of work.

Right after sketching out our initial understanding of what that might mean for learning, Jason and I used Uber to get a ride across San Francisco to attend the Institute for the Future’s ten-year forecast retreat. IFTF’s 2015 forecast “explore[s] the different platforms that might transform our corporate and consumer economies, build new creative, collaborative, and civil economies, and even disrupt the global economy of crime.” It points toward new ways of defining and pursuing value, of connecting resources to achieve our ends and exploring the interstices between them. Networked structures continue to seem like a salient feature of the future, while automation promises to come ever more to the fore.

As with Uber’s matching of passenger need with driver availability, application programming interfaces (APIs) are playing a role in executing more and more activities. Robots are increasingly serving as partners not just in manufacturing but also in less likely sectors such as healthcare and food services.  New encryption technologies such as blockchain are enabling new models for handling secure financial and legal transactions and could eventually impact some learning transactions and data flows. I’m still trying to get my head around the rationale behind distributed autonomous corporations even as I find myself intrigued by how expanding insight into microbiomes might affect human health and food systems.

While our forecasts take into account far more than technology and science, such developments underscore our sense that the changes on the horizon could be foundational this time. The next decade could see us forming new kinds of partnerships with machines, pursuing new transactional models, and navigating uncertain landscapes. We’re working on forecasting what such changes might mean for people, organizational structures, and cultures and will look forward to sharing more as our next forecast continues to unfold.  We’ll try to share the good bits without revealing too much of the mess!