Are machines getting smarter than us? With greater computational power and ever more sophisticated artificial intelligence comes a whole new way of understanding the world. Now that our machines are capable of analysing data from so many different sources, taking into consideration countless variables and possibilities, it is becoming increasingly difficult for humans to understand how they come to their conclusions. How will we cope when machines understand the world better than us, and make better decisions than we can?

We’ve always been engaged in the pursuit of knowledge, believing that studying the world will lead to us a better understanding of how it works, so will we be happy to not ‘know’? This signifies a change in our basic model of the future, representing a shift away from simple cause-and-effect models to larger, more complex models.

As the guest in this Live Show puts it, “The world didn’t happen to be designed, by God or by coincidence, to be knowable by human brains. The nature of the world is closer to the way our network of computers and sensors represent it than how the human mind perceives it.” Join us to hear more from David Weinberger about how the nature of knowledge has shifted, and what we should do about it.


Speaker(s)

David Weinburger

Academic, Harvard University

David Weinberger, Ph.D., writes about the effect of the Internet on ideas. He is a senior researcher  at Harvard's Berkman Klein Center for Internet & Society and was recently co-director of the Harvard Library Innovation Lab, and a journalism fellow at Harvard's Shorenstein Center. His most recent book, "Too Big to Know," looks at the networking of knowledge and expertise. He is a co-author of "The Cluetrain Manifesto" and is the author of "Small Pieces Loosely Joined" and "Everything Is Miscellaneous."  Dr. Weinberger has been a marketing VP and adviser to high tech companies, an adviser to several presidential campaigns, and a Franklin Fellow at the U.S. State Department. He has a doctorate in philosophy from the University of Toronto.


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