• Speaker: Melanie Mitchell, Santa Fe Institute, USA
• Moderator: Allison Stanger, Middlebury College, USA

Abstract

Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment (“AI Spring”) and periods of disappointment, loss of confidence, and reduced funding (“AI Winter”). Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. One reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself. In this talk I will discuss some fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I will also speculate on what is needed for the grand challenge of making AI systems more robust, general, and adaptable—in short, more intelligent.

About Melanie Mitchell

Melanie Mitchell is the Davis Professor of Complexity at the Santa Fe Institute. Her current research focuses on conceptual abstraction, analogy-making, and visual recognition in artificial intelligence systems. Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her book Complexity: A Guided Tour (Oxford University Press) won the 2010 Phi Beta Kappa Science Book Award and was named by Amazon.com as one of the ten best science books of 2009. Her latest book is Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).

About Allison Stanger

Allison Stanger is 2020-21 SAGE Sara Miller McCune Fellow at the Center for Advanced Study in the Behavioral Sciences, Stanford University; Cary and Ann Maguire Chair in Ethics and American History at the Library of Congress; Russell Leng ’60 Professor of International Politics and Economics at Middlebury College, and an External Professor at the Santa Fe Institute. She is the author of Whistleblowers: Honesty in America from Washington to Trump (Chinese edition under contract) and One Nation Under Contract: The Outsourcing of American Power and the Future of Foreign Policy, both with Yale University Press. She is the co-editor (with W. Brian Arthur and Eric Beinhocker) of Complexity Economics (SFI Press). Stanger’s writing has appeared in The Atlantic, Foreign Affairs, Foreign Policy, Financial Times, International Herald Tribune, New York Times, USA Today, and the Washington Post. She has been called to testify before Congress on five occasions and is a life member of the Council on Foreign Relations. Stanger received her Ph.D. in Political Science from Harvard University.

Online Event

We are looking forward to seeing you:

• Participate via Zoom (meeting: 9638 9928 143, password: 0dzqxqiy).
• The talk will also be live streamed and recorded on our YouTube Channel.
• For further announcements and information, please visit the DIGHUM Website, which also provides slides and recordings of all our past events.

The DIGHUM Lecture Series

Digital Humanism deals with the complex relationship between man and machine. It acknowledges the potential of Informatics and IT. At the same time, it points to related apparent threats such as privacy violations, ethical concerns with AI, automation, and loss of jobs, and the ongoing monopolization on the Web. The Corona crisis has shown these two faces of the accelerated digitalization—we are in a crucial moment in time.

For this reason, we started the DIGHUM Lecture Series, a new initiative with regular online events to discuss the different aspects of Digital Humanism. We will have a speaker on a specific topic (30 minutes) followed by a discussion of 30 minutes every second Tuesday of each month at 5:00 PM CEST. This crisis seriously affects our mobility, but it also offers the possibility to participate in events from all over the world—let’s take this chance to meet virtually.

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