AI is evolving from models to systems to agents—autonomous entities that act, adapt, and collaborate. As intelligence emerges from interactions, the future of AI depends on context, trust, and workflow integration. How we design social AI today will shape its role in amplifying human intelligence.
A lecture by Michael Levin, distinguished professor of biology at Tufts University and associate at Harvard's Wyss Institute
Preparatory material for our workshop on using generative AI for decision-making, generated by NotebookLM.
We talked with Steven Sloman, Professor of Cognitive, Linguistic and Psychological Sciences at Brown University who, along with Philip Fernbach, popularized this idea in a book called the Knowledge Illusion.
On a scale of 1 to 10, rate how well you understand how a toilet works. Now, take a moment to explain how it works. Now, after you’ve tried to explain it, does your rating of how well you understand change?
If you’re like most people, the act of trying to explain will highlight that you don’t understand it as well as you thought you did. This is called the Knowledge Illusion and it’s where we feel we know more than we do because we get our knowledge from our community—both human and machine.
What’s so interesting about this illusion is that it says so much about how we should approach others and it also says a lot about how we should approach having our knowledge inside of machines.
We talked with Steven Sloman, Professor of Cognitive, Linguistic and Psychological Sciences at Brown University who, along with Philip Fernbach, popularized this idea in a book called the Knowledge Illusion. How does a conscious recognition of our knowledge being derived from our community affect our experience in the world?
Writing and Conversations About AI (Not Written by AI)
