Yes, this.
An interview with Douglas Guilbeault, Assistant Professor in Organizational Behavior at Stanford University's Graduate School of Business. We explore how AI and large language models might teach us about our own collective humanity, drawing connections between the engineered and algorithmic world and the complex, cultural, and living. Douglas uses computational social science to study social structures, with fascinating implications for everything from content moderation to climate policy to the spread of behaviors like mask-wearing during COVID. What if LLMs weren't replacements for human intelligence, but instead portals into our collective cultural knowledge that depends on our continued creativity and agency? Episode Outline Bridging humanities, sciences, and computational methods [6:00 - 13:55] Computational Social Science and Meaning [14:00 - 22:05] Research methodologies and applications for understanding meaning in digital age [22:05 - 27:00] Case studies on group size, gender, and macro distortions [27:00 - 33:45] Content moderation and policy implications [33:45 - 47:45] Collective Intelligence [47:45 - 55:00] Complex Contagions [55:00 - 1:07:40] LLMs as Cultural Technologies [01:07:40 - 01:20:35] Optimistic Perspective on AI [01:20:35 - 01:25:35] Scientific discovery revealing greater complexity [01:25:35 - 01:32:45] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit yesthis.substack.com [https://yesthis.substack.com?utm_medium=podcast&utm_campaign=CTA_1]
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