David Bau on How—and Whether—Artificial Intelligence Thinks

Yascha Mounk and David Bau delve into the emerging science of AI interpretability and what we can learn from billions of neural signals. David Bau is Assistant Professor at Northeastern University and Director of the National Deep Inference Fabric, researching the emergent internal mechanisms of deep generative networks in both Natural Language Processing and Computer Vision. In this week’s conversation, Yascha Mounk and David Bau discuss how AI models actually produce their results and reflect about problems, whether the “thinking” process that models show users reveals their authentic thought processes, and how researchers can decode the internal representations of neural networks to understand what information they contain and use. If you have not yet signed up for our podcast, please do so now by following ⁠this link on your phone⁠. Email: leonora.barclay@persuasion.community Podcast production by Jack Shields and Leonora Barclay. Connect with us! ⁠Spotify⁠ | ⁠Apple⁠ X: ⁠@Yascha_Mounk⁠ & ⁠@JoinPersuasion⁠ YouTube: ⁠Yascha Mounk⁠, ⁠Persuasion⁠ LinkedIn: ⁠Persuasion Community Learn more about your ad choices. Visit megaphone.fm/adchoices