Recorded 9 January 2023. Bolei Zhou of the University of California, Los Angeles, presents "From Network Dissection to Policy Dissection: Discovering Emergent Concepts in Deep Representations" at IPAM's Explainable AI for the Sciences: Towards Novel Insights Workshop. Abstract: When the deep neural networks are trained to solve a primary task, many interpretable concepts emerge inside their representations. I will talk about our series work on discovering the interpretable concepts that emerge in the deep representations trained for solving a range of tasks, from image classification, image generation, to reinforcement learning. Discovering these concepts not only reveals the inner workings of deep neural networks, but also facilitates meaningful human-AI interactions and brings new applications such as human-guided AI content creation and human-AI shared control for robotics. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/explainable-ai-for-the-sciences-towards-novel-insights/