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We are hosting an EnCORE workshop on Old Questions and New Directions in Theory of Clustering at UCSD from March 4th to 6th, 2024. While in person registration is closed […]
From collaborative software to generative AI, computing technologies are redefining the way we work, communicate and collaborate. Yet with the growing complexities of computing platforms, it becomes increasingly challenging to foresee their impacts on human behavior, leading to not only poor user experience but also problematic applications that mirror and amplify societal issues. How can we better understand machine behavior and machine-mediated user behavior over computing platforms? How can we build applications that align with our needs and values with emerging computing technologies? My research aims to answer these questions through novel measurements and computational methods inspired by social science insights, such as mining increasingly available large-scale data on how people build, adopt, and interact with computing systems. In this talk, I will present my work demonstrating this approach in the future of work context, where I develop data-driven, AI-powered and human-centered methods to understand, evaluate and design sociotechnical systems at the workplace. I will present an analysis of remote meeting experience through mining millions of meetings, a study on how an AI algorithm can be built to predict team fracture, and a development and evaluation study on a generative AI-based scientific feedback system for researchers. These projects exemplify the opportunities to leverage computation and data to better understand, support and augment work practices.
The Institute for Practical Ethics welcomes David Danks as the 2024 keynote speaker.
Danks, a UC San Diego professor in the Department of Philosophy and Halıcıoğlu Data Science Institute, is an expert researcher at the intersection of philosophy, cognitive science and machine learning. He serves on multiple boards, including the United States National AI Advisory Committee.
Artificial intelligence is seemingly everywhere today, both in public perception and in our everyday lives. This growth has led to many stories about the widespread harms that can result from AI done poorly. As a result, there are now numerous demands for ‘ethical AI,’ but relatively little understanding of what that might involve.
In this keynote, David Danks will explore the nature of responsible AI, arguing that it involves much more than code or data. He will critically assess current approaches to producing more responsible AI, then suggest key policy and practical approaches that would likely be more effective. It is critical we create more responsible AI, but that will require rethinking many of our current practices in academia, government and industry.
The Ethics and Early Career Committee would like to invite you to our upcoming webinar on AI Ethics in Research. This will take place virtually through Zoom on Friday, March 8th at […]
Talk info: to be provided
Adam is a postdoctoral scholar at Stanford University, working with Leonidas Guibas. He received a Ph.D. in robotics from Carnegie Mellon University, where he worked with Katerina Fragkiadaki. He received his M.S. in Computer Science at Toronto Metropolitan University, working with Kosta Derpanis. Adam is a recipient of the NSERC PGS-D scholarship, and the Toronto Metropolitan University Gold Medal. His research interests lie in Computer Vision and Machine Learning, particularly for 3D understanding and fine-grained tracking.
Talk Abstract: Although incorporating causal concepts into deep learning shows promise for increasing explainability, fairness, and robustness, existing methods require unrealistic assumptions and aim to recover the full latent causal […]
Roy Fox, Assistant Professor and Director of the Intelligent Dynamics Lab at UC Irvine HDSI 123 and Zoom (Link below) Abstract: If learning from data is valuable, can learning from big […]