Abstract

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 experiences but also problematic applications that mirror and amplify societal issues. How can we better understand machine behavior and machine-mediated user behavior across computing platforms? How can we build applications that align with our needs and values using emerging computing technologies? My research aims to answer these questions by developing novel empirical measurements, technical methods, and designs. In this talk, I will present my work demonstrating this approach in the context of the future of work, where I have established data-driven, AI-powered, and human-centered methods to understand, evaluate, and design computing systems in the workplace. I will present an analysis of remote meeting experiences through mining millions of meetings, a study on how an AI algorithm can be built to predict team fractures, and a development and evaluation study on a generative AI-based scientific feedback system for researchers. These projects exemplify the opportunities to leverage computation to better understand, support, and augment work practices.

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Recording