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Evaluating and Designing Computing Systems for the Future of Work.
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Evaluating and Designing Computing Systems for the Future of Work.
자료유형  
 학위논문
Control Number  
0017162989
International Standard Book Number  
9798384345534
Dewey Decimal Classification Number  
621.384
Main Entry-Personal Name  
Cao, Hancheng.
Publication, Distribution, etc. (Imprint  
[S.l.] : Stanford University., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
152 p.
General Note  
Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
General Note  
Advisor: Bernstein, Michael;McFarland, Daniel.
Dissertation Note  
Thesis (Ph.D.)--Stanford University, 2024.
Summary, Etc.  
요약From collaborative software to generative AI, computing technologies are reshaping communication, collaboration, and productivity in the workplace. Yet with the growing complexities of computing platforms at the workplace, it becomes increasingly challenging to foresee their impacts on workers and organization. This can lead to not only poor user experience but also sometimes problematic applications that mirror and exacerbate societal issues. How can we better understand user behavior over workplace computing platforms? How can we build applications for better future of work that align with our needs and values with emerging computing technologies? Inspired by Herbert Simon's vision towards building the science of the artificial, this dissertation aims to shed light on these questions through the development of novel empirical measurements, technical methods, and designs for studying workplace computing systems enabled by recent advances in computing technologies. Specifically, this dissertation present three works demonstrating these approaches, including an analysis of remote meeting multitasking behavior through mining millions of online meetings, emails and file edits; the development of an AI algorithm for predicting team fractures; and a design 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.
Subject Added Entry-Topical Term  
Telemetry.
Subject Added Entry-Topical Term  
Multitasking.
Subject Added Entry-Topical Term  
Semantics.
Subject Added Entry-Topical Term  
Logic.
Added Entry-Corporate Name  
Stanford University.
Host Item Entry  
Dissertations Abstracts International. 86-03A.
Electronic Location and Access  
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Control Number  
joongbu:655420
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