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Evaluating and Designing Computing Systems for the Future of Work.
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
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:655420