Stanford Seminar - Evaluating and Designing Computing Systems for the Future of Work | Stanford Online

The podcast explores the speaker's PhD work on evaluating and designing computing systems for the future of work, questioning whether current technologies have created an ideal workplace. It highlights three projects influenced by Simon's vision of studying computing technologies as a science of the artificial. The first project analyzes multitasking behavior during remote meetings using data from Microsoft Teams, finding correlations between meeting characteristics and multitasking. The second uses AI and NLP to classify team viability based on chat interactions, identifying behavioral traits associated with high-viability teams. The third examines the use of large language models to provide scientific feedback on research papers, comparing AI-generated feedback with human reviews. The speaker also touches on ongoing work quantifying AI usage effects and building AI-based team communication intervention tools.

Outlines

Part 1: Introduction, Theoretical Framework

Part 2: Remote Meeting Analysis

Part 3: AI for Team Collaboration

Part 4: Generative AI for Research Feedback

Part 5: Future Outlook, Q&A

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Stanford Seminar - Evaluating and Designing Computing Systems for the Future of Work

Stanford Online

Part 1: Introduction, Theoretical Framework

The Evolution of Workplace Technology: From Arthur Mee's Vision to Modern AI

Studying Computing Technologies as a Science of the Artificial: Simon's Vision

PhD Research Overview: Empirical Evidence, Technical Methods, and Design in Workplace Technologies

Part 2: Remote Meeting Analysis

Three Projects Overview: Remote Meeting Analysis, AI for Team Collaboration, and Generative AI for Research Feedback

Large-Scale Analysis of Multitasking Behavior During Remote Meetings

Intrinsic and Extrinsic Factors Influencing Multitasking in Remote Meetings

Best Practices and Public Impact of the Multitasking Study

Part 3: AI for Team Collaboration

AI and Natural Language Processing for Understanding Team Collaboration

Classifying Team Viability Using Team Chat Interactions

Interaction Features and Classification Results for Team Viability

Behavioral Traits and Early Prediction of Team Viability

Implications and Limitations of the Team Viability Study

Part 4: Generative AI for Research Feedback

Using Large Language Models to Provide Scientific Feedback for Research Papers

Prototyping and Evaluating a Large Language Model Tool for Scientific Feedback

Retrospective Evaluation: Overlap Between AI and Human-Generated Feedback

User Study Results and the Role of AI in Scientific Feedback

Part 5: Future Outlook, Q&A

Ongoing and Future Work: AI's Implications for the Future of Work

Human-AI Interaction Guidelines and Acknowledgments

Q&A: AI-Generated Feedback, Perception of Helpfulness, and Team Liability

Stanford Seminar - Evaluating and Designing Computing Systems for the Future of Work

Stanford Online

Part 1: Introduction, Theoretical Framework

00:09The Evolution of Workplace Technology: From Arthur Mee's Vision to Modern AI

The Evolution of Workplace Technology: From Arthur Mee's Vision to Modern AI

02:07Studying Computing Technologies as a Science of the Artificial: Simon's Vision

Studying Computing Technologies as a Science of the Artificial: Simon's Vision

05:08PhD Research Overview: Empirical Evidence, Technical Methods, and Design in Workplace Technologies

PhD Research Overview: Empirical Evidence, Technical Methods, and Design in Workplace Technologies

Part 2: Remote Meeting Analysis

07:57Three Projects Overview: Remote Meeting Analysis, AI for Team Collaboration, and Generative AI for Research Feedback

Three Projects Overview: Remote Meeting Analysis, AI for Team Collaboration, and Generative AI for Research Feedback

10:36Large-Scale Analysis of Multitasking Behavior During Remote Meetings

Large-Scale Analysis of Multitasking Behavior During Remote Meetings

14:10Intrinsic and Extrinsic Factors Influencing Multitasking in Remote Meetings

Intrinsic and Extrinsic Factors Influencing Multitasking in Remote Meetings

17:55Best Practices and Public Impact of the Multitasking Study

Best Practices and Public Impact of the Multitasking Study

Part 3: AI for Team Collaboration

19:38AI and Natural Language Processing for Understanding Team Collaboration

AI and Natural Language Processing for Understanding Team Collaboration

22:05Classifying Team Viability Using Team Chat Interactions

Classifying Team Viability Using Team Chat Interactions

25:09Interaction Features and Classification Results for Team Viability

Interaction Features and Classification Results for Team Viability

27:00Behavioral Traits and Early Prediction of Team Viability

Behavioral Traits and Early Prediction of Team Viability

29:58Implications and Limitations of the Team Viability Study

Implications and Limitations of the Team Viability Study

Part 4: Generative AI for Research Feedback

31:20Using Large Language Models to Provide Scientific Feedback for Research Papers

Using Large Language Models to Provide Scientific Feedback for Research Papers

34:05Prototyping and Evaluating a Large Language Model Tool for Scientific Feedback

Prototyping and Evaluating a Large Language Model Tool for Scientific Feedback

37:34Retrospective Evaluation: Overlap Between AI and Human-Generated Feedback

Retrospective Evaluation: Overlap Between AI and Human-Generated Feedback

40:29User Study Results and the Role of AI in Scientific Feedback

User Study Results and the Role of AI in Scientific Feedback

Part 5: Future Outlook, Q&A

42:34Ongoing and Future Work: AI's Implications for the Future of Work

Ongoing and Future Work: AI's Implications for the Future of Work

45:58Human-AI Interaction Guidelines and Acknowledgments

Human-AI Interaction Guidelines and Acknowledgments

51:28Q&A: AI-Generated Feedback, Perception of Helpfulness, and Team Liability

Q&A: AI-Generated Feedback, Perception of Helpfulness, and Team Liability