Sensible and Sensitive AI for Worker Wellbeing: Factors Informing Adoption and Resistance

Offered By: Association for Computing Machinery (ACM) via YouTube

Course Description

Overview

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Explore a 15-minute conference talk from CHI 2024 examining the factors influencing adoption and resistance of Passive Sensing-enabled AI (PSAI) systems for worker wellbeing. Delve into the research findings on system components that maximize value and mitigate concerns in algorithmic estimations of worker behavior. Learn about the interactive online survey using the Experimental Vignette Method and the Linear Mixed-effects Models analysis. Discover insights on worker preferences for sensing digital time use and physical activity over visual modes, the acceptability of language-based inferences in work-restricted contexts, and the preference for mental wellbeing insights over performance metrics. Understand the implications for designing more worker-centered PSAI systems and reflect on existing implementations.

Syllabus

Sensible and Sensitive AI for Worker Wellbeing: Factors that Inform Adoption and Resistance for I...

Taught by

ACM SIGCHI

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