Teacher, Trainer, Counsel, Spy: How Generative AI can Bridge or Widen the Gaps in Worker-Centric Digital Phenotyping of Wellbeing
Article No.: 3, Pages 1 - 13
Abstract
The increasing integration of computing technologies in the workplace has also seen the conceptualization and development of data-driven and algorithmic tools that aim to improve workers’ wellbeing and performance. However, both research and practice have revealed several gaps in the effectiveness and deployment of these tools. Meanwhile, the recent advances in generative AI have highlighted the tremendous capabilities of large language models (LLMs) in processing large volumes of data in producing human-interactive natural language content. This paper explores the opportunities for LLMs in facilitating worker-centered design for Wellbeing Assessment Tools (WATs). In particular, we map features of LLMs against known challenges of WAT. We highlight how the LLMs can bridge or even widen the gaps in worker-centeric WAT. This paper aims to inspire new research directions focused on empowering workers and anticipating harms in integrating LLMs with workplace technologies.
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Index Terms
- Teacher, Trainer, Counsel, Spy: How Generative AI can Bridge or Widen the Gaps in Worker-Centric Digital Phenotyping of Wellbeing
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June 2024
297 pages
ISBN:9798400710179
DOI:10.1145/3663384
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CHIWORK 2024
CHIWORK 2024: Annual Symposium on Human-Computer Interaction for Work
June 25 - 27, 2024
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