Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational Stakeholders

Author:

Kawakami Anna1ORCID,Chowdhary Shreya2ORCID,Iqbal Shamsi T.3ORCID,Liao Q. Vera4ORCID,Olteanu Alexandra5ORCID,Suh Jina3ORCID,Saha Koustuv6ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. University of Michigan, Ann Arbor, USA

3. Microsoft Research, Redmond, WA, USA

4. Microsoft Research, Montreal, Canada

5. Microsoft Research, NY, NY, USA

6. University of Illinois Urbana-Champaign, Champaign, IL, Canada

Abstract

With the heightened digitization of the workplace, alongside the rise of remote and hybrid work prompted by the pandemic, there is growing corporate interest in using passive sensing technologies for workplace wellbeing. Existing research on these technologies often focus on understanding or improving interactions between an individual user and the technology. Workplace settings can, however, introduce a range of complexities that challenge the potential impact and in-practice desirability of wellbeing sensing technologies. Today, there is an inadequate empirical understanding of how everyday workers---including those who are impacted by, and impact the deployment of workplace technologies--envision its broader socio-ecological impacts. In this study, we conduct storyboard-driven interviews with 33 participants across three stakeholder groups: organizational governors, AI builders, and worker data subjects. Overall, our findings surface how workers envisioned wellbeing sensing technologies may lead to cascading impacts on their broader organizational culture, interpersonal relationships with colleagues, and individual day-to-day lives. Participants anticipated harms arising from ambiguity and misalignment around scaled notions of "worker wellbeing,'' underlying technical limitations to workplace-situated sensing, and assumptions regarding how social structures and relationships may shape the impacts and use of these technologies. Based on our findings, we discuss implications for designing worker-centered data-driven wellbeing technologies.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Teacher, Trainer, Counsel, Spy: How Generative AI can Bridge or Widen the Gaps in Worker-Centric Digital Phenotyping of Wellbeing;Proceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for Work;2024-06-25

2. Design Fiction on Capturing, Amplifying, and Instilling Happiness in Work;Proceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for Work;2024-06-25

3. Investigating Emotional Intelligence and Employees' Well-Being in an AI-Enhanced Workplace;International Journal of Management and Humanities;2024-05-30

4. Observer Effect in Social Media Use;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

5. Improving Work-Nonwork Balance with Data-Driven Implementation Intention and Mental Contrasting;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

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