Algorithmic Power or Punishment: Information Worker Perspectives on Passive Sensing Enabled AI Phenotyping of Performance and Wellbeing

要旨

We are witnessing an emergence in Passive Sensing enabled AI (PSAI) to provide dynamic insights for performance and wellbeing of information workers. Hybrid work paradigms have simultaneously created new opportunities for PSAI, but have also fostered anxieties of misuse and privacy intrusions within a power asymmetry. At this juncture, it is unclear if those who are sensed can find these systems acceptable. We conducted scenario-based interviews of 28 information workers to highlight their perspectives as data subjects in PSAI. We unpack their expectations using the Contextual Integrity framework of privacy and information gathering. Participants described appropriateness of PSAI based on its impact on job consequences, work-life boundaries, and preservation of flexibility. They perceived that PSAI inferences could be shared with selected stakeholders if they could negotiate the algorithmic inferences. Our findings help envision worker-centric approaches to implementing PSAI as an empowering tool in the future of work.

著者
Vedant Das Swain
Georgia Institute of Technology, Atlanta, Georgia, United States
Lan Gao
Georgia Institute of Technology, Atlanta, Georgia, United States
William A. Wood
Georgia Institute of Technology, Atlanta, Georgia, United States
Srikruthi C Matli
Georgia Institute of Technology, Atlanta, Georgia, United States
Gregory D.. Abowd
Northeastern University, Boston, Massachusetts, United States
Munmun De Choudhury
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://doi.org/10.1145/3544548.3581376

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Explainable, Responsible, Manageable AI

Hall D
6 件の発表
2023-04-26 18:00:00
2023-04-26 19:30:00