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An Exploratory Qualitative Investigation: Multi-modal AI Technology Concepts for Non-verbal Feedback During Remote Work Meetings

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HCI International 2022 Posters (HCII 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1580))

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Abstract

Prior research has shown that computer-mediated communication introduces barriers to effective non-verbal communication. This creates potential challenges as workers increasingly collaborate remotely in a post-pandemic world. To further investigate these barriers, we conducted an exploratory study with five remote workers featuring qualitative user testing of concepts designed to facilitate non-verbal feedback using multi-modal AI technologies. Prior to the study, a team of UX designers created low-fidelity concept prototypes using different variables important for participant feedback (that is, modality, type, user control, visibility, granularity, timing, and categories). Using these prototypes, we conducted semi-structured interviews (90-min long) with scenario-based questions. The results showed that the participants perceived the prototypes for multi-modal feedback positively, especially for the multi-tasking scenarios. However, this perception differed based on different roles: Presenters versus listeners. In general, the participants indicated that the presenters would be more interested in feedback than the listeners, as long as that feedback was uncluttered and actionable. By contrast, when commenting as listeners (that is, as individuals whose feedback would be monitored), the participants expressed concerns over the accuracy of AI models, a sense of being monitored (privacy concerns), and potential social risks to provide uncomfortable feedback. As a future work, we plan to iterate on the current prototypes to address these concerns, and deploy a larger study with refined and more functional prototypes.

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Acknowledgements

We would like to thank the Remote Collaboration project team at Intel Labs for their support in undertaking this study while in the middle of a pandemic. We dedicate this paper to the memory of our beloved colleague, Suzanne Thomas, whose research leadership and collegiality inspired and informed us during this project.

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Correspondence to Sinem Aslan .

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Aslan, S., Chierichetti, R., Sherry, J., Nachman, L. (2022). An Exploratory Qualitative Investigation: Multi-modal AI Technology Concepts for Non-verbal Feedback During Remote Work Meetings. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1580. Springer, Cham. https://doi.org/10.1007/978-3-031-06417-3_53

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  • DOI: https://doi.org/10.1007/978-3-031-06417-3_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06416-6

  • Online ISBN: 978-3-031-06417-3

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