Print Email Facebook Twitter Fast Drink Title Fast Drink: Mediating Empathy for Gig Workers Author Meijer, Wo (TU Delft Internet of Things) Verhoeff, Bent (Student TU Delft) Verma, H. (TU Delft Human-Centred Artificial Intelligence) Bourgeois, Jacky (TU Delft Internet of Things) Date 2023 Abstract The digitization of services and global lock-downs have led an explosion of delivery services, which use gig-workers as delivery personnel. They can face apathy from both their employers and users of the service. Previous studies focused on mediating interactions between workers or workers and tasks. However, delivery presents the opportunity for HCI interventions to mediate the interaction between worker and users to increase their empathy. We conducted an empirical study where 63 participants ordered a drink with an app which presented a different level of information about the delivery person (nothing; name and photo; heart rate). Initial results show no significant impact on empathy measures between conditions, however post-hoc analysis showed that heart rate lead to increased Compassionate and decreased Affective empathy. This raises the question of what "type"of empathy is beneficial for delivery personnel and the need to refine the concept and measures of empathy used in HCI. Subject biosignalsempathygig-work To reference this document use: http://resolver.tudelft.nl/uuid:87b4d744-1bd2-4520-8b7d-91f88d9ce764 DOI https://doi.org/10.1145/3588967.3588975 Publisher Association for Computing Machinery (ACM) ISBN 979-8-4007-0749-0 Source Proceedings of the 2nd Empathy-Centric Design Workshop, EmpathiCH 2023 - Collocated with ACM CHI Conference on Human Factors in Computing Systems Event 2nd Empathy-Centric Design Workshop, EmpathiCH 2023, 2023-04-23, Hamburg, Germany Series ACM International Conference Proceeding Series Part of collection Institutional Repository Document type conference paper Rights © 2023 Wo Meijer, Bent Verhoeff, H. Verma, Jacky Bourgeois Files PDF 3588967.3588975.pdf 1.01 MB Close viewer /islandora/object/uuid:87b4d744-1bd2-4520-8b7d-91f88d9ce764/datastream/OBJ/view