Critical Incident Technique and Gig-Economy Work (Deliveroo) : Working with and Challenging Assumptions around Algorithms

Lord, Carolynne and Bates, Oliver and Friday, Adrian (2022) Critical Incident Technique and Gig-Economy Work (Deliveroo) : Working with and Challenging Assumptions around Algorithms. In: CHI 2022 - Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems :. Conference on Human Factors in Computing Systems - Proceedings . ACM, New York, 258:1-258:6. ISBN 9781450391566

Abstract

Decision-making algorithms can be obscure and fast-moving. This is especially the case in the context of the algorithm that mediates the work of Deliveroo riders. Forming a critical part of the food delivery platform, the algorithm’s obscurity and shifting nature is a part of its design. In this paper, we argue that adapting usability techniques like the Critical Incident Technique (CIT) may provide one way to better understand algorithms and platform work. Though there are many methods to understand algorithms like this, asking people about negative or positive interactions with them and what they think provoked them can produce fruitful avenues for HCI research into the impacts of platforms on gig-economy work. We argue that despite the results being an assumption, assumptions from the algorithmically managed are interesting materials to challenge the researchers’ own assumptions about their context, and to, therefore, better scope out contexts and iterate future research.