Human-AI collaboration in high-stakes decision-making: work in progress
File(s)
Published version
Author(s)
ZHOU, Jianan
Aloufi, Ranya
Porat, Talya
Van Zalk, Nejra
Type
Conference Paper
Abstract
This work in progress investigates human interaction with an LLM-powered chatbot, presented as either a fellow human or a transparently disclosed AI collaborator, in a high-stakes decision-making simulation—the NASA Moon Survival Task. We will employ a one-way between-subjects design to examine how individuals’ collaboration and communication are influenced by the identity of their partner (AI vs. human). Specifically, we will evaluate individuals’ collaboration processes (i.e., collaborative behaviour and communicative dynamics) and outcomes, alongside their retrospective interaction experience and perceptions of the partner. We will also examine dyadic-level linguistic coordination during the interaction and conduct user profiling to uncover variations in AI collaborative benefits. We anticipate that this study will have four key impacts: safeguarding human-AI collaboration, democratising AI benefits, guiding model improvement, and making methodological contributions. The anonymised dialogues and associated data will be open-sourced upon study completion.
Date Issued
2025-11-01
Date Acceptance
2025-09-02
Citation
2025, pp.465-470
Publisher
BCS Learning and Development Ltd
Start Page
465
End Page
470
Copyright Statement
© Zhou et al. Published by BCS Learning and Development Ltd. Proceedings of BCS HCI 2025, UK. This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0
License URL
Source
38th International BCS Human-Computer Interaction Conference (BCS HCI 25)
Publication Status
Published
Start Date
2025-11-09
Finish Date
2025-11-11
Coverage Spatial
Cardiff, Wales