Publication

When to explain: Field study insights on robot failure explanations for older adults

Conference Article

Conference

ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Edition

2026

Pages

584-588

Doc link

https://doi.org/10.1145/3776734.3794462

File

Download the digital copy of the doc pdf document

Abstract

Explainability has been proposed as an approach to robot failure recovery, facilitating understanding and repairing trust, especially relevant in domestic assistive tasks. This study conducts a preliminary exploration of older adults' preferences regarding the content and context of robot-generated explanations for failures to guide future research. An exploratory study was conducted in three phases: 1) gathering high-level requirements from caregivers, 2) implementing a semi-autonomous robot for object retrieval that identifies and explains different types of failures, and 3) engaging N=8 older adults in real-life interactions as well as in focus groups to assess their perspectives. Our preliminary observations highlight a tension in preferences: a general desire for short, direct explanations to minimize disruption, versus a need for more detailed, actionable explanations specifically in failure cases. Crucially, we also note that these preferences are unstable and contextually constructed, reinforcing that the technical failures cannot be separated from their social context, as users' experiences and opinions are shaped by both the robot’s functional capabilities and the values and organisational settings in which they are introduced.

Categories

social aspects of automation.

Author keywords

Explainability, Failure Explanations, Human-Robot Interaction

Scientific reference

T. Love, V. Bermejo, A. Olivares-Alarcos, A. Andriella, N. Vallès-Peris, C. Barrué and G. Alenyà. When to explain: Field study insights on robot failure explanations for older adults, 2026 ACM/IEEE International Conference on Human-Robot Interaction, 2026, Edinburgh, Scotland, UK, pp. 584-588, ACM/IEEE.