Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions
Giulio Antonio Abbo and Tony BelpaemeTL;DR
An overview of my research so far, starting with the focus group, the work on LLM’s alignment and VLM’s alignment, embodied awareness and using VLMs for improved contextual awareness.
PUBLICATIONS IN THIS RESEARCH LINE
VALAWAI
Abstract
Developing value-aware social robots is crucial to improve human-robot interactions, as current designs often lack sensitivity to users’ diverse values, impacting inclusivity and user experience. By integrating value-aware mechanisms, robots could adapt to contextual cues like cultural or ethical norms. Our research proposes to implement a value-aware architecture inspired by the global neuronal workspace theory, using the Robot Operating System as the supporting framework, powered by large language models for real-time understanding of user preferences and common ground. Mitigating the models’ bias to ensure cultural inclusivity is a key priority. The research carried out so far includes focus groups, a scoping review, and an assessment of the value alignment of several large language models and vision language models. The main challenges are understanding how to model and learn human values, and how to shape the robot’s behaviour accordingly. The evaluation will rely on user studies, with a focus on users’ experience and inclusivity, aiming to enhance the relevance and sensitivity of social robots for diverse users in everyday interactions.
ACM Reference
Giulio Antonio Abbo and Tony Belpaeme. 2025. Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions. In Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction (HRI '25). IEEE Press, 1826–1828.BibTeX
@inproceedings{10.5555/3721488.3721783,
author = {Abbo, Giulio Antonio and Belpaeme, Tony},
title = {Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions},
year = {2025},
publisher = {IEEE Press},
abstract = {Developing value-aware social robots is crucial to improve human-robot interactions, as current designs often lack sensitivity to users' diverse values, impacting inclusivity and user experience. By integrating value-aware mechanisms, robots could adapt to contextual cues like cultural or ethical norms. Our research proposes to implement a value-aware architecture inspired by the global neuronal workspace theory, using the Robot Operating System as the supporting framework, powered by large language models for real-time understanding of user preferences and common ground. Mitigating the models' bias to ensure cultural inclusivity is a key priority. The research carried out so far includes focus groups, a scoping review, and an assessment of the value alignment of several large language models and vision language models. The main challenges are understanding how to model and learn human values, and how to shape the robot's behaviour accordingly. The evaluation will rely on user studies, with a focus on users' experience and inclusivity, aiming to enhance the relevance and sensitivity of social robots for diverse users in everyday interactions.},
booktitle = {Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction},
pages = {1826–1828},
numpages = {3},
keywords = {awareness, dehaene-changeux model, ethic, global neuronal workspace, large language model, ros},
location = {Melbourne, Australia},
series = {HRI '25}
}