Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions

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.

Authors

Institutions

Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/hri61500.2025.10974149
Citations
1
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions

Giulio Antonio Abbo, Tony Belpaeme
1 citations
Reinforcement Learning in Robotics
2.48
article

Values in Social Robots: Implementing Inclusive, Value-Aware Human-Robot Interactions

Giulio Antonio Abbo, Tony Belpaeme
article en
1 citations

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.

Ghent University (BE)
Reduced inequalities
Openalex Percentile: Top 11%
Reinforcement Learning in Robotics
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.