Conference Paper/Proceeding/Abstract 80 views
Designing Bias Suppressing Robots for `fair' Robot moderated Human-Human Interactions.
,
Matt Roach ,
Muneeb Ahmad
Proceedings of the 12th International Conference on Human-Agent Interaction, Pages: 347 - 349
Swansea University Authors:
Peter Daish, Matt Roach , Muneeb Ahmad
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DOI (Published version): 10.1145/3687272.3690877
Abstract
Research has shown that data-driven robots deployed in social settings are likely to unconsciously perpetuate systemic social biases. Despite this, robots can also be deployed to promote fair behaviour in humans. These phenomena have led to the development of two broad sub-disciplines in HRI concern...
| Published in: | Proceedings of the 12th International Conference on Human-Agent Interaction |
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| ISBN: | 979-8-4007-1178-7 979-8-4007-1178-7 |
| Published: |
New York, NY, USA
ACM
2024
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68340 |
| Abstract: |
Research has shown that data-driven robots deployed in social settings are likely to unconsciously perpetuate systemic social biases. Despite this, robots can also be deployed to promote fair behaviour in humans. These phenomena have led to the development of two broad sub-disciplines in HRI concerning ‘fairness’: a data-centric approach to ensuring robots operate fairly and a human-centric approach which aims to use robots as interventions to promote fairness in society. To date, these two fields have developed independently, thus it is unknown how data-driven robots can be used to suppress biases in human-human interactions. In this paper, we present a conceptual framework and hypothetical example of how robots might deploy data-driven fairness interventions, to actively suppress social biases in human-human interactions. |
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| Item Description: |
Poster |
| College: |
Faculty of Science and Engineering |
| Start Page: |
347 |
| End Page: |
349 |