Designing Bias Suppressing Robots for `fair' Robot moderated Human-Human Interactions.
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.
Authors
- Muneeb Ahmad
- Takayuki Kanda (ORCID: https://orcid.org/0000-0002-9546-5825)
- Matthew Roach (ORCID: https://orcid.org/0000-0002-1486-5537)
- Peter Daish (ORCID: https://orcid.org/0009-0006-6812-1791)
Institutions
- Kyoto University (JP)
- Swansea University (GB)
Publication Details
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1145/3687272.3690877
- Citations
- 1
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.53