Machine Learning Security as a Source of Unfairness in Human-Robot Interaction
| dc.contributor.author | Richards, Luke E. | |
| dc.contributor.author | Matuszek, Cynthia | |
| dc.date.accessioned | 2023-05-25T18:58:21Z | |
| dc.date.available | 2023-05-25T18:58:21Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Machine learning models that sense human speech, body placement, and other key features are commonplace in human-robot interaction. However, the deployment of such models in themselves is not without risk. Research in the security of machine learning examines how such models can be exploited and the risks associated with these exploits. Unfortunately, the threat models of risks produced by machine learning security do not incorporate the rich sociotechnical underpinnings of the defenses they propose; as a result, efforts to improve the security of machine learning models may actually increase the difference in performance across different demographic groups, yielding systems that have risk mitigation that work better for one group than another. In this work, we outline why current approaches to machine learning security present DEI concerns for the human-robot interaction community and where there are open areas for collaboration. | en_US |
| dc.description.uri | https://iral.cs.umbc.edu/Pubs/Richards2023DEIHRI.pdf | en_US |
| dc.format.extent | 3 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m2pwsu-fxeu | |
| dc.identifier.uri | http://hdl.handle.net/11603/28085 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
| dc.subject | UMBC Interactive Robotics and Language Lab | |
| dc.title | Machine Learning Security as a Source of Unfairness in Human-Robot Interaction | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0001-5744-8736 | en_US |
| dcterms.creator | https://orcid.org/0000-0003-1383-8120 | en_US |