Publikationen

2023[ to top ]

Reducing Racial Bias by Interacting with Virtual Agents: An Intervention in Virtual Reality. Obremski, David; Akuffo, Ohenewa Bediako; Lücke, Leonie; Semineth, Miriam; Tomiczek, Sarah; Weichert, Hanna-Finja; Lugrin, Birgit. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, of AAMAS ’23, pp. 747–755. International Foundation for Autonomous Agents and Multiagent Systems, London, United Kingdom, 2023.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ DOI ]
Racial bias, implicit or explicit, is still a widespread phenomenon in our modern society, negatively affecting the way we interact with foreigners. These biases can also lead to the general tendency to avoid encounters with foreigners, which has a critical impact on society as a whole. This paper presents an approach to reduce implicit and explicit racial bias using two Intelligent Virtual Agents (IVAs) in Virtual Reality (VR). Based on previous research from social psychology and the field of enculturated IVAs, a sympathetic East African-German mixed-cultural IVA, and an antipathetic German mono-cultural IVA were implemented to interact with the participants in a virtual pub quiz. Pre- and post-intervention measures of participants' implicit and explicit bias showed a significant decrease in both scores. This work demonstrates the capability of enculturated IVAs to reduce real-world racial biases and sets the base for cultural interventions with IVAs.

@inproceedings{obremski2023AAMAS, abstract = {Racial bias, implicit or explicit, is still a widespread phenomenon in our modern society, negatively affecting the way we interact with foreigners. These biases can also lead to the general tendency to avoid encounters with foreigners, which has a critical impact on society as a whole. This paper presents an approach to reduce implicit and explicit racial bias using two Intelligent Virtual Agents (IVAs) in Virtual Reality (VR). Based on previous research from social psychology and the field of enculturated IVAs, a sympathetic East African-German mixed-cultural IVA, and an antipathetic German mono-cultural IVA were implemented to interact with the participants in a virtual pub quiz. Pre- and post-intervention measures of participants' implicit and explicit bias showed a significant decrease in both scores. This work demonstrates the capability of enculturated IVAs to reduce real-world racial biases and sets the base for cultural interventions with IVAs.}, address = {Richland, SC}, author = {Obremski, David and Akuffo, Ohenewa Bediako and Lücke, Leonie and Semineth, Miriam and Tomiczek, Sarah and Weichert, Hanna-Finja and Lugrin, Birgit}, booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems}, keywords = {mi}, pages = {747–755}, publisher = {International Foundation for Autonomous Agents and Multiagent Systems}, series = {AAMAS '23}, title = {Reducing Racial Bias by Interacting with Virtual Agents: An Intervention in Virtual Reality}, year = 2023 }

%0 Conference Paper %1 obremski2023AAMAS %A Obremski, David %A Akuffo, Ohenewa Bediako %A Lücke, Leonie %A Semineth, Miriam %A Tomiczek, Sarah %A Weichert, Hanna-Finja %A Lugrin, Birgit %B Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems %C Richland, SC %D 2023 %I International Foundation for Autonomous Agents and Multiagent Systems %P 747–755 %R 10.5555/3545946.3598707 %T Reducing Racial Bias by Interacting with Virtual Agents: An Intervention in Virtual Reality %X Racial bias, implicit or explicit, is still a widespread phenomenon in our modern society, negatively affecting the way we interact with foreigners. These biases can also lead to the general tendency to avoid encounters with foreigners, which has a critical impact on society as a whole. This paper presents an approach to reduce implicit and explicit racial bias using two Intelligent Virtual Agents (IVAs) in Virtual Reality (VR). Based on previous research from social psychology and the field of enculturated IVAs, a sympathetic East African-German mixed-cultural IVA, and an antipathetic German mono-cultural IVA were implemented to interact with the participants in a virtual pub quiz. Pre- and post-intervention measures of participants' implicit and explicit bias showed a significant decrease in both scores. This work demonstrates the capability of enculturated IVAs to reduce real-world racial biases and sets the base for cultural interventions with IVAs. %@ 9781450394321

2021[ to top ]

Anthropomorphize me! - Effects of Robot Gender on Listeners’ Perception of the Social Robot NAO in a Storytelling Use Case. Steinhaeusser, Sophia C.; Schaper, Philipp; Akuffo, Ohenewa Bediako; Friedrich, Paula; Ön, Jülide; Lugrin, Birgit. In Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2021), C. Bethel, A. Paiva, E. Broadbent, D. Feil-Seifer, D. Szafir (eds.). ACM, 2021.
- [ BibTeX ]
- [ EndNote ]
- [ URL ]
- [ DOI ]
@inproceedings{Steinhaeusser_2021, author = {Steinhaeusser, Sophia C. and Schaper, Philipp and Akuffo, Ohenewa Bediako and Friedrich, Paula and Ön, Jülide and Lugrin, Birgit}, booktitle = {Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2021)}, editor = {Bethel, Cindy and Paiva, Ana and Broadbent, Elizabeth and Feil-Seifer, David and Szafir, Daniel}, keywords = {steinhaeusser}, publisher = {ACM}, title = {Anthropomorphize me! - Effects of Robot Gender on Listeners' Perception of the Social Robot NAO in a Storytelling Use Case}, year = 2021 }

%0 Conference Paper %1 Steinhaeusser_2021 %A Steinhaeusser, Sophia C. %A Schaper, Philipp %A Akuffo, Ohenewa Bediako %A Friedrich, Paula %A Ön, Jülide %A Lugrin, Birgit %B Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2021) %D 2021 %E Bethel, Cindy %E Paiva, Ana %E Broadbent, Elizabeth %E Feil-Seifer, David %E Szafir, Daniel %I ACM %R 10.1145/3434074.3447228 %T Anthropomorphize me! - Effects of Robot Gender on Listeners' Perception of the Social Robot NAO in a Storytelling Use Case %U https://doi.org/10.1145%2F3434074.3447228

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