UFSKW Paper-of-the-Month Award for March 2024

The article „‚Ick bin een Berlina‘: dialect proficiency impacts a robot’s trustworthiness and competence evaluation“ by Katharina Kühne, Erika Herbold, Oliver Bendel, Yuefang Zhou, and Martin H. Fischer has been granted the UFSKW Paper-of-the-Month Award for March 2024. All authors are researchers in the Potsdam Embodied Cognition Group (PECoG) at the University of Potsdam, with the exception of Oliver Bendel, who works at the FHNW School of Business and is an associated researcher in the group. „UFSKW“ stands for „Universitärer Forschungsschwerpunkt Kognitionswissenschaften“. It is based at the University of Potsdam. The UFSKW Paper of the Month provides a special stage for current cognitive science research at the UFSKW. It is chosen monthly by the selection committee from all submissions. The paper says about the background of the project: „Robots are increasingly used as interaction partners with humans. Social robots are designed to follow expected behavioral norms when engaging with humans and are available with different voices and even accents. Some studies suggest that people prefer robots to speak in the user’s dialect, while others indicate a preference for different dialects.“ The following results are mentioned: „We found a positive relationship between participants‘ self-reported Berlin dialect proficiency and trustworthiness in the dialect-speaking robot. Only when controlled for demographic factors, there was a positive association between participants‘ dialect proficiency, dialect performance and their assessment of robot’s competence for the standard German-speaking robot. Participants‘ age, gender, length of residency in Berlin, and device used to respond also influenced assessments. Finally, the robot’s competence positively predicted its trustworthiness.“ The article can be accessed at www.frontiersin.org/articles/10.3389/frobt.2023.1241519/full.

Fig.: NAO in Oliver Bendel’s office in Switzerland

Great Media Interest in Study on Dialect in Robots

At the end of January 2024, the article „‚Ick bin een Berlina‘: dialect proficiency impacts a robot’s trustworthiness and competence evaluation“ was published in Frontiers in Robotics and AI. Authors are Katharina Kühne, Erika Herbold, Prof. Dr. Oliver Bendel, Dr. Yuefang Zhou, and Prof. Dr. Martin H. Fischer. With the exception of Oliver Bendel – who is a professor at the School of Business FHNW and an associated researcher in the PECoG group – all of them are members of the University of Potsdam. Newspapers and platforms from all over the world have reported on the study, including the USA, Mexico, Argentina, Chile, Puerto Rico, Scotland, and Germany. German radio stations such as MDR and BR have also presented the results. On February 1, 2024, Der Spiegel published an interview with the lead author Katharina Kühne. She is being supervised in her doctoral thesis by Prof. Dr. Martin Fischer and Prof. Dr. Oliver Bendel. The open access article can be downloaded at www.frontiersin.org/articles/10.3389/frobt.2023.1241519/full.

Fig.: The NAO robot

Ick bin een Berlina, Says the Robot

On January 29, 2024, the article „‚Ick bin een Berlina‘: dialect proficiency impacts a robot’s trustworthiness and competence evaluation“ was published in Frontiers in Robotics and AI. Authors are Katharina Kühne, Erika Herbold, Oliver Bendel, Yuefang Zhou, and Martin H. Fischer. With the exception of Oliver Bendel – who is a professor at the School of Business FHNW and an associated researcher in the PECoG group – all of them are members of the University of Potsdam. The paper says about the background: „Robots are increasingly used as interaction partners with humans. Social robots are designed to follow expected behavioral norms when engaging with humans and are available with different voices and even accents. Some studies suggest that people prefer robots to speak in the user’s dialect, while others indicate a preference for different dialects.“ The following results are mentioned: „We found a positive relationship between participants’ self-reported Berlin dialect proficiency and trustworthiness in the dialect-speaking robot. Only when controlled for demographic factors, there was a positive association between participants’ dialect proficiency, dialect performance and their assessment of robot’s competence for the standard German-speaking robot. Participants‘ age, gender, length of residency in Berlin, and device used to respond also influenced assessments. Finally, the robot’s competence positively predicted its trustworthiness.“ The article can be accessed at www.frontiersin.org/articles/10.3389/frobt.2023.1241519/full.

Fig.: A robot in Berlin (Image: DALL-E 3)