Remember me - user-centered implementation of working memory architectures on an industrial robot.

The present research is innovative as we followed a user-centered approach to implement and train two working memory architectures on an industrial RB-KAIROS + robot: GRU, a state-of-the-art architecture, and WorkMATe, a biologically-inspired alternative. Although user-centered approaches are essential to create a comfortable and safe HRI, they are still rare in industrial settings. Closing this research gap, we conducted two online user studies with large heterogeneous samples. The major aim of these studies was to evaluate the RB-KAIROS + robot's appearance, movements, and perceived memory functions before (User Study 1) and after the implementation and training of robot working memory (User Study 2). In User Study 1, we furthermore explored participants' ideas about robot memory and what aspects of the robot's movements participants found positive and what aspects they would change. The effects of participants' demographic background and attitudes were controlled for. In User Study 1, participants' overall evaluations of the robot were moderate. Participant age and negative attitudes toward robots led to more negative robot evaluations. According to exploratory analyses, these effects were driven by perceived low experience with robots. Participants expressed clear ideas of robot memory and precise suggestions for a safe, efficient, and comfortable robot navigation which are valuable for further research and development. In User Study 2, the implementation of WorkMATe and GRU led to more positive evaluations of perceived robot memory, but not of robot appearance and movements. Participants' robot evaluations were driven by their positive views of robots. Our results demonstrate that considering potential users' views can greatly contribute to an efficient and positively perceived robot navigation, while users' experience with robots is crucial for a positive HRI.

Ladies First: Gender Stereotypes Drive Anticipatory Eye-Movements During Incremental Sentence Interpretation.

Immediate contextual information and world knowledge allow comprehenders to anticipate incoming language in real time. The cognitive mechanisms that underlie such behavior are, however, still only partially understood. We examined the novel idea that gender attitudes may influence how people make predictions during sentence processing. To this end, we conducted an eye-tracking experiment where participants listened to passive-voice sentences expressing gender-stereotypical actions (e.g., "The wood is being painted by the florist") while observing displays containing both female and male characters representing gender-stereotypical professions (e.g., florists, soldiers). In addition, we assessed participants' explicit gender-related attitudes to explore whether they might predict potential effects of gender-stereotypical information on anticipatory eye movements. The observed gaze pattern reflected that participants used gendered information to predict who was agent of the action. These effects were larger for female- vs. male-stereotypical contextual information but were not related to participants' gender-related attitudes. Our results showed that predictive language processing can be moderated by gender stereotypes, and that anticipation is stronger for female (vs. male) depicted characters. Further research should test the direct relation between gender-stereotypical sentence processing and implicit gender attitudes. These findings contribute to both social psychology and psycholinguistics research, as they extend our understanding of stereotype processing in multimodal contexts and regarding the role of attitudes (on top of world knowledge) in language prediction.