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1. The Effects of Locus of Control and Big Five Personality Traits on Collaborative Engineering Design Tasks With Negotiation

   https://doi.org/10.1115/DETC2019-97311  

   Avşar, Alkım Z. ; Valencia-Romero, Ambrosio ; Grogan, Paul T. ( August 2019 , ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference)

   Collaborative systems design is a human-centered activity dependent on individual decision-making processes. Personality traits have been found to influence individual behaviors and tendencies to compete or cooperate. This paper investigates the effects of Big Five and Locus of Control personality traits on negotiated outcomes of a simplified collaborative engineering design task. Secondary data includes results from short-form personality inventories and outcomes of pair design tasks. The data includes ten sessions of four participants each, where each participant completes a sequence of 12 pair tasks involving design space exploration and negotiation. Regression analysis shows a statistically-significant relationship between Big Five and Locus of Control and total individual value accumulated across the 12 design tasks. Results show the Big Five, aggregating extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination to a single factor, negatively affects individual value and internal Locus of Control positively affects individual value. Future work should consider a dedicated experiment to refine understanding of how personality traits influence collaborative systems design and propose interventions to improve collaborative design processes. 

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2. Exploring the Relationship between Mindfulness and Personality to Improve Construction Safety and Work Performance

   Solomon, T. ; Esmaeili, B. ( March 2020 , Construction Research Congress 2020)

   The construction industry still leads the world as one of the sectors with the most work-related injuries and worker fatalities. Recent studies show that both a state of mindfulness and various personality traits contribute to individuals’ safety and work performance. This study examines the relationship between mindfulness and personality by measuring the mindfulness state of individuals against their personality traits. To achieve this objective, data were collected from a sample of 55 undergraduate students at George Mason University. Scores from the Big Five Inventory were ranked by each traits’ score (independent variable) and split into three groups: high, moderate, and low scores. The corresponding mindfulness scores (dependent variable) were analyzed to determine the relationship between high/low personality traits and mindfulness. Comparing the high/low groups using statistical analyses showed that three of the five personality traits—conscientiousness, agreeableness, and neuroticism—significantly correlate with higher mindfulness scores of individuals. As mindfulness has been shown to increase individual safety and work performance and to reduce stress, the results of this study help inform future work into translating personality and mindfulness characteristics into factors that predict specific elements of unsafe human behaviors. 

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3. Robots for Social Justice (R4SJ): Toward a More Equitable Practice of Human-Robot Interaction

   Zhu, Yifei ; Wen, Ruchen ; Williams, Tom ( March 2024 , ACM/IEEE International Conference on Human-Robot Interaction)

   In this work, we present Robots for Social Justice (R4SJ): a framework for an equitable engineering practice of Human-Robot Interaction, grounded in the Engineering for Social Justice (E4SJ) framework for Engineering Education and intended to complement existing frameworks for guiding equitable HRI research. To understand the new insights this framework could provide to the field of HRI, we analyze the past decade of papers published at the ACM/IEEE International Conference on Human-Robot Interaction, and examine how well current HRI research aligns with the principles espoused in the E4SJ framework. Based on the gaps identified through this analysis, we make five concrete recommendations, and highlight key questions that can guide the introspection for engineers, designers, and researchers. We believe these considerations are a necessary step not only to ensure that our engineering education efforts encourage students to engage in equitable and societally beneficial engineering practices (the purpose of E4SJ), but also to ensure that the technical advances we present at conferences like HRI promise true advances to society, and not just to fellow researchers and engineers. 

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4. Why Should We Gender?: The Effect of Robot Gendering and Occupational Stereotypes on Human Trust and Perceived Competency

   https://doi.org/10.1145/3319502.3374778  

   Bryant, De'Aira ; Borenstein, Jason ; Howard, Ayanna ( March 2020 , HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction)

   The attribution of human-like characteristics onto humanoid robots has become a common practice in Human-Robot Interaction by designers and users alike. Robot gendering, the attribution of gender onto a robotic platform via voice, name, physique, or other features is a prevalent technique used to increase aspects of user acceptance of robots. One important factor relating to acceptance is user trust. As robots continue to integrate themselves into common societal roles, it will be critical to evaluate user trust in the robot's ability to perform its job. This paper examines the relationship among occupational gender-roles, user trust and gendered design features of humanoid robots. Results from the study indicate that there was no significant difference in the perception of trust in the robot's competency when considering the gender of the robot. This expands the findings found in prior efforts that suggest performance-based factors have larger influences on user trust than the robot's gender characteristics. In fact, our study suggests that perceived occupational competency is a better predictor for human trust than robot gender or participant gender. As such, gendering in robot design should be considered critically in the context of the application by designers. Such precautions would reduce the potential for robotic technologies to perpetuate societal gender stereotypes. 

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5. Human mobile robot interaction in the retail environment

   https://doi.org/10.1038/s41597-022-01802-8  

   Chen, Yuhao ; Luo, Yue ; Yang, Chizhao ; Yerebakan, Mustafa Ozkan ; Hao, Shuai ; Grimaldi, Nicolas ; Li, Song ; Hayes, Read ; Hu, Boyi ( November 2022 , Scientific Data)

   As technology advances, Human-Robot Interaction (HRI) is boosting overall system efficiency and productivity. However, allowing robots to be present closely with humans will inevitably put higher demands on precise human motion tracking and prediction. Datasets that contain both humans and robots operating in the shared space are receiving growing attention as they may facilitate a variety of robotics and human-systems research. Datasets that track HRI with rich information other than video images during daily activities are rarely seen. In this paper, we introduce a novel dataset that focuses on social navigation between humans and robots in a future-oriented Wholesale and Retail Trade (WRT) environment (https://uf-retail-cobot-dataset.github.io/). Eight participants performed the tasks that are commonly undertaken by consumers and retail workers. More than 260 minutes of data were collected, including robot and human trajectories, human full-body motion capture, eye gaze directions, and other contextual information. Comprehensive descriptions of each category of data stream, as well as potential use cases are included. Furthermore, analysis with multiple data sources and future directions are discussed.

    

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