abstract
- Understanding human behavior is crucial for enhancing interactions between humans and machines, especially in complex, collaborative tasks. This paper focuses on developing surveys to understand better and adapt to human behavior while acknowledging the role of cultural differences. Social robots and autonomous vehicles, referred to as `social products¿, exemplify the need for machines to adapt to human nuances. To improve their acceptability and adoption, tailoring machines to increase performance based on personality and behavioral insights is essential. Research in this field is extensive, with questionnaires being a key tool for understanding behavior and personality. Studies have explored eye movements as predictors of personality traits and the genetic basis of prosocial behavior. However, surveys are fundamental elements considered in designing better interfaces. This paper presents a streamlined survey approach and proposes a set of interfaces tailored according to personality and behavior. Besides, these tailored experiences can extend into other fields like education. The proposed reduced survey is validated using a data set from Mexican citizens but could be used in different places. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.