Examining Diverse Gender Dynamics in Human-Robot Interaction: Trust Privacy and Safety Perceptions

Abstract

This research adopts a multidisciplinary approach, synthesizing insights from psychology, technology, and ethics to unravel the intricate threads of diverse gender perceptions regarding trust-building, privacy considerations, and safety concerns in Human-Robot Interaction (HRI). Our study contributes to a holistic understanding of HRI dynamics, providing valuable insights for designing robots to assist individuals with their Activities of Daily Living (ADL) at home, including tasks such as preparing their daily meals independently. This study delves into the correlation between robot failures and gender perceptions of trust, privacy, and safety when a human communicates with a robot in a natural way by using unstructured speech. In this approach, the user commands the robot conversationally using natural spoken language to fetch cooking-related items in a research lab’s mocked-up kitchen. With a participant pool of 35 adults (13 females with an average age of 35.58 ± 12.06 and 22 males with an average age of 35.68 ± 15.35), Kendall’s Tau correlations are employed for statistical analysis, offering a comprehensive investigation into the intricate interplay of gender, interaction methods, and perceptions in the realm of human-robot dynamics.