Trust in Robots: Challenges and Opportunities

Abstract

Purpose of Review To assess the state-of-the-art in research on trust in robots and to examine if recent methodological advances can aid in the development of trustworthy robots. Recent Findings While traditional work in trustworthy robotics has focused on studying the antecedents and consequences of trust in robots, recent work has gravitated towards the development of strategies for robots to actively gain, calibrate, and maintain the human user's trust. Among these works, there is emphasis on endowing robotic agents with reasoning capabilities (e.g., via probabilistic modeling). Summary The state-of-the-art in trust research provides roboticists with a large trove of tools to develop trustworthy robots. However, challenges remain when it comes to trust in real-world human-robot interaction (HRI) settings: there exist outstanding issues in trust measurement, guarantees on robot behavior (e.g., with respect to user privacy), and handling rich multidimensional data. We examine how recent advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can provide resolution to each of these issues. In conclusion, we are of the opinion that these methodological advances could pave the way for the creation of truly autonomous, trustworthy social robots.

A Unified Bi-directional Model for Natural and Artificial Trust in Human–Robot Collaboration

“…Several trust definitions have been proposed, generally pointing to the trustor's attitude or willingness to be vulnerable to the trustee's actions [2], [4]. In this work, we assume the (adapted) definition for trust recently proposed by Kok and Soh, which states that: "given a trustor agent A and a trustee agent B, A's trust in B is a multidimensional latent variable that mediates the relationship between events in the past and A's subsequent choice of relying on B in an uncertain environment" [19]. Kok and Soh's definition establishes important aspects of our model, such as the multidimensionality of trust and its dependence on a history of events involving the trustor and the trustee agents.…”

Hurry Up, We Need to Find the Key! How Regulatory Focus Design Affects Children’s Trust in a Social Robot

“…No previous work has studied regulatory focus design and its effects on trust or relationship formation in HRI or cHRI. However, there is evidence that the robot’s design can prime and induce users to a certain level of trust ( Kok and Soh, 2020 ). Moreover, due to the fact that RFT originates from distinct survival needs, regulatory focus design might have significant implications with regard to trust perception and relationship formation that are worth exploring.…”

Exploring the Role of Trust and Expectations in CRI Using In-the-Wild Studies

“…For characterizing multidimensionality of trust in children's relationships, some researchers distinguish among its cognitive, emotional and behavioral dimensions [26], while others [27] study features of trust and identify capabilities, ethical behaviors and reliability descriptions as the most measurable and distinctive ones. However, many researchers have emphasized the lack of a generally agreed definition of trust in human-robot interaction in the current literature [28,29] and the urgent need to rectify this [30]. In the context of our study on child-robot interaction, we use a working definition of trust as a set of children's behaviors indicating their belief that a robot will not undertake actions detrimental to their well-being.…”

“…This setting allows us to observe children's expressions, attitudes and behaviors associated with trust. Although it has been argued that trust cannot be observed [28], we aim to understand behaviors that indicate that the interaction between the robot and a group of children is based on mutual understanding [32]. We plan to use the checklist proposed by Jian et al [33] for measuring trust between people and automation: feelings of security, integrity, dependability and reliability.…”