Deborah R. Billings

A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction

Objective: We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). Background: To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Method: Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. Results: The overall correlational effect size for trust was r̄ = +0.26, with an experimental effect size of d̄ = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Conclusion: Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. Application: The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Can You Trust Your Robot

It is proposed that trust is a critical element in the interactive relations between humans and the automated and robotic technology they create. This article presents (a) why trust is an important issue for this type of interaction, (b) a brief history of the development of human-robot trust issues, and (c) guidelines for input by human factors/ergonomics professionals to the design of human-robot systems with emphasis on trust issues. Our work considers trust an ongoing and dynamic dimension as robots evolve from simple tools to active, sentient teammates.

A Model of Human-Robot Trust: Theoretical Model Development

This work explores the theoretical foundations of trust which provide the framework for the development of our model of human-robot team trust. The pragmatic purpose for this model is to provide a greater understanding of the factors that facilitate the development of human operator trust in robotic teammates. We predicate the model’s structure with our findings from a quantitative meta-analysis that we have completed. Our approach categorizes the dimensions influencing trust in human-robot interaction. To date, we have explored human, robot and environmental-based factors. Our road map for model development and refinement is here outlined.

Human-robot interaction: developing trust in robots

In all human-robot interaction, trust is an important element to consider because the presence or absence of trust certainly impacts the ultimate outcome of that interaction. Limited research exists that delineates the development and maintenance of this trust in various operational contexts. Our own prior research has investigated theoretical and empirically supported antecedents of human-robot trust. Here, we describe progress to date relating to the development of a comprehensive human-robot trust model based on our ongoing program of research.

Antecedents of trust in human-robot collaborations

Robotic systems are being introduced into military echelons to extend warfighter capabilities in complex, dynamic environments. While these systems are designed to complement human capabilities (e.g., aiding in battlefield situation awareness and decision making, etc), they are often misused or disused because the user does not have an appropriate level of trust in his or her robotic counterpart(s). We describe a continuing body of research that identifies factors impacting a humans level of trust in a robotic teammate. The factors identified to date can be categorized as human influences (e.g., individual differences in terms of personality, experience, culture), machine influences (e.g., robotic platform, robot performance in terms of levels of automation, failure rates, false alarms), and environmental influences (e.g. task type, operational environment, shared mental models). A framework for human-robot team trust was constructed, which is evolving into a working model contingent upon the results of an on-going meta-analysis.

Classification of Robot Form: Factors Predicting Perceived Trustworthiness

Many factors influence perceived usability of robots, including attributes of the human user, the environment, and the robot itself. Traditionally, the primary focus of research has been on performance-based characteristics of the robot for the purposes of classification, design, and understanding human-robot trust. In this work, we examine the human perceptions of the aesthetic dimensions of a variety of robot domains to gain insight into the impact of physical form on perceived trustworthiness that occurs prior to human-robot interaction. Results show that the physical form does matter when predicting initial trustworthiness of a robot, primarily through the perceived intelligence and classification of the robot.

Human-animal teams as an analog for future human-robot teams: influencing design and fostering trust

Our work posits that existing human-animal teams can serve as an analog for developing effective human-robot teams. Existing knowledge of human-animal partnerships can be readily applied to the HRI domain to foster accurate mental models and appropriately calibrated trust in future human-robot teams. Human-animal relationships are examined in terms of the benefiting roles animals can play in enabling effective teaming, as well as the level of team interdependency and team communication, with the goal of developing applications in future human-robot teams.