相关论文: Toward quantifying trust dynamics: How people adju…

Human trust in automation plays an essential role in interactions between humans and automation. While a lack of trust can lead to a human's disuse of automation, over-trust can result in a human trusting a faulty autonomous system which…

Trust in automation, or more recently trust in autonomy, has received extensive research attention in the past two decades. The majority of prior literature adopted a "snapshot" view of trust and typically evaluated trust through…

As autonomous vehicles have benefited the society, understanding the dynamic change of humans' trust during human-autonomous vehicle interaction can help to improve the safety and performance of autonomous driving. We designed and conducted…

Artificial Intelligence based systems may be used as digital nudging techniques that can steer or coerce users to make decisions not always aligned with their true interests. When such systems properly address the issues of Fairness,…

Trust in robots has been gathering attention from multiple directions, as it has special relevance in the theoretical descriptions of human-robot interactions. It is essential for reaching high acceptance and usage rates of robotic…

In this paper, we present a framework for trust-aware sequential decision-making in a human-robot team. We model the problem as a finite-horizon Markov Decision Process with a reward-based performance metric, allowing the robotic agent to…

This study aims to explore the associations between individuals' trust dynamics in automated/autonomous technologies and their personal characteristics, and to further examine whether personal characteristics can be used to predict a user's…

As robots become increasingly integrated into various industries, understanding how humans respond to robotic failures is critical. This study systematically examines trust dynamics and system design by analyzing human reactions to robot…

Objective We model factors contributing to rating timing for a single-dimensional, any-time trust in robotics measure. Background Many studies view trust as a slow-changing value after subjects complete a trial or at regular intervals.…

Despite recent advances in robotics and human-robot collaboration in the AEC industry, trust has mostly been treated as a static factor, with little guidance on how it changes across events during collaboration. This paper investigates how…

Trust biases how users rely on AI recommendations in AI-assisted decision-making tasks, with low and high levels of trust resulting in increased under- and over-reliance, respectively. We propose that AI assistants should adapt their…

Understanding how trust is built over time is essential, as trust plays an important role in the acceptance and adoption of automated vehicles (AVs). This study aimed to investigate the effects of system performance and participants' trust…

Trust has been shown to be a key factor in effective human-robot collaboration. In the context of assistive robotics, the effect of trust factors on human experience is further pronounced. Personalization of assistive robots is an…

Explainability, interpretability and how much they affect human trust in AI systems are ultimately problems of human cognition as much as machine learning, yet the effectiveness of AI recommendations and the trust afforded by end-users are…

Trust plays a central role in human--robot collaboration, yet its formation is rarely examined under the constraints of fully autonomous interaction. This pilot study investigated how interaction policy influences trust during in-person…

Trust calibration between humans and Artificial Intelligence (AI) is crucial for optimal decision-making in collaborative settings. Excessive trust can lead users to accept AI-generated outputs without question, overlooking critical flaws,…

Trust calibration is necessary to ensure appropriate user acceptance in advanced automation technologies. A significant challenge to achieve trust calibration is to quantitatively estimate human trust in real-time. Although multiple trust…

This paper examines the effect of real-time, personalized alignment of a robot's reward function to the human's values on trust and team performance. We present and compare three distinct robot interaction strategies: a non-learner strategy…

Objective We model the dynamic trust of human subjects in a human-autonomy-teaming screen-based task. Background Trust is an emerging area of study in human-robot collaboration. Many studies have looked at the issue of robot performance as…

Decision support systems enhanced by Artificial Intelligence (AI) are increasingly being used in high-stakes scenarios where errors or biased outcomes can have significant consequences. In this work, we explore the conditions under which…