Explainable artificial intelligence: Evaluating the objective and subjective impacts of xai on human-agent interaction
Intelligent agents must be able to communicate intentions and explain their decision-making
processes to build trust, foster confidence, and improve human-agent team dynamics …
processes to build trust, foster confidence, and improve human-agent team dynamics …
Measuring and understanding trust calibrations for automated systems: a survey of the state-of-the-art and future directions
Trust has been recognized as a central variable to explain the resistance to using automated
systems (under-trust) and the overreliance on automated systems (over-trust). To achieve …
systems (under-trust) and the overreliance on automated systems (over-trust). To achieve …
Toward quantifying trust dynamics: How people adjust their trust after moment-to-moment interaction with automation
XJ Yang, C Schemanske, C Searle - Human Factors, 2023 - journals.sagepub.com
Objective We examine how human operators adjust their trust in automation as a result of
their moment-to-moment interaction with automation. Background Most existing studies …
their moment-to-moment interaction with automation. Background Most existing studies …
A systematic review on fostering appropriate trust in human-AI interaction
S Mehrotra, C Degachi, O Vereschak… - arXiv preprint arXiv …, 2023 - arxiv.org
Appropriate Trust in Artificial Intelligence (AI) systems has rapidly become an important area
of focus for both researchers and practitioners. Various approaches have been used to …
of focus for both researchers and practitioners. Various approaches have been used to …
Being trustworthy is not enough: How untrustworthy artificial intelligence (AI) can deceive the end-users and gain their trust
Trustworthy Artificial Intelligence (AI) is characterized, among other things, by: 1)
competence, 2) transparency, and 3) fairness. However, end-users may fail to recognize …
competence, 2) transparency, and 3) fairness. However, end-users may fail to recognize …
Robot, uninterrupted: Telemedical robots to mitigate care disruption
Emergency department (ED) healthcare workers (HCWs) are interrupted as often as once
every six minutes, increasing the risk of errors and preventable patient harm. As more robots …
every six minutes, increasing the risk of errors and preventable patient harm. As more robots …
[HTML][HTML] Enhancing human-AI collaboration: The case of colonoscopy
Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows
promise in mitigating this burden by supporting Medical Doctors in decision-making …
promise in mitigating this burden by supporting Medical Doctors in decision-making …
Impacts of robot learning on user attitude and behavior
With an aging population and a growing shortage of caregivers, the need for in-home robots
is increasing. However, it is intractable for robots to have all functionalities pre-programmed …
is increasing. However, it is intractable for robots to have all functionalities pre-programmed …
Explainable robotic systems: Understanding goal-driven actions in a reinforcement learning scenario
Robotic systems are more present in our society everyday. In human–robot environments, it
is crucial that end-users may correctly understand their robotic team-partners, in order to …
is crucial that end-users may correctly understand their robotic team-partners, in order to …
[PDF][PDF] Autonomous Justification for Enabling Explainable Decision Support in Human-Robot Teaming.
Justification is an important facet of policy explanation, a process for describing the behavior
of an autonomous system. In human-robot collaboration, an autonomous agent can attempt …
of an autonomous system. In human-robot collaboration, an autonomous agent can attempt …