| Title | AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Marino, Daniel L., Grandio, Javier, Wickramasinghe, Chathurika S., Schroeder, Kyle, Bourne, Keith, Filippas, Afroditi V., Manic, Milos |
| Conference Name | 2020 13th International Conference on Human System Interaction (HSI) |
| Keywords | artificial intelligence, Augmentation, Automation, Buildings, composability, cyber physical security, cyber physical systems, pubcrawl, resilience, Resiliency, robots, Robustness, Shared Autonomy, Task Analysis, Teleoperation, Trustworthy AI, Trustworthy Systems, Uncertainty |
| Abstract | Despite the performance of state-of-the-art Artificial Intelligence (AI) systems, some sectors hesitate to adopt AI because of a lack of trust in these systems. This attitude is prevalent among high-risk areas, where there is a reluctance to remove humans entirely from the loop. In these scenarios, Augmentation provides a preferred alternative over complete Automation. Instead of replacing humans, AI Augmentation uses AI to improve and support human operations, creating an environment where humans work side by side with AI systems. In this paper, we discuss how AI Augmentation can provide a path for building Trustworthy AI. We exemplify this approach using Robot Teleoperation. We lay out design guidelines and motivations for the development of AI Augmentation for Robot Teleoperation. Finally, we discuss the design of a Robot Teleoperation testbed for the development of AI Augmentation systems. |
| DOI | 10.1109/HSI49210.2020.9142659 |
| Citation Key | marino_ai_2020 |
AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation