Leveraging Artificial Intelligence to Promote Awareness in Augmented Reality Systems
<|reference_start|>Leveraging Artificial Intelligence to Promote Awareness in Augmented Reality Systems: Recent developments in artificial intelligence (AI) have permeated through an array of different immersive environments, including virtual, augmented, and mixed realities. AI brings a wealth of potential that centers on its ability to critically analyze environments, identify relevant artifacts to a goal or action, and then autonomously execute decision-making strategies to optimize the reward-to-risk ratio. However, the inherent benefits of AI are not without disadvantages as the autonomy and communication methodology can interfere with the human's awareness of their environment. More specifically in the case of autonomy, the relevant human-computer interaction literature cites that high autonomy results in an "out-of-the-loop" experience for the human such that they are not aware of critical artifacts or situational changes that require their attention. At the same time, low autonomy of an AI system can limit the human's own autonomy with repeated requests to approve its decisions. In these circumstances, humans enter into supervisor roles, which tend to increase their workload and, therefore, decrease their awareness in a multitude of ways. In this position statement, we call for the development of human-centered AI in immersive environments to sustain and promote awareness. It is our position then that we believe with the inherent risk presented in both AI and AR/VR systems, we need to examine the interaction between them when we integrate the two to create a new system for any unforeseen risks, and that it is crucial to do so because of its practical application in many high-risk environments.<|reference_end|>
@article{li2024leveraging,
    title={Leveraging Artificial Intelligence to Promote Awareness in Augmented
  Reality Systems},
    author={Wangfan Li, Rohit Mallick, Carlos Toxtli-Hernandez, Christopher
  Flathmann, Nathan J. McNeese},
    journal={arXiv preprint arXiv:2405.05916},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.05916},
    primaryClass={cs.HC}
}