@inproceedings{9165da995b5e4d578e9cbc6d31848136,
title = "Human-Machine Task Allocation in Learning Reciprocally to Solve Problems",
abstract = "Solving problems by human-AI configurations will likely become a pervasive practice. Traditional models of task allocation between human and machine must be revisited in light of the differences in the learning of humans versus intelligent machines; performance can no longer be the sole criterion for task allocation. We offer a new procedure for allocating tasks dynamically that begins with the determination of the desired level of machine autonomy.",
keywords = "Human-machine collaboration, Human-machine interaction, Learning, Machine learning, Reciprocity, Task allocation",
author = "Dov Te{\textquoteright}eni",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 25th International Conference on Human-Computer Interaction, HCII 2023 ; Conference date: 23-07-2023 Through 28-07-2023",
year = "2024",
doi = "10.1007/978-3-031-49215-0_9",
language = "אנגלית",
isbn = "9783031492143",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "65--77",
editor = "Constantine Stephanidis and Margherita Antona and Stavroula Ntoa and Gavriel Salvendy",
booktitle = "HCI International 2023 – Late Breaking Posters - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings",
address = "גרמניה",
}