Titlebook: HCI International 2023 – Late Breaking Posters; 25th International C Constantine Stephanidis,Margherita Antona,Gavriel Conference proceedi

設(shè)施

Human-Machine Task Allocation in Learning Reciprocally to Solve Problemsust 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.

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https://doi.org/10.1007/978-3-031-49215-0artificial intelligence; communication systems; computer hardware; computer networks; computer systems; c

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Masculinities and Physical Power,hese natural human behaviors. When users interact with AI models trained in this way, they will not need to think consciously about the model’s working mechanism anymore. The paper elaborates on this approach further with a practical case that can be encountered in our daily lives; the vision and la