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

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https://doi.org/10.1007/978-1-4020-6650-4of human-AI task sharing has to take these varieties into account. In many instances the modes of reacting on each other are symmetrically distributed between humans and AI. Certain activities of coordinating the task sharing between human and AI are in a meta-relation to the interaction between hum

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Rosemarie Day,Niko Lehman-Whiteined much attention due to the promising performance of deep learning models. However, progress is still slow due to an overreliance on large datasets and a lack of reliable evaluation methodology. To address the data challenge, the present research proposes the usage of prompting techniques which h

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https://doi.org/10.1007/978-1-4614-8351-9ust 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 autono

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Soviet Strategy, Tactics, and Dilemmas, know very little. As AI (Artificial intelligence) penetrates deeper into life, the development of AI is maybe uncontrollable under the influence of human data. Questions about privacy, autonomy, fairness, and the potential for misuse of technology will become even more pressing..In the unstoppable

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The African Human Rights Systemation into the field. This study illustrates prevailing generative models and datasets currently influential in music generation. Four publications have been selected for detailed discussion, representing a spectrum of salient concepts in music generation and potential areas of further inquiry. By f