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Titlebook: Artificial Intelligence in HCI; 4th International Co Helmut Degen,Stavroula Ntoa Conference proceedings 2023 The Editor(s) (if applicable)

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樓主: Indigent
21#
發(fā)表于 2025-3-25 03:53:55 | 只看該作者
22#
發(fā)表于 2025-3-25 09:29:22 | 只看該作者
Therapist Perceptions of?Automated Deception Detection in?Mental Health Applicationselligence for deception detection in therapy sessions. Four themes emerged from coding analysis of the interview data, including Functional Components of the Computer Science Implementation, Perceptions of the Computer Science Implementation, Integration of the Computer Science Implementation, and S
23#
發(fā)表于 2025-3-25 12:21:22 | 只看該作者
Aggregating Human Domain Knowledge for?Feature Rankingspecific focus on eliciting and aggregating feature rankings by human subjects. The elicitation is guided by the principles of expert judgment elicitation, a field of study that has investigated the aggregation of multiple opinions for the purpose of mitigating biases and enhancing accuracy. An onli
24#
發(fā)表于 2025-3-25 17:52:06 | 只看該作者
25#
發(fā)表于 2025-3-25 22:19:00 | 只看該作者
The Role of?Response Time for?Algorithm Aversion in?Fast and Slow Thinking Tasksments on both personal and societal levels. However, algorithm aversion is known to reduce the effectiveness of human-AI interaction and diminish the potential benefits of AI. In this paper, we built upon the Dual System Theory and investigate the effect of the AI response time on algorithm aversion
26#
發(fā)表于 2025-3-26 02:42:50 | 只看該作者
27#
發(fā)表于 2025-3-26 07:53:07 | 只看該作者
Is It Possible to Measure Real-Time VR Motion Sickness with EDA Wavelet Features?a result, many methods, physiological indicators: electrogastrography (EGG), heart rate (HR), temperature, electrodermal activity (EDA), subjective measurement methods, simulator sickness questionnaire (SSQ), virtual reality symptom questionnaire (VRSQ), fast motion sickness score (FMS), have been s
28#
發(fā)表于 2025-3-26 09:32:59 | 只看該作者
29#
發(fā)表于 2025-3-26 15:33:46 | 只看該作者
The Thousand Faces of?Explainable AI Along the?Machine Learning Life Cycle: Industrial Reality and?Cd relate them to the current state of academic XAI research. Our findings are based on an extensive series of interviews regarding the role and applicability of XAI along the Machine Learning (ML) lifecycle in current industrial practice and its expected relevance in the future. The interviews were
30#
發(fā)表于 2025-3-26 17:54:27 | 只看該作者
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