Titlebook: Explainable Artificial Intelligence; First World Conferen Luca Longo Conference proceedings 2023 The Editor(s) (if applicable) and The Auth

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Adding Why to?What? Analyses of?an?Everyday Explanationfrom a video recall to explore how Explainers (EX) justified their explanation. We found that EX were focusing on the physical aspects of the game first (Architecture) and only later on aspects of the Relevance. Reasoning in the video recalls indicated that EX regarded the focus on the Architecture

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The Importance of?Distrust in?AIto prevent both disuse of these systems as well as overtrust. From our analysis of research on interpersonal trust, trust in automation, and trust in (X)AI, we identify the potential merit of the distinction between trust and distrust (in AI). We propose that alongside trust a healthy amount of dist

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Leveraging Group Contrastive Explanations for?Handling Fairnesssights through a comprehensive explanation of the decision-making process, enabling businesses to: detect the presence of direct discrimination on the target variable and choose the most appropriate fairness framework.

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Handbook of Phenomenological Aesthetics problem-solving strategies. Additionally, by inspecting the attention weights layer by layer, we uncover an unconventional finding that layer 10, rather than the model’s final layer, is the optimal layer to unfreeze for the least parameter-intensive approach to fine-tune the model. We support these

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Handbook of Philosophical Logicdata features effectively. Experimental results on industrial datasets demonstrate that the proposed method outperforms existing baselines and achieves state-of-the-art performance. The proposed approach offers a promising solution for accurate and interpretable spatio-temporal data forecasting.