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Human Emotions in AI Explanations

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Explainable Artificial Intelligence (xAI 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2156))

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Abstract

For adapting to humans, explainable AI (XAI) quality can benefit from human expressions beyond verbal expressions. This is particularly true for emotions, as emotions affect how information is processed and subsequent decision-making. We analyze how different explanation strategies of XAI are perceived when the human interaction partner shows high arousal and/or valence. In a between-subjects experimental setting, we show that individuals with low arousal follow advice with no attempt to any explanation. On the contrary, individuals in a highly aroused state respond best to explanations with some justification (guided explanations). Concerning varying levels of valence, we find no similar pattern. Our results suggest that specific XAI strategies should be adapted not only to humans’ cognitive needs but also to humans’ information processing capacities and needs, which depend on emotional arousal.

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Notes

  1. 1.

    Note, however, that personality traits have been shown to affect advice-taking: Matarese et al. [41] found that explainees who were high in agreeableness were more likely to follow robot advice than people with low agreeableness.

  2. 2.

    See also Lammert et al. [28] for more explanation about the method and materials.

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Acknowledgments

This research is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): TRR 318/1 2021 - 438445824.

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Authors and Affiliations

  1. Faculty of Business Administration and Economics, Department of Management, Paderborn University, Warburger Street 100, 33098, Paderborn, Germany

    Kirsten Thommes & Olesja Lammert

  2. Medical School OWL, Medical Assistance Systems, Bielefeld University, Morgenbreede 1, 33615, Bielefeld, Germany

    Christian Schütze, Birte Richter & Britta Wrede

  3. Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Inspiration 1, 33619, Bielefeld, Germany

    Christian Schütze, Birte Richter & Britta Wrede

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  1. Kirsten Thommes
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  2. Olesja Lammert
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Correspondence to Olesja Lammert .

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  1. Technological University Dublin, Dublin, Ireland

    Luca Longo

  2. Fraunhofer Institute for Telecommunications, Berlin, Germany

    Sebastian Lapuschkin

  3. University of Marburg, Marburg, Germany

    Christin Seifert

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Thommes, K., Lammert, O., Schütze, C., Richter, B., Wrede, B. (2024). Human Emotions in AI Explanations. In: Longo, L., Lapuschkin, S., Seifert, C. (eds) Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2156. Springer, Cham. https://doi.org/10.1007/978-3-031-63803-9_15

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