Abstract
In the classical Human-Machine Dialogue (HMD) setting, existing research has mainly focused on the objective quality of the machine answer. However, it has been recently shown that humans do not perceive in the same manner a human made answer and respectively a machine made answer. In this paper, we put ourselves in the context of conversational Artificial Intelligence software and introduce the setting of postmodern human machine dialogues by focusing on the factual relativism of the human perception of the interaction. We demonstrate the above-mentioned setting in a practical setting via a pedagogical experiment using ChatGPT3.
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Bocquelet, M. et al. (2023). Postmodern Human-Machine Dialogues: Pedagogical Inquiry Experiments. In: Ojeda-Aciego, M., Sauerwald, K., Jäschke, R. (eds) Graph-Based Representation and Reasoning. ICCS 2023. Lecture Notes in Computer Science(). Springer, Cham. https://doi.org/10.1007/978-3-031-40960-8_10
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