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ORIGINAL RESEARCH article

Front. Artif. Intell.
Sec. AI for Human Learning and Behavior Change
Volume 7 - 2024 | doi: 10.3389/frai.2024.1493348
This article is part of the Research Topic Generative AI in Education View all 11 articles

Deception Detection in Educational AI: Challenges for Japanese Middle School Students in Interacting with Generative AI Robots

Provisionally accepted
Ahmed Salem Ahmed Salem *Kaoru Sumi Kaoru Sumi
  • School of Systems Information Science, Future University Hakodate, Hakodate, Japan

The final, formatted version of the article will be published soon.

    Educational materials that utilize generative AI (e.g., ChatGPT) have been developed, thus, allowing students to learn through conversations with robots or agents. However, if these artificial entities provide incorrect information (hallucinating), it could lead to confusion among students.To investigate whether students can detect lies from these artificial entities, we conducted an experiment using the social robot Furhat and we make it engage in various types of deceptive interactions. Twenty-two Japanese middle school students participated in ten teaching sessions with Furhat using a human and an anime facial appearances while employing different types of deception: Lying, Paltering, Pandering, and Bullshit. The results revealed that the majority of students were deceived by those lies. Additionally, the robot's facial appearance (i.e., social agency) affected both the learning effectiveness and the likelihood of being deceived. We conclude that an anime robot face is recommended to be used as it excelled in learning effectiveness as it attracts students attention. An anime face also provided protection against deceptive techniques due to its low social agency which leads to ineffectiveness in persuasion and deception. This study underscores the importance of preparing AI-based educational tools and scripts carefully to prevent the dissemination of false information produced through generative AI hallucinations to students.

    Keywords: deception, generative AI hallucination, educational robots, lying, Paltering, Pandering, bullshit

    Received: 09 Sep 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Salem and Sumi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ahmed Salem, School of Systems Information Science, Future University Hakodate, Hakodate, Japan

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