Validity Claims in Children-AI Discourse: Experiment with ChatGPT

Johannes Schneider, Leona Kruse, Isabella Seeber

2024

Abstract

Large language models like ChatGPT are increasingly used by people from all age groups. They have already started to transform education and research. However, these models are also known to have a number of shortcomings, i.e., they can hallucinate or provide biased responses. While adults might be able to assess such shortcomings, the most vulnerable group of our society – children – might not be able to do so. Thus, in this paper, we analyze responses to commonly asked questions tailored to different age groups by OpenAI’s ChatGPT. Our assessment uses Habermas’ validity claims. We operationalize them using computational measures such as established reading scores and interpretative analysis. Our results indicate that responses were mostly (but not always) truthful, legitimate, and comprehensible and aligned with the developmental phases, but with one important exception: responses for two-year-olds.

Paper Citation

in Harvard Style

Schneider J., Kruse L. and Seeber I. (2024). Validity Claims in Children-AI Discourse: Experiment with ChatGPT. In Proceedings of the 16th International Conference on Computer Supported Education - Volume 1: CSEDU; ISBN 978-989-758-697-2, SciTePress, pages 289-296. DOI: 10.5220/0012552300003693

in Bibtex Style

@conference{csedu24,
author={Johannes Schneider and Leona Kruse and Isabella Seeber},
title={Validity Claims in Children-AI Discourse: Experiment with ChatGPT},
booktitle={Proceedings of the 16th International Conference on Computer Supported Education - Volume 1: CSEDU},
year={2024},
pages={289-296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012552300003693},
isbn={978-989-758-697-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Computer Supported Education - Volume 1: CSEDU
TI - Validity Claims in Children-AI Discourse: Experiment with ChatGPT
SN - 978-989-758-697-2
AU - Schneider J.
AU - Kruse L.
AU - Seeber I.
PY - 2024
SP - 289
EP - 296
DO - 10.5220/0012552300003693
PB - SciTePress