Teaching Explainable Artificial Intelligence to High School Students

Authors

Jose M. Alonso^*,

Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain

^*Email: josemaria.alonso.moral@usc.es

DOI

10.2991/ijcis.d.200715.003How to use a DOI?

Keywords

Explainable artificial intelligence; Interpretable computational intelligence; Decision trees; Fuzzy rule-based classifiers; Educational AI resources

Abstract

Artificial Intelligence (AI) is part of our everyday life and has become one of the most outstanding and strategic technologies. Explainable AI (XAI) is expected to endow intelligent systems with fairness, accountability, transparency and explanation ability when interacting with humans. This paper describes how to teach fundamentals of XAI to high school students who take part in interactive workshop activities at CiTIUS-USC. These workshop activities are carried out in the context of a strategic plan for promoting careers on Science, Technology, Engineering and Mathematics. Students learn (1) how to build datasets free of bias, (2) how to build interpretable classifiers and (3) how to build multi-modal explanations.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Jose M. Alonso
PY  - 2020
DA  - 2020/07/24
TI  - Teaching Explainable Artificial Intelligence to High School Students
JO  - International Journal of Computational Intelligence Systems
SP  - 974
EP  - 987
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200715.003
DO  - 10.2991/ijcis.d.200715.003
ID  - Alonso2020
ER  -