Natural Language Generation of Explanations of Fuzzy Inference Decisions

As Artificial Intelligence and fuzzy systems are at the center of the emergence of advanced technologies such as autonomous vehicles or medical decision support systems, a problem of trust from a human point of view is strongly appearing. In this article, we tackle the problem of explanation of a fu...

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Bibliographic Details
Published in2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) pp. 1 - 6
Main Authors Baaj, Ismail, Poli, Jean-Philippe
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
Cognition
Expert systems
Explainable Artificial Intelligence
Fuzzy Inference System
Fuzzy logic
Fuzzy systems
Intelligent systems
Linguistics
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Summary:As Artificial Intelligence and fuzzy systems are at the center of the emergence of advanced technologies such as autonomous vehicles or medical decision support systems, a problem of trust from a human point of view is strongly appearing. In this article, we tackle the problem of explanation of a fuzzy inference system decision in its entirety: from the conception of an algorithm that produces a textual explanation to its evaluation.We define a function which is able to associate to any activated fuzzy rule, the structure responsible of its activation degree. To assess our method, we defined a protocol to evaluate AIgenerated explanation, and made an experiment: explanations obtained from the classification of pastas. Despite limitations, the results show a good transparency of the reasoning, consistency and good global effectiveness in generated explanations.
ISSN:1558-4739
DOI:10.1109/FUZZ-IEEE.2019.8858994