Challenge Grant: Toward the Realization of Explainable Computing Environments

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Summary

In recent years, AI tools based on deep learning have rapidly evolved, and the issues surrounding the explainability of Large Language Models (LLMs) are becoming increasingly serious. This study aims to present concrete methodologies using logical approaches to address the various issues related to the explainability and fairness of computing environments that influence our social lives. We seek to promote Japan-France research collaboration and explore explainability models of LLMs that lead to societal benefits.

SDGs

Project Members

About Project Members, Researchers

Note: ◎ indicates the project leader

Name	Affiliation	Position	Field of Specialization/Research Interests
◎ Koji Mineshima	Faculty of Letters	Associate Professor	Director of Research Activities
Mitsuhiro Okada	Faculty of Letters	Professor Emeritus	Analysis of Fairness and Explainability in Computational Environments
Yuichiro Hosokawa	Gunma Prefectural Women's University, Department of Culture and Informatics	Lecturer	Philosophical Logic, Practical Reasoning, and Application of Counterfactual Conditionals to Explainability Issues
Kentaro Ozeki	The University of Tokyo／KGRI	JSPS Researcher (PD)／Part-time researcher	Evaluation and Improvement of LLMs, Ontology Engineering, and Software Explainability Analysis
Risako Ando	Graduate School of Letters	Doctoral Program	Proof-theoretic Explanations and Translations into Natural Language, Evaluation and Benchmarking of LLMs
Pierre Wagner	University of Paris 1 Panthéon-Sorbonne／IHPST	Professor／Director	Explanations through Logic and Reasoning, Application of Explainability Research in LLMs to Education
Gilles Dowek	Inria／ENS Paris-Saclay	Director of Research／Professor	Analysis of Explainability and Fairness in Computational Algorithms, Applications to Digital Ethics
Claude Kirchner	The French National Committee for Digital Ethics／ Inria	President／Emeritus Research Director	Analysis of Explainability and Fairness in Computational Algorithms, Applications to Digital Ethics
Catuscia Palamidessi	Inria Saclay and LIX	Director of Research	Causal Explanations and Fairness in Algorithms and Machine Learning Models, Application to Digital Ethics Education
Ruta Binkyte	Inria Saclay and LIX／Aivancity School for Business, Technology and Society	Doctoral Researcher／Associate Professor	Causal Explanations and Fairness in Algorithms and Machine Learning Models, Application to Digital Ethics Education