AI program that explains statistical data in an evil way by exploiting thinking traits of humans

Japanese version

Grants-in-Aid for Challenging Research (Exploratory), JP21K19795

Japan Society for the Promotion of Science (JSPS)

2021/7/9 - 2023/3/31

Research organization

Einoshin Suzuki

Principal investigator, Professor

Department of Informatics, ISEE, Kyushu University

Research abstract:
Contrary to the excessive expectations of the general public, the capability of the current AI is low in handling a wide range of problems which require common sense reasoning. In this project, we explore the process of persuading human beings from both computer science and information engineering by building and testing AI programs that classify harmless explanations and bad explanations, transform harmless explanations to bad explanations, and replicate bad explanations. Few past works exist for this kind of research. We aim to find seeds of a paradigm shift with this challenge. We plan to use techniques such as deep learning, machine learning, and data mining in the challenge. Our target domains include healthy longevity, international politics and economics, and pandemics. Needless to say, we take our greatest care to avoid Internet flaming and technological abuse.

Selected outcomes:
1. Kang Zhang, Hiroaki Shinden, Tatsuki Mutsuro, Einoshin Suzuki: "Judging Instinct Exploitation in Statistical Data Explanations Based on Word Embedding", Proc. Fifth AAAI/ACM Conference on AI, Ethics, and Society (AIES 2022), pp. ?-?, Oxford, UK, August 2022. DOI ? (accepted for publication)