Work

All modern AI needs is intuitionistic fuzzy

Year: 2026

Type: article

Abstract: While modern AI techniques are very successful, they are not as reliable as we would like them to be: in about 5% of the cases, they provide wrong answers. In this paper, we show that the problem facing modern AI tools is similar to the problem that, in the past, faced the original fuzzy logic – and that led to the development of intuitionistic fuzzy techniques: the need to consider the "don't know" option in addition to the usual "yes" and "no" answers to a binary ("yes"–"no") question. Based on this analogy, we provide recommendations on how to make AI tools more reliable, and we analyze advantages and limitations on these recommendations.

Source: Notes on Intuitionistic Fuzzy Sets

DOI: 10.7546/nifs.2026.32.3.193-202

Authors: Vladik Kreinovich, Olga Kosheleva, Victor Timchenko, Yuriy Kondratenko

Institutions: The University of Texas at El Paso, Admiral Makarov National University of Shipbuilding, Petro Mohyla Black Sea National University

Language: English

Topic: Advanced Algebra and Logic

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: European Commission, Deutsche Forschungsgemeinschaft, Leibniz-Gemeinschaft, Faculty of Economics, Chiang Mai University

Award: Intelligente Resilienzanalyse von Infrastruktur unter Berücksichtigung unsicherheitsbehafteter Echtzeitdaten