Fuzzy Multi-Criteria Decision-Making Models for Strengthening University–Government–Industry Collaboration in AI Development

This chapter describes how fuzzy multi-criteria decision-making (MCDM) might enhance collaboration between government, business, and academic institutions. It demonstrates why cooperation in AI development entails ambiguity and conflicting viewpoints. Vague judgments are transformed into usable values with the use of fuzzy sets and triangular fuzzy numbers. Fuzzy numbers are used to assess various factors, including research strength, finance, policy flexibility, technology preparedness, and social impact. The shifting significance of each criterion for various partners is displayed by fuzzy weights. All viewpoints are combined into a single meaningful score using aggregation and defuzzification techniques. Fuzzy soft sets highlight areas of agreement and aid in identifying areas of disagreements between partners. Partners can select AI laboratories, internships, and ethical committees, as demonstrated by several cases. The chapter demonstrates how fuzzy models improve the clarity and fairness of collaborative judgments in AI development.