EVALUATING ARTIFICIAL INTELLIGENCE GOVERNANCE MODELS IN IMMIGRATION ADMINISTRATION: A RULE OF LAW BASED MULTI CRITERIA DECISION FRAMEWORK
DOI:
https://doi.org/10.18623/rvd.v23.5580Palabras clave:
Artificial Intelligence Governance, Immigration Administration, Rule of Law, Asylum, Border ControlResumen
The main problem addressed in this study is how states can integrate artificial intelligence into immigration procedures without undermining rule of law principles. The key issue that must be analyzed is the selection of the most appropriate governance model based on legally grounded criteria. The literature lacks structured and quantitative frameworks that systematically evaluate artificial intelligence governance alternatives in migration administration. This study proposes a novel multi criteria decision making model to fill this gap. The model combines stepwise weight assessment ratio analysis (SWARA) for weighting criteria, root assessment model (RAM) for ranking governance strategies, and interval valued q rung orthopair fuzzy sets to address uncertainty in expert judgments. The findings show that the positioning of decision-making authority and the obligation to provide reasoned decisions are the most influential criteria, and that the administrative support model is the most appropriate approach. The study contributes by integrating legal analysis with advanced decision tools. It recommends governance strategies that preserve human authority, ensure transparency, and limit artificial intelligence to supportive administrative functions.
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