Year: 2025
Type: conference-paper
Abstract: Large Language Models (LLMs) are increasingly used in high-stakes domains like law and research, yet their inconsistencies and response instability raise concerns about trustworthiness.This study evaluates six leading LLMs-GPT-3.5, GPT-4, Claude, Gemini, Mistral, and LLaMA 2-on rationality, stability, and ethical fairness through reasoning tests, legal challenges, and bias-sensitive scenarios.Results reveal significant inconsistencies, highlighting trade-offs between model scale, architecture, and logical coherence.These findings underscore the risks of deploying LLMs in legal and policy settings, emphasizing the need for AI systems that prioritize transparency, fairness, and ethical robustness.
Authors: Dana R Alsagheer, Abdulrahman Kamal, Mohammad Kamal, Cosmo Yang Wu, Weidong Shi
Institution: University of Houston
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4412945487