A critical analysis of MBTI-based personality profiling with large language models
Belkacem Chikhaoui
This paper critically analyzes MBTI-based personality profiling using Large Language Models (LLMs), examining both their use as tools for inferring human personality and as subjects evaluated through psychometric frameworks. We review recent work (2020–2025) spanning traditional machine learning, fine-tuned transformer models, and zero-shot prompting approaches across datasets such as Kaggle MBTI, PersonalityCafe, Pandora, and MBTIBench. While top-performing LLM-based systems report 75%–85% accu