Unraveling Generative AI from a Human Intelligence Perspective: A Battery of Experiments
从人类智力角度出发，通过在线实验评估GPT-4的认知、情感、创造和社会智力，发现其在社会智力方面存在不足，并为企业与政策制定者提供了评估大语言模型及预测岗位影响的工具。
This study introduces a novel, human-centered framework for evaluating the holistic intelligence of large language models (LLMs), using behavioral theory and experimental benchmarks drawn from human intelligence. Through extensive online experiments, the framework reveals that GPT-4 outperforms humans in cognitive, emotional, and creative intelligence, but falls short in social intelligence, especially in social interest, self-efficacy, and understanding mental states. Beyond theoretical insight, the study validates this framework by assessing GPT-4’s impact across diverse job roles, finding results consistent with established labor market research. It also offers a reusable tool for firms and policymakers to evaluate LLM intelligence and forecast job-level impacts. This enables informed decisions about where and how to integrate LLMs, match models to specific job requirements, and identify risks in socially intensive roles. The framework provides a foundation for responsible LLM deployment, ensuring alignment with human-centered structures and supporting strategic workforce planning.