We investigate whether modern AI can emulate expert creativity in complex
scientific endeavors. We introduce novel methodology that utilizes original
research articles published after the AI's training cutoff, ensuring no prior
exposure, mitigating concerns of rote memorization and prior training. The AI
are tasked with redacting findings, predicting outcomes from redacted research,
and assessing prediction accuracy against reported results. Analysis on 589
published studies in four leading psychology journals over a 28-month period,
showcase the AI's proficiency in understanding specialized research, deductive
reasoning, and evaluating evidentiary alignment--cognitive hallmarks of human
subject matter expertise and creativity. These findings suggest the potential
of general-purpose AI to transform academia, with roles requiring
knowledge-based creativity become increasingly susceptible to technological
substitution.

通过研究 589 份发表于四本领先心理学期刊的研究论文，我们调查了现代人工智能是否能够模仿专家在复杂科学领域的创造力，并介绍了一种新的方法论，利用 AI 的训练截止日期之后发表的原创研究文章，确保没有事先接触，减轻死记硬背和事先训练的担忧。结果显示，AI 能够擅长理解专业研究、演绎推理以及评估证据与结果之间的一致性，这些是人类专业领域专家和创造力的认知特征。这些发现表明通用人工智能在转变学术界方面的潜力，需要基于知识的创造力的角色越来越容易被技术所替代。