AI知识与推理：在科学研究中模拟专家创造力
AI Knowledge and Reasoning: Emulating Expert Creativity in Scientific Research
AI总结：
本文利用训练截止后发表的589篇心理学论文，通过遮盖发现、预测结果并评估准确率，检验通用AI模拟专家科研创造力的能力。
摘要：
我们研究现代AI能否在复杂科学事业中模拟专家创造力。我们提出一种新方法，使用在AI训练截止日期之后发表的原创研究论文，以确保AI此前未曾接触，从而缓解对机械记忆和先前训练的担忧。AI的任务包括：遮盖研究发现、根据被遮盖的研究预测结果，并对照已报告结果评估预测准确性。对28个月期间发表于四本顶尖心理学期刊的589项已发表研究进行的分析，展示了AI在理解专业研究、演绎推理以及评估证据一致性方面的能力——这些正是人类领域专业知识与创造力的认知标志。这些发现表明，通用AI具有变革学术界的潜力，而需要基于知识的创造力的岗位将越来越容易受到技术替代。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
