Desdevises Joy
OCTO Technology, Accenture, Paris, France.
Front Psychol. 2025 Aug 7;16:1628486. doi: 10.3389/fpsyg.2025.1628486. eCollection 2025.
Creativity plays a crucial role in helping individuals and organisations generate innovative solutions to arising challenges. To support this creative process, generative Artificial Intelligence (AI), such as ChatGPT is being used increasingly. However, whether such a generative AI model can truly enhance creativity or whether it exhibits similar creative biases to humans is unclear. This study, conducted in 2025, consisted of an experiment which involved ChatGPT-4o performing the egg task, a creativity task which measures fixation bias and original idea generation (expansion). The AI model's results were compared both to a sample of 47 human participants and to aggregated data from eight previous studies using the same procedure with the egg task. This dual comparison provides a comprehensive perspective on creative biases in both AI and humans at multiple levels. While ChatGPT demonstrated greater productivity than humans, it exhibited a comparable fixation bias, with most ideas falling within conventional categories. Furthermore, the model showed a limited capability to differentially evaluate originality, as it struggled to distinguish between original and conventional ideas, unlike humans who are typically able to make this distinction. In conclusion, although generative AI demonstrates impressive fluency by producing a large number of creative ideas, its inability to critically assess their originality and overcome the fixation bias highlights the necessity of human involvement, particularly for properly evaluating and filtering the ideas generated.
创造力在帮助个人和组织针对出现的挑战产生创新解决方案方面发挥着关键作用。为了支持这一创造性过程,诸如ChatGPT之类的生成式人工智能(AI)正被越来越多地使用。然而,这种生成式AI模型是否真的能提高创造力,或者它是否表现出与人类相似的创造性偏差尚不清楚。这项于2025年进行的研究包括一项实验,该实验让ChatGPT - 4o执行鸡蛋任务,这是一项衡量固着偏差和原创想法产生(拓展)的创造力任务。将AI模型的结果与47名人类参与者的样本以及之前八项使用相同鸡蛋任务程序的研究的汇总数据进行了比较。这种双重比较从多个层面全面展现了AI和人类的创造性偏差。虽然ChatGPT的产出效率高于人类,但它表现出了类似的固着偏差,大多数想法都属于传统类别。此外,该模型在区分原创性方面能力有限,因为它难以区分原创想法和传统想法,而人类通常能够做到这一点。总之,尽管生成式AI通过产生大量创造性想法展现出了令人印象深刻的流畅性,但其无法批判性地评估这些想法的原创性并克服固着偏差凸显了人类参与的必要性,特别是在正确评估和筛选所产生的想法方面。