Augmented Learning for Joint Creativity in Human-GenAI Co-Creation

创造力 接头(建筑物) 计算机科学 知识管理 生成语法 基础(证据) 人机交互 共同注意 生成模型 建筑 增强现实 心理学 构思 利用 培训(气象学) 语境学习 认知心理学 人工智能
作者
Yingyue Luan,Yeun Joon Kim,Jing Zhou
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences]
被引量:3
标识
DOI:10.1287/isre.2024.0984
摘要

The recent introduction of generative artificial intelligence (GenAI) has opened new opportunities for human–GenAI co-creation, in which humans and GenAI collaborate to produce creative outcomes. However, our findings indicate that mere integration does not guarantee augmented learning—the foundation for the continuous improvement of joint creativity over time. Effective integration depends on how well humans understand and collaborate with GenAI. We propose a two-step approach. First, organizations should critically assess GenAI’s strengths and limitations, recognizing its capacity to analyze data and generate diverse ideas, but also its lack of contextual and emotional understanding. Second, organizations should design targeted strategies and training programs that cultivate employees’ skills in Idea Co-Development—a co-creation activity in which humans and GenAI engage in critical feedback exchanges and the joint refinement of generated ideas. Our study demonstrates that even basic explanations and examples of Idea Co-Development significantly enhance joint creativity, suggesting that formal training with contextualized exercises can further amplify results. From a policy and design perspective, GenAI developers should build systems that actively support co-creative interaction through features such as feedback loops and prompts for elaboration. Together, these organizational and technological initiatives can foster more effective, sustained, and creative human-GenAI collaboration.
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