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Using Generative Art to Convey Past and Future Climate Transitions
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生成型人工智能,人类的创造力和艺术.

Eric Zhou1, Dokyun Lee1,2

  • 1Department of Information Systems, Boston University Questrom School of Business, Boston, MA 02215, USA.

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概括
此摘要是机器生成的。

文本到图像人工智能 (AI) 工具可以将人类的创造性生产力提高25%,并将艺术品价值提高50%. 虽然人工智能增强了想法探索,但它减少了视觉新性,需要人类的构想和过,以实现最佳的创意工作流.

关键词:
艺术 艺术 艺术 艺术创意工作流程 创意工作流生成型的人工智能人类人工智能合作人工智能对AI的影响.

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科学领域:

  • 人工智能的人工智能
  • 数字艺术 数字艺术 数字艺术
  • 人与计算机的交互

背景情况:

  • 文本到图像生成人工智能系统自动化艺术创作,产生数字艺术品.
  • 这些人工智能工具越来越多地被艺术家用于创作任务.

研究的目的:

  • 量化文本对图像人工智能对人类创造性生产力和艺术品价值的影响.
  • 分析人工智能辅助艺术中的内容变化和视觉新性.
  • 了解人工智能采用,艺术技能和同行评价之间的关系.

主要方法:

  • 分析了一套数据集,其中包括来自5万多用户的400多万件艺术品.
  • 随着时间的推移,对创意生产力,艺术品价值 (每次查看最喜欢的),内容新性和视觉新性的定量评估.
  • 人工智能协助,新奇探索和同行评价之间的相关性分析.

主要成果:

  • 文本对图像人工智能提高了人类的创造性生产率25%,艺术品价值提高了50%.
  • 峰值内容的新性增加,但平均内容和视觉新性随着时间的推移而下降.
  • 探索新想法的人工智能辅助艺术家获得了更有利的同行评价.
  • 人工智能的采用减少了用户之间的价值捕获集中.

结论:

  • 文本对图像人工智能作为人类创造性生产力和感知艺术品价值的显著增强剂.
  • 使用人工智能的创作过程涉及一个不断扩大的但潜在的低效的想法空间,需要人类的构想和过.
  • 这些发现引入了"生成共感"的概念,突出了人类-人工智能协作在发现新型创意工作流程方面的协同潜力.