AI能生成诗歌绘画，但缺乏真正创造性解决问题的能力。
Creativity in AI: Progresses and Challenges
- 从认知科学出发，分析AI在语言、艺术、科学等领域的创造能力
- 当前模型生成内容多样性和原创性不足，存在幻觉与长程不连贯问题
- 适合关注AI创造力评估与伦理问题的研究者和从业者
创造力是产生新颖、有用且出人意料想法的能力，被广泛视为人类认知的关键方面。机器创造力长期以来面临挑战。随着先进生成式AI的兴起，关于AI是否具备创造力的问题再次引发关注与讨论。因此，有必要重新审视当前AI创造力的发展现状，识别关键进展与尚未解决的挑战。本文综述了研究AI系统创造力的前沿工作，重点涵盖创造性问题解决、语言、艺术及科学创造力。研究表明，尽管最新AI模型在生成诗歌、图像和音乐等语言与艺术类内容上已表现出较强能力，但在需要创造性问题解决、抽象思维与组合性表达的任务中仍表现不佳；其生成结果普遍存在多样性低、原创性不足、长程逻辑不连贯以及幻觉等问题。我们还探讨了生成模型带来的版权与作者权争议。此外，强调需建立以过程为导向、多维度的创造力评估体系。最后，提出未来研究方向，借鉴认知科学与心理学以提升AI输出的创造力。
原文摘要 · Abstract (English)
Creativity is the ability to produce novel, useful, and surprising ideas, and has been widely studied as a crucial aspect of human cognition. Machine creativity on the other hand has been a long-standing challenge. With the rise of advanced generative AI, there has been renewed interest and debate regarding AI's creative capabilities. Therefore, it is imperative to revisit the state of creativity in AI and identify key progresses and remaining challenges. In this work, we survey leading works studying the creative capabilities of AI systems, focusing on creative problem-solving, linguistic, artistic, and scientific creativity. Our review suggests that while the latest AI models are largely capable of producing linguistically and artistically creative outputs such as poems, images, and musical pieces, they struggle with tasks that require creative problem-solving, abstract thinking and compositionality and their generations suffer from a lack of diversity, originality, long-range incoherence and hallucinations. We also discuss key questions concerning copyright and authorship issues with generative models. Furthermore, we highlight the need for a comprehensive evaluation of creativity that is process-driven and considers several dimensions of creativity. Finally, we propose future research directions to improve the creativity of AI outputs, drawing inspiration from cognitive science and psychology.
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