AI in the Public Eye: Investigating Public AI Literacy Through AI Art
AI in the Public Eye: Investigating Public AI Literacy Through AI Art
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公众眼中的人工智能：通过人工智能艺术调查公众人工智能素养
DOI：
10.1145/3593013.3594052
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Hemment D
中科院分区：
文献类型：
--
作者：
Hemment D
扩散模型和大型语言模型的最新进展为新一代强大且易于使用的工具提供了基础，其中一些最公开可见的应用程序用于艺术创作。然而，这些工具几乎没有为更深入地了解人工智能系统提供空间，而公众对它们日益增长的兴趣可能会掩盖长期与其他形式的人工智能合作的充满活力的艺术家社区的注意力。我们探索人工智能艺术的潜力-特别是人工智能既是工具又是主题的工作-以促进公众的人工智能知识，并考虑在当前生成人工智能热潮之前开发的策略如何在今天继续相关。我们研究了关键人工智能艺术家的策略，以帮助公众理解人工智能，并增强非专家的可读性。本文还探讨了艺术家与人工智能研究人员和设计师之间的合作如何阐明与人工智能发展相关的关键技术和社会问题。这项研究涉及三位与人工智能合作的专业艺术家和一组跨学科的学术参与者之间的研讨会。本文报告了这些研讨会，并介绍了艺术家表达的意图和策略，以及与研究社区有关的公共AI素养的见解。我们发现，关键的人工智能艺术可以将底层技术系统与权力的结构性问题联系起来，并促进体验式学习，这种学习是定位和体现的，重视解释而不是解释。研究结果还表明了围绕人工智能技术的艺术、伦理和政治经济学进行跨学科对话的重要性，以及这些对话如何融入人工智能设计过程。
Recent advances in diffusion models and large language models have underpinned a new generation of powerful and accessible tools, and some of the most publicly visible applications are for artistic endeavour. Such tools, however, provide little scope for deeper understanding of AI systems, while the growing public interest in them can eclipse notice of the vibrant community of artists who have long worked with other forms of AI. We explore the potential for AI Art – particularly work in which AI is both tool and topic – to facilitate public AI literacies and consider how tactics developed before the current generative AI boom have continued relevance today. We look at the strategies of critical AI artists to scaffold public understanding of AI and enhance legibility for non-experts. This paper also investigates how collaborations between artists and AI researchers and designers can illuminate key technical and social issues relevant to the development of AI. The study entailed workshops between three professional artists who work with AI and a cross-disciplinary set of academic participants. This paper reports on these workshops and presents the intentions and strategies expressed by the artists, as well as insights of relevance to the research community on public AI literacies. We find that critical AI art can link underlying technical systems to structural issues of power and facilitate experiential learning that is situated and embodied, valuing interpretation over explanation. The findings also demonstrate the importance of transdisciplinary conversations around art, ethics and the political economy of AI technologies and how these dialogues may feed into AI design processes.
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影响因子：
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作者：
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DOI：
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