This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT. Given the pressing need to teach "critical AI literacy", discussion of metaphor provides an opportunity for inquiry and dialogue with space for nuance, playfulness, and critique. Using a collaborative autoethnographic methodology, we analyzed metaphors from a range of sources, and reflected on them individually according to seven questions, then met and discussed our interpretations. We then analyzed how our reflections contributed to the three kinds of literacies delineated in Selber's multiliteracies framework: functional, critical, and rhetorical. These allowed us to analyze questions of ethics, equity, and accessibility in relation to AI. We explored each metaphor along the dimension of whether or not it was promoting anthropomorphizing, and to what extent such metaphors imply that AI is sentient. Our findings highlight the role of metaphor reflection in fostering a nuanced understanding of AI, suggesting that our collaborative autoethnographic approach as well as the heuristic model of plotting AI metaphors on dimensions of anthropomorphism and multiliteracies, might be useful for educators and researchers in the pursuit of advancing critical AI literacy.

翻译：本研究探讨如何通过讨论人工智能隐喻，帮助建立对塑造我们理解AI系统（特别是ChatGPT等大型语言模型）的认知框架的意识。鉴于教授"批判性AI素养"的迫切需求，隐喻的讨论为探究和对话提供了空间，容纳了细微差别、趣味性和批判性。采用协作式自民族志方法，我们分析了来自多种来源的隐喻，并根据七个问题对每个隐喻进行个人反思，随后会面讨论各自的解读。我们进一步分析了这些反思如何促成Selber多元素养框架中界定的三类素养：功能性素养、批判性素养和修辞性素养。这些素养使我们能够分析AI相关的伦理、公平性和可及性问题。我们沿着隐喻是否促进拟人化这一维度进行探究，并考察此类隐喻在何种程度上暗示AI具有感知能力。研究结果凸显了隐喻反思在培养对AI的细致理解中所起的作用，表明我们的协作式自民族志方法以及将AI隐喻映射到拟人化和多元素养维度上的启发式模型，可能对致力于推进批判性AI素养的教育者和研究人员具有实用价值。