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This study explores how discussing metaphors for AI can help build awarenessof the frames that shape our understanding of AI systems, particularly largelanguage models (LLMs) like ChatGPT. Given the pressing need to teach "criticalAI literacy", discussion of metaphor provides an opportunity for inquiry anddialogue with space for nuance, playfulness, and critique. Using acollaborative autoethnographic methodology, we analyzed metaphors from a rangeof sources, and reflected on them individually according to seven questions,then met and discussed our interpretations. We then analyzed how ourreflections contributed to the three kinds of literacies delineated in Selber'smultiliteracies framework: functional, critical, and rhetorical. These allowedus to analyze questions of ethics, equity, and accessibility in relation to AI.We explored each metaphor along the dimension of whether or not it waspromoting anthropomorphizing, and to what extent such metaphors imply that AIis sentient. Our findings highlight the role of metaphor reflection infostering a nuanced understanding of AI, suggesting that our collaborativeautoethnographic approach as well as the heuristic model of plotting AImetaphors on dimensions of anthropomorphism and multiliteracies, might beuseful for educators and researchers in the pursuit of advancing critical AIliteracy.

Assistant, Parrot, or Colonizing Loudspeaker? ChatGPT Metaphors for Developing Critical AI Literacies