  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.
