I’m facilitating AI roundtables at my department’s Symposium and I’ve invited faculty members from across disciplines to share what they’re doing in their classes. I’v…

I’ve written a lot, on and off, about the importance of developing critical AI literacy, but I realize now that it is not enough, and I’ve recently started thinking about all of this wi…

If you’ve been following this blog, you know I’ve written about critical AI literacy, and as I’ve keynoted, taught, and workshopped this, I’ve been developing my model furth…

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.

How can colleges and universities best engage with artificial intelligence?This week the Future Trends Forum explores that major question from a new perspective. The experience of developing and implementing open education resources (OER) has given us many lessons and practices which we can apply to AI. We're hosting the authors of a new paper, "How do we respond to generative AI in education? Open educational practices give us a framework for an ongoing process": Anna Mills, Lance Eaton, and Forum favorite Maha Bali.https://journals.sfu.ca/jalt/index.php/jalt/article/view/843https://www.annarmills.com/https://www.lanceeaton.com/https://blog.mahabali.me/This event is powered by Shindig, the video chat event provider. On Shindig, audiences all can see one another and engage in private video chats sharing and discussing the content of the presentation. Event hosts may also bring selected audience members to the stage to ask questions or otherwise interact with guest speakers. Shindig; the dynamics of in person events, online.

To unpack this, we should first maybe unpack crticial, AI, and literacy. By critical, I mean this in multiple senses of the word. One is critical as in critical thinking, as in skepticism and quest…