--- tags: ai --- # writing about AI ## questions * what form should writing about AI take? * what constitutes a blog post about an AI tool? * how can we--as the LL--articulate what it does? * the rhetorical moves * what is the relationship between the writing about AI and content intended for social media? ## forms * visuals * couple of short paragraphs of text * link to social media counterpart (if there is one) * links to tutorials * links to research/further reading/references? ## rhetorical moves * democratizing technical skills (e.g., coding/webdev) * AI challenges the idea of the single-authored work in visual realm esp. (long-held as an important critical intervention from humanists) * helping students do more ambitious multimedia projects * helping students get into the content of those projects rather than getting hung up on technical stuff * help students prepare for careers that will integrate AI tools and workflows (future workforce stuff) * should know how to interpret AI results (i.e., learn how to fact check, how to use it in an ethical and professional manner - like learning how to use research generally!) ## models * [Berkeley Artificial Intelligence Research blog](https://bair.berkeley.edu/blog/) * [distill blog](https://distill.pub/) ## notes * blogs a good place to: * create static representations of visual data (e.g., explaining what the AI applied from a literary text to a visual in Midjourney) * create + unpack new data visualizations that synthesize what was learned from an AI experiment captured on film/that's otherwise visual in nature * report on what's happening in the AI space * which could then maybe link to short videos that show how some tool works * like a roundup * reflect on our individual learning journeys using AI tools/metacognitive reflections on a specific project or something we can do now that we couldn't before * or maybe even something we couldn't get AI to do that shows its limitations * lean into the storytelling aspect of blogging/like features writing in a mag or newspaper * really lean into the public-facing component, foregrounding our lack of technical/engineering/coding expertise as a value-add in the space of AI tool exploration and using it as a tool for thinking and learning * most of the blogs I've seen so far are very technical, very much foregrounding the work a lab is doing to develop AI capabilities