How to talk about "AI" without adding to the anthropomorphization Emily M. Bender and Nanna Inie In our op-ed for Tech Policy Press ("We Need to Talk About How We Talk About 'AI'"), we made the case against the anthropomorphizing language that makes it harder to have clear discussions of what so-called "AI" technologies actually do, and when and whether to use them. But these ways of speaking are deeply ingrained at this point, and it takes work carve new conversational and writing habits. That work involves at least three steps: - Noticing which word choices are anthropomorphizing - Finding alternatives - Getting in the habit of using the alternatives In our research (summarized in the op-ed) we have been working on the first two steps, categorizing the kinds of anthropomorphizing language and using those categories to organize potential alternatives. De-anthropomorphizing language talks about computer systems in terms of their functionality (what people build and/or use them to do), assigns agency to people using systems and not systems, and avoids aggrandizing metaphors about cognition. We aim to find substitutes that are as self-explanatory as possible, so that you can just go ahead and use them without having to explain. (Though of course, if someone asks "Why are you calling it that?" that's also a great opening.) Some of these rephrasings may feel a little clunky, and they can end up longer than the anthropomorphizing shorthand. This means it takes a little more dedication to use them, but also isn't necessarily a bad thing. We should stop and think about the tech we are using, or even discussing, and what it actually does. We'll go through the categories of anthropomorphizing language we identified in Inie et al 2026, and give examples of de-anthropomorphized versions for each. Our suggestions Cognizer and products