Professor Hansun Zhang Waring, a conversation analyst at Teachers College, Columbia University, and her colleague have researched AI conversation, identifying three missing elements. The first is emergence, as human conversation is built in real time, while AI arrives pre-assembled. The second is recipient design, where a person talks to you specifically, unlike AI. The third is indexicality, as every exchange depends on shared context that AI lacks. Dr. Waring also studies a framework called FAB for productive conversation. F is for fostering, creating space where people feel free to contribute through small things like eye contact and timing. A is for attending, actually listening instead of preparing your next point. B is for balancing multiple demands, holding what you want to say alongside what the other person needs. The article highlights the “very good” problem, where saying “very good” in a conversation actually shuts it down. A student gives an answer, the teacher says “very good,” and the moment is finished, leaving almost no room to ask more or keep thinking out loud. This pattern appears everywhere, including when an AI gives a complete, polished answer. The exchange technically worked, but nothing new had room to happen.