In AI-saturated writing environments, students can generate “good enough” documents without ever asking a deeply human question: Who am I writing for, and what do I owe them? This session offers a humanities-forward approach to technical writing that treats audience identification as ethical care and human-in-the-loop reasoning. I share a sequence of classroom practices, including stakeholder mapping, persona interviews, community agreements, and feedback circles, that moves students from generic audience labels to real, accountable relationships.

These practices strengthen clarity and usability, and they also reduce online isolation by helping students see peers and publics as present, named, and worth listening to. Participants will leave with adaptable prompts and assessment moves that require meaningful human intervention, such as weighing tradeoffs, anticipating consequences, and evaluating AI-generated text, visuals, and data through empathy and ethics. We will also discuss transparent AI use policies that position students as responsible authors and collaborators. The goal is a classroom village where technology supports critical thinking, curiosity, and humane communication.

Presenters

• Lynn Strong ldw0027@auburn.edu, University of South Alabama