Portland Community College | Portland, Oregon

You Don’t Know What You’ve Got ’til It’s Gone: Authentic Voice and Generative AI

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Presented By: Melissa Goodman Elgar, Part-Time Faculty in Anthropology, Public Service, Education, and Social Sciences Pathway.

Summary

This Anderson Conference session explores generative AI through the lens of student voice, writing, learning, and equity. Melissa Goodman Elgar brings an anthropological perspective to questions many instructors are facing as students increasingly use AI tools for writing. Rather than presenting a single solution, the session invites educators to consider what they value about student writing and how AI policies can support learning while recognizing that these technologies are now part of the educational landscape.

The session distinguishes between generative AI, which can produce text from a prompt, and tools that help students edit or refine writing they have already created. Participants discuss concerns such as plagiarism, accuracy, critical thinking, attribution, and the possibility that AI-generated work may bypass important learning objectives. At the same time, the conversation recognizes that AI tools can provide useful support when instructors and students understand how and why they are being used.

A central theme is authentic student voice. Participants consider how instructors come to recognize a student’s writing through personal details, tone, experience, and ways of expressing ideas. Generative AI may produce polished writing while removing some of the individuality that helps instructors see a student’s thinking and development. Goodman Elgar encourages faculty to consider writing not simply as a finished product, but as a form of self-expression and a process through which students develop their identities and abilities.

The session also examines academic language and the power structures connected to expectations about “correct” writing. Students may enter college with different linguistic, cultural, socioeconomic, and educational backgrounds, and conventional academic language can present its own barriers. Participants are encouraged to make expectations transparent and think carefully about which forms of writing and AI assistance are appropriate for different assignments rather than assuming one approach will work across every discipline or course.

Finally, the presentation connects writing with the learning process itself. Goodman Elgar asks instructors to consider what cognitive skills their assignments are designed to develop, including synthesizing information, summarizing complex ideas, making connections, and expressing an emerging understanding. The session frames thoughtful AI use as an equity issue: students should have access to useful tools while still having opportunities to build confidence, develop functional skills, and discover their own voices.

Presentation outcomes

• Explore faculty perspectives and concerns about generative AI and student writing.
• Distinguish between generative AI tools that produce text and tools that support editing or refinement of student-created writing.
• Consider how generative AI may affect authentic student voice, self-expression, and instructors’ ability to observe the learning process.
• Examine academic language expectations through an anthropological and equity-focused lens.
• Reflect on the skills and learning processes that writing assignments are intended to develop.
• Consider appropriate boundaries and expectations for AI use across different disciplines, assignments, and learning outcomes.
• Explore ways to make expectations about writing and AI transparent to students.
• Identify approaches that support student confidence, identity, functional skills, and thoughtful use of AI tools.