Mechanistic Literacy in the Age of Generative AI: Critique‑Centered Pedagogy in Graduate Organic and Medicinal Chemistry

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Poster Presentation

Presenters: Dr. Amol Kulkarni, Associate Professor, Chemistry and Biochemistry

This session examines how generative AI can be incorporated into graduate‑level organic and medicinal chemistry as an object of analysis rather than a source of answers. It focuses on the design of critique‑centered assignments in which PhD students evaluate AI‑generated mechanisms, retrosynthetic plans, and synthetic strategies for complex targets and catalyzed reactions. By working through examples from an advanced organic/medicinal chemistry course, participants will see how AI outputs can be used to expose gaps in mechanistic reasoning, stereochemical control, and strategic planning, and how structured critique can reinforce students’ disciplinary expertise.

The challenge this session addresses is the disconnect between widespread access to generative AI and the expectation of deep, domain‑specific reasoning in graduate STEM education. In advanced chemistry courses, students can now delegate mechanism and synthesis tasks to AI without engaging the underlying concepts, yet these tools also have genuine value for exploring alternative pathways and revealing blind spots. The session frames a concrete opportunity: designing AI‑mediated assignments that require students to analyze, correct, and reflect on AI proposals, thereby strengthening mechanistic thinking, ethical AI literacy, and preparedness for research environments where AI will be present but not reliably correct.