Essays about a well-known book are among the assignments most vulnerable to misuse of generative AI, since a chatbot can produce plausible summaries of nearly any title. A paper on Because of Sex could be assembled without the student reading a chapter. Instructors need clear policies and assignment designs that make genuine engagement the easiest path. The goal is not surveillance but a course in which learning is visible.

Start with a clear, written policy about what kinds of AI use are allowed. Ambiguity is the main source of problems, because students may genuinely not know whether brainstorming with a chatbot counts as cheating. A good policy specifies what is permitted, such as grammar checking or generating practice questions, and what is not, such as producing text submitted as the student's own. Explaining the reasoning behind the rules helps students accept them.

The policy should also address disclosure. Some instructors require students to note any AI use and describe how it was used, which promotes honesty and gives you insight into student practices. Others ban AI entirely for certain assignments. Whichever approach you choose, state it in the syllabus and repeat it on the assignment sheet.

Design assignments that require real engagement

Prompts that ask for generic summaries are easy to automate, while prompts requiring specific, personal, or class-based engagement are harder. Ask students to connect the case of Dothard v. Rawlinson to a discussion you held in class, or to quote and analyze a particular passage they select. Requiring evidence from the text with page references makes it more difficult to fabricate. Such designs encourage honest work and also produce better writing.

• Require specific quotations or page references that can be checked against the book
• Tie the prompt to class discussions, lectures, or in-class activities
• Include process steps such as outlines, drafts, and reflection notes
• Ask students to explain their reasoning in a short oral or written follow-up
• Vary prompts across sections or semesters to reduce reuse of old answers

Use process evidence

Collecting evidence of the writing process makes it easier to see whether a student engaged with the material. Outlines, annotated bibliographies, and rough drafts show how ideas developed over time. A student who submits a polished essay with no earlier work raises questions, while one who shows steady progress demonstrates authenticity. This also benefits learning, since students receive feedback at several points.

Short in-class writing activities provide a baseline of the student's voice and skills. Comparing this with later submissions can help identify concerns, though it should be done carefully and without assumptions. Conversations with students about their work are often more productive than accusations. Many cases of misuse can be resolved through dialogue.

Be cautious with detection tools

AI detection software is not reliable enough to serve as the sole basis for an academic integrity charge. False positives can harm students, particularly multilingual writers whose prose may resemble machine-generated patterns. Instructors should treat any detection result as a prompt for conversation, not a verdict. Fairness requires evidence beyond a single score.

A better approach is to focus on prevention and on the quality of the work itself. Rubrics that reward specific textual evidence and original analysis tend to expose generic, unsupported writing. Instructors who know their students and assignments are often the best judges. This human judgment, supported by good design, is more reliable than any software.

Teach responsible use as a skill

Students will encounter AI throughout their academic and professional lives, so teaching responsible use is a worthwhile goal. Discuss when AI can help, such as clarifying a confusing passage, and when it undermines learning, such as writing the analysis. Encouraging students to verify AI output against the book models the critical habits you want them to develop. This approach respects their maturity and prepares them for real-world situations.

Instructors can also use AI themselves in transparent, limited ways, such as drafting rubric-based feedback that they review before returning. Modeling thoughtful use shows students what responsible practice looks like. Open conversation about benefits and limits builds trust. A course culture grounded in honesty is the strongest foundation for academic integrity.