Using AI in Group Projects

A group project succeeds when members understand the goal, divide work fairly and integrate their contributions. Cornell’s teaching guidance recommends clear roles, responsibilities and grading standards for collaborative work; its student guidance asks groups to follow the instructor’s academic-integrity expectations. AI can reduce clerical work such as drafting an agenda or turning approved notes into a task list, but the group still needs to make decisions together. Begin by reading the assignment and agreeing on permitted tools and disclosure requirements. Break the project into deliverables, dependencies and review points. Assign an owner for each task and a separate reviewer for important factual claims. Ask AI to propose an agenda or identify missing handoffs, then let members revise it. A generated task list can assign work unevenly or omit an important step. Record decisions in a shared space that everyone can access, including why a plan changed. If a meeting is recorded, get the permission required by the course and participants before uploading audio or a transcript. For research or writing, keep source checking tied to the person who uses the evidence. A fluent AI summary may misrepresent a paper or merge teammates’ ideas without attribution. Maintain a version history of drafts and notes so each person can explain their part. Discuss conflicts directly; do not let a chatbot speak for a teammate or decide whose contribution counts. Review the combined product for consistent terminology, citations and alignment with the rubric. Before submission, verify every member understands the final work and the group’s AI-use statement is accurate. Course policies may distinguish collaboration from unauthorized outside help. A good AI-assisted group process uses automation to clarify tasks while preserving human accountability, equal participation and a final artifact that the team can defend.