AI Policy

Table of Contents

TL;DR

No AI use of any kind, period (this includes Google’s AI overview on google searches). First offense gets a warning. Second offense gets a zero on the assignment–no exceptions.

Guiding Principles

Similar to how you have to learn to do multiplication before using a calculator, it is essential that you learn the fundamentals or you will not be successful as an engineer or cyber-security expert.

This class teaches the fundamentals of computer systems. If you use AI in this course and do not learn to handle the fundamentals on your own you will severely limit your capabilities and the success of your college degree and future career.

These policies are grounded in the following educational goals:

  1. Reduce “effort outsourcing”: When AI is allowed to solve labs and problems for students, they are effectively outsourcing their efforts. An integral part of these introductory classes is building the necessary skills and knowledge to tackle real-world engineering problems, which requires students to invest personal time in learning, failing, and developing.

  2. Provide realistic expectations: Engineering is a difficult discipline, and this class provides a reasonable but challenging entry point designed to communicate the need for dedication and effort. If students outsource challenges to AI early on, they put themselves at risk of being unable to complete the major when later challenges cannot be solved by AI. It is better to discover the major is not the right fit in the first class, not the fifth.

  3. Increase student engagement: Provide motivation and reasoning for students to develop skills without the assistance of AI. Demonstrate the value of a personal knowledge base, and encourage students to participate and collaborate in their learning. Heightened student collaboration improves test scores, increases major completion rates, and helps prepare students to work on real engineering teams.

Policy

We hold to the official department policy on AI. The use of AI in any capacity is not allowed. Students are expected to develop these basic coding skills before they learn how to use advanced tools, including AI, to assist them in the design process. This includes but is not limited to:

  • Copying code from AI and submitting it as your own work. This includes agentic tools and Google AI overview.
  • Using AI to solve labs, homework problems, or projects.
  • Passing the lab prompts or provided lab code into an AI system.
  • Using AI to generate code or lab assignment submissions (including co-pilot within VS Code).
  • Using AI to generate answers to quizzes, exams, or homeworks.

Enforcement Policy

Using AI constitutes an unfair advantage and is considered cheating. This policy enforces a one-warning system:

  1. First offense: Students using AI are given a clear, friendly, and direct reminder of the policy.
  2. Second offense: Students who continue to use AI where prohibited will receive a 0 on that assignment, without question. This is likely to result in a report to the Honor Code Office and/or a zero in the course.