Universities across the country, including the University of Maryland (UMD), are putting forth AI use policies, but with new policies and technology evolving, students are unclear on how these AI use policies work in practice. If you’re being accused of inappropriate AI use at UMD, the LLF National Law Firm can advise you. To learn how we can protect your academic career, call us at 888-535-3686 or use our online form.

The University of Maryland’s AI Use Policy

The University of Maryland’s AI policy is referred to as the Guidelines for Use. The University states that the purpose of the guide is to “provide best practices for ethical, responsible, and equitable use of GenAI in teaching, learning, scholarship, and administrative functions. The goal is to promote transparency, enhance productivity, and uphold UMD’s core values of integrity, inclusivity, and respect.” The Guidelines detail the permissible and impermissible uses of AI in a variety of contexts.

As a student facing AI-misconduct allegations, you need to be familiar with both the policy as it relates to students and professors. While UMD’s Guidelines discuss them both in separate sections, it is even more important to understand the processor’s obligations. When a professor violates the policy, and it results in your allegation of misconduct, you need to ensure you aren’t the scapegoat for your professor’s misstep. Below is an overview of each party’s obligations.

Instructors

At UMD, instructors are responsible for strictly defining the appropriate and inappropriate uses of AI in the classroom. Instructors should convey their specific classroom and course policies in their syllabus and in each assignment’s instructions.

Further, professors should be “help[ing] students develop critical thinking skills about the use of GenAI tools.” They shouldn’t be having students navigate incorporating AI into education alone. The school has done everything in its power to provide professors with the resources they need to accomplish this goal. This includes bringing UMD’s AI Literacy Module into the classroom. The school claims that once students have been guided through this model, they should be able to:

  • Articulate how AI-based tools
  • The benefits and risks of AI-based tools
  • Identify when AI is supplying inaccurate or misleading answers
  • How to fact-check AI output
  • Cite AI-generated work

In addition to the training model, UMD administration has provided professors with suggested language to be included in the course syllabus AI-use section to clearly outline how and when AI can be used in their courses. The document provides examples of specific language to be used in a few different scenarios, including:

  • Prohibiting AI
  • Allowing AI use in some cases
  • Allowing any AI uses

If your professor has failed in any of these suggestions or obligations, this is an important thing we need to highlight in your defense.

Students

Without straightforward guidance or where there is ambiguity, students should always assume that AI use is not permitted in a course. It is generally accepted for students to use AI as a learning tool, for things like practicing certain problems (for example, in math courses), exploring concepts, and other basic functions. In courses where students are allowed to use AI, UMD has an expectation that students will “acknowledge and cite their use of GenAI applications.” At the LLF National Law Firm, we assist you in identifying areas of weakness in the allegations against you and carefully review every aspect of the Guidelines.

Teaching Assistants, Graders, and Tutors

Teaching assistants, graders, and tutors must follow the policies of the professors on AI use. This means reviewing the syllabus and speaking to their supervisor if there is any ambiguity. If your AI-related accusations are due to work you did with a TA or tutor, you may not be in the wrong. If they assured you that your AI use was okay or encouraged use because they believe the professor would be okay with it, it means they are partially, if not wholly, to blame for your situation.

The Disciplinary Action Process for AI Misconduct Allegations at the University of Maryland

At UMD, AI-related misconduct is treated as academic misconduct, falling into the category of cheating/unauthorized assistance or plagiarism. When a UMD student is accused of AI-based misconduct, the allegations will be addressed by the Office of Student Conduct 

Complaint

When the Office of Student Conduct receives a complaint of AI misconduct, it will first decide if there is reasonable cause supporting the allegations.

Informal Resolution

The informal resolution process gives you two options to address the allegations without undergoing a formal hearing:

Academic Deferral

If this is a minor first-time offense, an Academic Deferral allows a student to bypass preliminary interviews. You would do this by accepting a zero on the assignment and completing an educational sanction. Most importantly, the AI misconduct allegation isn’t visible on your disciplinary record once the requirements are met. This is particularly important if you are considering graduate school or other post-graduate programs.

Informal Agreement

Alternatively, an Informal Agreement is available for students who admit responsibility and reach a consensus with the Director of Student Conduct and their instructor regarding appropriate sanctions. Both options require the student to waive their right to a formal Honor Review and appeal process, ensuring a swift resolution that prioritizes educational outcomes over adversarial proceedings.

Formal Disciplinary Action Process

Disciplinary Conference with the Director of Student Conduct

Your case may be resolved through a Disciplinary Conference with the Director of Student Conduct. This is used in minor AI misconduct cases, those that would not normally result in severe sanctions such as suspension, expulsion, or a permanent “XF.” You will get to present your defense and bring an attorney advisor to the conference. Your LLF National Law Firm attorney will prepare you and attend. The Director will then review the information using a clear and convincing evidence standard and issue a written determination.

Disciplinary Conference Board

A Disciplinary Conference Board provides a similar but includes student peer participation. The board typically consists of two students from the University Student Judiciary and a staff member from the Office of Student Conduct. Again, you may bring your LLF National Law Firm attorney for your defense. After reviewing the information, the board determines responsibility by majority vote using the clear and convincing evidence standard and issues a written outcome.

Honor Review

For the most serious allegations, particularly those that could result in sanctions such as a permanent “XF,” suspension, expulsion, or degree revocation, you will have the right to an Honor Review. This is a formal investigation conducted by an Honor Board composed of student members and faculty or staff, led by a Presiding Officer. You will be given advance written notice of the formal charge, access to the case file, and the opportunity to present evidence and question witnesses. Both the Community Advocate and the responding student may present arguments and closing statements. After deliberation, the Honor Board determines responsibility by majority vote using the clear and convincing evidence standard and may recommend sanctions. As always, your LLF National Law Firm attorney is permitted.

Determinations

If you are found guilty of AI misconduct at UMD, the disciplinary action the Office of Student Conduct may issue includes: 

  • Assignment failure
  • Grade adjustment of “XF”
  • Grade adjustment of “F”
  • Grade adjustment of a letter grade
  • Suspension
  • Expulsion
  • Degree revocation

If You’re Being Accused of AI Misconduct at the University of Maryland, the LLF National Law Firm Can Help

Don’t let an AI misconduct allegation ruin your grades, your academic career, and your whole future. Get started with the LLF National Law Firm Student Defense Team today by calling 888-535-3686 or reaching out online.

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