Hahn Legal Group, APC founder and managing attorney Adrienne Hahn was recently featured in the Los Angeles Times for her work representing California students accused of improperly using artificial intelligence in their coursework.
The article examined the growing conflict between students and colleges as generative AI becomes more common in education. While schools are trying to protect academic integrity, unclear policies and unreliable methods of identifying AI-generated work can leave students facing serious accusations without convincing evidence that they cheated.
For Hahn Legal Group, APC, these cases are becoming an increasingly important part of the firm’s education law practice. Hahn told the Los Angeles Times that defending students against AI-related allegations is the fastest-growing area of the firm’s education caseload.
That growth reflects a larger problem on California campuses: Colleges are being asked to make disciplinary decisions about rapidly changing technology without consistent rules, dependable detection methods, or procedures designed for the complexity of these cases.
When Suspicion Becomes an Academic Misconduct Case
Not every AI cheating accusation begins with clear evidence that a student used ChatGPT or another generative AI platform.
An instructor may become suspicious because a paper sounds different from the student’s previous work, includes an unfamiliar method, uses unusually polished language, or receives a high score from an AI detection program. That suspicion may then be reported to an academic integrity office or disciplinary board.
The problem is that none of those circumstances necessarily proves misconduct.
A student’s writing may improve after tutoring, extensive revision, or additional research. A student may learn a formula or technique in another class. Multilingual students may use editing tools to improve grammar without asking AI to generate their assignments. Detection software may also flag writing that was created entirely by the student.
Once an accusation is made, however, the student may be placed in the difficult position of proving how they completed an assignment days, weeks, or even months earlier.
Adrienne Hahn Discusses a Case Involving a Math Formula
The Los Angeles Times article included an example from Hahn’s work involving a student who received a failing grade after using a math formula that had not yet been taught in the professor’s class.
The professor reportedly concluded that the student must have obtained the formula through AI because the student had not learned it from that particular instructor. In reality, the student had previously learned the formula in another course.
Hahn Legal Group, APC intervened, and the failing grade was removed.
The case demonstrates why an accusation should not be treated as proof. Conduct that initially appears suspicious may have a reasonable explanation. A student’s educational history, drafts, notes, communications, and prior coursework can provide context that an instructor or disciplinary officer did not initially consider.
It also shows why students must be given a meaningful opportunity to respond before a school imposes academic or disciplinary consequences.
AI Detection Tools Cannot Tell the Whole Story
AI detection programs are frequently presented as one piece of evidence in academic misconduct matters. These tools analyze patterns within a piece of writing and estimate whether the text may have been generated by AI.
An estimate is not the same thing as a factual determination.
AI detectors do not have direct knowledge of who wrote an assignment. They cannot see a student conducting research, revising a paragraph, meeting with a tutor, or working late in the library. They evaluate the finished text based on patterns their systems associate with AI-generated writing.
That can create problems when a school gives too much weight to a detection score. A flag may prompt further review, but it should not replace an investigation into the student’s actual writing process.
Unclear AI Policies Create Additional Confusion
Another challenge is that colleges and professors do not all define acceptable AI use in the same way.
One instructor may allow students to use AI for brainstorming or grammar assistance as long as they disclose it. Another may prohibit generative AI entirely. Some assignments may permit limited use while others do not. Policies may also change between semesters or appear only in a syllabus, assignment sheet, or class announcement.
A general concern about AI use should not be enough to establish that an individual student cheated.
Students Should Preserve Evidence of Their Work
Hahn told the Los Angeles Times that students facing AI accusations should gather evidence showing how they completed their assignments.
Useful documentation may include:
- Google Docs or Microsoft Word version histories
- Earlier drafts and outlines
- Handwritten or digital notes
- Research materials and saved sources
- Messages discussing the assignment
- Tutoring or writing-center records
- Prior coursework involving the same subject or method
- File metadata and timestamps
Students may also need to preserve the course syllabus, assignment instructions, AI policy, emails from the professor, detection reports, and notices from the school. These materials can become important when determining whether the college followed its own procedures.
Responding to an AI Misconduct Allegation
Students should take an AI cheating accusation seriously from the beginning.
An immediate emotional response to the professor may unintentionally make the situation more difficult. Before submitting a written statement or attending a disciplinary meeting, the student should review the accusation carefully, identify the applicable school policy, and preserve all available evidence.
Deadlines can be short. A student may have only a limited amount of time to challenge a grade, respond to an integrity complaint, request supporting documentation, or appeal an adverse decision.
The appropriate response will depend on the institution, the possible sanction, and the school’s disciplinary procedures. Public and private colleges may also be subject to different legal requirements, although both are generally expected to follow their established policies.
Hahn Legal Group, APC Represents Students Facing AI Accusations
Adrienne Hahn’s inclusion in the Los Angeles Times reflects the growing need for experienced guidance in AI-related academic misconduct cases.
As AI continues to change the classroom, disputes over what constitutes cheating are likely to become more complicated. Students should not assume that a professor’s suspicion or an AI detection score automatically determines the outcome.
If you or your student has been accused of using AI in violation of a college or university policy, contact Hahn Legal Group, APC to discuss the disciplinary process and the options available for protecting the student’s education and future.