Can You Get Kicked Out of College for using AI?

Yes, you can get kicked out of college for using AI. While it may seem like a convenient shortcut, most universities now classify AI-generated submissions as academic dishonesty or plagiarism. Passing off machine-written work as your own violates the core of your school’s academic integrity policy.

Expulsion is the most severe penalty, but it is a real risk. The process typically starts with a failing grade or a formal disciplinary hearing. However, repeatedly violating the rules or using AI to cheat on exams can result in permanent dismissal. This leaves a lasting mark on your transcript, which can prevent other institutions from accepting you in the future.

To protect your academic career, follow these three simple steps:

• Review the syllabus: Every professor has different rules regarding AI tools.
• Ask for permission: When in doubt, clarify with your instructor before using AI for any part of an assignment.
• Write your own work: Use AI for brainstorming or outlining, but ensure the final draft is your own original writing.

The Current Landscape of AI Use in Colleges

AI Becomes Part of Everyday Academic Workflows

The innovations within the ever-changing technological landscape in recent years have introduced artificial intelligence (AI) services like ChatGPT by OpenAI, Claude by Anthropic, Copilot by Microsoft, and Gemini by Google, which are common and well-known examples of AI. AI services like ChatGPT have come to provide a convenient way to generate content, whether text, audio, or even images, and are also able to handle tasks like mathematics and computer programming.

Because students these days actively use technology as a tool in their learning journey, AI services are just the latest tool that many students, of all ages, are increasingly relying on

Many of these AI tools are even integrated into existing services, such as Google Docs and Microsoft Word. Students use these tools to complete their assignments, check them for grammatical or spelling errors (Grammarly is a popular service for this), and conduct research for their work.

AI has effectively become a one-stop shop for many students’ educational needs, as they feel that the use of AI is no longer optional, because it has become a necessary part of how they learn, especially when writing.

AI Use in Academia Has Created Concern and Backlash

However, the increasing use of AI in academia has not been controversial.

The use of AI is often considered dishonest by many students and teachers. They argue that using AI encourages students to rely on it to do their work for them, rather than using it as an assistive tool. This, in turn, stunts students’ ability to develop actual skills and even learn anything in the long term.

Additionally, AI presents a unique challenge when it comes to plagiarism: since all AI services are trained on the work of others, every time an AI tool generates text, it synthesizes content from existing work. This is essentially a form of plagiarism, which many institutions still prohibit.

However, given the widespread use of AI and its ability to produce legible text, educational institutions have struggled to define plagiarism in the modern era. This has led to uneven policy enforcement across colleagues and universities worldwide.

Students Feel AI Use is a Gray Zone

Most students who use AI often claim to be extremely comfortable using it in their work. They feel it helps them produce work faster and to a higher standard and helps them break through any mental barriers they might have when doing their assignments.

This belief has only been bolstered by unclear or non-existent policies on the use of AI in education. Most educational institutions are still defining the boundaries of what they consider acceptable or unacceptable use of AI.

However, this uncertainty has also had a negative effect, increasing the risk of being accused of using AI. These accusations, which do not often consider or even establish cheating intent, create significant stigma, and place an uneven burden of proof on the accused. The risk is especially pernicious, given that those who produce original work might still be questioned, as many people have developed their own perceptions of what constitutes “AI writing”.

Based on the above, it is likely that a student could face disciplinary action for using AI, but the chances of being kicked out of college might be low for many students. Overall, it is hard to say, as not all AI use is considered cheating, while some professors even encourage it.

How Common are False AI Accusations?

As the use of AI tools grows, educational institutions are trying to keep pace with regulating their use by students. However, detection methods used by educational institutions, such as Turnitin’s AI indicator or GPTZero, often produce false positives.

This is because AI use is often determined through so-called AI-detectors. These detectors themselves are immensely flawed, as they often are unable to distinguish language written by a human from language generated using AI. This can often be seen by having an AI detector assess someone’s written work and then having it also assess, for example, the United States Declaration of Independence; many AI-detectors, especially ones that are free to access, will flag even the Declaration of Independence as having a high chance of being AI-generated.

Proponents of AI tools often posit that as AI tools advance, AI-detection will as well, which might reduce the likelihood of false positives. However, critics argue that, as a tech that is trained on copious amounts of human-made text, image, sound, and video data, AI may never be able to fully produce something fully original and will still produce something plagiarized.

In addition to the above, the existence of AI has also led to an increase in suspicion towards all written text, as people have developed their own perceptions of what constitutes AI writing. A common example is the perception that the use of certain punctuation, chiefly the em dash (i.e., the “–” symbol), indicates that an AI was used to write the text. The problem with this perception is that the em dash has been in use as a punctuation mark for centuries, well before the existence of AI.

These perceptions also create confusion and suspicions among people about patterns in writing that they may perceive to have been the result of AI generation, without having any actual proof of misconduct.

All the above factors combined have started to create an environment of anxiety and unease with the use of AI, but also, ironically, with attempts at detecting and punishing the use of AI in education.

What Writing Factors Can Trigger a False AI Accusation?

Most accusations of AI-generated writing have some common underlying factors.

One of the most commonly cited reasons for an accusation of AI use is that a certain piece of writing is too “mechanical” or “formal” and uses vocabulary that is too refined and polished; the underlying assumption of the accuser is that the writer somehow is not capable of such writing, without assistance. Naturally, qualifying an accusation of AI use with this reasoning is highly problematic, as it penalizes someone’s effort to produce high-quality work, but also presumes a level of competence without judging a person’s work on its own merits.

Some accusations of AI use often cite the use of well-structured, even formulaic writing (such as in academic papers, lab reports, policy briefs, etc.) as evidence of AI use. Moreover, short pieces of writing in general have also come under attack. Someone sees a five-paragraph essay, and they assume that the writer will not have bothered to write it themselves, so they used AI to generate the essay.

AI use could also be flagged if someone writes something completely on their own but then uses assistive software such as Grammarly to spellcheck and grammar-check. The latter two are features that have existed in software like Microsoft Word for years before the existence of AI tools, and their use has never been controversial. However, the use of AI, which is particularly good at automated pattern recognition and information lookup, by services like Grammarly to check for writing errors, is considered by some to be sufficient grounds for misconduct for AI use.

Lastly, if AI is used to translate text from one language to another, which AI tools are quite competent at, AI detectors might flag the whole text as AI-generated.

AI Detection Tools are Limited in What They Can Prove

AI is a technological marvel that has the potential to be life-changing, but it is not without its faults, even if those faults may not exist in the future. At present, however, most AI tools in use have a key feature that is both their strength and the source of their biggest weakness: pattern recognition/analysis.

When AI is trained, it takes substantial amounts of written text and “learns” the inherent patterns in it, such as how grammar works, how certain pieces of information go together, etc. When a human user prompts an AI like ChatGPT to write text, ChatGPT produces text that approximates what a user might want; that is, the AI produces a piece of polished-looking writing that it thinks looks like what the user’s prompt describes.

There is an important nuance at work here: the text produced by AI is not an answer to a question, but a sophisticated algorithm’s impression (which is based on enormous amounts of training data) of what the answer to the question might look like. This is why AI-generated text often has fabricated references to books, academic papers, and other materials that do not exist (a phenomenon often called “AI-hallucination”).

For this reason, AI detectors also fail to do their job reliably, as they rely on pattern analysis rather than authorship verification, and focus on probabilistic outputs rather than certainty.

Adding to the complexity of AI detection is the fact that some AI detectors are more accessible than others because they might be free or have truly little cost, but there is immense inconsistency across different AI detectors. Ultimately, the use of AI detectors comes with an inherent risk of flagging clearly human-written texts.

Certain Student Groups are More Vulnerable to Falsely-Flagged AI Use

As AI-detectors work by looking for patterns and approximating what might be AI-written text, they are prone to flagging work by some students more than others.

One category of students whose work might be flagged more often is English as a Second Language (ESL) students. These are students for whom English is a second language, one that they use in an academic environment in many cases. As non-native speakers, especially in an academic setting, ESL students’ writing styles might be prone to very formal, sometimes even archaic, written expressions. Their writing might appear “stiff” and verbose to a native speaker, who may write in a more casual voice.

Due to the nature of their writing, ESL students’ work might be flagged as AI-generated by AI detectors: these detectors might assess the work alongside the work produced by native speakers, and might conclude, through probabilistic determination, that the ESL students’ work used AI for polish.

This problem also affects many neurodivergent students, many of whom might have communication ticks or styles developed over the years through special education assistive writing programs (for example, IEPs) that might lead them to over- or even under-articulate things. Writing with these characteristics is often falsely flagged by many AI detectors.

Lastly, students in Science, Technology, Engineering and Mathematics (STEM) fields/subjects, who often have to write very rigorously structured papers and assignments with precise language, also struggle to prove that their work was human produced.

What Happens When a Student is Accused of Using AI Improperly?

What Immediate Academic Penalties Can Follow an AI Accusation?

Punishment for the use of AI by a student who is considered cheating or in any way unethical by the student’s school/university can lead to disciplinary action. These can take the form of:

• Failing an assignment
• Failing a course
• Academic probation
• Loss of scholarships
• Suspension or expulsion

What Long-Term Consequences Can Extend Beyond the Classroom?

If a student is determined to have used AI in a way that is considered misconduct, the effects of their penalties might extend beyond any immediate punishments. These can include:

• Harm to graduate school applications
• Damage to internship opportunities
• Damage to employment prospects
• Reputational consequences, especially in ethics-oriented or faith-based institutions

How Can Students Respond Effectively to a False AI Accusation?

What Should a Student Do First After Being Accused?

Being accused of something that you did not do is always stressful and brings with it a host of emotions ranging from shock, anger, and extreme anxiety. However, in the event of a false accusation, it is important to keep a few things in mind, as a student’s conduct after an accusation might also be scrutinized.

Primarily, it is important to remain calm, polite, and professional in all communications with teachers/professors. While it may feel unfair and even insulting to have been accused, it is important to remember that a professor is also just trying to do their job, part of which is to make and then enforce a set of rules that apply equally to every student. Therefore, it is important to take accusations calmly and in good faith, without assumption of malice on a professor’s part.

From there, it is very crucial to maintain communication and collect information, to establish a clear set of facts and ask for any clarifications if necessary. Accused students should ask their professors to provide them with specific evidence that they consider is proof of AI use, especially in cases where an AI detector was used; in such a case, students should ask their professors which detector was used and should also request a copy of the detector’s assessment report.

Once a clear line of communication is established and the student also has evidence from the professor, it is useful to review the school/college’s policies on AI use, plagiarism, etc. This helps keep things in perspective, without devolving this sensitive matter into subjective assertions about what should or should not be considered fair use of AI. Moreover, if the policies are unclear in some way, that could be brought up, as that is a legitimate policy design failure.

Another key step an accused student could take is to submit samples of previously submitted work that were not flagged, or even notes/outlines of the current flagged work. This helps to establish credibility and comparison with past work, showing a consistent voice and a pattern where a student has done their own work rather than generating it using AI.

Lastly, it should be well within reason in each case where a student is accused of using AI to request a human reviewer. As discussed earlier in this very article, AI detectors are prone to error and misjudgments. Requesting that another professor review your work might be both useful and even warranted.

Author’s Note:  Dr. Amanda Stewart

Is it safe to say that everyone has used AI, either in their professional or personal life? As a Student Defense Advisor, I have spent hours with clients and looking over documents when a student is faced with cheating allegations. Specifically, when the allegation is the use of AI. The way we advocate for a student being accused of using AI is different from someone accused of taking a phone into a secure testing environment. My colleagues and I have quickly seen an emergent tool that requires us to strongly impress upon the school that AI detectors are faulty and that using the argument that the student should not be able to write that well is a poor position to take.

When I was completing my dissertation, I would save my documents and each file started with the date that I saved the document. I was never accused of misconduct, but I know that I could have shown my committee the time I took editing my document. During my writing, I would even add comments to the document. I know, based on my personal and professional experiences, the more drafts and notes a student has the better. So, I would strongly suggest keeping dated drafts, notes, and comments!

What Evidence Can Help Build a Strong Defense against the Use of AI?

Each assignment, paper, or other submission that a student works on tends to have an entire trail of work behind it before it reaches the proverbial finish line: notes, outlines, drafts, etc. All these things become potentially crucial evidence for defense in cases where a student is accused of using AI.

So, if a student is accused of using AI, they should share the following with the professor:

Version history from Google Docs or similar platforms

• Version history from Google Docs or similar platforms
• Saved drafts, handwritten outlines/brainstorming notes, and reference lists Saved drafts, handwritten outlines/brainstorming notes, and reference lists
• Communications about the work

Version history from Google Docs or similar platforms

Many students use Google Docs for writing assignments because of the convenience it offers. Being a cloud-based tool, it does not require a user to work with a specific file on a specific laptop/computer; a student could start a Google Doc and begin working on it wherever they are, using whatever device.

This can have the added advantage of there being a version history of the Google Doc, which is immensely useful in proving your case if you have been accused of using AI. By showing your professor the document version history, you can demonstrate a history of working on the assignment yourself, with clear proof of which ideas were yours and from where you found them.

Saved drafts, handwritten outlines/brainstorming notes, and reference lists

Even if a cloud platform like Google Docs was not used, using any word processing software creates a file within which the student must work. By simply maintaining, for example, a Word file, a student creates an inherent file history, whereby the Word file can be checked for the date of creation and the date it was last updated. An ideal additional step is to save a new draft Word file for every date you work on your assignment, so that there is a consistent step-by-step picture of how you progressed through your work overtime.

Another viable step that an accused student could take is to keep all the other materials related to their assignment: the poorly scribbled notes in the corner of a notebook page during a lecture, the hand-written bullet-point brainstorming outline on a loose piece of paper, etc. A common “supporting” document is often the list of references that have been used, along with their PDFs and any notes on those PDFs, especially if the PDFs themselves have sections highlighted by the student or have comments left as notes.

Communications about the work

Online communication is ubiquitous, with text messaging and email being a daily fact of life. Students can use this to their advantage if they have text messages or emails with fellow students or even their professor where they are talking about their work (expressing their ideas about the work, their concerns, etc.).

This further helps establish credibility in favor of the accused student, as it can demonstrate that they actually put time into the work that is now being falsely flagged for AI use.

How Can a Student Strengthen the Review Process?

If a student is accused of using AI, it is likely that there will be a process and a lot of back and forth before they are either penalized or “acquitted”. It is especially important that they take a few basic steps to strengthen the review process in their favor.

• Request human review of the flagged work: As already mentioned, the student should point out the inherent flaws in AI detection tools and should thus request review either by a different professor or an independent academic committee.
• Compare detector results against known human-written samples: A useful exercise to demonstrate the flaws of an AI detector is to take a known and irrefutable piece of human writing (such as the United States Declaration of Independence) and run it through the same detector that flagged the work being accused of AI use. If the detector claims any amount of AI use in this human-produced writing, it can strengthen the student’s case that they have been falsely accused.
• Show process-based evidence rather than only final output: Showing that you wrote something by sharing notes, early drafts, and outlines can be a good way to establish credibility, as this way you show your process, rather than argue for the strength and quality of the final work. Doing this can also show how the student constructed and structured their argument, rather than showing the end result.

How Can Students Proactively Reduce the Risk of Being Falsely Accused?

Adopt Transparent Writing Practices

As discussed in detail earlier, students should develop writing habits whereby they:

• Use writing tools that save progress automatically
• Use platforms with revision history and tracked changes
• Preserve their drafts, notes, outlines, and sources, especially when handwritten

Use AI Ethically Without Increasing Risk

Students should develop a list of personal best practices when it comes to using AI. This can be a set of rules that guides them each time they start work on a new assignment, where they look at, for example, a checklist that says:

• Use AI sparingly, and only when expressly permitted by the education institution
• Use AI as support (for example, grammar and spelling correction) rather than replacement (i.e., generating work outright)
• Rewrite any AI-assisted material in the student’s own voice, to maintain consistency
• Transparently declaring AI use, especially when required, but also when appropriate, even when not required; this has the effect of signaling honesty.

Understanding Institutional Policy as a Preventive Step

In one’s education, it is important to remain aware of all important policies regarding assignments, lecture attendance, and other matters. Not only does this help students keep sight of what the rules are at their educational institution, it also helps them prevent any undue stress, as institutional policies can also be helpful guidelines on what to do, in addition to telling students what they shouldn’t do.

Any student looking to use AI must do the same level of due diligence as well. They should start by checking their syllabus for each course, as that is where professors provide outlines and overviews of all course materials that will be covered, as well as providing a handy set of rules and policies with which the professor will govern their course. Some professors may be permissive in using AI by students, whereas others may prohibit it. It is important to know which side of the spectrum your professor might be on!

For that matter, the best course of action may be the most direct: students should simply ask their professors whether they can use AI tools to do assignments. College professors are known for their candidness and for keeping a pragmatic level of communication with their students. Asking them directly about AI could be the easiest and quickest way to know where they stand, removing any doubts or the need for guesswork.

Lastly, it can be beneficial to look at college-wide policies, such as those on academic integrity, along with any major announcements. Most educational institutions have guidelines on AI use tucked in with policies on the use of technology, as well as the rules for plagiarism. Similarly, college-wide announcements are often communicating on special issues that are meant to be in urgent focus; these announcements could potentially cover AI use, which schools like Harvard and Stanford have done in the past.

What Ethical Questions does AI Raise in Academic Integrity?

AI Use is Also a Moral issue, Not Just a Policy issue

All current AI models, whether ChatGPT, Gemini, Copilot, or Claude, are trained on substantial amounts of data. This includes material that has been publicly and freely available on the internet for years, as well as proprietary data such as books, artwork, music, and other media.

Regardless of the source and nature of data, all AI service providers have made no secret of the fact that they have trained their proprietary models on the work produced by others; this training has been done without attribution to the original content creators, their permission, or even knowledge, much less compensation.

As a result, the use of AI in general has created a lively debate in recent years as to the ethics of its use, since AI is considered by its detractors to “steal” people’s work to enrich corporations that train models that they charge people a subscription fee to use. Therefore, there are those who feel that using AI reflects a lack of personal honesty and integrity among those who use it, as they are more concerned with outcomes than the process that creates outcomes.

For students, there is an additional issue: many believe that using AI offloads executive function to external software, preventing students from truly learning and growing. In other words, detractors of AI use in education argue that using AI in school makes students less capable, regardless of whatever degree they obtain. Additionally, for students, the ethical responsibility associated with the use of AI may carry added weight when they study in values-based institutions, as academic conduct involves more than avoiding punishment.

Original Thought Still Matters in the Age of AI

The proliferation of AI use has led people to grow increasingly suspicious of all content, whether online or in print. The effect is akin to the feelings people had when mass production became the norm, such that a factory-made statue, though it could be produced cheaply and quickly, was perceived as less valuable than a statue made by hand.

This is also the case in academia: since everyone knows what AI is capable of producing, there is now an even bigger premium on original ideas, developed in the “old-fashioned” way of conducting deep research and then synthesizing the lessons from this research into novel analyses.

Aside from these reasons, many believe that merely “producing” work to get a good grade is not enough, as grades should reflect the actual effort that went into the work they represent. Similarly, a degree on its own is not enough; it should reflect earned learning and serve as an important milestone in a person’s growth.

Most important of all is concern about the long-term use of AI. If a student becomes so habituated to using AI that they can barely do any task on their own anymore, their own executive function suffers. Additionally, many AI models tend to produce similar responses to the same question, raising concerns that overreliance on AI can diminish a student’s authentic voice or even ideas; everyone appears to regurgitate the same thing, creating a false sense of consensus in academia.

How Do Faculty View AI Use, Student Denial, and Misconduct Claims?

Why Might a Student Deny Improper AI Use?

Since AI use and AI detection are both becoming increasingly common in education, students who feel they have been falsely flagged as having used AI might especially be defensive in contesting allegations.

This is, however, understandable as being flagged for AI might feel like a serious accusation, especially if there is strict disciplinary action for it. Students might fear being labeled as a cheater, which carries its own stigma.

However, a student may deny the use of AI for one very simple reason: they did not use AI. As this article has already established, AI detection at present is still prone to errors, and many students often find their work falsely flagged. These students must be given grace and an opportunity to explain themselves.

The latter should also be extended to those who may have used AI, but did not know it, because they did not know that a tool they used (e.g., Grammarly) counts as AI. These students can simply be made aware of what counts as AI and provided an explanation on the difference between use and misuse of AI (e.g., OK when using for brainstorming but not OK to write a paper, whole or in part).

Lastly, some students may use AI but may not want to admit it because they were deliberately dishonest and tried to cheat. In such cases, students are simply trying to escape the consequences of their actions.

How Can Faculty Address Student Denial More Effectively?

Faculty can address student denial more effectively by taking the following three core steps:

• Step 1: Explaining what counts as AI and what counts as misuse
• Step 2: Clarifying the difference between acceptable use and misconduct
• Step 3: Acknowledging how difficult it is to prove AI use conclusively

Strategies Faculty Can Use When They Suspect Misuse of AI

Trying to determine misconduct from a student is a delicate and fraught act, as professors might not want to falsely accuse anyone and cause unintentional harm. So, the following are a few ways that faculty members at any educational institution can attempt to prevent the misuse of AI:

• Appealing to the integrity and character of students
• Appealing to long-term career and reputation concerns of students, so that they are motivated to avoid misconduct in AI use
• Appealing to the fear of academic punishment for misusing AI

How does the Grammarly Authorship Integrity Report Fit Into This Discussion?

Grammarly is rolling out a feature called Authorship, which is meant to track the entire writing process from start to finish. The feature will track how many times a user (i.e., a student) cuts, copies, or pastes something into their working document from websites or from other programs. Based on this, Grammarly will produce a final report once the assignment is finished, determining the number of “original” words versus those that originated from AI text generators.

This new feature is being positioned by Grammarly as part of the broader conversation around authorship and verification of written educational work in the age of AI. It is, therefore, relevant to disputes about the writing process and originality.

How Do Institutional AI Policies Define Ethical Use Versus Academic Misconduct?

AI Policies Differ Across Colleges and Universities

Many educational institutions have academic integrity policies regarding the use of AI. Some, like Vanderbilt University, consider work done using AI-generated text to be plagiarism, especially if done without prior permission or notification.

However, some institutions, like the University of Michigan, permit the use of AI tools so that students can do research, brainstorm ideas (the reasoning being if they can do this with other people, why not AI as well?), or just improve what they write themselves; however, students are required to disclose AI use.

In most institutions, faculty members set their own rules, and so one professor may permit the use of AI, which another might not.

How Can Ethical AI Use Be Distinguished from Academic Dishonesty?

Many institutions consider different use cases for AI in education. Brainstorming or grammar support is often treated differently from submission-level generation. However, submitting AI-generated writing as one’s own crosses the line into misconduct.

In other words, the student’s intent and the extent of use matter when considering their conduct in line with institutional policies.

What are Common Examples of Ethical AI Use in Academic Work?

Common ways to use AI in an ethical manner, i.e., avoiding misconduct, are as follows:

• Idea generation
• Research support
• Grammar checking
• Using AI as a tool rather than as a substitute for original thinking

Why is Staying Updated on AI Policy and Practice So Important?

The Relationship Between AI and Education Still Evolving

AI tools have developed fast, and their adoption by everyone, including students, has spread just as quickly. Many people argue that AI tools are still being refined, and so there are growing pains with this ongoing technological innovation.

This is true for education as well, as educational institutions continue to better their understanding of AI and refine their AI policies accordingly. Definitions of legitimate uses versus plagiarism, for example, are constantly changing or being updated, with many colleges still finding the best ways to enforce policies.

What Should Students and Faculty Do to Stay Informed?

Considering how much regarding AI is still in flux, the best that any student or faculty member can do is to remain vigilant by:

• Monitoring all institutional policy updates
• Reviewing course-level expectations regularly
• Treating AI rules as dynamic rather than fixed

AI is becoming normalized in academic workflows, which creates uncertainty and accusations. False positives in AI detection are becoming common because AI detection tools and standards are currently imperfect.

However, accusations still carry weight and can lead to major academic and long-term consequences. Students need strong defense strategies and preventive habits to navigate this new educational paradigm, where ethics and integrity remain central. Faculty must also remain vigilant and navigate ambiguity carefully.

Ultimately, institutional policies determine what counts as allowed use of AI. Ongoing updates to these policies are necessary because the AI and education landscape keeps changing