Generative A.I. tools are rapidly evolving, and universities are quickly developing guidelines for how – and if – students should use them in the classroom. But what do students think? This op-ed, written by first-year college student Tylar Macintyre, responds to the growing use of A.I. detector tools to determine whether students have illicitly used generative A.I. chatbots to compose their writing.
Tylar Macintyre, “A.I. Detectors Are the Smoking Guns That Prove Nothing.” Venture, 5 March 2025
- Macintyre describes how teachers turn to A.I. detectors to check if a student’s writing is their own. What’s the central problem with this approach, according to Macintyre? What are the ethical issues with using A.I. detectors on student writing?
- Which groups of students are at a higher risk of being wrongly accused of using generative A.I. in unauthorized ways? Why is their writing flagged at a higher rate than other students?
- Macintyre’s argument draws on his perspective as a student. What is another view that could be part of this conversation about A.I. detectors and academic integrity? Find a place in Macintyre’s essay where he could insert this naysayer perspective. Use the templates from Chapter 6 to name this alternative view and introduce it fairly. How might Macintyre respond to this naysayer?
- So what? Who cares? Macintyre explains the consequences for students whose writing is falsely “flagged” by A.I. detectors. Who else, besides these students, is affected by the increasingly prevalent use of A.I. detectors by educators? How does the use of A.I. detectors in education affect students, teachers, and classroom environments more broadly? You can draw on your own experiences in your response.
- Some have argued that there is a new “cheating vibe” on college campuses fueled in part by online learning during the COVID-19 pandemic and the rapid development of generative A.I. Read this op-ed by a student at Washington University in St. Louis, who argues that academic integrity standards need to be redefined for the realities of the 21st century. What two main reasons does he give to support his argument? Respond to his argument: do you agree, disagree, or both?
They Say I Blog 
After reading this article about how Artificial Intelligence is significantly changing the way coursework is done I think it is truly hurting the students of our generation. The idea of AI for me personally, I disagree with it in its entirety which also means I agree with this article. I truly believe that at one point because this wasn’t a thing for my parents to use and a resource for them that we as students don’t need this resource either. This is also not helping the students like me, who don’t use AI and could be accused of using it when it is just their excelled writing. Because of AI, it makes me as a college student feel very unsure with any assignment I’ve turned in given these professors have begun to rely on these AI detectors when to me I don’t even use it for any of my assignments. Now don’t get me wrong, AI is a great tool for other reasons but for academic purposes I think it is the worst advancement that technology has ever come up with because it hurts in both ways whether your using it and get caught or if you don’t use it and get accused of that because others are relying heavily on it in every assignment they do. While it seems, many have argued that the positives and benefits of AI outweigh the negatives I strongly believe that this is the worst thing to have happened for education because it is not allowing us as students to use our brains properly and rely on a robot to give this generic answer that is not always the right answer or even the correct answer. So circling back to this article, I agree with all the points that have been made because this technological advancement is the worst thing to happen in our generation and all the points made about students, professors, and assignments are only hurting the students and isn’t displaying the work done in a positive light and rather are being looked at as students cheating when a lot of the time that isn’t the case.
LikeLike
After reading the article, I agree that AI is changing schoolwork in a negative way. I personally don’t like using AI for academic work, and I don’t think students today really need it just because it exists. One problem is that students who don’t use AI, like me, can still be accused of using it because teachers now rely on AI detectors that aren’t always accurate. It makes turning in assignments feel stressful even when the work is completely our own. While AI can be helpful in other areas, I think it creates more issues than benefits in school.
LikeLike
Concerns about academic integrity have led many people to argue that A.I. detectors are necessary in college classrooms. As generative A.I. tools become more common, instructors feel pressure to confirm whether student writing is original. Some commenters on this blog also describe how A.I. has changed education in negative ways, creating uncertainty for both students and professors. Against this background, Tylar Macintyre argues that A.I. Detectors are unreliable and may wrongly blame students, creating a situation where students feel guilty before they have done anything wrong.
My response aligns with Macintyre’s position because these tools often evaluate writing patterns rather than actual evidence of misconduct. Clear structure, strong grammar, or a formal tone can easily be interpreted as signs of A.I. involvement, which places honest students at risk. Students who are non-native English speakers or those who work hard to improve their academic writing may be flagged simply because their work appears polished. Rather than encouraging confidence, this possibility creates anxiety, making students fear that strong writing might be viewed with suspicion.
At the same time, the opposing side deserves more attention than Macintyre gives it. Teachers face genuine pressure, including large class sizes, limited grading time, and growing reports of students submitting A.I.-generated work. Imagine grading one hundred essays and noticing several that suddenly sound very different from earlier assignments. In situations like this, instructors may feel they have few realistic options to protect fairness for students who complete their work honestly. A.I. detectors, even with clear limits, can seem like a practical solution because they promise quick answers.
This reliance on software, though, can reshape the classroom in negative ways. A defensive learning environment develops when students avoid complex language or ambitious ideas because they fear being flagged. Teachers may also read assignments with suspicion instead of focusing on growth and feedback. As trust decreases, learning becomes less collaborative and more cautious.
There are cases where detector tools might still serve a limited purpose. Used carefully, a detector score could begin a conversation between teacher and student instead of ending one. In that role, it becomes a signal to investigate further rather than a final judgment.
A stronger long-term solution would be assignment design that shows the writing process clearly. For example, students could submit a proposal, a draft with revisions, and a final reflection describing how their ideas developed. This process makes it easier for teachers to see real thinking and reduces the need to rely on automated detection.
Taken together, these concerns support Macintyre’s argument that A.I. detectors raise serious ethical questions. Learning works best when trust comes first, and technology should assist human judgment rather than replace it.
LikeLike