One Way AI Has Changed Plagiarism

Generative Artificial Intelligence, whether we like it or not, is the hot topic of 2023.

To be clear, we don’t know what the endgame is yet. AI could be just another fad that, despite all the headlines it is generating right now, could become something like NFTs, something very niche for a small audience that most people completely moved on from.

However, it could also have lasting impacts on everyone, though maybe not to the point of revolutionary. Current applications such as AI-powered search and AI-assistants could aid in work, but not completely overhaul most people’s lives.

Or, it could go the way of the internet itself, becoming a revolutionary technology that touches the lives of every person on the planet, even if they don’t have access to it or use it directly.

All that said, we can track some of the ways AI is changing our culture and one of the more interesting ones is how it is changing the conversation about plagiarism, in particular in academia.

That’s because AI-based plagiarism no longer about theft and more about the lie that comes with it. In short, it’s forced a broad reexamination of the ethics around plagiarism and the way we talk about.

And, if we’re honest, it’s a reckoning that was long overdue.

Plagiarism as Theft

In most plagiarism cases, there are two victims to consider. The first is the person who was plagiarized, and thus deprived of whatever benefit (no matter how small) attribution would have provided. The second is the audience who was lied to and misled into thinking that a work was original when it was not.

However, the language around plagiarism has long centered around the narrative that plagiarism is a form of theft. In some ways, that makes sense. Someone was denied the attribution and credit that our standards say they were owed. 

As someone who was the victim of plagiarism hundreds of times, I can say with certainty that it does feel very much like theft, and like a very personal one at that. 

But the plagiarism as theft narrative omits a great deal of things that we consider plagiarism. For example, a student using an essay mill or having another student write their paper is a form of plagiarism, but the “victim” isn’t a victim, they’re a conspirator.

If plagiarism is purely theft, why can’t students use essay mills? Why don’t all authors use ghostwriters? Why would anyone who can afford it ever write anything original?

That, in turn, is where AI stepped in.

Changing the Narrative

Though there’s no data yet on how many students have used AI to commit plagiarism, anecdotal reports indicate that the problem is definitely growing and, because of the attention AI has been given, it’s on the minds of schools and their instructors.

And that has forced a rethinking of the way we look at and discuss plagiarism. While the “plagiarism as theft” narrative breaks down when the would-be victim is a conspirator, it becomes utterly demolished when it comes to AI.

If we set aside the argument that AI is plagiarizing the work it was trained on, that approach of looking at plagiarism completely disintegrates if there’s no human author involved at all. 

And yet, despite the lack of a victim, plagiarism is still being treated very seriously. For example, back in January, CNET was heavily criticized and forced to pause an AI-reporting initiative after backlash of the undisclosed use of AI. 

Granted, that story was bolstered by the fact that the AI did plagiarize from human authors, but the anger and outrage was present before that was discovered, especially in light of factual errors that went undetected by the publication’s editorial team.

The audience felt lied to, and for good reason. The fact no person was plagiarized from was unimportant, it was the lie (or the omission) that was the issue.

This cuts more to the fundamental issue of what plagiarism is. It is a lie. It is an author saying, either directly or implicitly, that the work is theirs and is original when, in fact, it is not. 

This puts the focus on what the actual act of plagiarism is. It’s not a sneaky attempt to deprive attribution, but an attempt to lie and pass off the work to others. 

With no direct victim, willing or not, the conversation can finally focus on that.

Bottom Line

To be clear, none of this is meant to take away from the importance of working with and helping victims of plagiarism. As I found out, being the victim of a plagiarist getting international attention is a very lonely place, and there was no consideration for what resolutions I wanted or thought might be appropriate.

As we saw in July of last year, there are ways to resolve plagiarism cases that both support the victim and make it sure that the truth is known. 

However, when approaching the act of plagiarism itself, it’s important to not limit it to “theft” or “stealing”. While the feelings are understandable and, in many cases, the descriptor is appropriate, it omits a great deal from the conversation, including AI-generated work.

So, no matter where AI goes from here and what impacts it does or doesn’t have on our lives moving forward, it has undoubtedly forced people to rethink the way they look at and talk about plagiarism.

And that, in the long run, is probably a good thing.