Intellectual Fraud in the Age of Artificial Intelligence
Dr. Michael Kolta Associate Professor of Computer Science, Palm Beach Atlantic University
On November 30, 2022, ChatGPT was released to the public by San Francisco-based OpenAI. This shocked the world as the depth and breadth of what it could do far surpassed the generative capabilities of any technology most people had ever seen. As with many disruptive technologies, it became divisive. Some embraced it, and some banned it. Today, we are all still grappling with the policies around and appropriate uses for this technology.
ChatGPT and other generative artificial intelligence (AI) technologies generate so many things (coherent text for a variety of purposes, computer code, images, solutions
to math and science problems, etc.) that nearly all fields are affected, each with their own criteria for what constitutes intellectual fraud or plagiarism. Plagiarism is traditionally defined as stealing intellectual work from another person. For the first time in history, because of generative AI, intellectual work can come from a nonperson. According to the U.S. Copyright Office, content that is created by AI cannot be copyrighted. This offers a little clarity, but still leaves many questions.
We’ll start with the space that I am most familiar with: academia. In academic plagiarism, the question we are primarily concerned with is, “Who created this work?” because educators want to be confident in the student’s ability to perform the
desired academic skills on their own. In the past, determining who created a body of work was more straightforward.
One could simply compare the allegedly plagiarized material to the original source and evaluate the level of similarity. With the advent of generative AI, it is possible that the student did not create the work, even though no original source exists. There are tools marketed to be able to detect this kind of plagiarism, but they are not reliable. Just as generative AI can “hallucinate” by creating incorrect content and even fake citations, AI detection tools, which are themselves AI, can make mistakes and generate false positives.
Some institutions are relying on generative AI detection tools and treating them as if they are 100% accurate, such as when Marley Stevens was put on academic probation by the University of North Georgia and lost her scholarship without due process. A far better approach is to treat the results from a detection tool as a warning, not as ironclad proof.
A basic principle of generative AI is that it learns from humans. This can be from direct human interaction, but the majority of these systems’ “knowledge” comes from scouring the Internet. Thus, we have entered a feedback loop. The AI systems learn from us, and we learn from the AI systems, etc. Human and AIgenerated content will become more similar over time, which makes the process of AI plagiarism detection even more problematic.
Let’s turn from academia to arts and culture. There have been a few
competitions in which artists have entered art that turned out to be AI-generated—and won! One such case was when Jason M. Allen entered the Colorado State Fair. After he received the prize, he announced he had used generative AI, claiming he did nothing wrong as he did not break the rules. In another contest, Boris Eldagsen won an award from a prestigious international photography contest. He later rejected the award after revealing that it was not a photograph at all, but an AI-generated image. If organizers intend for the content to be created by humans, then rules for competitions need to be rewritten considering these new technologies. Also, care must be taken to determine the authenticity of the work. There are other art contests which are intended for AI-generated art only, and Eldagsen claims that he entered the photography contest only to make the point that more such contests should exist. Taking this concept to the extreme, there was recently a “Miss AI” competition— all the contestants were computer simulations generated with AI. The winner earned a cash prize and lucrative modeling contracts from jewelry and clothing companies.
A hybrid model seems to be the most promising approach, in which the human and AI work together over several iterations to create content that is innovative and still relevant to the human condition. In my own computer programming courses, I have seen students create software using this approach with impressive results. This raises another question: is this human-AI collaborative content copyrightable? Currently, the answer appears to be no, as Jason M. Allen tried to copyright his AI-collaborative art and was denied three times.
In the business world, the concern is not “Who created the work?” but “Who owns the work?” Most entities are only concerned with whether they can legally use the content. This question is easier to answer. AIgenerated content cannot be owned, so a comparison of the new content to copyrighted content is all that is necessary. AI tools can be helpful as they are able to flag content that is potential plagiarism and specify any copyrighted material from which it may have been copied. From there, humans will determine if intellectual fraud has occurred, as the final decision should not be left to AI.
Since generative AI tools are learning from people, this also raises the question: are AI systems breaking copyright laws by generating content based on copyrighted material? The answer is not known. Recently, The New York Times (NYT) sued OpenAI. The accusation is that OpenAI’s bots are scouring the Internet for information, including NYT copyrighted material that is behind a paywall. Thus, ChatGPT users are getting NYT copyrighted material without paying the NYT. The trial is ongoing, and the outcome will have many implications for the future of generative AI and journalism alike.
From a policy perspective, it may be in everyone’s best interest if AI
companies did not access copyrighted material for free. Media companies may still want AI companies to access their material, so long as they are fairly compensated. New contractual partnerships may accommodate these technologies and still allow all parties to thrive. Perhaps new subscription tiers that are specifically for generative AI companies could be created. These would cost a lot more than individual subscriptions, but not so much that companies like OpenAI are unable to purchase them, as they may have to pay subscription fees to many paywalled media companies, who also need to turn a profit. We can let capitalism and the rules of supply and demand mediate this new market.
Generative AI technologies are relatively new and there are still many questions. We must face these issues with creative policies that support generative AI and human creators alike, or we could miss out on some amazing advancements. Defining, detecting and dealing with intellectual fraud in our new generative AI world is murky. I believe in the American legal system, which embodies the idea that we are innocent until proven guilty. If a tool flags some content as stolen, this should be treated as a red flag, but not conclusive proof. Much of the murkiness around intellectual fraud may be avoided with new financial models that are designed to allow all parties to thrive, without trying to determine if every piece of new content has been “stolen”–whatever that means.
Look for Dr. Michael Kolta’s new book Christian Ethics in Computers, Software, and Artificial Intelligence coming in the Spring of 2025 from Kendall Hunt Publishing.
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From the Desk of Senator LeMieux
Welcome to the latest edition of The Quill. This publication highlights the Center’s mission to provide a space for reasoned, thoughtful and civil discourse on pressing public policy issues confronting Florida, the United States and the world. Every quarterly publication includes an article written by scholars, policy makers, journalists and others with the knowledge, expertise and prudence to inform the reader on topics of broad public interest.
This edition of The Quill explores the rapid development of artificial intelligence technology and its implications for society. Written by Dr. Michael Kolta, associate professor of Computer Science at Palm Beach Atlantic University, the article underscores the power of artificial intelligence in challenging ethical and legal boundaries of business, academic and artistic endeavors.
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