When Humans Write, They Leave Subtle Signatures
When humans write, they leave subtle signatures that hint at the prose’s fleshy, brainy origins. Their word and phrase choices are more varied than those selected by machines that write. Human writers also draw from short- and long-term memories that recall a range of lived experiences and inform personal writing styles. And unlike machines, people are susceptible to inserting minor typos, such as a misplaced comma or a misspelled word. Such attributes betray the text’s humanity.
Signature Hunting Presents a Conundrum
For these reasons, AI-writing detection tools are often designed to “look” for human signatures hiding in prose. But signature hunting presents a conundrum for sleuths attempting to distinguish between human- and machine-written prose.
The ‘Burstiness’ of Human Prose
During the recent holiday break, Edward Tian, a senior at Princeton University, headed to a local coffeeshop. There, he developed GPTZero, an app that seeks to detect whether a piece of writing was written by a human or ChatGPT—an AI-powered chat bot that interacts with users in a conversational way, including by answering questions, admitting its mistakes, challenging falsehoods and rejecting inappropriate requests. Tian’s effort took only a few days but was based on years of research.
His app relies on two writing attributes: “perplexity” and “burstiness.” Perplexity measures the degree to which ChatGPT is perplexed by the prose; a high perplexity score suggests that ChatGPT may not have produced the words. Burstiness is a big-picture indicator that plots perplexity over time.
“For a human, burstiness looks like it goes all over the place. It has sudden spikes and sudden bursts,” Tian said. “Versus for a computer or machine essay, that graph will look pretty boring, pretty constant over time.”
Detectors Without Penalties
Much like weather-forecasting tools, existing AI-writing detection tools deliver verdicts in probabilities. As such, even high probability scores may not foretell whether an author was sentient.
“The big concern is that an instructor would use the detector and then traumatize the student by accusing them, and it turns out to be a false positive,” Anna Mills, an English instructor at the College of Marin, said of the emergent technology.
A Long-Term Challenge
In an earlier era, a birth mother who anonymously placed a child with adoptive parents with the assistance of a reputable adoption agency may have felt confident that her parentage would never be revealed. All that changed when quick, accessible DNA testing from companies like 23andMe empowered adoptees to access information about their genetic legacy.
Though today’s AI-writing detection tools are imperfect at best, any writer hoping to pass an AI writer’s text off as their own could be outed in the future, when detection tools may improve.
Higher Ed Adapts (Again)
“Think about what we want to nurture,” said Joseph Helble, president of Lehigh University. “In the pre-internet and pre-generative-AI ages, it used to be about mastery of content. Now, students need to understand content, but it’s much more about mastery of the interpretation and utilization of the content.”
ChatGPT calls on higher ed to rethink how best to educate students, Helble said. He recounted the story of an engineering professor he knew years ago who assessed students by administering oral exams. The exams scaled with a student in real time, so every student was able to demonstrate something. Also, the professor adapted the questions while administering the test, which probed the limits of students’ knowledge and comprehension.
Conclusion
The emergence of AI-writing detection tools has sparked a cat-and-mouse game between writers and detectors. While some computer scientists are working to make AI writers more humanlike, others are working to improve detection tools. The scientific community and higher ed have not abandoned AI-writing detection efforts—and those efforts are worthwhile. Whether motivated by a desire to ferret out dishonesty in academic pursuits, protect public discourse from malicious uses of text generators, or understand what makes prose human, all must contend with one fact: it’s really hard to detect machine- or AI-generated text, especially with ChatGPT.
FAQs
Q: What is the purpose of AI-writing detection tools?
A: AI-writing detection tools are designed to distinguish between human-written and machine-generated text, with the goal of detecting potential plagiarism, academic dishonesty, and malicious uses of text generators.
Q: How accurate are AI-writing detection tools?
A: AI-writing detection tools are not yet 100% accurate, and their accuracy depends on various factors, including the complexity of the text, the type of AI used to generate the text, and the training data used to develop the detection tool.
Q: Can AI-writing detection tools be used to detect AI-generated text in real-time?
A: Yes, some AI-writing detection tools can be used to detect AI-generated text in real-time, but their accuracy may vary depending on the specific tool and the context in which it is used.
Q: What are the potential consequences of using AI-writing detection tools?
A: The potential consequences of using AI-writing detection tools include false positives, which can lead to unnecessary stress and anxiety for students, and false negatives, which can allow AI-generated text to go undetected. Additionally, the use of AI-writing detection tools may raise ethical concerns, such as the potential for bias and the impact on academic freedom.
