OpenAI's New AI Detection Tool: A Game-Changer in Preventing Student Cheating?

According to a survey by BestColleges, over half of students are turning to AI as a shortcut to academic success. This aligns with a Stanford University study that found between 60 to 70 percent of students resort to cheating. However, the days of effortlessly using AI like ChatGPT to write essays might be numbered. A Wall Street Journal article highlights that OpenAI claims to have developed a method to detect AI-generated content with a staggering 99.9% accuracy.

My colleague David Gewirtz has noted that several programs already claim to spot AI-written text. Yet, he remains skeptical, stating, "I certainly wouldn't feel comfortable threatening a student's academic standing or accusing them of cheating based on the results of these tools."

OpenAI hasn't spilled the beans on how their method achieves such near-perfect detection. It's not about catching AI's tendency to "hallucinate" or produce false information, as OpenAI co-founder John Schulman admitted last year, "Our biggest concern was around factuality because the model likes to fabricate things."

Mohamed Elgendy, co-founder and CEO of Kolena, a machine learning testing service, believes that while AI's hallucination rate may decrease, it will never disappear entirely. He compares it to even the most educated individuals occasionally spreading misinformation.

Rather than relying on some mysterious deep tech, OpenAI seems to be using a straightforward approach: watermarking. In a recently updated blog post titled "Understanding the source of what we see and hear online," OpenAI mentions exploring classifiers, watermarking, and metadata to identify AI-generated content. The exact mechanics of this watermarking remain under wraps.

OpenAI claims this method has proven highly accurate and resilient against localized tampering like paraphrasing. However, it struggles with globalized tampering, such as translated text or inserting and then deleting special characters. Moreover, it's not designed to detect content produced by other AI models, like Google Gemini or Perplexity.

In essence, with a bit more effort, students and writers might still be able to sneak AI-generated work past detectors. From my own experience, AI-produced content often feels second-rate, but for some, a passing grade might be all that's needed.

A self-proclaimed professor on Reddit isn't convinced, stating, "The problem is that you can just copy-paste the text into another program, translate it into another language, and then translate it back. But honestly, most students aren't going to do that, so it would catch pretty much everyone."

OpenAI CEO Sam Altman seems less concerned about academic cheating, telling The Harvard Gazette, "Cheating on homework is obviously bad. But what we mean by cheating and what the expected rules are does change over time."

I'm not sure I agree with that perspective. Cheating is cheating, and this new tool from OpenAI doesn't seem like it will make a significant dent in the problem.

Interestingly, while OpenAI debates the release of this text detection service, they're moving forward with a DALL·E 3 provenance classifier. Soon, nearly every image created with DALL-E will be tagged as AI-generated, using C2PA metadata. If you're a graphic designer who's been leaning on DALL-E for "original" graphics, it might be time to brush up on your Photoshop skills.