The rise of generative AI tools is creating parallel demand for a new class of systems that can help distinguish AI-generated text and images from those created by humans.
was created by college student Edward Tian and works similarly to the new tool from OpenAI, assessing the overall likelihood that a piece of content was machine-generated.is testing a product with educational institutions that analyzes content paragraph-by-paragraph rather than just providing an overall score.to help writers detect if their writing will pass as human, since search engines penalize content they believe to be machine-generated.
The tools will no doubt improve, but so will the means for evading detection, likely creating something of a cat-and-mouse game. "We believe that techniques for detecting AI content will improve, and continue to surpass human ability to discern between machine- and human-written content," a Fictitious.ai representative told Axios. "With that said, there is clearly a limit at which sufficient human editing will always obscure traces of AI-generated content."
OpenAI and others are also exploring other approaches, such as watermarking their systems' creations to make it easier to spot machine-generated content.and that means all manner of computer-created content is about to explode. The challenge will be developing enough systems — both human and automated — to deal with the flood of additional content at a time when misinformation is already a significant problem.Here's how several detectors performed when we asked it to analyze a portion of yesterday's Login newsletter.
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