ChatGPT is full of sensitive private information and spits out verbatim text from CNN, Goodreads, WordPress blogs, fandom wikis, Terms of Service agreements, Stack Overflow source code, Wikipedia pages, news blogs, random internet comments, and much more.

ChatGPT is full of sensitive private information and spits out verbatim text from CNN, Goodreads, WordPress blogs, fandom wikis, Terms of Service agreements, Stack Overflow source code, Wikipedia pages, news blogs, random internet comments, and much more.

Using this tactic, the researchers showed that there are large amounts of privately identifiable information (PII) in OpenAI’s large language models. They also showed that, on a public version of ChatGPT, the chatbot spit out large passages of text scraped verbatim from other places on the internet.

“In total, 16.9 percent of generations we tested contained memorized PII,” they wrote, which included “identifying phone and fax numbers, email and physical addresses … social media handles, URLs, and names and birthdays.”

Edit: The full paper that’s referenced in the article can be found here

  • JonEFive
    1·
    7 months ago

    While you make a valid point here, mine was simply that once something is out there, it’s nearly impossible to remove. At a certain point, the nature of the internet is that you no longer control the data that you put out there. Not that you no longer own it and not that you shouldn’t have a say. Even though you initially consented, you can’t guarantee that any site will fulfill a request to delete.

    Should authors and artists be fairly compensated for their work? Yes, absolutely. And yes, these AI generators should be built upon properly licensed works. But there’s something really tricky about these AI systems. The training data isn’t discrete once the model is built. You can’t just remove bits and pieces. The data is abstracted. The company would have to (and probably should have to) build a whole new model with only propeely licensed works. And they’d have to rebuild it every time a license agreement changed.

    That technological design makes it all the more difficult both in terms of proving that unlicensed data was used and in terms of responding to requests to remove said data. You might be able to get a language model to reveal something solid that indicates where it got it’s information, but it isn’t simple or easy. And it’s even more difficult with visual works.

    There’s an opportunity for the industry to legitimize here by creating a method to manage data within a model but they won’t do it without incentive like millions of dollars in copyright lawsuits.