Protecting Against Malicious AI: Using The ChatGPT Turing Test
AI systems like ChatGPT are increasingly being used to support businesses, but their ability to mimic human responses also makes them a potential tool for malicious activities, such as denial-of-service attacks. It’s crucial to find a way to distinguish between bots and real humans. Hong Wang at the University of California, Santa Barbara, and colleagues have developed a new Turing test, called FLAIR, that can determine whether a party in a conversation is a human or a bot.
The Turing Test and CAPTCHA
In the late 90s, researchers created CAPTCHA as a way to distinguish between bots and humans. CAPTCHA asked users to recognize distorted letters, which bots could not read but humans could. More recently, ChatGPT and Bard, among other generative AI systems, have advanced to hold realistic conversations that are difficult to tell apart from those with real humans. To prevent nefarious activities, Wang and his team created several strategies based on the known limitations of generative AI systems and large language models.
FLAIR—Finding Large Language Model Authenticity via a Single Inquiry and Response
The researchers came up with several questions that are challenging for bots but simple for humans to answer. They named their questions FLAIR and made them available as an open-sourced dataset. Wang and co. suggest that their work could provide online service providers with a new line of defense against nefarious activities and ensure that they’re serving real users.
The Ongoing Cat-and-Mouse Game
Although the FLAIR test may be effective for now, the quest for total invisibility will fuel an ongoing cat-and-mouse game between malicious users and AI systems. The concern is that it’s getting increasingly harder to imagine that a bot will never be able to produce entirely indistinguishable results from those of a human.
Editor Notes
In conclusion, it’s not easy to stop malicious AI, but we can protect ourselves by finding new ways of distinguishing between bots and humans. The FLAIR test is an excellent start, but it also highlights the need for a constant evaluation of AI tests to ensure that they remain effective.
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