Chatbots are genuinely impressive when you watch them do things they're good at, like writing a basic email or creating weird, futuristic-looking images. But ask generative AI to solve one of those puzzles in the back of a newspaper, and things can quickly go off the rails.
That's what researchers at the University of Colorado at Boulder found when they challenged large language models to solve sudoku. And not even the standard 9x9 puzzles. An easier 6x6 puzzle was often beyond the capabilities of an LLM without outside help (in this case, specific puzzle-solving tools).
A more important finding came when the models were asked to show their work. For the most part, they couldn't. Sometimes they lied. Sometimes they explained things in ways that made no sense. Sometimes they hallucinated and started talking about the weather.
If gen AI tools can't explain their decisions accurately or transparently, that should cause us to be cautious as we give these things more control over our lives and decisions, said Ashutosh Trivedi, a computer science professor at the University of Colorado at Boulder and one of the authors of the paper published in July in the Findings of the Association for Computational Linguistics.
"We would really like those explanations to be transparent and be reflective of why AI made that decision, and not AI trying to manipulate the human by providing an explanation that a human might like," Trivedi said.
Don't miss any of our unbiased tech content and lab-based reviews. Add CNET as a preferred Google source.
The paper is part of a growing body of research into the behavior of large language models. Other recent studies have found, for example, that models hallucinate in part because their training procedures incentivize them to produce results a user will like, rather than what is accurate, or that people who use LLMs to help them write essays are less likely to remember what they wrote. As gen AI becomes more and more a part of our daily lives, the implications of how this technology works and how we behave when using it become hugely important.
When you make a decision, you can try to justify it, or at least explain how you arrived at it. An AI model may not be able to accurately or transparently do the same. Would you trust it?
Watch this: I Built an AI PC From Scratch 04:07
Why LLMs struggle with sudoku
... continue reading