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ChatGPT Answers Programming Questions Incorrectly 52% of the Time: Study (gizmodo.com)

submitted 5 months ago by [email protected] to c/[email protected]

198 comments fedilink hide all child comments

The research from Purdue University, first spotted by news outlet Futurism, was presented earlier this month at the Computer-Human Interaction Conference in Hawaii and looked at 517 programming questions on Stack Overflow that were then fed to ChatGPT.

“Our analysis shows that 52% of ChatGPT answers contain incorrect information and 77% are verbose,” the new study explained. “Nonetheless, our user study participants still preferred ChatGPT answers 35% of the time due to their comprehensiveness and well-articulated language style.”

Disturbingly, programmers in the study didn’t always catch the mistakes being produced by the AI chatbot.

“However, they also overlooked the misinformation in the ChatGPT answers 39% of the time,” according to the study. “This implies the need to counter misinformation in ChatGPT answers to programming questions and raise awareness of the risks associated with seemingly correct answers.”

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[–] [email protected] 18 points 5 months ago* (last edited 5 months ago) (3 children)

My experience with an AI coding tool today.

Me: Can you optimize this method.

AI: Okay, here's an optimized method.

Me seeing the AI completely removed a critical conditional check.

Me: Hey, you completely removed this check with variable xyz

Ai: oops you're right, here you go I fixed it.

It did this 3 times on 3 different optimization requests.

It was 0 for 3

Although there was some good suggestions in the suggestions once you get past the blatant first error

[–] [email protected] 8 points 5 months ago (1 children)

Don't mean to victim blame but i don't understand why you would use ChatGPT for hard problems like optimization. And i say this as a heavy ChatGPT/Copilot user.

From my observation, the angle of LLMs on code is linked to the linguistic / syntactic aspects, not to the technical effects of it.

[–] [email protected] 2 points 5 months ago* (last edited 5 months ago) (1 children)

Because I had some methods I thought were too complex and I wanted to see what it'd come up with?

In one case part of the method was checking if a value was within one of 4 ranges and it just dropped 2 of the ranges in the output.

I don't think that's asking too much of it.

[–] [email protected] 4 points 5 months ago

I don’t think that’s asking too much of it.

Apparently it was :D i mean the confines of the tool are very limited, despite what the Devin.ai cult would like to believe.

[–] [email protected] 5 points 5 months ago (2 children)

That's been my experience with GPT - every answer Is a hallucination to some extent, so nearly every answer I receive is inaccurate in some ways. However, the same applies if I was asking a human colleague unfamiliar with a particular system to help me debug something - their answers will be quite inaccurate too, but I'm not expecting them to be accurate, just to have helpful suggestions of things to try.

I still prefer the human colleague in most situations, but if that's not possible or convenient GPT sometimes at least gets me on the right path.

[–] [email protected] 2 points 5 months ago

And ya, it did provide some useful info, so it's not like it was all wrong.

I'm more just surprised that it was wrong in that way.

[–] [email protected] 2 points 5 months ago (1 children)

I'm curious about what percentage of programmers would give error free answers to these questions in seconds.

[–] [email protected] 2 points 5 months ago

Probably less than the same amount of developers whose code runs on the first try.

[–] [email protected] 4 points 5 months ago

My favorite is when I ask for something and it gets stuck in a loop, pasting the same comment over and over