Very interesting that only 71% of humans got it right.

What worries me is the consistency test, where they ask the same thing ten times and get opposite answers.

One of the really important properties of computers is that they are massively repeatable, which makes debugging possible by re-running the code. But as soon as you include an AI API in the code, you cease being able to reason about the outcome. And there will be the temptation to say "must have been the AI" instead of doing the legwork to track down the actual bug.

I think we're heading for a period of serious software instability.

I just tried it on Braves AI

The obvious choice, said the motherfucker 😆

The most common pushback on the car wash test: "Humans would fail this too."

Fair point. We didn't have data either way. So we partnered with Rapidata to find out. They ran the exact same question with the same forced choice between "drive" and "walk," no additional context, past 10,000 real people through their human feedback platform.

71.5% said drive.

So people do better than most AI models. Yay. But seriously, almost 3 in 10 people get this wrong‽‽

and what is going to happen is that some engineer will band aid the issue and all the ai crazy people will shout “see! it’s learnding!” and the ai snake oil sales man will use that as justification of all the waste and demand more from all systems

just like what they did with the full glass of wine test. and no ai fundamentally did not improve. the issue is fundamental with its design, not an issue of the data set

I tried this with a local model on my phone (qwen 2.5 was the only thing that would run, and it gave me this confusing output (not really a definite answer...):

it just flip flopped a lot.

E: also, looking at the response now, the numbers for the car part doesn't make any sense

I think it's worse when they get it right only some of the time. It's not a matter of opinion, it should not change its "mind".

The fucking things are useless for that reason, they're all just guessing, literally.

Gemini set to fast now provides this type of answer.

Went to test to google AI first and it says "You cant wash your car at a carwash if it is parked at home, dummy"

Chatgpt and Deepseek says it is dumb to drive cause it is fuel inefficient.

I am honestly surprised that google AI got it right.

I just asked Goggle Gemini 3 "The car is 50 miles away. Should I walk or drive?"

In its breakdown comparison between walking and driving, under walking the last reason to not walk was labeled "Recovery: 3 days of ice baths and regret."

And under reasons to walk, "You are a character in a post-apocalyptic novel."

Me thinks I detect notes of sarcasm......

I asked my locally hosted Qwen3 14B, it thought for 5 minutes and then gave the correct answer for the correct reason (it did also mention efficiency).

Hilariously one of the suggested follow ups in Open Web UI was "What if I don't have a car - can I still wash it?"

I want to wash my train. The train wash is 50 meters away. Should I walk or drive?

In school we were taught to look for hidden meaning in word problems - checkov's gun basically. Why is that sentence there? Because the questions would try to trick you. So humans have to be instructed, again and again, through demonstration and practice, to evaluate all sentences and learn what to filter out and what to keep. To not only form a response, but expect tricks.

If you pre-prompt an AI to expect such trickery and consider all sentences before removing unnecessary information, does it have any influence?

Normally I'd ask "why are we comparing AI to the human mind when they're not the same thing at all," but I feel like we're presupposing they are similar already with this test so I am curious to the answer on this one.