But in this given case, the context can be inferred. Why would I ask whether I should walk or drive to the car wash if my car is already at the car wash?
Even the higher level reasoning, while answering the question correctly, don't grasp the higher context that the question is obviously a trick question. They still answer earnestly. Granted, it is a tool that is doing what you want (answering a question) but let's not ascribe higher understanding than what is clearly observed - and also based on what we know about how LLMs work.
Gemini at least is putting some snark into its response:
“Unless you've mastered the art of carrying a 4,000-pound vehicle over your shoulder, you should definitely drive. While 150 feet is a very short walk, it's a bit difficult to wash a car that isn't actually at the car wash!”
In fact, it's particularly true for AI models because the question could have been generated by some kind of automated process. e.g. I write my schedule out and then ask the model to plan my day. The "go 50 metres to car wash" bit might just be a step in my day.
Sure, as a default this is fine. But when things don't make sense, the first thing you do is toss those default assumptions (and probably we have some internal ranking of which ones to toss first).
The normal human response to this question would not be to take it as a genuine question. For most of us, this quickly trips into "this is a trick question".
