The Turing test is a literal benchmark. Its purpose was to replace an ill-posed question (what does it mean to ask if a machine could "think", when we don't know ourselves what this means- and given that the subjective experience of the machine is unknowable in any case) with a question about the product of this process we call "thinking". That is, if a machine can satisfactorily imitate the output of a human brain, then what it does is at least equivalent to thinking.

"I believe that in about fifty years' time it will be possible, to programme computers, with a storage capacity of about 10^9, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning. The original question, "Can machines think?" I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted."

Turing seems to be saying several things. He writes:

>If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd.

This anticipates the very modern social media discussion where someone has nothing substantive to say on the topic but delights in showing off their preferred definition of a word.

For example someone shows up in a discussion of LLMs to say:

"Humans and machines both use tokens".

This would be true as long as you choose a sufficiently broad definition of "token" but tells us nothing substantive about either Humans or LLMs.