A story that explains some of these is the Social Intelligence Hypothesis.
Some characteristics of human intelligence are reviewed including it's: interactive nature, learning abilities, imitative tendencies, linguistic ability and context-dependency. We show that there is a well-defined sequence of problems which are not effectively designable but are learnable, in the form of the bounded halting problem. To illustrate this difference we compare (a) designing a Turing machine and (b) learning a Turing machine, defining them for the purpose of the argument. Here we argue that learning or adaption is fundamentally different from computation, though it does involve processes that can be seen as computations. This raises the question of whether learning is just another computational process, i.e., can be implemented as a Turing machine. It is a macro-level post-hoc test in contrast to the definition of a Turing machine, which is a prior micro-level definition. It involves repeated interaction requiring learning in the form of adaption to the human conversation partner.
The Turing Test checks for human intelligence, rather than any putative general intelligence.
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