Word traps and false logic don't lead to dominance of the future or monopolistic grips on limitless profits.
The heart of the current euphoric expectations for AI is a simple but problematic proposition: the equivalence of function equals intelligence. If using natural language requires intelligence, and a computer can use natural language, then it's intelligent. If it takes intelligence to compose an essay on Charles Darwin, and an AI program can compose an essay on Charles Darwin, then the AI program is intelligent.
The problem here is this "equivalence is proof of intelligence" is a function of word-traps and false logic, not actual equivalence; what is claimed to be be equivalent isn't equivalent at all. In other words, the source of confusion is how we choose to define "intelligence," which is itself a word-trap of the sort that philosopher Ludwig Wittgenstein attempted to resolve using koan-like propositions and logic.
Imagine for a moment we had twenty words to describe all the characteristics of what we lump into "intelligence." We would then be parsing the characteristics and output of AI programs by a much larger set of comparisons.
The notion of equivalence goes back a long way. As science developed models for how Nature functioned, the idea that Nature was akin to a mechanism like a clock gained mindshare.
The discoveries of relativity and quantum effects blew this model to pieces, as Nature turned out to be a very strange clock, to the point that the "Nature as a mechanism" model was abandoned as inadequate.
We have yet to reach the limits of the "equivalence is proof of intelligence" model, which is as outdated and nonsensical as "the universe is a mechanism" model. We keep finding new examples of equivalence to support the idea that a computer program running instructions is "intelligent" because it can perform tasks we associate with "intelligence" because we're embedded in a mechanistic conceptualization of the entirety of Nature--including ourselves.
