Strong AI vs Narrow AI
There was a famous thought experiment conducted in the 80s by the philosopher John Searle called the Chinese Room. The premise was to refute what he referred to as Strong AI. The premise was…“suppose that artificial intelligence research has succeeded in constructing a computer that behaves as if it understands Chinese.”
It takes Chinese characters as input and, by following the instructions of a computer programme, produces other Chinese characters, which it presents as output. The computer performs its task so convincingly that it comfortably passes the Turing Test: it convinces a human Chinese speaker that the programme is itself a live Chinese speaker.
Developed by Alan Turing in the 1950s, the Turing Test was designed as a test of a machine's ability to exhibit intelligent behaviour, equivalent to or indistinguishable from, a human. A human evaluator judged a natural language conversation between a human and a machine designed to generate human-like responses. The machine passed the test as if it was indistinguishable from the human.
Searle’s question was “does the machine literally "understand" Chinese?” Or is it merely simulating the ability to understand Chinese?”. He calls the first position “Strong AI” and the latter “Weak AI” - what we've referred to as Narrow AI.
Searle then supposes that if he's in a closed room and has an English version of the computer programme, a large batch of Chinese writing, the set of rules, along with all the symbols used, he could receive the Chinese characters from the human evaluator. He could process them according to the programme's instructions, and produce Chinese characters as output.
If the computer had passed the Turing test this way, it stands to reason that Searle would also pass the test by simply running the programme manually. Searle asserts that there's no essential difference between the roles of the computer and himself in the experiment. Each is following the program step-by-step, producing a behaviour which is then interpreted by the evaluator as demonstrating intelligent conversation.
However, as Searle doesn't speak Chinese he doesn't understand the conversation at all. He therefore argues that the computer wouldn't be able to understand the conversation either.
He argues that, “without "understanding" (or "intentionality"), we cannot describe what the machine is doing as “thinking”. Therefore, since it does not think, it does not have a "mind" in anything like the normal sense of the word.”
He concludes that Strong AI is false. Although controversial, I think it highlights some key pointers to where AI research is now and a misunderstanding of current AI in the mainstream.