As for your stated interest consider Searle's remarks here re: the ambiguity of "intelligence"
“Intelligence” is also ambiguous because it is ambiguous between real, honest to John observer-independent intelligence – as, for example, when a human being is thinking about something – and the observer-relative, derivative, metaphorical sense of intelligence – for instance, when we speak of my pocket calculator or computer as displaying intelligence.
Straw people, however, are easy to knock over:
Searle's Chinese Room basically argues that a program cannot make a
Searle is not arguing "that a program cannot make a computer 'intelligent'" (and this in whichever sense you mean program, intelligent or computer). Searle's Chinese Room demonstrates that semantics are not intrinsic to syntax. Big difference.
The Chinese Room Argument is a refutation of the computational theory of mind, not a refutation of "artificial intelligence". Searle is very clear that he is only arguing against what he identifies as "strong AI" and not "weak AI". Furthermore, he points out that we are biological machines in a sense of the words. As we know computational machines today (i.e. Turing machines), they are insufficient for anything more that syntactical manipulations and do not (read: can not) achieve semantic content. To understand Searle's argument, you will need to familiarize yourself with the distinctions between observer-relative and observer-independent, the epistemic and ontological senses of first- and third-person objectivity and subjectivity, as well the ambiguity of concepts such as "artificial", "intelligent", "information" and such.
To broaden your understanding of counter-arguments, first start with the actual argument you seek counter to:
Searle, John. R. (1980)
"Minds, Brains, and Programs"
This article can be viewed as an attempt to explore the consequences of two propositions. (1) Intentionality in human beings (and animals) is a product of causal features of the brain. I assume this is an empirical fact about the actual causal relations between mental processes and brains. It says simply that certain brain processes are sufficient for intentionality. (2) Instantiating a computer program is never by itself a sufficient condition of intentionality. The main argument of this paper is directed at establishing this claim. The form of the argument is to show how a human agent could instantiate the program and still not have the relevant intentionality. These two propositions have the following consequences (3) The explanation of how the brain produces intentionality cannot be that it does it by instantiating a computer program. This is a strict logical consequence of 1 and 2. (4) Any mechanism capable of producing intentionality must have causal powers equal to those of the brain. This is meant to be a trivial consequence of 1. (5) Any attempt literally to create intentionality artificially (strong AI) could not succeed just by designing programs but would have to duplicate the causal powers of the human brain. This follows from 2 and 4.
"Could a machine think?" On the argument advanced here only a machine could think, and only very special kinds of machines, namely brains and machines with internal causal powers equivalent to those of brains. And that is why strong AI has little to tell us about thinking, since it is not about machines but about programs, and no program by itself is sufficient for thinking.
Furthermore, see this article for a continuation of Searle's argument which demonstrates that syntax is not intrinsic to physics.
You might also enjoy this exchange in the NYR between Searle and Motzkin (note in particular the technical end note re: the Turing test & Turing machines)
The test is very much part of the behaviorism of the era in which Turing wrote his article; and like all such forms of behaviorism it makes a fundamental confusion between the way we would verify the presence of a mental phenomenon from the third person point of view with the actual first person existence of the phenomenon. As interpreted by Motzkin, the Turing test confuses epistemology with ontology.
Lastly, the Turing test is a high bar to get under and it really says nothing at all about the test subject. It says much more about the tester. The Turing test is by no means a litmus test for consciousness. Passing it has been described as little more than "a parlor trick" - the focus upon which has been derided as "obnoxious and stupid" by no less than Marvin Minsky. For exciting work being done in the field of machine learning, check out Jürgen Schmidhuber.