This paper examines the question of whether artificial intelligence can ever achieve genuine consciousness by engaging with Daniel Dennett's Darwin's Dangerous Idea and John Searle's Chinese Room argument. It explores functionalist models of mind, the limitations of algorithmic thinking, and the distinction between simulating thought and truly understanding it. Drawing on examples from popular culture such as HBO's Westworld, the paper argues that while advances in technology have renewed interest in AI consciousness, fundamental barriers — including the complexity of human evolution, the non-deterministic nature of the brain, and the impossibility of programming true self-directed understanding — suggest that real machine consciousness remains out of reach.
Artificial intelligence has been at the center of many science fiction stories over the last fifty years. Some thinkers have become obsessed with proving or disproving the idea that computers can possess real minds and real consciousness. A recent cultural example is HBO's Westworld, a show about androids achieving consciousness. Realistically, however, many regard this as an impossibility. While true artificial intelligence seems unrealistic, many have tried to actualize such a dream through AI projects and the development of new robotic technologies. Will the goal of real consciousness derived from artificial intelligence ever be achieved? Will humanity ever possess the technology and understanding to cultivate life from machine?
In "The Library of Toshiba," the chapter opens with a quote from John Maynard Smith. He shares the notion that humans are essentially programmed robots designed to perpetuate their genes through reproduction. Humans are, after all, part of creation, and as such may be programmed by nature to perform certain tasks and functions, much like an artificial program. This is a jarring concept because it implies that if humans are like programs and can be programmed, what makes them any different from artificial intelligence? What makes humans different from robots?
Dennett observes that programs are "not random strings of bits, but highly designed sequences of bits, the products of thousands of hours of R. and D." (Dennett 437). This is important because what appears to be random chance or an act of randomness to a human being may indeed be a pre-programmed occurrence that was designed long ago. Dennett continues by discussing his Toshiba and eventually returns to Gödel's Theorem, again comparing humans with artificial intelligence, making it seem plausible that humans and robots are fundamentally alike — and thus that AI could develop into real consciousness. As he puts it: "That is exactly what people in AI believe: that there are risky, heuristic algorithms for human intelligence in general, just as there are for playing good checkers and good chess and a thousand other tasks." (Dennett 438).
Looking at AI through functionalism, early pioneers of AI thought of the human brain as the hardware and the human mind as the software. They eventually began using examples such as running Microsoft Word on numerous different computers, comparing this to running the "mind program" on any type of hardware. They convinced themselves that the human brain is a computer and that, because the mind is its program, this program can not only be replicated but also transferred into other machines such as robots. This sounds reasonable and potentially insightful. However, the brain is not a computer.
The human brain cannot be regarded as a non-deterministic analog system with a finite number of possible states. At least on some level, the human mind can store and process information in a multitude of ways that research and analysis have yet to fully understand and map. Add to that the tens of thousands of years of evolution that enabled humans to reach their current level of intelligence, and it becomes apparent that computers are not the same as human brains — they represent, at most, one small characteristic of human cognition.
Many who argue against the possibility of computers achieving real consciousness rely on the Chinese Room argument to refute such claims. Proposed by John Searle in a 1980 thought experiment — with a 1984 derivation — it remains the most well-known counter to arguments for AI consciousness. The main claims of the Chinese Room argument are that "syntax does not suffice for semantics" and that "brains cause minds." Searle uses the distinction between strong AI and weak AI to describe how computers can simulate thought much like a weather simulator can simulate weather, without truly understanding it. While AI can, with the right programs, process and respond to input in ways that resemble cognitive states, it cannot understand on its own — and this absence of genuine understanding forecloses the possibility of real consciousness.
This parallels the situation depicted in Westworld. While the "hosts" could replicate human emotion and be programmed to manage conversation and objectives, they could not independently understand the nature of their own thoughts. Although the show eventually allows one host, Dolores, to achieve real consciousness, those who reject the possibility of AI use the Chinese Room argument to insist such an outcome could never occur in reality. Returning to the Dennett text, Dennett continues laying the groundwork for understanding artificial intelligence by using the chess metaphor.
"Chess metaphor illustrating algorithmic complexity limits"
"Modern AI growth versus enduring philosophical obstacles"
Even if humans come to understand their own potential and the complexity of the human mind, the question remains whether that could ever be replicated by artificial means. The third and final reason for skepticism is precisely this: so far, technology has demonstrated that artificial intelligence in its fullest sense — genuine, self-directed consciousness — is not achievable. It may seem like a potential reality in the future, but it appears to be a step that must be preceded by a thorough understanding of the human mind itself. That understanding, too, may never be fully attained.
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