We Cannot Create Artificial Intelligence via Computation Alone

Thanks! It seems as if there is some serious misunderstanding with how the term semantics is used. Once we see this misunderstanding we will see how a majority of Con’s round fails. I am using semantics in the term of logic. The computer may be able to work with the semantics of language, but its reasoning has no semantics. In that its reason has no conscious meaning. When I say syntax isn’t sufficient for semantics, I am saying the actions of a computer isn’t sufficient for consciousness or intentionality. This has nothing to do with a computer working with language or using language correctly. Also I meant to copy the other half of syntax definition from the source but forgot to do so. I have no problem with Con’s definition, but be sure to realize when I use the term semantics I am referring to the meaning of the computer’s supposed intelligence. I have made this repeatedly clear. In my main argument I made it clear mental contents is semantics and in my last round I stated “I defined syntax in the last round as symbol processing and semantics as mental content”. 1: Does the CRA affirm the resolution? Con drops his original argument. Instead Con argues that I must show the CRA is correct.. Remember his original argument was about the CRA not affirming the resolution if it’s correct. Con is arguing something entirely different here. Rebuttal 2 Con again drops his argument for a new one. Remember in his original round he argued the CRA isn’t computationally intelligent. Now he is bringing up the systems reply and an argument based on the equivocation of semantics. In the false equivalence section Con presents the systems reply. He states just because the man doesn’t understand Chinese, doesn’t mean the system doesn’t. However, he would have to take the absurd position that an inanimate room is intelligent. This is what defenders of the systems reply advocate for [1] and it’s what they must advocate for. If one doesn’t advocate for a conscious room, then they would agree a system can still act intelligent without being intelligent. This shows the absurd ad hoc nature of the systems reply. Another problem with the systems reply is that it seems the room is irrelevant. Have the man memorize the book and step out of the room. There is nothing more to the system but the man, yet he still doesn’t understand Chinese. Con then presents a dilemma, but once we understand what’s meant by semantics it’s very easy to see Con’s fallacy of equivocation. Con is arguing the CR must be able to use words semantically (in terms of using language correctly) correct and concluding it is self refuting as it must be semantically intelligent (in terms of consciousness). When laid out like this we instantly see how flawed Con’s argument is. Con needs to understand the CRA isn’t making a statement about using language properly, it’s making a statement about conscious understanding of the language properly. Con’s next argument is about how computers use language in semantically correct ways. Again the argument makes the same error as his previous one in the equivocation of semantics. The section has been nothing but a big fallacy of equivocation, the CRA stands. 3: The BOP Con drops his third rebuttal on the BOP entirely, meaning I win in this section. 4: Connectionism Con objects the CR being able to learn. This fails because I have shown how it can learn. In my last round, section 2, second paragraph is all about how the CR can change it’s responses and learn. Con has dropped my argument for a changing Chinese Room making his argument refuted. He then goes on to equivocate semantics again. In the next section Con states the formal structure of the brain isn’t the only thing simulated. However, the abilities dynamics, and plasticity of the brain still must be simulated in a formal way to be considered computation. By the Church-Turing thesis any computer can do the job of another computer. One computer may be faster, but it still can do the same computation as the other. This follows when you realize computation is just an execution of an algorithm. You can execute an algorithm with sticks, doors, ping-pong balls, other computers ,ect. This means if we can create AI through a connectionist neural net, then we can also create AI on a Von Neumann machine which means simulating the formal structure of the brain is sufficient for an actual mind. You can actually run a connectionist neural net on your normal Von Neumann computer, there’s tons of free connectionist programs you can download to do so (they’re really fun) [4][5][6][7]. If we cannot create an AI via the formal structure, then it’s no longer computation and therefore irrelevant to the debate. Con’s rebuttals have failed. His attacks on the CRA are based on equivocation and misunderstandings. My argument remains standing. Con’s argument I would like to note, this argument can only succeed if the CRA is refuted. Since my the CRA remains sound, then Con’s argument fails. Con disputes my claim that the argument is a fallacy of composition. First, he only responded to my first claim of it. The one where I negated the idea the human intellect is computational, but I had another claim of it. My second claim that if parts of human intellect is computational, this doesn’t entail all of human consciousness is computational. The second accusation remains standing. However, my first claim of it is still standing, because the way we would know human intellect is computaional because parts of it can be simulated. Con states my back propagation is only how some connectionist neural nets learn, however the very paper he cites which is supposedly a better biological model itself says it’s neural nets learned by back propagation.[8] Con also says models using back propagation aren’t meant to simulate the brain, despite in the last round he argued they do. “Neurons can be accurately simulated as binary output units which compute non-linear functions of their summed inputs weighted by the strength of their synaptic connections to input neurons,” My argument that connectionist machines cannot account for the systematic nature of the mind was dropped and thus remains standing. Con’s attempt to refute the observer dependent nature of computation never gets off the ground. Nothing Con said was contradictory to the claim that computation is observer dependent. Appealing to humans being able to compute, computation in nature (which supports my argument) and claiming human intelligence can be simulated do nothing to show computation is intrinsic. I can agree with all points, but point out it’s trivial because computation isn’t intrinsic. The statement that since humans can compute, then the brain is a computer is very fallacious. It’s like saying since humans smell, there must be some smelling in the brain. It also assumes a token identity theory of the mind. Although there are many other theories of the mind that say the mind supervenes on the brain, not identical to it [9][10]. Computation in nature supports my argument, as anything can be a computer. It fails as a refutation. As for our brains being computanal by being explained by neural computation, this is too does nothing to refute the argument. Anything can be explained by computation because computation is observer dependent. My argument is that computation is observer dependent because anything can be a computer by the Church-Turing thesis. Con has failed to show there is something about computation which makes in intrinsic. My rebuttals remain standing. Conclusion Con has dropped a lot of arguments and has made several errors. Con’s first argument was dropped. My argument about a changing CR was dropped Con repeatedly uses the fallacy of equivocation Con dropped his third rebuttal about the burden of proof Con has dropped my argument that connectionism cannot account for the systematic nature of the mind. My arguments remain standing, whereas Con’s fail. The resolution is affirmed. Sources in comments