Critical analysis of a contributor’s argument.

Student Tutor Course Date Critical Analysis of a Contributor’s Argument Quote from Turing: “We now ask the question, “What will happen when a machine takes the part of A in this game?” Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman?” (Turing 2). NAKIB JALAL: I feel as though if a machine is placed in this predicament it will lead to a higher chance of the interrogator choosing wrong. However, this only depends on the programming of the machine. We can argue that a machine that is programmed extensively can do tasks better than a man. For instance, in assembly lines and such, the precision of a machine far outranks that of man. So if a machine were to be programmed in a way that it is meant to fool the interrogator under any circumstances it will manage better than a man who is capable of making mistakes. Nakib argues that if a machine was placed in Turing’s imitation game, it may outperform a human since it can be programmed to avoid mistakes. However, this overlooks that Turing’s test is not about accuracy but about imitating human thought and consciousness. Additionally, since machines are programmed by humans, they remain suspectable to human errors and biases. My analysis will argue that Nakib’s view reduces the imitation game to more about performance rather than addressing whether machines can genuinely think like humans. Critical Analysis According to Nakib Jalal, a device put in the Imitation Game “will give a higher probability of the interrogator choosing wrong”. A machine, it is argued, can be programmed in the details to such an extent that it will perform more efficiently than a person who makes mistakes. Although superior precision might initially appear to confuse an interrogator, this argument fails for two reasons. Firstly, it misunderstands the basic purpose of the Imitation Game. Secondly, it overlooks an important distinction Turing himself makes between different kinds of errors a machine can make. The Imitation Game was not introduced by Turing to imply a test of functional perfection. Turing wanted to buttress the ambiguous question: can machines think? Hence, we are not trying to find out which contestant is the most accurate or precise. Instead, it fosters which contestant can mimic a thinking human being closely enough to be taken for one. Thinking people are determined to be capable of intellectual mistakes or errors of conclusion. Those are different from miscalculations. Nakib’s view that the "precision of a machine far surpasses that of man" wrongly infers that machine superiority in simple, repetitive, or numerical tasks (like those on production lines or in spider’s calculations) equates to being intellectually sophisticated enough to pass the test. Turing describes two senses of error. This view only addresses the error of functioning or malfunction. This is a hardware or programming error that causes a machine to do something outside the rules of its operation, such as saying that $2+2=5$. Turing points out that these are not mistakes which relate to the question of whether or not a machine can think. They are engineering missteps which can be fixed. If this error was noticeable to the interrogator in the game, he would identify the machine, not because it is not thinking, but because it is not functioning optimally. The error on human thought that Nakib’s argument fails to notice is the mistake of conclusion. This is when the machine, or human, reaches a logically, or empirically, flawed conclusion, through the data and internal processes. We may have errors/drift in our thinking and we humans are not perfect. This is the process of analysing data and making a judgemant. As an example, if a machine is tasked to finish a line of verse and completes it with a cliché or an awkward rhyme, it makes an error of conclusion. As Nakib suggests, if humans programmed a machine to be perfectly precise in the sense that it never makes a single logical mistake and its responses are flawless, such a machine would almost certainly fail the Imitation Game. A thinking man must have a chance to show the intellectual weakness that is itself human. Also, the lack of errors of conclusion would be a telltale sign that it was not human, because being human means making mistakes. So, to prove the machine's identity as a machine would be the demonstration that it cannot make a natural, human-like mistake at such an abstract level of conversation. In short, Nakib’s focus on programming a machine to avoid error reduces the Imitation Game to a mere performance contest rather than genuine cognitive imitation. In the game, the object of the algorithm is not the power of the machine. For example, a machine that can cause perfectly accurate, but which can model the whole of the range human intellectual behaviour. Moreover, which importantly, yields errors of conclusion. Nakib is unable to determine the difference between a physical defect and logical error that leads him not to realize the philosophy behind Turing’s test. Quote from Vaidya (9): “If you don’t know what anger feels like, you cannot have anger.” KATHERINE A LAU: I disagree with this because newborn babies are blank slates, and yet they can feel discomfort, happiness, and most certainly, frustration and discontent. They diversify...