Could A Machine Think

In Chapter seven of Problems from Philosophy we are asked to analyze the question “could a machine think (Rachels 83)?” This question has perplexed a vast amount of intellectuals for centuries, some of whom agree that it is possible, meanwhile others disagree entirely. Perhaps the question isn’t of could a machine think, but would humans be the ones to build it? For instance, the human genome is an example of program execution similar to that of a machine. Although, we are biological and not mechanical in nature, we share a commonality with machines in the fact that our body’s execute programs. These programs are known as Codons, which consist of three nucleotides adenine, thymine, guanine, cytosine, and uracil (replaces cytosine in RNA).

For example, in the animal kingdom herbivores become faster over generations escape carnivores, if they do not they will be eaten. Likewise, carnivores become faster to capture prey if not, they will starve to death. Machines cannot do this and become obsolete after their usefulness runs its course, this coming via technological advancement or normal wear and tear. Machines don’t have the option to pass on genes (because they have no DNA) to continue the improvement of its species (model). Therefore, how can they improve to become thinkers? The common thought would be that as humans improved technologically the machines will become more sophisticated, but that doesn’t seem to be the case at all. After centuries of technological improvements mankind has yet to create true AI (artificial intelligence) that is capable of thought and

This machine would be able to self repair and learn from previous injuries, such as how a child learns not to touch fire after being burned. Roboticist Antoine Cully stated "Once damaged, the robot becomes like a scientist,. . .. It has prior expectations about different behaviors that might work, and begins testing them. However, these predictions come from the simulated, undamaged robot. It has to find out which of them work, not only in reality, but given the damage. The robot can effectively experiment with different behaviors and rule out ones that don't work,. . .. For example, if walking, mostly on its hind legs, does not work well, it will try walking mostly on its front legs,. . .. What's surprising is how quickly it can learn a new way to walk. It's amazing to watch a robot go from crippled and flailing around to efficiently limping away in about two minutes (Choi)." This may be the beginning of self improving robots, which have the capabilities to create a generation of newer and more efficient