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Can a machine know?

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Introduction

Theory of Knowledge Essay: Essay Question: Can a machine know? To fully appreciate a concept or to know a person must apply different methods to acquire knowledge. A machine can never truly know. Machines just merely recreate what humans tell them to do. They cannot apply the methods that humans use to acquire knowledge. There are many ways of acquiring information; however I will illustrate 6 main methods; Empiricism, perception, Intuition, language, past experience, and thought are essential in the art of knowing. However, before I allude to my main argument I firstly want to discuss the main limitations that computers possess. Machines are not human and thus they cannot possess the ability to act like humans. Machines are pre-programmed and react in a particular way in a particular circumstance. However, machines can think and only can reach knowledge that has already been proven. An example of this is a designing program called Aaron created by Harold Cohen in 2001. He has given the program a knowledge base full of information about how people look and how their bodies move. The program also understands composition, brushwork and how to paint. However it is also obvious that computers will never obtain the human attributes of creativity from inspiration or observation as they don't have minds. ...read more.

Middle

For instance, when I looked at a coin from a certain angle, it seemed to have an elliptical shape. However, my mother doesn't see an elliptical shape but a round shape. Thus, our perceptions of the coin were different due to our senses acting differently. On the other hand, a machine is unable to achieve knowledge through perception and the use of the senses. Both cannot be translated into a numerical equivalent for the computer to recognise. However, the problem with empiricism is that it includes experience as well as sense perception. Knowledge of the physical world is considered a generalisation and can never reach more than a high degree of probability. Yet another method of ascertaining information is through language. Natural language use is determined by context and experience. A natural language can be understood in a variety of ways on the basis of the information it contains. Language owes some of its fundamental properties to the fact that it is used to express, store and convey information. Machines on the other hand understand information not by the use of language but by binary codes. As such, the computer translates information into binary in order for it to understand the information given by a human. Therefore, a computer would not understand slang, vague or socially unaccepted words. ...read more.

Conclusion

In this case, you would not have to know John Tom or Mary or know whether they exist or not to know if the proposition is true. All that is needed to solve this problem is the understanding of the concepts involved. This would include someone being taller than someone else. Thus, No particular experience is needed for the claim to be solved. However, a computer would not be able to solve this problem as they would only look at this knowledge from a language perspective. They would just be able to read the words on the page, or for others that are programmed, a mathematical way to solving the problem. However, due to us humans seeing these types of questions from our past experiences, and our ability to relate to vague language a lot easier, we can solve the problem much more quickly than computers as the answer comes intuitively. As we can see machines need to know the ways in which humans acquire knowledge in order to 'know'. Machines have the ability to learn an abundance of facts and information, however this doesn't constitute to knowing. Knowing something stems a lot further than just information. Machines cannot have the same awareness, observatory skills, thoughts or experiences that humans have. As such their knowledge is limited to specific subjects whereas humans can learn new and different types of knowledge everyday. ...read more.

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