Can a machine know?



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Machines have become part of our everyday life, humans cannot live without them. In order to answer the: “Can a machine know?”, it is important to define certain aspects of the question. What is a machine? What is knowledge? Is the relation between these two things very evident? I will divide the essay into three main parts. The first one will talk about the definition of a machine, the meaning of knowledge, and I will make clear that there is a difference between “to know” and “to think”.

The second one, which will agree with the statement, will explain the concept of artificial intelligence stating the differences between conventional artificial intelligence and computational artificial intelligence. I will also explain the different ways of knowing that a machine and a human share. Finally, I will talk about the machines being programmed by humans; I will choose some examples of machines, which I will submit to Plato’s definition of knowledge. I will show that a machine cannot know like a human, stating the ways of knowing that it does not share with a human being. I will discuss two experiments related to knowledge and machines, and I will consider ethical implications.

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In the 21st century, people use the word “machine” for electronic tools or as a word coming from the slang for a computer, but a machine is any mechanical or organic device that transmits or modifies energy to perform or assist in the performance of tasks. It makes life easier for humans and gives them more power, as Henry Ward Beecher said: “A tool is but the extension of a man’s hand and a machine is but a complex tool, and he that invents a machine augments the power of man and the well-being of mankind”1. It normally requires some energy source and accomplishes some sort of work. So wheels, chronometers, pumps, calculators, and of course, computers, are all machines. But there are also biological machines such as cells, viruses, and therefore human beings.

To answer the question: “Can a machine know?” we also have to define the term “knowledge”. Plato said that knowledge was a “Justified true belief”2 but in general, knowledge is what is known. There is no single definition of knowledge on which people agree, but there are numerous theories and continued debates about the nature of knowledge. Knowledge acquisition involves complex cognitive processes: perception, learning, communication, association, and reasoning. The term knowledge is also used to mean the confident understanding of a subject, potentially with the ability to use it for a specific purpose.

There are different kinds of knowledge: someone can know if someone else is feeling bad – this is “knowing that”. This is related to perception and emotions. We can also know that it will rain tomorrow because the sky is getting darker: this is related to reason. There is also the “knowing how”, which means that we know how to do things, helped by our instinct. When we answer the question about whether a machine can know or not, we have to discuss the difference between “to know” and “to think”. Indeed, thinking involves a judgment, it exercises the mind in order to make inferences, decisions, or arrive at a solution. Knowing is completely different. It is being aware of the truth, having a belief or faith in something regarded as true beyond any doubt. So we can say that “to know” is objective because it doesn’t involve our opinion, but “to think” is subjective because it does.

In certain cases a machine can know. Indeed, if we choose specific aspects of the meaning of “to know”, a machine can know things through different methods. Like a human being, it can reason, solve problems (mathematical equations for example, calculations using specific programmes such as Excel…). A machine is good with logical problems. It can also translate words and sentences because it “knows” the translation of the words. A machine knows what a human put into its electronic system. But only specific machines can do that. Indeed, coffee machine could not translate a word! Computers, calculators, translators are capable of solving problems or, in the case of the latter, translating a text. Computers are the machines that are most likely to be considered as “knower machines”.

When we agree that a machine can know, we have to talk about artificial intelligence which is an important contemporary science. It is a multidisciplinary field encompassing computer science, neuroscience, philosophy, psychology, robotics and linguistics, and devoted to the reproduction of the methods or results of human reasoning and brain activity. There is the conventional artificial intelligence which is a branch of artificial intelligence mainly dealing with symbolic problems and the computational artificial intelligence which its research aims to use learning, adaptive, or evolutionary computation to create programs that are, in some sense, intelligent. Computational intelligence research either explicitly rejects statistics or tacitly ignores them. So those machines are imitating the human brain. Some of them know more that certain persons, but only because humans gave them information.

Humans have access to knowledge through language. Indeed, this is a way of communication. However, machines do not talk or interact with each other as humans do. As Hans Reichenbach said: “If you can’t say it, you don’t know it”3. Computers can communicate between each others through the internet but other machines such as cars, vacuum cleaners, or televisions cannot. To illustrate the language as a way of knowing, the Chinese room experiment is very relevant. It was done by John Searle in 1980. In this experiment, Searle asks us to suppose that he is sitting inside a computer which is in a small locked room.

In other words, he is in a small room in which he receives Chinese characters, consults a rule book, and returns the Chinese characters that the rules dictate. Searle notes that he does not, of course, understand a word of Chinese. Furthermore, he argues that his lack of understanding goes to show that computers do not understand Chinese either, because they are in the same situation as he is. They are mindless “manipulators of symbols”4, just as he is, and they do not understand what they are ‘saying’, just as he does not.

There is no point in knowing something if you cannot understand it and then use it. That was what Goethe meant when he said: “Knowing is not enough, we must apply.” We know that machines (apart from computers, cars and specific machines…) have only one or two functions programmed by humans: for example a coffee machine makes coffee, a camera takes pictures. Being programmed is not the same thing as knowing.

A machine cannot break into the abstract from its primary programming: it must serve its function and nothing more. For a machine to be able to know, something would mean it is aware and conscious, and for something to be aware and conscious on that level, then it is not a machine anymore, and it has become a life form with free will and free imagination. As Rabelais said: “Science without conscience is only ruin of the soul”6. It does not have the ability to change things it learnt to make it better. It can only restore what has been given to it. Plato’s definition of knowledge was “a justified true belief”. A belief means nothing for a machine because it cannot think; it cannot have a judgment or an opinion about anything.

A human being cannot know something if he does not believe it. Indeed, he cannot know a fact if he does not believe that the fact is true. But a machine is not capable of believing because it doesn’t have faith in anything. It differs really from human knowledge which has a faith in something, like religion for example. Moreover, machines have no concept of “what is right” and “what is wrong”. Ethics are not a part of the machines’ system. When we answer the question “Can a machine know?” we have to talk about Turing’s experiment that proved that a machine cannot fool a human even if Turing predicted that it would be able to fool 30% of human judges during a five minutes’ test. (It was a written conversation between a human and a computer). It had a little success but not as much as Turing’s prediction.

Humans have different ways of knowing which a machine cannot share with them. Let’s take the example of a car accident. You crash the car into a tree: the car will be broken but will not cry or feel any pain: indeed, a machine does not have feelings or emotions which are very important for a human to know. Also a machine has neither perception nor intuition. These elements are what constitute the soul. So we can say that a machine does not have a soul.

Personally, I do not think that a machine can know because of its lack of soul, mind, perception, emotions, intuition and feelings. It is just a human tool and it obeys to its master. There could be some exceptions like the computers that can sometimes “imitate” human behaviour. By that, I mean that they can do things that humans are used to doing such as translations, calculations… Otherwise they are just tools. However, it maybe possible that, in the future, humans will be the tools of machines..

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