In science fiction movies, robots are portrayed as thinking and conversing naturally with humans, but in reality, AI reacts based on pre-stored data and doesn’t have the ability to truly think. The quest for strong artificial intelligence has been ongoing since the Turing Test and the Chinese Room experiment, but the emergence of AI that can understand new concepts and think creatively like humans remains elusive.
Many science fiction movies, from Star Wars to Transformers, feature robots as a main character. In reality, many robots have been developed and are making our lives easier by helping us clean or performing sophisticated surgeries. However, robots in movies are very different from robots in real life. For example, in the Transformers movies, there are frequent scenes where the main character and the robot talk to each other, and most robot movies include conversations with robots. To have a conversation, you need to be able to understand what the other person is saying and respond accordingly.
‘A’: “Have you eaten?”
‘B’: “I’m going to school now.”
In the example above, ‘A’ and ‘B’ are speaking to each other, but they’re not actually having a conversation. Conversation is more than just exchanging words, it’s the process of communicating your thoughts to the other person. The reason why we see so many scenes like this in movies is that they reflect our dreams of talking to robots. Artificial intelligence is the discipline that is needed to create “thinking machines” that can communicate with humans.
Most of us have heard the term artificial intelligence, but not many people know what it means. The term refers to intelligence created by humans or other intelligent beings, or artificial intelligence. There are two main types of AI: strong AI and weak AI. While both are computer-based, strong AI can actually think and solve problems, while weak AI cannot. In this article, we’ll discuss the kind of AI we need to build robots that can talk to us.
In the discussion of strong AI, philosophers have debated from a philosophical perspective whether it is possible to embody human intelligence or consciousness in a machine. The Turing Test is a famous experiment that supports the possibility of AI, and the Chinese Room experiment is a counter-example.
The Turing Test was designed to answer the question “Can a machine think?” and is based on the claim that “a computer can think if its responses are indistinguishable from those of a human being.” In other words, if a machine’s responses are indistinguishable from those of a human being, then the machine should be considered intelligent.
The “Chinese Room” experiment, on the other hand, shows that just because a computer reacts doesn’t necessarily mean it has gone through a thought process. In a nutshell, the experiment involves putting a person who doesn’t know Chinese in a room, providing them with a writing utensil and a list of pre-written Chinese questions and answers. The person outside the room writes a question in Chinese, and the person inside the room writes the answer according to the prepared list and sends it out. The person outside the room may feel that they have communicated with the person inside the room, but in reality, the person inside the room is just writing down the prepared list without thinking. From this, we can conclude that even if a computer can answer a question, we cannot assume that the answer came from intelligent thought. In other words, it is difficult to determine whether a machine can actually think using the Turing test alone. The debate about whether machines can think has been going on for a long time.
In order to discuss whether machines can think, we need to be able to understand the meaning of the question. The technology that makes this possible is machine learning. Machine learning is exactly what it sounds like: giving computers the ability to learn so that they can perform behaviors that are not specified in code. Humans learn to expand their knowledge, understand new situations, and adapt to change. Machine learning is an attempt to implement these human learning abilities into computers. Before a computer can understand a sentence, it needs a huge amount of data. It stores tons of data in a database with the appropriate answers to each question, and utilizes big data and data mining techniques to find statistical rules or patterns in large amounts of data. This process enables the computer to give the right answer to a given question.
In this way, it is possible for a computer to have a conversation with a human based on data that is already available. However, if you ask if computers can “think”, depending on how you define it, it’s likely not possible at this point. It’s hard to process data that doesn’t exist. Babies can combine the words “gone” and “there” to form the phrase “there is,” and this kind of creative expression is beyond the capabilities of computers. Of course, with our current technology, we can beat a world chess champion or win a quiz show. However, chess is played by storing all the possible moves in a database and using them, and quiz shows are played by analyzing questions and searching for relevant information in a database to find the answer. In other words, it is not possible for a machine to “think” like a human, but to find the answer based on a large amount of data. But just as we’ve gone from the novelty of the folding phone to the everyday smartphone in a matter of years, we hope that one day we’ll be able to talk to robots as naturally as we talk to people.
