How do humans and robots cooperate in the era of artificial intelligence?
Date：2019-08-14
In addition to promoting industrial and technological transformation, the era of artificial intelligence has also brought people's worries about the future fate of mankind. It stems from the fear that "most of human work will be replaced by machines". The real result of artificial intelligence is to occupy the upper value chain, involving values or having a very high level of knowledge. Threshold work. So, in the era of artificial intelligence, how should man and robot work together?
The smarter the machine, the more human beings understand it.
In the era of artificial intelligence, one of the abilities that people must possess is the ability to get along with artificial intelligence. Whether we like it or not, this era has come before us. In the next five to ten or twenty years, we will see that they are widely used in various fields. The ability to get along with AI, just like our ability to get along with the mobile Internet today, will become a necessity of life.
With the development of science and technology, human beings need to know more about science and technology; the smarter the machine, the more we need to understand the machine, beyond the machine to explore the boundaries of science and technology. So how can we have such scientific thinking and keep pace with the development of science and technology? We should go back to the most basic place to understand the nature of science and artificial intelligence.
Artificial intelligence is a kind of information processing algorithm after all. At present, the most promising algorithm is called deep learning, which imitates the neural network of human cerebral cortex. Only the human cerebral cortex has six layers of neural networks, and the current artificial intelligence program can have one hundred layers of neural networks, so it is called deep learning. However, no matter how complex the algorithm itself is, we can still know the essence of the algorithm, which is to process data with a deep network to get the correct answer.
When we use such basic thinking to understand AI, we can easily know what it can do and what it can not do in the future. First of all, the ability to get along with people. Artificial intelligence, a deep neural network, can deal with massive data and information, but it also has great limitations, such as the lack of self-reflection, the ability to truly understand the world's common sense, and the ability to understand the inner thoughts of others.
Although AI can talk to people at present, it can only deal with specific data in specific fields, and it does not have a large amount of background knowledge and common sense system of the world. It can recognize a lot of data and images, but it is very difficult for it to really understand a situation and understand everyone's mind in this situation. In addition, AI does not have all the physiological functions of human beings, including human emotions, human sympathetic neurons, mirror neurons and so on.
Artificial intelligence algorithm, there is no part of self-awareness, self-reflection, self-awareness, so it is difficult to understand itself. It's hard to understand oneself and others, because most of the time we push ourselves and others, but AI doesn't have such ability.
Because of the above limitations, in the future work, AI is still good at repetitive areas with clear rules, and people need to communicate with others, to understand the intentions of others in a large number of communications. In the final analysis, the machine
The smarter the machine, the more human beings understand it.
In the era of artificial intelligence, one of the abilities that people must possess is the ability to get along with artificial intelligence. Whether we like it or not, this era has come before us. In the next five to ten or twenty years, we will see that they are widely used in various fields. The ability to get along with AI, just like our ability to get along with the mobile Internet today, will become a necessity of life.
With the development of science and technology, human beings need to know more about science and technology; the smarter the machine, the more we need to understand the machine, beyond the machine to explore the boundaries of science and technology. So how can we have such scientific thinking and keep pace with the development of science and technology? We should go back to the most basic place to understand the nature of science and artificial intelligence.
Artificial intelligence is a kind of information processing algorithm after all. At present, the most promising algorithm is called deep learning, which imitates the neural network of human cerebral cortex. Only the human cerebral cortex has six layers of neural networks, and the current artificial intelligence program can have one hundred layers of neural networks, so it is called deep learning. However, no matter how complex the algorithm itself is, we can still know the essence of the algorithm, which is to process data with a deep network to get the correct answer.
When we use such basic thinking to understand AI, we can easily know what it can do and what it can not do in the future. First of all, the ability to get along with people. Artificial intelligence, a deep neural network, can deal with massive data and information, but it also has great limitations, such as the lack of self-reflection, the ability to truly understand the world's common sense, and the ability to understand the inner thoughts of others.
Although AI can talk to people at present, it can only deal with specific data in specific fields, and it does not have a large amount of background knowledge and common sense system of the world. It can recognize a lot of data and images, but it is very difficult for it to really understand a situation and understand everyone's mind in this situation. In addition, AI does not have all the physiological functions of human beings, including human emotions, human sympathetic neurons, mirror neurons and so on.
Artificial intelligence algorithm, there is no part of self-awareness, self-reflection, self-awareness, so it is difficult to understand itself. It's hard to understand oneself and others, because most of the time we push ourselves and others, but AI doesn't have such ability.
Because of the above limitations, in the future work, AI is still good at repetitive areas with clear rules, and people need to communicate with others, to understand the intentions of others in a large number of communications. In the final analysis, the machine
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