Author: Zen and the Art of Computer Programming
With the widespread application of emerging technologies such as artificial intelligence, machine learning, and deep learning, humans are increasingly dependent on the wisdom of nature. The same is true in the manufacturing field. The production process of intelligent manufacturing itself is a highly complex project that requires a certain degree of control and guidance of human factors. Therefore, how to make AI truly play its role and become a true human-machine collaboration tool has become an important and challenging issue. The key to this issue is how to make AI innovation generate reasonable and feasible value while protecting people's basic rights and freedoms from infringement.
Artificial intelligence will involve many complex technical and management issues in the manufacturing field. Among them, ethical and legal issues are the most important ones. Traditional manufacturing processes are usually performed by humans and can lead to various inhumane behaviors during execution, such as killing workers or causing occupational hazards. Since there is no way to prevent this from happening, it is actually difficult for factories to gain sufficient incentives to regulate and control. Therefore, how should machine-intelligent manufacturing systems establish rules so that they can better coordinate workers’ workflow and productivity? Based on this, we can discuss it from the following two aspects.
- Data protection and security
Data protection and security is a relatively sensitive topic. Since machine intelligent manufacturing systems automatically process large amounts of data, corresponding measures need to be taken to ensure the integrity and security of the data. For example, encryption technology can be used to encrypt data to improve data security; data monitoring can be implemented through monitoring systems to detect abnormal data and provide reminders and punishments; and personal data privacy can be guaranteed through data privacy protection laws and regulations.
- Individual differences and intelligence bias
Individual differences mean that different individuals may have different types of psychological characteristics, personality habits and preferences, which affect the results of the manufacturing process. Different people's physiological structures, living habits, professional experiences, etc. may lead to deviations in the manufacturing process. For example, individuals may like certain foods such as bread, yogurt, and beverages, while others are less enthusiastic about eating these foods. Therefore, manufacturing systems need to take into account people’s