Information Technology and Ethics/Privacy and Artificial Intelligence

The privacy issue is one of the major threats in the development and utilization of data resources at artificial intelligence area

Privacy Risks in Data AcquisitionEdit

With the extensive use of various types of data collection facilities, intelligent systems can not only identify identities through fingerprints, heartbeats, and other physiological characteristics, but also automatically adjust lighting, room temperature, music, and even sleep time according to different people's behavioral preferences. Exercise conditions, eating habits, and changes in physical signs determine whether the body is healthy. However, the use of these smart technologies means that intelligent systems grasp a significant amount of personal information, and even know themselves better than you. If used correctly, these data can improve the quality of human life, but if private information is used illegally for commercial purposes, it can cause privacy violations.

Privacy Risks in Cloud ComputingEdit

Because cloud-computing technology is easy to use, it provides a model, which use based on shared pools. Many companies and government organizations begin to store data in the cloud. After storing private information in the cloud, this information is available to various threats and attacks. Because artificial intelligence systems have high requirements for computing power, cloud computing has been configured as the primary architecture in many artificial intelligence applications. Therefore, when developing such smart applications, cloud privacy protection is also a problem that people need to consider.

Privacy Risks in Knowledge ExtractionEdit

Data extraction to knowledge is the primary function of artificial intelligence. Knowledge extraction tools have become more and more powerful. Many seemingly unrelated pieces of data may be integrated to identify individual behavioral characteristics, even personality characteristics. For example, by combining website browsing history records, chat content, shopping flow, and other types of record data, one can outline a person's behavioral trajectory, analyze personal preferences and behavioral habits, and further predict the potential needs of consumers. Companies can provide consumers with Provide necessary information, products or services in advance. However, these personalized customization processes are accompanied by the discovery and exposure of personal privacy. How to regulate privacy protection is a problem that needs to be considered simultaneously with technology applications.