With the advent of the era of big data, AI learning and analysis technology has become a new wave of educational digitalization. The ethical issues, especially a series of user data security and privacy issues in the process of AI learning analysis, have become the focus of educational development.

The greatest value of big data AI learning analysis is using machine learning for data mining. Collecting, measuring and reporting user learning data through data regression analysis with certain algorithms makes us understand and optimize the learning process. Thus, we can have an opportunity to develop an individualized and personalized education. However, in order to achieve this goal, AI learning requires a large amount of data to build and train its model. In general, the developers of these educational applications with AI learning analysis will choose to host their data on a cloud server from companies such as Amazon, Google, etc. Therefore, the security of the server becomes the key to protect users’ privacy.

As developers of educational applications, they should have the ability to distinguish whether the cloud service provider is good or not and try their best to choose cloud servers that conform to the Internet information security laws from their own countries and regions. When using an open-source project for research and development, developers need to be sure to do a good job of using data encryption in case the server is attacked and cause user data leaking. Finally, it is always important to inform users of the categories of collected data in a prominent place in its application UI, so users can know that they are providing their data for a better experience rather than a commercial purpose. As users, try to avoid using applications that user privacy policies are ambiguous or even unable to find. Having a sense of self-protection is vital in personal data protection.