Author: Zhao Leilei (Associate Professor, School of Education, Jiangnan University); Dai Ruihua (Professor of the Department of Education, East China Normal University, Director of the Training Center of the Middle School Principal of the Ministry of Education)

Artificial intelligence is becoming a new focus of international competition, and it has also brought new development opportunities to human society. The rapid development of technologies such as machine learning, natural language processing, emotional computing, and virtual reality not only provides strong support for students to obtain higher-quality educational experiences, but also helps to further expand the space for teachers to develop freely. But at the same time, artificial intelligence technologies such as intelligent tutor systems and intelligent data mining face many ethical problems in educational applications, such as data leakage, public security, malicious competition, etc.

Artificial intelligence (AI) is part of computer science, including the research and development of theories, methods, technologies and application systems used to simulate, extend and expand human intelligence. The ethics of educational artificial intelligence are used to regulate the principles and principles of relationships and behaviors in the development and application of educational artificial intelligence.

Although educational artificial intelligence has strong data integration and analysis capabilities, it will also trigger a series of new ethical risks. Systematically, it is mainly reflected in the following four aspects.

First, information security. While artificial intelligence helps education and teaching, it not only creates opportunities for the development of teachers and students, but also produces massive educational data such as personal identity information, behavioral trajectory, learning preferences, etc. If such data is not effectively protected or used illegally, it will cause a series of information security issues, such as malicious leakage and improper use of personal privacy information, malicious push of emails, illegal electronic monitoring, online fraud, and data infringement. Then, the privacy rights of teachers and students will become very fragile under the artificial intelligence perspective mirror.

Second, goal conflict. The risk of conflict in targets of educational artificial intelligence is mainly caused by inconsistent basic goals of artificial intelligence developers and users. For the private sector, due to the deep-rooted concept of business interests, it may rely on artificial intelligence technology tools to pursue self-interest too much. Moreover, many educational artificial intelligence designers and developers lack the sense of responsibility to be committed to "educational public services" and lack value care for educational growth. If the artificial intelligence developers and school management teams do not reach a consensus on the educational application of artificial intelligence, it will be difficult for teachers and students to be effectively protected in the long run.

Third, there is a lack of institutional constraints. At present, the system used to restrict the development and application of educational artificial intelligence has not yet been sound, and the legitimate rights and interests of educational users are difficult to be effectively protected. Moreover, the absence, loss and dislocation of the professional system constraint system have become important factors that lead to the emergence of immoral behavior of educational artificial intelligence. If effective technical standards and "mandatory" legal means are lacking to regulate, the design, development and practical application of educational artificial intelligence may gradually deviate from the educational value and humanistic stance. Accountability and sanctions should be imposed on behaviors and measures that violate the ethical norms of educational artificial intelligence in order to reasonably regulate the behavior of artificial intelligence developers, educational users, etc.

Fourth, excessive resource dependence. Currently, although machine learning and algorithm recommendations can realize personalized push of teaching resources, this seemingly fair and reasonable artificial intelligence application implies unknown algorithm discrimination and technical bias, which may lead to the teaching resources obtained by students. With high homogeneity, students gradually form resource dependence and are unwilling to break free from rigid thinking, which in turn affects students' broad vision and innovative development. Moreover, in order to save their own time and work costs, teachers may rely too much on teaching resources pushed by artificial intelligence and lose their unique understanding and thinking about education and teaching.

Clarifying the path to eliminate related ethical risks will help encourage education to be able to morally utilize artificial intelligence opportunities and achieve fair and ethical educational decision-making.

First, focus on the cultivation of information literacy for teachers and students in the intelligent era. First of all, we need to focus on cultivating information discrimination between teachers and students. Schools should guide teachers and students to understand and think about issues such as information resource acquisition and screening, information ethical risks, and enhance teachers and students' information discrimination ability. Secondly, pay attention to cultivating information feedback from teachers and students. Schools should guide teachers and students to reasonably feedback on the information security, ethics and comfort of artificial intelligence, and build a smooth information feedback channel to continuously improve the effectiveness of artificial intelligence's educational application.

Second, improve the review and resolution mechanism of educational artificial intelligence algorithms. First of all, we should focus on building a review mechanism for artificial intelligence algorithms. The operational deviation of artificial intelligence algorithms may persist and may even be amplified. Basic specifications and security protocols for training and testing of artificial intelligence algorithms should be formulated to analyze the educational essence of the premise assumptions of artificial intelligence algorithm models. In particular, whether the educational artificial intelligence algorithm system contains algorithm discrimination and abuse problems should be reviewed so that the maximum Ensure the accuracy, privacy and security of user data and information to the limit. Secondly, it is necessary to clarify the resolution mechanism of artificial intelligence education application solutions. Governments, schools, enterprises, etc. must adhere to the principle of brainstorming decision-making, encourage the proposal and open discussion of different opinions, think about the optimal decisions for the application of educational artificial intelligence through some form of voting and evaluation, and strive to realize the demands of public interest in education. reasonable satisfaction.

Third, strengthen regulatory supervision of artificial intelligence and data. The current development of educational artificial intelligence has exposed many technical and data abnormalities. Therefore, it is necessary to improve the risk accountability mechanism of intelligent technology and educational data to achieve standardized supervision of intelligent technology and data. First, you can try to formulate and promulgate legally binding educational artificial intelligence regulations to regulate ethical responsibilities for technology development and application. Illegal development, use and sales of artificial intelligence will face legal consequences and responsibilities. Secondly, focus on data supervision in the application of educational artificial intelligence and build a professional data privacy supervision organization or organization. Privacy regulatory organizations or institutions should evaluate the data security of an artificial intelligence technology before it is promoted and applied to avoid illegal sharing and use of data.

Fourth, strengthen the investigation and assessment of ethical risks of education artificial intelligence. To realize ethical educational artificial intelligence, we should not rely solely on technological improvements. We should also adopt "systematic thinking" to examine and investigate the ethical risks of educational artificial intelligence, which is crucial to maximizing the protection of the public interests of education. The existence of ethical risks of education artificial intelligence involves not only the development stage, but also the production and distribution stages. In addition to ensuring the security of educational artificial intelligence design, the hazard levels of intelligent algorithm ethical risks, educational data ethical risks, etc. should also be carefully evaluated in order to timely formulate a solution to the ethical risks of educational artificial intelligence.

Fifth, build a school-based education artificial intelligence ethical normative system. The school-based ethical normative system of educational artificial intelligence must be highly fair and interpretable, clearly stipulate the basic requirements, review procedures and ethical norms for the application of artificial intelligence in schools, and educate technology developers, school administrators, etc. The responsibilities, rights and obligations of ethical supervision shall be reasonably divided and limited. School administrators can set permissions for the application of artificial intelligence in school education based on the school-level education ethical normative system. If an artificial intelligence technology poses a major ethical risk in its application, the application license permissions of artificial intelligence should be appropriately restricted based on the level of evaluation of the ethical risk.

(This article is the result of the 2020 special key project of the Chinese Society of Higher Education "Research on Prevention and Resolving Risks in Information Security in Colleges and Universities" [])