翻译：
What challenges will “AI + Education” face?
On a global scale, the continuous development of artificial intelligence technology has become an important force to promote education change. The deep integration of artificial intelligence technology and education has not only had a profound impact on teaching methods and learning methods, but also touched the core of education concepts, and will certainly promote the fundamental change of education paradigm. However, like a double-edged sword, the wide application of artificial intelligence technology in the field of education has also brought a series of problems and challenges to the development and reform of education.
● Technical challenges.
Technical applicability challenge. Current artificial intelligence technology, despite significant progress, is still inadequate in the face of complex scenarios in education. The essence of artificial intelligence is to simulate human intelligence, which relies on algorithms and data to perform tasks, provides a new way of personalized learning and teaching for education, and improves the efficiency and experience of education. However, this technology has not yet reached the stage of full maturity, and still faces the challenge brought by the sparsity of learning data, which may lead to the lack of accuracy of personalized schemes. At the same time, in the case of limited data resources, the model is also biased. These problems not only affect the deep application of artificial intelligence in education, but also cause many educational artificial intelligence products on the market to be not “intelligent” enough in practical application, and it is difficult to meet the changing and complex needs of the education scene.
Technology depends on risk. The wide application of artificial intelligence technology in the field of education also brings a potential risk, that is, educators and managers may over-rely on these technologies to solve teaching and management problems, and learners may over-rely on artificial intelligence technology to obtain knowledge and information, which may lead to “technology dependence syndrome” in teaching and learning. The importance of independent thinking in the process of teaching and learning is ignored. Therefore, although the application of artificial intelligence in the field of education shows an irreversible trend, we should still adhere to the original intention of education, continue to focus on the core value of education and the comprehensive development of people, and avoid the excessive dominance of technology and weaken the educational function of education.
● Data security and privacy protection challenges.
According to the 2024 Artificial Intelligence Index report released by Stanford University, continuous progress and widespread use of technology have significantly improved productivity, but the promotion and application of current artificial intelligence technologies may also be limited by the limitations of the technology itself, and raise issues such as privacy, the spread of misinformation and intellectual property risks.
Data security challenges. During the collection, storage and transmission of data, it is important to ensure the security of data. In the field of education, the accumulated data not only covers the basic personal information of students, but also involves important records in their learning process, such as sensitive data such as learning progress, academic performance and behavior patterns. This kind of information has a high degree of privacy and sensitivity, if inadvertently leaked or maliciously used, will pose a serious threat to the safety of individual students, and may have an adverse impact on the stability and healthy operation of the overall education system. Therefore, how to establish a set of perfect data security mechanism to ensure the safety of data in the whole life cycle has become an urgent and crucial task in the field of artificial intelligence technology application.
The challenge of privacy protection. In the “AI + Education” scenario, large amounts of student data are collected and analyzed in order to provide a personalized learning program for each student. Students’ personal information, learning behavior and grades are all in the category of personal privacy, and the collection and use of such data must be based on full respect for students’ privacy. However, in practice, due to the influence of many factors such as philosophy, technology and management, the protection of student privacy may face uncertainties. In the integrated development of “artificial intelligence + education”, the protection of students’ privacy also needs to be given high attention to ensure the safety and reliability of the educational environment.
● Value challenges.
In the field of education, values and ethics are an indispensable part, and how to ensure that the application of artificial intelligence technology in the field of education meets the expectations and requirements of society is a challenge that “artificial intelligence + education” needs to face in terms of value.
The value function of technical products is absent. At present, most AI education products are mainly focused on adaptive learning, which provides students with customized learning content and feedback through intelligent algorithms. However, the goal of education is far more than the transfer of knowledge, but also includes the overall development of students, such as the cultivation of social skills, psychological quality, moral character and so on. However, the existing artificial intelligence education products are insufficient in the cultivation of these qualities, and the functional defects of artificial intelligence education products in the value level limit the comprehensive application and far-reaching impact of artificial intelligence technology in the field of education to a certain extent.
The difficulty of reconciling different values. Under the background of the deepening development of globalization and information technology, social ideas and concepts are increasingly diversified. In the process of promoting the integration of “artificial intelligence + education”, ensuring that the application of artificial intelligence technology can comply with this diversified development trend, especially with the core values and ethics of society, has become an urgent and challenging task. Specifically, there are significant differences in the understanding and practice of culture in different scenarios. For example, in some enterprises, collectivism and team spirit are regarded as important value orientation; In other companies, personal endeavor may be celebrated. Therefore, the design and application of artificial intelligence technology products should fully consider these cultural differences to avoid misleading.
● Challenges in the way knowledge is produced and disseminated.
The continuous deepening of the application of artificial intelligence technology not only changes the production and dissemination of knowledge, but also poses a new challenge to the mode of talent training. The challenge of the transformation of knowledge production mode to students’ independent thinking. Advances in artificial intelligence have changed the way humans acquire, create, and apply knowledge. The automation and intelligence of knowledge production mode have lowered the threshold of knowledge acquisition, but over-reliance on the content generated by artificial intelligence may form students’ inertia in learning, resulting in students gradually losing the ability to independently search, screen and integrate information. This change has brought new challenges to students’ ability of independent thinking.
The challenge of the paradigm revolution in the mode of knowledge dissemination to the function of schools. The application of artificial intelligence technology has brought about significant changes in the way knowledge is transmitted. The traditional “teacher-student” dual teaching mode is gradually changing into “teacher-machine-student” ternary structure. In this new model, teachers, machines and students promote and influence each other, and jointly promote the development of intelligent education. However, this change also means that people’s concept of school will change with The Times, that is, the function of school knowledge transmission will be weakened, which also challenges the functional positioning of school knowledge transmission.
● The challenge of adapting the roles of teachers and students.
In the “artificial intelligence + education” scenario, the roles of teachers and students have changed, and they need to constantly learn to better adapt to the changes in the education scene. The challenge of teacher role adaptation. In the “artificial intelligence + education” scenario, teachers are no longer just imparted knowledge, but gradually evolve into guides and assistants in the learning process of students. This not only requires teachers to have solid professional knowledge, but also requires them to master a range of new teaching tools and methods, and this shift undoubtedly puts higher demands on teachers. The challenge of student role adaptation. In the “artificial intelligence + education” scenario, students should not only have good autonomous learning ability, but also have the ability to effectively interact with artificial intelligence technology. For some students who are passive recipients under the traditional learning mode, independent learning will face unprecedented challenges and difficulties, which may further widen the academic achievement gap.
● Resource sharing challenges.
While AI technology presents many opportunities for education, it also poses challenges for equity. How to allow all students to enjoy the benefits of the application of artificial intelligence technology has become a crucial issue.
Transparency concerns raised by “algorithmic black boxes”. Algorithmic black box refers to the fact that the internal logic and decision-making process of an algorithm is opaque and difficult for users to understand, so it is difficult to detect and correct errors in it, and decisions based on these errors may have a negative impact on fairness. “Algorithmic black boxes” are often highlighted by problems such as algorithmic bias and lack of transparency. Technology potential difference affects application cost. Specifically, some developed regions and schools, due to their rich educational resources and financial support, can have relatively good technical infrastructure, and these regions and schools can use artificial intelligence technology to assist teaching earlier and more comprehensively, thus providing students with a richer and more efficient learning experience. Conversely, schools in remote areas or with poor economic conditions may not be able to afford the high cost of technology, and thus face different situations in the allocation of artificial intelligence education resources.
