[Historical Commentator] While redoing a presentation, I thought of the concept of the V.U.C.A era (Volatility, Uncertainty, Complexity, and Ambiguity). The term “V.U.C.A” is an acronym formed from the first letters of the following four English words: Volatility, Uncertainty, Complexity, and Ambiguity. This concept originated in the early 1990s, proposed by the U.S. Army War College after the Cold War, to describe a more volatile, unpredictable, and complex global security environment. We have long been in this era, and the rapid development of Artificial Intelligence (AI) has become a concentrated embodiment and amplifier of V.U.C.A characteristics: it drives market and technological fluctuations at an unprecedented speed, exacerbates future uncertainties, makes social systems more complex and interconnected, and triggers a plethora of ethical and cognitive ambiguities.The high integration of the V.U.C.A era and the AI era poses fundamental challenges to education, forcing it to accelerate its shift from the traditional “knowledge transmission” model to a new paradigm centered on “competency development”.Under the dual shaping of V.U.C.A and the AI era, in the face of information explosion and accelerated knowledge iteration, the focus of education has shifted from mere “knowledge impartation” to “competency development”. Traditional static knowledge has become extraordinarily easy to acquire in the face of AI, and its “shelf life” is increasingly shortened, requiring education to cultivate students’ abilities to acquire, analyze, and discern information, as well as core competencies such as critical thinking, innovative thinking, communication and collaboration, and complex problem-solving skills, enabling them not only to cope with current challenges but also to navigate the future.
In the AI era, education will inevitably transition from “standardization” to “personalized and adaptive learning”, as AI technology can analyze students’ learning data, provide customized learning content, pace, and feedback, achieving true tailored instruction to help each individual better adapt to uncertainty.To adapt to the reality of increasingly shortened skill “shelf life”, the importance of “lifelong learning and iteration” will become even more significant—many traditional jobs and skills may be automated or reshaped by AI, making continuous learning a necessity for individual survival and development. Learning is no longer confined to the classroom but spans the entire life process, requiring the cultivation of students’ abilities for self-directed learning, exploratory learning, and reflective learning to continuously update knowledge and skills. At the same time, in terms of learning paradigms, education is shifting from “one-way teaching” to “inquiry-based, project-based, and human-machine collaborative learning” models. This means that teaching needs to help students actively discover problems, explore knowledge, and solve problems in practice. Students need to learn to collaborate with AI tools, utilizing AI for data analysis, content generation, and efficiency enhancement, while also understanding the limitations and ethical issues of AI.We must recognize that AI’s continuous surpassing in the cognitive domain highlights the importance of uniquely human values. It requires education to no longer focus solely on “cognitive skills” but to place “emotional, social, and ethical literacy” on an equally important level. Human-specific non-cognitive abilities such as emotional intelligence, empathy, cross-cultural understanding, moral judgment, and innovative inspiration become core competencies that AI cannot replace. At the same time, the development of AI also brings a series of ethical challenges related to privacy, fairness, employment, and social governance, thus education needs to guide students to engage in deep thinking and judgment, cultivating their sense of responsible digital citizenship and global citizenship literacy.
In the V.U.C.A and AI era, the role of teachers is no longer simply that of knowledge transmitters but rather as facilitators, designers, motivators, and companions in life. This requires teachers to first possess profound subject knowledge and interdisciplinary integration abilities, capable of breaking down disciplinary barriers and guiding students in comprehensive, cross-domain inquiries. Secondly, teachers need to have excellent teaching design and learning facilitation skills, able to shift from “teaching” to “learning”, designing inspiring, challenging, and personalized learning activities, and utilizing data and AI tools for differentiated instruction. More critically, teachers must possess high digital literacy and AI application capabilities.Therefore, teachers need to understand AI principles and trends, proficiently apply AI tools to enhance teaching efficiency, and guide students to use AI critically and responsibly.
Thus, teachers’ emotional intelligence, empathy, and interpersonal communication skills are particularly valuable in the AI era. In a context where cognitive tasks are increasingly assisted or even undertaken by AI, the caring, understanding, and motivating role of teachers as “humans” is amplified. They need to deeply understand students’ emotional needs, establish trust and supportive teacher-student relationships, and stimulate students’ intrinsic motivation for learning and growth mindset. At the same time, teachers bear the ethical responsibility and guiding role of values, leading students to think about the complex ethical issues brought about by AI development, such as social equity, privacy, and employment, cultivating their sense of social responsibility and global citizenship. Teachers themselves must also be lifelong learners, continuously iterating their knowledge and skills to keep pace with educational reforms.The intersection of V.U.C.A and the AI era presents unprecedented high demands on education and bestows a deeper mission on teachers. Teachers must enhance their AI literacy to meet the challenges of the AI era. Research in the United States indicates that “AI literacy is a set of knowledge and skills for understanding, using, and critically evaluating AI; AI literate individuals can effectively use AI to achieve goals, develop knowledge and career potential, and participate and judge as workers, consumers, and citizens in modern society without needing to master the underlying technical details.”