In recent days, the launch of Sora, a large model developed by OpenAI, the parent company of the renowned language model ChatGPT, capable of instantly generating short videos based on text commands, has become a hot topic of discussion across various sectors. Some industry experts point out that the birth of Sora signifies that the realization of General Artificial Intelligence (AI) might be shortened from a decade to just one or two years.
The rapid development of artificial intelligence will also reshape the higher education system, where the cultivation of specialized knowledge and skills forms the core foundation. The emphasis on fostering imagination, reasoning, speculation, and judgment as essential components of critical thinking will become more crucial than ever before.
Traditional higher education places a strong emphasis on specialized knowledge and skills. The curriculum of a university major consists of a set of specialized courses, encompassing both the imparting of specialized knowledge and the cultivation of specialized skills. In an era where specialized talent is in high demand, narrow specialization and rapid knowledge and skill training can rapidly supply a large number of professionals to various industries.
However, since the turn of the century, this training model closely aligned with the industrial age has faced significant challenges. Universities are increasingly focusing on general education, hoping to help young people better adapt to future developments by strengthening the cultivation of general thinking and abilities.
From the era of "scoring points" in primary and secondary school to the era of "grade point averages" in college, there is essentially no difference in nature. Even in many top universities in China, students still devote a significant amount of time to knowledge memorization and coursework. A considerable portion of the academic burden actually involves "piling up workload." This repetitive pattern of academic training does not contribute to the improvement of thinking and innovation abilities. It also dampens the enthusiasm of many students for learning, leading them to constantly "escape" from these majors.
Currently, continuing to excessively emphasize "memorization" and "drilling exercises" has lost its significance. With artificial intelligence gradually advancing from weak AI to General AI, the necessity of extensive memorization of repetitive knowledge and mathematical calculations has diminished. With the assistance of various AI tools and cloud computing, college students can engage in more imaginative and creative learning. Universities do not need to force students to compete with AI using human brainpower. The goal of education should be to continuously enhance individuals' independent thinking and judgment abilities, with a focus on guiding college students to improve their abilities in higher-order thinking, rather than continuing to bind them in repetitive, low-level thinking training through courses and exams.
In the training of talents in various disciplines, the deep integration of artificial intelligence has become a basic trend both domestically and internationally. Top universities in the United States have already achieved AI integration coverage in many disciplinary fields. For example, at Stanford University, the business school has developed courses aimed at helping managers and policymakers responsibly utilize artificial intelligence, while the CRAFT program at the School of Education collaborates with the Artificial Intelligence Research Institute to provide teaching resources for high school teachers.
In addition, the School of Engineering at Stanford University has established an artificial intelligence track under computer science, covering core topics such as knowledge representation and machine learning; the School of Humanities and Sciences offers undergraduate courses in symbolic systems, combining traditional humanities methods with modern computational science... In short, the university has integrated AI literacy and skills into the overall disciplinary layout through innovative reforms in course specialization and training objectives, achieving interdisciplinary integration of disciplines.
AI-related program offerings are not limited to traditional AI disciplines or majors. For instance, Carnegie Mellon University in the United States has covered multiple aspects ranging from fundamental research in artificial intelligence to the application of AI technology in social issues. MIT offers majors such as Artificial Intelligence and Decision-Making, Computation and Cognition, Computer Science, and Molecular Biology, all aimed at cultivating composite talents in artificial intelligence.
Most schools in the United States also offer majors that combine artificial intelligence with fields such as healthcare, autonomous driving, and financial technology. These courses and program offerings cover not only core AI technologies but also include content such as data analysis, machine learning, deep learning, human-computer interaction, and electronic engineering, aiming to cultivate composite talents capable of applying AI technology in multiple fields. This diverse and interdisciplinary education model provides students with broad learning perspectives and flexible career development paths.
Universities focusing on AI talents must pay special attention to the cultivation of critical thinking, innovation ability, and ethical values, among other non-technical abilities. Only in this way can they comprehensively address the social challenges brought about by AI technology.
In the course design of AI-related programs at US universities, particular emphasis is placed on social ethics and legal knowledge. Not only do undergraduate and graduate courses incorporate relevant content, but some university institutions also establish specialized research institutes and centers to delve into ethical issues in AI data system design and application, ensuring that students grasp advanced technology while also considering humanistic care and legal responsibilities.
AI with powerful computing capabilities will surpass humans in more and more aspects. An important direction for higher education is AI-assisted teaching and learning. Universities must focus on developing and procuring various AI tools for learning and research to provide necessary support for faculty and students. The future university will undoubtedly be a new type of organization where AI-assisted teaching and learning will occur in the vast majority of scenarios.
Moreover, students should be given ample space for reading, thinking, and socializing. Only in this way can they avoid being burdened by fragmented academic tasks. Overly detailed specialization, excessively specific course content, and overly dull learning processes will only increasingly erode students' interests. Only through independent, cooperative, and exploratory learning processes can students develop lofty aspirations, broad minds, stable emotions, and cross-cultural communication skills. If students can master fundamental principles, engage in independent thinking and judgment, accept ethical and moral constraints, and possess healthy minds and stable emotions, they will undoubtedly be able to adapt to any rapid changes in the economy and society.
