Summary of the Core Content
This conversation begins with Hou Haoran's choice of major for the college entrance examination and, through Gao Yuliang's analysis, explores various aspects such as changes in trends in major selection across different eras, the underlying logic behind the establishment of new popular majors in universities, the distribution of benefits in high-tech industries, the pathways for ordinary people to benefit from technological advancements, and the differences in major choices between elite and less affluent families. Essentially, it discusses the core issue of how individual choices should align with the development of the times.
The Shift in Major Selection Trends: From “Elite Liberal Arts” to “Priority for Hard Skills”
Before the 1990s, higher education was an “elite era” – college students were scarce, and jobs were guaranteed after graduation; the choice of major was not as important (the focus was on recruiting talent first and then training them). Elite families preferred majors in liberal arts such as history, law, and economics, following the PPE (Philosophy, Politics, Economics) tradition seen in European and American politics (for example, George W. Bush and Barack Obama both came from liberal arts backgrounds). However, things have changed now: the country's focus has shifted to high-tech industries, and elite families are encouraging their children to study science and engineering first to acquire practical skills, with management or law as secondary pursuits. Traditional liberal arts majors are no longer as sought-after as they used to be.
In simple terms, in the past, college graduates were highly valued and guaranteed stable jobs; nowadays, one must have real skills to succeed – relying solely on charisma or connections is becoming increasingly difficult.
The Establishment of New Popular Majors in Universities: Not Out of Thin Air, but a Reorganization of Resources
The Ministry of Education’s addition of new majors such as AI, intelligent robotics, and low-altitude economy does not mean that universities have suddenly acquired new teachers. Instead, it involves reorganizing existing academic resources. For example, teachers from computer science and mathematics departments are assigned to teach AI, while those from automation and mechanical engineering departments are moved to work on intelligent robotics, with adjustments made to the research directions. The purpose of this is twofold: to attract students interested in these popular majors and to secure more funding for research from the government or corporations.
To illustrate, it’s like a restaurant that recombines existing ingredients to create “internet-famous dishes” to cater to customer preferences – the goal is both to attract customers and to qualify for subsidies for innovative dishes.
Why Isn’t High-Tech as Inclusive as Real Estate?
The real estate industry is considered inclusive, as almost everyone can benefit from it, from construction workers and contractors to home appliance manufacturers and property developers (even someone with a middle school education can work in these fields). However, high-tech is different; the benefits mainly flow to corporate shareholders and senior engineers (such as those in semiconductors, who typically require a doctoral degree), making it difficult for ordinary people to participate directly. For instance, during a real estate boom, anyone selling building materials at the neighborhood could make money; but with the rise of AI, if you haven’t studied programming, you might not even have access to work related to this technology.
The Benefits of High-Tech: Opportunities for Ordinary People Come When the “Application Layer” Blooms
The benefits of high-tech development come in two waves. The first wave is associated with foundational technologies (such as GPUs, computing power, and large models), which are accessible only to scientists, top engineers, and investors. The second wave comes when these technologies are applied in practical contexts – just as the early internet era saw the emergence of e-commerce platforms, ride-hailing services, and live-streaming influencers, who did not need to understand the underlying technology but could still benefit from its advancements.
Gao Yuliang suggests that AI is currently in the foundational technology phase, and when it becomes as widespread as the Windows operating system, ordinary people will have new opportunities. New professions such as “AI content planning” or “AI assistant operations” may emerge, where one only needs to know how to use the tools, not understand their inner workings.
The Difference in Confidence When Choosing a Major Between Elites and Less Affluent Families
Elite families (like Hou Haoran’s) can afford to make more speculative choices when picking a major, as they have the resources and connections to support their children, whether it’s in liberal arts (such as PPE) or more practical fields. For less affluent families, choosing a major is a matter of life and death; a wrong choice could affect a child’s entire career, so they opt for practical majors with quick employment prospects (such as computer science or nursing). Zhong Xiaoi’s decision to choose PPE is also practical: popular engineering majors require high scores and are difficult to enter, and even if Hou Haoran were interested, he might not be able to compete. Elite families have more flexibility, while less affluent families face greater limitations.
This conversation may seem to be about choosing a major, but it actually reflects the logic of personal choices in the context of broader trends. Whether it’s a major or an industry, one must keep up with the times. Ordinary people don’t need to worry about falling behind in high-tech developments; once the technology becomes widely available, opportunities will arise. Additionally, family backgrounds significantly affect the room for error when making such decisions.