AI is advancing. Now it’s up to humans to redefine their worth

Generative artificial intelligence (AI) powered by large language models presents a significant breakthrough. For the first time, humans are communicating with computers using language instructions. This has enabled the use of AI agents to perform intelligent tasks involving some degree of advanced reasoning and complex logic. Vibe coding – the use of AI for programming and software development by lay persons – empowers end-user application deployments. One-person companies using AI agents to manage business and handle clients are gaining support in places like San Francisco, Singapore and Chinese cities such as Shenzhen and Hangzhou. As white-collar workers are empowered by AI, companies are gearing up to consolidate or slash jobs. A recent index published by Tufts University ranks writers and authors (57 per cent), computer programmers (55 per cent) and web and digital interface designers (55 per cent) as being most vulnerable to AI-driven job losses. Tech companies such as Amazon and Meta have commissioned massive lay-off plans to prune tens of thousands of workers. Job prospects seem gloomy in banking, finance and consultancy too. When AI can autonomously undertake intelligent tasks, we need to ponder – should schools still teach subjects such as programming or financial portfolio analysis? Bill Gates once said that AI will replace teachers, doctors and other professionals. Indeed, surveys suggest that many students are using AI in schools to help with learning. When students can interact with multi-modal AI agents to learn, build applications and complete tasks, what becomes of the role of teachers? Taking one step backwards, why would most students need to learn foundational subjects such as programming or statistics? As educational workers have pointed out, learning is more than knowledge acquisition; it encompasses mentorship and guidance, emotional support and inspiration, so human presence is essential. That said, we must admit the fact that some subjects may be directly substitutable by AI, and perhaps even better taught by AI than by humans. Why attend a lecture on algorithms when an AI agent can generate code and explain it on demand with vivid illustrations and step-by-step guidance? The focus of this discussion should not be whether we need teachers or professionals in the age of AI. Instead, we must recognise that knowledge “expires” over time. I used to use a word processor called WordStar in the 1980s. Back then, WYSIWYG (what you see is what you get) wasn’t widely accessible, so to produce a typesetter document, I had to memorise a long list of “dot” commands such as. OP for omitting page numbers or. LM to set the left margin size. Similarly, to construct a web page in the 1990s, we had to memorise a long list of HTML tags and attributes. Universities used to teach such knowledge, alongside tools such as Microsoft Office utilities or programming languages such as Assembler or COBOL. With AI, it is now time for programming classes that focus on syntax, and possibly other subjects, to retire from the curriculum. We must recognise that knowledge is not a static commodity. Instead, it is a living ecosystem that evolves over time. Foundational skills today were once cutting-edge innovations decades ago. Many things we consider basic now were once advanced, and many things we consider essential now may soon expire. Therefore, the most pragmatic way to internalise AI is to proactively phase out old knowledge and introduce new, value-added knowledge as we develop tools such as AI agents. Just as we stopped teaching WordStar commands without abandoning the teaching of writing, we must stop teaching obsolete coding practices or syntax without abandoning the teaching of engineering. Similarly, concerns about job loss are misguided. Jobs always transform and evolve under new technologies. We have seen this in earlier industrial revolutions. The introduction of the steam engine did not end work; it shifted it from intensive manual labour to mechanical operation. The important assessment now is figuring out what needs to be automated away and what new jobs can add value for people. With the emergence of powerful search engines such as Google, the teacher’s job has gone from practising rote learning to emphasising analytical reasoning and problem-solving abilities. Now, even AI can perform limited levels of reasoning and analysis. Teachers must advance to the next level, perhaps by guiding and inspiring students to pursue comparative assessments, judgments and innovations. In the context of Hong Kong transitioning to become a global educational hub that prides itself on high-quality institutions and rigorous standards, this evolution and iteration of knowledge is critical. We cannot afford to teach students to be obsolete before they graduate. The rise of agentic AI offers a chance to redefine what it means to be educated. It forces us to ask not “what can I build?” or “how can I build?”, but “what should I build?” and “why am I building?” Those who view this as the end of learning are mistaken. The end of the coding syllabus is not the end of education. It is merely the next chapter in a long story of human innovation. The curriculum must evolve, not vanish. We are going through technology iterations, not substitution. New technologies such as AI render some old knowledge obsolete. It is incumbent on the teaching professionals to refresh curricula and construct the knowledge of the future.

AI is advancing. Now it’s up to humans to redefine their worth

.css-1c6uqr6{color:inherit;font-weight:inherit;font-size:inherit;font-family:inherit;line-height:inherit;overflow-wrap:break-word;}As artificial intelligence upends job markets and academic norms, we must go beyond the fear of change to redefine what it means to be educated

As artificial intelligence upends job markets and academic norms, we must go beyond the fear of change to redefine what it means to be educated