A 90-Year Evolution of AI and a Guide to Future Survival: Professor Zhang Junping's Layman's Explanation at the Bund Conference
Hello everyone, I'm your financial journalist and economist. Today, we're not talking about boring code, but about matters of great importance that affect each of us—our jobs, lifestyles, and future career development.
On September 12th, at the 2026 Inclusion·Bund Conference held in the Shanghai Huangpu Expo Park, the School of Philosophy at Fudan University, in collaboration with Yicai, organized a very interesting forum. The star speaker was Professor Zhang Junping from the School of Computing and Intelligent Innovation at Fudan University. His lecture was titled "The Age of Artificial Intelligence: How Can Humans Coexist?"
Don't let the academic title scare you; Professor Zhang explained the past 90 years of AI development, the current technological bottlenecks, and how we should live in the future in a clear and understandable way. Let me first highlight the key points and then break down the five key arguments behind his speech.
Summary of the Core Content
In simple terms, Professor Zhang Junping told us that AI has been around for 90 years, evolving from playing chess to writing code, and it is now moving from "imitating humans" to "going beyond human logic." In the coming years, AI agents will become as common as smartphones, and ordinary people will be able to easily create their own AI assistants.
One of the most counterintuitive ideas is that AI excels at tasks that humans find complex but have clear rules (such as programming and writing reports), while it struggles with tasks that humans find simple but rely on instinctive reactions (such as complex manual labor and judgment that requires a unique perspective).
So, the future workplace won't be about who can memorize the most rules, but about who has a more "human touch," critical thinking, and a unique personal perspective. Our goal should not be to compete with AI in terms of computing power, but to become "hexagonal warriors" with multidimensional skills.
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In-Depth Analysis: Understanding the Changes of the AI Era from Five Dimensions
1. From "Chess Expert" to "All-Round Butler": The 90-Year Evolution of AI
Many people think AI has only become popular in the past couple of years, but in fact, it's already a "post-90s" technology. Professor Zhang outlined a clear evolutionary path, which we can imagine as an AI "growth diary":
- Stage 1.0 (Early): A top student who could only play chess. Early AI could only handle checkers and defeated a chess champion in 1997. At that time, AI was like a student who memorized rules by rote.
- Stage 2.0 (2016): A genius that opened new paths. AlphaGo's victory against a Go champion was a milestone because Go has so many variations that human rules were insufficient. AlphaGo began to learn from scratch and even made moves never seen in human chess games, showing its ability to think beyond traditional human patterns.
- Stage 3.0 (2017 to present): An explosive general-purpose brain. The emergence of the Transformer architecture in 2017 laid the foundation for large language models (LLMs). Combined with diffusion models and other technologies, AI can now chat, draw, write code, and create videos (AIGC).
- Stage 4.0 (Looking ahead to 2026): AI agents available to everyone. Professor Zhang predicts that 2026 will see the accelerated adoption of AI agents. This means that in the past, you needed to know how to write prompts, but in the future, you'll just need to say, "Create a weekly report with a humorous style," and AI will automatically break down the task, use the right tools, and complete the work. The technical barrier has been completely lowered, and "natural language programming" will become the norm.
Layman's explanation: AI is evolving from a specialist in a specific field to a super assistant that can do everything.
2. The Counterintuitive Truth: AI Fears the Simple, Not the Complex
This is the most disruptive idea in the entire speech and also what many people misunderstand. Professor Zhang cited a classic paradox: "What humans find complex, machines find easy; what machines find easy, humans find difficult."
- Why is AI good at complex tasks? For example, writing a complex legal report or writing difficult code. These tasks are challenging for humans because they involve many rules and strict logic, but as long as they can be standardized, programmed, and streamlined, AI can do them better than humans because it doesn't need to understand the "why."
- Why does AI struggle with simple tasks? For example, asking a robot to clean a messy room or understanding a sarcastic joke. These are tasks that rely on human instincts and evolved over millions of years. It's difficult for AI to fully mimic these through simple data training.
Layman's explanation: Don't worry that AI will replace you with manual labor or jobs that require flexibility. However, if your daily work involves processing data, writing documents, or analyzing according to fixed procedures, you might be a perfect target for AI.
3. The Workplace Revolution: White-Collar Crisis vs. Blue-Collar Safety?
Based on this logic, Professor Zhang made a clear prediction about the job market:
- High-risk areas: Standardized white-collar jobs. Jobs that rely on "learning" and rules, such as junior programmers, basic copywriters, data analysts, and financial accountants, are at risk because they involve applying known rules to new situations, which is AI's forte.
- Safe areas: Blue-collar manual labor. Many blue-collar jobs, such as electricians, plumbers, and complex machinery maintenance, require non-standard environments, strong spatial awareness, and immediate judgment—these are AI's weaknesses.
- New opportunities: AI interpreters. New professions will emerge, such as AI interpreters, who will need to evaluate data or proposals to determine their reliability, ethics, and relevance to specific contexts.
Layman's explanation: In the past, a "stable job" meant one within a traditional system. In the future, a stable job might be one that cannot be completely defined by code. If you rely on skill or experience, you're in a better position; if you rely on adaptability and intuition, you're even more secure.
4. Human Core Competencies: Becoming a "Hexagonal Warrior" with Critical Thinking and Personality
Since AI is so powerful, what value do humans have left? Professor Zhang highlighted three key areas: critical thinking, personal uniqueness, and imagination.
- The essence of AI is statistical results. No matter how advanced AI is, its output is based on statistical probabilities. It lacks personality, bias, and soul; it provides average excellence, not unique brilliance.
- The "human touch" becomes extremely valuable. In an era where AI can generate 100 perfect articles instantly, an article with a strong personal perspective, unique emotions, and even some flaws but authenticity is more valuable. Your perspective, experiences, and values make you unique.
- Become a "hexagonal warrior." Professor Zhang suggests not specializing in just one skill. In the future, you need to be versatile, understanding both technology and humanities, with both logic and creativity. This is the most reliable strategy for survival in the AI era.
Layman's explanation: Don't become a machine. Your value lies not in how much knowledge you remember (AI can remember more), but in how you think, how you view the world, and your unique way of expressing yourself. Maintaining your humanity is a defense that AI cannot replicate.
5. The Great Integration of Disciplines: AI as the New "Universal Language"
Finally, Professor Zhang proposed a grand vision: Many disciplines may gradually merge under the framework of artificial intelligence research:
- Breaking down disciplinary barriers. Physics, biology, economics, and literature were once independent with their own jargon and rules. In the future, AI could become the bridge connecting these disciplines.
- Beyond human cognition. The laws summarized by human civilization over thousands of years are often simplified and linear. But the real world is complex. AI, with its computing power, data, and models, can learn more complex and non-linear patterns. This means that in the future, we may study the universe, life, and economics using AI-driven "black box" theories, rather than traditional mathematical formulas.
Layman's explanation: Future scientists, engineers, and even artists may need to understand AI. AI is not just a tool; it will become a new "operating system" for understanding the world, just as the internet changed how we communicate information.
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Conclusion: Coexisting with AI, Not Confronting It
Professor Zhang Junping's speech was both comforting and a wake-up call:
- Comforting: AI won't replace humans because humans have instincts and personalities that AI cannot mimic.
- Wake-up call: If you're content with the status quo and only do standardized, procedural work, you'll be replaced.
In this wave of AI, we don't need to fear, but we must evolve. Stay curious, develop critical thinking, and use your unique perspective to become a "hexagonal warrior" that AI cannot define. This is the best strategy for ordinary people to survive in the AI era.