When AI Begins to Take Jobs: A Wake-Up Call about the Rules of Future Survival
Hello everyone, I'm your financial observer.
On September 12th, a sub-forum at the Shanghai Bund Conference, titled "Intelligent Replacement and Spiraling Upward under the AI Wave," was actually more thought-provoking for the general public than the main sessions where new chips and models were unveiled. The focus was not on how powerful AI is, but on what we ordinary people should do when AI becomes so advanced.
This forum was co-hosted by the School of Philosophy at Fudan University and Yicai, bringing together experts from technology, philosophy, investment, and media. Instead of互相 flattering, they discussed the harsh but realistic realities of the AI era.
To make the information easier to understand and remember, I have broken down the forum content into five key areas. This is not just news; it's also a "navigation map" for your career planning and lifestyle over the next decade.
---
1. The Counterintuitive Truth: The Bottleneck of AI Isn't Code, It's Electricity
Many people think of AI as algorithms, large models, or NVIDIA chips. However, Yang Yudong, the chief editor of Yicai, presented a very counterintuitive truth: The biggest bottleneck in global AI development is not the algorithm, but electricity.
- Computing Power is Electricity: You can think of current AI models as super consumers. Each time they are trained or answer a question, they consume a lot of electricity. NVIDIA CEO Jensen Huang predicts that by 2030, investments in AI infrastructure will reach 7.9 trillion US dollars. A large portion of this will go towards data centers and power facilities.
- China's Hidden Ace: Yang Yudong pointed out that China's most underappreciated AI asset might not be the large model companies, but rather our electricity system. China has the world's largest electricity system, the most advanced renewable energy installations (wind and solar power), and cutting-edge high-voltage transmission technology, as well as the capability to manufacture all necessary power equipment. This means that while the world struggles with power shortages, China could have a significant cost advantage and certainty in AI implementation.
💡 In Plain Language: Don't just focus on the AI assistants in your phones; also consider the power plants, transformers, and cables behind them. In the future, those who supply the power (electricity equipment and infrastructure) might be more stable than those who develop the software. If you're interested in investing, the entire power industry chain (from generation to liquid cooling) represents a trillion-dollar market with clear opportunities.
---
2. The Great Job Reconfiguration: White-Collar Jobs Are at Risk, While Blue-Collar Jobs Are More Stable?
This was the most surprising and concerning viewpoint of the forum. Professor Zhang Junping from Fudan University mentioned the famous "Moravec Paradox":
- Things humans find difficult (such as playing chess, solving math problems, writing code) are easily learned by AI and even done better by it.
- Things humans find easy (like playing football, folding clothes, navigating crowded spaces) are difficult for AI to handle.
- White-Collar Crisis: Office workers doing standardized, procedural tasks (such as junior programmers, data analysts, copywriters) are most vulnerable because AI excels at these tasks.
- Blue-Collar Safety: Jobs that require physical coordination, complex physical environments, and non-standard situations are less likely to be replaced by AI in the short term. For example, it's hard for AI to play football like a top athlete due to the uncertainties, physical interactions, and quick decisions on the field. Jobs like babysitting, cleaning, and plumbing are also less likely to be automated because each household's situation is unique and requires flexible responses.
- New Jobs Emerging: Professor Zhang predicts the emergence of new roles like "AI interpreters," where the focus shifts from execution to coordination and oversight.
💡 In Plain Language: If your current job involves following routines with data or text, be cautious as AI becomes a competitor. However, jobs that require hands-on skills, face-to-face interactions, and handling unexpected situations are relatively safe. The core competence in the future will be the ability to handle complexity and uncertainty.
---
3. The Battle for Dignity: Humanity Cannot Be Replaced by AI
Professor Zhang Rongnan from East China Normal University discussed the question of human dignity from a philosophical perspective. She argued that dignity comes from our vulnerability, aging, and the need for care, not from being smarter or stronger than machines.
- Three Risks to Dignity: AI erodes dignity in three areas:
1. Loss of Agency: Recruitment algorithms may discriminate, and you have no recourse.
2. Extraction of Experience: Personal experiences and emotions are used to train AI, turning us into data sources.
3. Replacement of Relationships: If we rely entirely on AI for elderly care and education, genuine human connections are lost.
- Machine Service for Humans: The future of coexistence should be about machines serving us, not the other way around. Responsibility for AI errors must be clearly defined, and human care must be preserved in critical areas like healthcare.
💡 In Plain Language: AI can help with tasks like writing emails and reports, but it cannot replace the comfort of a doctor's touch or the encouragement of a teacher's gaze. We need to guard against over-reliance on technology and preserve the warm, human interactions that define our humanity.
---
4. A New Investment Map: Where Are the Hidden Champions?
For investors and entrepreneurs, Yang Yudong and Song Jun from Hongjiang Capital provided a guide to avoid pitfalls and find opportunities:
- Don't Just Focus on Large Models: While large models are essential, the real profits lie in the "last mile" of application. China's industry-specific knowledge and non-standard processes create opportunities for translating AI into practical solutions.
- Hidden Champions: Small companies that apply AI to traditional industries to solve specific problems may be more resilient.
- Unexplored Areas: Opportunities include AI in energy infrastructure (electricity, cooling, power electronics chips), cross-border investments, and the integration of AI with traditional industries (agriculture, manufacturing).
- Robots: The "ChatGPT moment" for embodied intelligence is still 2-3 years away. Breakthroughs will come in dangerous or labor-intensive tasks, not in mundane tasks like delivery or chatting.
💡 In Plain Language: Don't chase the latest trends blindly. Focus on electricity, energy, and infrastructure. Look for companies that can apply AI to real industries and have deep industry expertise. For robots, expect breakthroughs in dangerous or labor-intensive tasks, not in household chores.
---
5. Governance and the Future: Putting Brakes on AI
The forum concluded with a discussion on how to control AI's development:
- Regulation is Needed: Regulation should be public and not monopolized by a few companies. AI should be a public asset managed collaboratively.
- Education Restrictions: Strict limits on AI use in education before the age of 18 are suggested to help children develop a well-rounded personality.
- Career Transformation: Skilled workers can become AI trainers, passing on their experience to robots, which enhances their dignity.
- Enhancement, Not Replacement: The goal of AI is to enhance human capabilities, not replace them. For example, AI can help doctors make decisions, freeing humans from dangerous or repetitive tasks.
💡 In Plain Language: We need a system to protect against the negative impacts of AI. Stay critical, think creatively, and maintain meaningful human interactions. The future society should ensure that AI enhances, not replaces, human capabilities.
---
Conclusion: What Should Ordinary People Do?
The main message of this forum is that anxiety is useless; clarity is key.
- Embrace Change, but Preserve Humanity: Learn to use AI as a tool, not a master.
- Dive into Non-Standardized Areas: Standardized, repetitive jobs are at risk; creative, emotional, and complex tasks are safer.
- Focus on Essential Foundations: Power, energy, and infrastructure are crucial for the AI era.
- Guard Dignity: In a world of efficiency, preserve the warm, human interactions that define us as humans.
The AI wave is coming; we can't stop it, but we can choose to be at the forefront, not swept away by it.