Summary of the Core Content
This article focuses on the impact of AI on traditional modes of livelihood, arguing that AI is fundamentally disrupting the two dominant approaches to making a living: working for others (in an employed position) and running a small business. As a result, the certainty of one's source of income is disappearing. The article begins by examining the evolution of livelihood patterns, from self-sufficient agriculture to industrial employment, then analyzes how the employment system has weakened during globalization and financial crises. It ultimately emphasizes how AI is destroying the foundations of these traditional models and proposes three potential solutions: innovation in business models, wealth sharing, and universal social security.
Detailed Analysis
1. The Evolution of Livelihood Patterns: From Self-Sufficiency to Employment
The concept of working for a salary, which we take for granted today, is a product of the Industrial Revolution:
- Agricultural Society: Most people relied on self-sufficiency, growing crops and engaging in handicrafts; only a few (such as officials and craftsmen) were employed.
- After the Industrial Revolution: Factories emerged on a large scale, creating a demand for a large workforce, and the employment system became widespread. For example, during Britain's Industrial Revolution, 70% of the population was employed; in the United States, this figure rose to 80% in 1930, and in China, it was 69% in 2020.
- The Benefits of Employment: Stability was a key advantage. Although wages were low, people believed that as long as they worked hard, they would have a job for life. For instance, in the 1950s in the United States, a manufacturing worker's salary could support a family of five; Japan had a system of "lifetime employment" in the 1960s and 1970s, and Europe followed similar patterns. Back then, people had fewer worries and were more concerned with what was on TV in the evening.
2. The Stability of Employment Is No Longer Guaranteed: The Challenges of Globalization and Crises
Even before the advent of AI, the stability of the employment system was already under threat:
- Globalization: Factories moved to lower-cost regions (such as China and Southeast Asia), leading to job losses in areas like the Rust Belt in the United States.
- Financial Crises: The two major crises at the end of the last century forced companies to rely more on part-time and temporary workers. In the United States, 8.9 million people currently hold two jobs (5.4% of the workforce), and one full-time job is no longer sufficient to support a middle-class lifestyle. In Japan, "lifetime employment" gave way to contract workers with lower salaries and fewer benefits; South Korea entered an era of temporary employment after the Asian financial crisis.
The employment system has shifted from providing stability to being highly precarious.
3. The Double Blow of AI: Disrupting Traditional Livelihood Patterns
AI does not just lead to job losses; it fundamentally changes the foundation of how people make a living:
- Disruption of Employment: AI will replace many jobs (McKinsey estimates that 800 million jobs will be restructured or eliminated by 2030, and Goldman Sachs predicts 300 million full-time positions will be at risk). More troubling is the decoupling between economic growth and employment. For example, OpenAI, valued at $800 billion, has only 8,000 employees. Companies may profit, but ordinary people may lose their jobs, leading to reduced consumer spending and a phenomenon known as "ghost GDP" (increased output with no corresponding demand).
- Disruption of Small Businesses: How do small businesses make money? They often rely on information asymmetry (e.g., knowing about high-quality products in Shanghai) and high logistics costs. With online price comparisons and faster, cheaper shipping, it's becoming increasingly difficult to profit from price differences. For instance, if a cup costs 5 yuan, you might sell it for 10 yuan, but someone else can sell it for 9 yuan, leaving small businesses at a competitive disadvantage.
Whether working in an office or running a business, the options are becoming narrower.
4. The Loss of Livelihood Certainty
Traditional livelihood patterns provided clear paths: either work for others or start a business. However, AI has blurred these boundaries:
- Blurred Paths: Working for others may become the exception, with most people switching between freelance jobs, self-employment, and small projects.
- Unclear Roles: One day you might be a delivery driver, the next a content creator on social media, and the day after that a designer. It's no longer clear what category you belong to.
- Uncertain Futures: Hard work may no longer guarantee promotion or higher wages. Even those with strong skills may struggle to find stable employment. The article describes this as entering a "post-work era" where work is no longer a guaranteed source of income, identity, or meaning in life.
5. Solutions: What Can We Do?
The article suggests three approaches:
- Innovation in Business Models: New models such as solo businesses (where individuals earn money through their skills) and platform economies (using technology to connect supply and demand) can provide stable income.
- Wealth Sharing: Implementing a universal basic income guarantee so that everyone, regardless of employment status, receives a portion of the economic benefits.
- Universal Social Security: Establishing a social security system that covers all people, providing healthcare and retirement benefits regardless of their employment status.
While these solutions may not solve all problems, they represent a starting point in dealing with the uncertainties brought about by AI.
Conclusion
AI is not just causing temporary unemployment; it is fundamentally reshaping how we make a living. In the future, we may need to adapt to new ways of earning a living in an uncertain world. Societies must also innovate their systems to ensure that everyone has access to basic necessities, as the certainty of income is a fundamental aspect of people's sense of security.