Summary of Key Points
This article focuses on the development of AI technology, emphasizing that its value lies not merely in technological advancements (such as more powerful models or greater computing power) but also in its ability to generate “social benefits”—improving education and healthcare, reducing inequality, and enhancing people's well-being. China has set an example by integrating AI with practical issues such as addressing aging populations, transitioning to renewable energy, and improving public services through what it calls “new quality productivity.” The article highlights the need for educational reforms, infrastructure improvements, and enhanced international cooperation in the AI era, ultimately using social benefits as a measure of whether AI truly benefits humanity.
1. Don’t Just Focus on How Smart AI Is; Look at What Practical Benefits It Provides
In the past, the evaluation of AI focused on which models were more advanced or had greater computing power. However, the article argues that this is far from sufficient. True success lies in AI’s ability to help ordinary people solve problems—enabling children in remote areas to access quality online education, allowing the elderly to receive expert consultations at home, helping small businesses improve efficiency, and even narrowing the gap between the rich and the poor. This kind of “social benefit” is the ultimate goal of AI. It’s similar to buying a smartphone: you don’t compare which chip has the highest performance; you want to know if it makes your life more convenient. China advocates for using AI for good purposes, ensuring that technology serves people rather than the other way around.
2. China’s “New Quality Productivity”: Using AI to Solve Real Problems, Not Just to Show Off
The term “new quality productivity” refers to combining new technologies like AI with real-life needs. For example, China is using AI to develop intelligent elderly care devices, optimize energy grids to reduce waste, and streamline public services. The “East-West Data Transfer” project demonstrates how technology can be used for development by transferring computing resources from the east to the west, solving both regional challenges and making advanced resources more accessible to universities and small businesses in the western regions.
3. Will AI Take Jobs? Don’t Panic; Focus on Developing Skills That AI Cannot Replace
Many people worry that AI will replace jobs. While this concern is valid, it’s important to consider the bigger picture. Historical technological revolutions have always eliminated some jobs while creating new ones (for instance, programmers emerged with the rise of computers). AI will likely replace repetitive and mechanical tasks, but jobs that require creativity, collaboration, and independent thinking (such as designing, teaching, and medical work) will remain. Therefore, education must adapt: instead of rote learning, students should be taught to ask questions, collaborate, and innovate. As Confucius said, education should be tailored to individual needs. AI can assist teachers in understanding each student’s unique characteristics, making education more personalized, but the role of teachers will not be replaced—machines cannot understand emotions or support personal growth.
4. The “Infrastructure” of the AI Era: More Than Just Roads and Power Grids—Computing Power and Digital Connectivity
The infrastructure of the 20th century included electricity, railways, and telephones. In the AI era, computing power (data centers) and digital networks (such as 5G) are just as essential. China’s “East-West Data Transfer” project is an example of building new infrastructure that utilizes resources in less developed regions while reducing costs for everyone. For developing countries, it’s more practical to focus on establishing digital infrastructure first, enabling farmers to use AI for weather forecasting and doctors to use it for diagnostic assistance, rather than striving for the most advanced models.
5. AI Challenges Are Global Issues That Require International Cooperation
The challenges posed by AI (such as data security, algorithmic bias, and job displacement) are not limited by national borders. For example, biased algorithms in one country can affect users worldwide, and data breaches can spread across countries. Countries need to work together to establish rules for ensuring AI transparency, protecting personal data, and making AI more accountable. Developing countries should use AI to solve their own problems (such as increasing agricultural productivity and improving healthcare) rather than competing with developed nations in terms of model size.
In Conclusion
The article concludes that the true measure of progress in the AI era will not be how intelligent machines are, but how much we have improved our lives through them. Just as history remembers those who used the steam engine to make trains run more efficiently and factories more productive, so too will future generations recognize those who use AI to improve people’s lives. China’s experience shows that technology is a tool; the real goal is to benefit society.