- The report “Building Pro-Worker Artificial Intelligence” by MIT economists Daron Acemoglu, David Autor, and Simon Johnson argues that most businesses are using AI for automation rather than augmenting human capabilities.
- Simon Johnson, co-author of the report and co-recipient of the 2024 Nobel Prize in Economics, defines “Pro-worker AI” as AI that increases the value of workers’ skills, expertise, and judgment.
- According to him, AI should not only help humans work faster but also help them perform tasks that were previously impossible.
- The report classifies technology into five groups: labor-augmenting, capital-augmenting, automation, expertise-leveling, and new-task-creating.
- Among these five groups, only new-task-creating technology is considered clearly “pro-worker.”
- Automation technologies increase productivity but can reduce the demand for existing expertise and shift value from labor to capital.
- “Expertise-leveling” technologies, such as pulse oximeters, allow those with less expertise to perform work previously requiring experts, but they can simultaneously devalue old expertise.
- New-task-creating technologies, like Ethernet, fiber optics, or smart sensor systems, create demand for entirely new skills and increase labor value. The report suggests AI should be developed in this direction instead of focusing solely on cutting personnel costs.
- For example, data center technicians could use AI to analyze operational data flows, detect risks, and make more complex decisions.
- In the field of patents, the US Patent Office has used AI to assist in searching relevant documents, helping experts evaluate filings more deeply rather than just processing them faster.
- Schneider Electric developed an AI tool to assist electrical engineers and field technicians in troubleshooting equipment and power systems by combining images, hardware data, and knowledge bases to suggest appropriate steps.
- According to the report, AI helped reduce the time needed to complete maintenance reports at Schneider Electric by about 50%.
- However, the greatest value lies not in time savings but in helping engineers apply their expertise more effectively in real-world environments.
- Simon Johnson argues that many businesses are taking the “path of least resistance,” which is replacing humans with machines instead of redesigning work. He warns this approach could cause businesses to miss larger innovation opportunities and fail to exploit AI’s full potential.
- The report recommends that organizations evaluate AI not just by costs saved but by its ability to create new jobs, new skills, and better customer experiences.
- According to the authors, future competitive advantage will belong to businesses that use AI to expand human capacity instead of just optimizing existing labor.
📌 Báo cáo của các nhà kinh tế MIT, trong đó có Nobel Kinh tế 2024 Simon Johnson và Daron Acemoglu, đưa ra một luận điểm đáng chú ý: AI chỉ thực sự mang lại lợi ích cho người lao động khi nó tạo ra những nhiệm vụ và khả năng mới thay vì đơn thuần thay thế công việc hiện có. Trong năm nhóm công nghệ được phân tích, chỉ nhóm công nghệ tạo nhiệm vụ mới được xem là rõ ràng có lợi cho lao động. Các ví dụ như Schneider Electric hay hệ thống hỗ trợ thẩm định bằng sáng chế cho thấy AI có thể giúp chuyên gia giải quyết các vấn đề phức tạp hơn và nâng cao giá trị chuyên môn. Theo báo cáo, doanh nghiệp nào chỉ dùng AI để cắt giảm chi phí sẽ khó khai thác hết tiềm năng chuyển đổi của công nghệ này.
