ASRI: AI Substitution and Reshaping Index – Quantifying AI's Impact on the Labor Market

ASRI (AI Substitution and Reshaping Index) is a groundbreaking data science project aimed at evaluating the potential impact of AI on different occupations and industries through quantitative analysis. This index not only focuses on jobs that may be replaced by AI but also identifies occupational areas reshaped by AI, providing decision-making references for policymakers, workers, and others. This article will introduce its core concepts, methodology, application scenarios, and other aspects.

Traditional discussions on automation often focus on 'which jobs will be replaced', which is an overly simplified perspective. ASRI proposes a dual-dimension framework of Substitution and Reshaping:

• Substitution Dimension: Measures the degree to which AI can complete tasks independently. Tasks like standardized data processing and decision-making based on clear rules have higher substitution risks.
• Reshaping Dimension: Focuses on how AI changes the nature of work. For example, graphic designers will not lose their jobs due to AI image generation tools, but their work processes and creative processes will undergo profound changes.

The ASRI Index is built based on multi-dimensional data integration and analysis:

1. Occupational Description Data: Job responsibilities and skill requirements from official occupational classification systems
2. Technical Capability Assessment: Performance benchmarks of current AI in various task types
3. Industry Trend Data: Adoption speed and depth of AI in different industries
4. Labor Market Information: Macro indicators such as employment numbers and salary levels Through machine learning and natural language processing technologies, it automatically analyzes occupational descriptions, extracts task features, and matches AI capability maps to ensure the objectivity and updatability of the index.

The ASRI Index provides decision support for multiple parties:

• Policymakers: Identify industries/regions severely impacted, design retraining programs and social security policies
• Educational Institutions: Adjust curricula and major settings based on changes in labor market demand
• Individuals: Objectively assess occupational risks, guide career choices and transitions
• Enterprise Managers: Predict changes in job structure, plan human resource strategies

ASRI has limitations: AI technology develops rapidly, so current evaluations are prone to obsolescence; hard-to-quantify variables such as social and cultural factors are not fully incorporated into the model. Future plans: Continuously update methodologies and data sources, incorporate more qualitative research and social science perspectives, and welcome cooperation from academia and industry to improve it.

ASRI represents a more detailed approach to evaluating AI's impact. It not only predicts unemployment but also depicts the evolution of work in the AI era, changes in the value of skills, and directions for transition preparation. Against the backdrop of accelerated technological change, this tool is of great significance for building a more resilient labor market.