Artificial-Intelligence-Enhanced Study on the Optimization of the Responsibility and Compensation Mechanism for Provincial Cultivated Land Retention from a Fairness Perspective

Abstract

Research Objectives: Considering the complex challenges arising from urbanization, population growth, and the consequential strain on China’s cultivated land resources, we integrate insights from advanced artificial intelligence (AI) technology. The primary objective is to quantitatively assess the cultivated land-holding responsibility of local governments in China from a fairness perspective. Our aim is to integrate the cultivated land responsibility ownership amount into the compensation mechanism for cultivated land protection, thereby promoting fairness, cultivated land conservation, and sustainable agricultural development across Chinese provinces while ensuring efficient agricultural product distribution. Research Methodology: Beyond a traditional literature review and model analysis, we incorporated AI technology for data analysis and model optimization. Findings: ① The findings demonstrate a surplus in both food security and ecological security within cultivated land. ② In-depth analysis via AI revealed that the provinces with the largest surplus include Heilongjiang, Jilin, and Hubei. ③ With the precision provided by AI, we delineated the minimum value of the cultivated land responsibility ownership amount for each province. Eleven provinces met this criterion, primarily located in the northeast and central regions and including Yunnan in the west. ④ From a fairness perspective, coupled with AI insights, we established a compensation mechanism for cultivated land protection that is better suited to the Chinese context. Based on this mechanism, the national average compensation standard was calculated to be 26,900 CNY per hectare. The highest standards were observed in Shanghai, Beijing, and Jiangsu, while the lowest were in Shanxi, Heilongjiang, and Gansu.