論文

While the adoption of Artificial Intelligence (AI) is advancing globally, its pace varies significantly across nations. This study statistically examines the associations between Hofstede’s cultural dimensions and national-level AI readiness. A correlation analysis was conducted using data from the Oxford Insights’ “Government AI Readiness Index 2024” and Hofstede’s cultural dimension scores. The findings reveal that Individualism and Long-Term Orientation have a significant positive correlation with AI readiness, whereas Power Distance and Uncertainty Avoidance show a significant negative correlation. Conversely, Masculinity and Indulgence did not have a statistically significant relationship. These results suggest that national cultural characteristics are associated with differences in the adoption of advanced technologies such as AI. To contextualize the statistics, we include an illustrative, non-causal comparison of Japan, the United States, and Singapore.

Demand for food products, often from international trade, has brought agricultural land use into direct competition with biodiversity. Where these potential conflicts occur and which consumers are responsible is poorly understood. By combining conservation priority (CP) maps with agricultural trade data, we estimate current potential conservation risk hotspots driven by 197 countries across 48 agricultural products. Globally, a third of agricultural production occurs in sites of high CP (CP > 0.75, max = 1.0). While cattle, maize, rice, and soybean pose the greatest threat to very high-CP sites, other low-conservation risk products (e.g., sugar beet, pearl millet, and sunflower) currently are less likely to be grown in sites of agriculture–conservation conflict. Our analysis suggests that a commodity can cause dissimilar conservation threats in different production regions. Accordingly, some of the conservation risks posed by different countries depend on their demand and sourcing patterns of agricultural commodities. Our spatial analyses identify potential hotspots of competition between agriculture and high-conservation value sites (i.e., 0.5° resolution, or ~367 to 3,077km2, grid cells containing both agriculture and high-biodiversity priority habitat), thereby providing additional information that could help prioritize conservation activities and safeguard biodiversity in individual countries and globally. A web-based GIS tool at https://agriculture.spatialfootprint.com/biodiversity/ systematically visualizes the results of our analyses.