Space-AI Governance Nexus Framework and Analysis

Nagwan Alqershi's 83.5 KB PDF introduces the Space-AI Governance Nexus, a framework linking space data and AI to governance outcomes. The mixed-methods study combines quantitative analysis of 20 countries with qualitative evidence from 22 expert interviews and comparative case studies. The work, published on figshare in April 2026, highlights how unequal access to data infrastructures reinforces geopolitical hierarchies.

Use Cases

• Analyzing the relationship between space data access and predictive governance capabilities based on the cross-national quantitative analysis
• Studying the moderating effect of institutional openness on AI capacity and governance outcomes based on the moderation analysis
• Investigating epistemic asymmetries in global governance based on the qualitative expert interviews
• Developing inclusive data-sharing frameworks for predictive governance based on the study's conclusions

Strengths

• Mixed-methods design combining quantitative analysis of 20 countries and qualitative evidence from 22 expert interviews
• Framework introduces a novel conceptual nexus linking space data, AI capacity, and governance outcomes
• Analysis demonstrates positive associations between space data access, AI capacity, and policy innovation

Limitations

• Dataset is a PDF document; the underlying quantitative data and interview transcripts are not provided
• Row count and column-level documentation for the quantitative analysis are unknown
• The 83.5 KB file size suggests limited scope, likely containing only the paper's text

Provenance

Source

figshare

Collection Method

Mixed-methods design combining cross-national quantitative analysis and qualitative expert interviews

Freshness

Last updated 2026-04-29 05:41:31

Geography

Analysis includes 20 countries; specific geography is not detailed