https://taxonomy.eticas.ai/risk/institutional-capacity
Maturity: emerging
The broader institutional or societal context lacks foundational capabilities (digital infrastructure, data literacy, regulatory frameworks) needed before AI deployment is viable. Premature deployment may reallocate scarce resources, exacerbate inequality, or create technological dependency.
This subcategory is emerging. It has not yet been validated through established assessment methods.
System type: ADM and LLM systems
Lifecycle stages: Pre Processing
| Framework | Reference |
|---|---|
| OECD AI Principles | Building human capacity & preparing for labour-market transition |
| Framework | Reference |
|---|---|
| MIT AI Risk Repository | Increased inequality and decline in employment quality |