Regenerative Socio-Technical framework
Definition
The Regenerative Socio-Technical (RST) framework is a system-of-systems model designed for the governance of AI infrastructure. It shifts the perspective of infrastructure from a linear consumption pipeline to a metabolic loop that internalizes ecological and thermodynamic impacts into operational decision-making.
Key Characteristics
- Metabolic Infrastructure Design: Treats AI infrastructure as a closed-loop system rather than a linear extractive pipeline.
- Planetary Boundary Governance: Utilizes real-time telemetry and data to enforce operational limits derived from planetary thresholds.
- Integrated Decision-Making: Synchronizes economic profitability with social welfare and ecological sustainability (People, Planet, Profit).
- System-of-Systems Orientation: Governs AI infrastructure as a complex, interconnected set of nested systems.
Applications
- AI Infrastructure Planning: Providing a roadmap for sustainable deployment of high-compute data centers.
- Policy Enforcement: Integrating real-time sustainability metrics into corporate and governmental regulatory oversight.
- Resource Management: Optimizing energy and material flows in large-scale semiconductor and computing supply chains.
Mentions in Source
- “This study proposes a Regenerative Socio-Technical roadmap that repurposes the Sustainable Production and Consumption system map to reframe artificial intelligence infrastructure as a system-of-systems governed ultimately by planetary limits.” — sources/_id-401_current_version|_id-401_current_version