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6. Socioeconomic and Environmental2 - Post-deployment

Indirect Material Harms

AI proliferation causes harm to the environment through energy use and e-waste thereby destroying animal habitat

Source: MIT AI Risk Repositorymit677

ENTITY

2 - AI

INTENT

2 - Unintentional

TIMING

2 - Post-deployment

Risk ID

mit677

Domain lineage

6. Socioeconomic and Environmental

262 mapped risks

6.6 > Environmental harm

Mitigation strategy

1. Implement a Green Compute Mandate requiring the exclusive use of certified renewable energy sources for AI infrastructure operations and the deployment of carbon-aware scheduling protocols to align high-intensity compute tasks with periods of low grid carbon intensity. 2. Mandate the adoption of algorithmic efficiency techniques, such as Knowledge Distillation and low-precision computation (e.g., FP16/INT8 quantization), to minimize the computational complexity and subsequent energy demand per AI inference and training epoch. 3. Establish and rigorously enforce Extended Producer Responsibility (EPR) frameworks for AI-specific hardware and data center components, coupled with investment in AI-powered e-waste management systems for automated sorting and material characterization to maximize resource recovery.