Environmental & Societal Impact
Addresses AI's broader societal effects, including labor displacement, mental health impacts, and issues from manipulative technologies like deepfakes. Additionally, it considers AI's environmental footprint, balancing resource strain and training-related carbon emissions against AI's potential to help address environmental problems.
ENTITY
3 - Other
INTENT
3 - Other
TIMING
2 - Post-deployment
Risk ID
mit160
Domain lineage
6. Socioeconomic and Environmental
6.0 > Socioeconomic & Environmental
Mitigation strategy
1. Systematically reform fiscal and labor policies to incentivize human capital investment and reskilling, specifically by achieving tax parity between spending on worker training and investment in physical capital to mitigate AI-driven labor displacement. 2. Implement mandatory, standardized frameworks for measuring and disclosing the operational and embodied environmental impact (energy, water, carbon emissions) of AI infrastructure, complemented by regulatory requirements for data center efficiency and grid decarbonization. 3. Establish content provenance standards, such as watermarking and traceability mechanisms, for all generative AI outputs, paired with comprehensive media literacy programs to bolster public resilience against manipulative deepfake technologies.