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AI and sustainability:
The hidden health costs of AI
As artificial intelligence continues to revolutionize industries, its environmental footprint needs increasing attention. In addition to some of the documented energy consumption and carbon emissions issues, recent research highlights a less visible but equally pressing concern: the public health implications of AI's lifecycle.
A study titled "The Unpaid Toll: Quantifying the Public Health Impact of AI" (currently under peer review) digs into the health consequences associated with AI from chip manufacturing to data center operations. This study shows that by 2030, U.S. data centers could impose a public health burden valued at over $20 billion annually, more than the health costs of US coal-based steelmaking and rivaling those from California's on-road vehicle emissions.
These health impacts are not evenly distributed. Communities near power plants or data centers bear a larger share of the burden. In some cases, the per-household health impact in these areas could be 200 times greater than in other areas.
To address these challenges, the researchers support more standardized pollutant reporting and transparency, community engagement in decision-making processes and the addition of public health considerations into AI systems design and use.
As AI becomes a part of our daily lives, we must consider its broader impacts on society. By considering environmental and public health impacts, we can steer AI development towards a more sustainable and equitable future.
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