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Generative AI: Uncovering its environmental and social costs

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          🞛 This publication is a summary or evaluation of another publication 🞛 This publication contains editorial commentary or bias from the source
A recent commentary article by researchers from Northwestern University, Harvard University, and The University of Texas at San Antonio highlights the significant but overlooked environmental and social impacts of Generative Artificial Intelligence (GenAI).
The article from MSN discusses the environmental and social costs associated with generative AI technologies. It highlights how the energy consumption required for training and running AI models contributes significantly to carbon emissions, exacerbating climate change. Additionally, the article points out the vast water usage for cooling data centers, which can strain local water resources. On the social front, it addresses concerns like job displacement due to automation, the potential for AI to widen the digital divide, and ethical issues such as data privacy and the use of AI in surveillance. The piece also touches on the opaque nature of AI development, where the environmental footprint and social implications are often not transparently reported by tech companies, leading to calls for more accountability and sustainable practices in AI development.

Read the Full MSN Article at:
[ https://www.msn.com/en-us/technology/artificial-intelligence/generative-ai-uncovering-its-environmental-and-social-costs/ar-BB1rnsR8 ]