

Campus: Pros and cons of AI in higher education
18 snips Feb 20, 2025
Joining the discussion are Shaolei Ren, an expert in AI's environmental impacts at UC Riverside; José Bowen, co-author of a practical guide on teaching with AI; and Shushma Patel, pro vice-chancellor for AI at De Montfort University. They explore the environmental costs of AI, including its significant water footprint, and argue for a balanced approach to its integration in higher education. The conversation covers strategies for sustainable AI implementation, the need for AI literacy among educators, and the transformative potential of AI for personalized learning experiences.
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AI's Environmental Impact
- AI's environmental impact includes carbon emissions, water consumption, and air pollution.
- However, AI can also be used for environmental good, like integrating renewables and predicting weather.
Shaolei Ren's Motivation
- Shaolei Ren's research on data center water usage began in 2013, sparked by childhood experiences with water scarcity.
- His first paper on the topic was published shortly after graduating from UCLA.
AI Model Resource Intensity
- Not all AI models are equally resource-intensive; large generative models consume more than smaller, specialized ones.
- Efficiency improvements, like DeepSeek, reduce resource use, but overall AI demand continues to grow.