Sustainability

Frances attends a small local college and will graduate this year from a program called Creative Coding. She looks for ways to reduce her environmental footprint but is unsure how to deal with the rapid advances of generative AI. On the one hand, she's fascinated by all the new tools that have been emerging and wants to create digital art using platforms she sees her friends using, which can transform a simple sentence into a stunning visual and even generate the code for a new app. However, her excitement was diminished by a guest lecturer in one of her environmental science classes. The lecturer discussed the hidden environmental cost of some AI tools and highlighted the substantial energy consumption and carbon emissions associated with training and running AI models. 

Frances realized she might need to revisit her plans to incorporate AI tools into her projects. She wanted to learn more, so she explored the assertion that one image generated by an AI tool could require a lot of computational power. This power is generated in large data centers that need vast amounts of nonrenewable energy, electricity, and water to cool them down.

As she looked into it further, Frances became more familiar with the ongoing debate within the tech and creative communities. Some people think that AI's current environmental cost is justified by its potential to solve complex problems and even address climate change. “AI-driven innovations in renewable energy, smart grid systems, and climate modeling are examples of how AI could ultimately lead to a more sustainable future,” one person argued. “Short-term environmental impact of AI development,” another claimed, “was a necessary investment for long-term global sustainability.”

Frances wanted to hear from people in her local community, so she organized a panel discussion at her school. She invited professors who research AI, environmental science, and sustainable technology. The AI expert said the focus on AI's energy consumption was misplaced since it is still a tiny percentage of global energy used, compared to industries like transportation or manufacturing. The environmental scientist countered that the rapid growth of AI made it necessary to intervene before the environmental impact was too significant to manage. The sustainable technologist suggested that AI might optimize its energy consumption to make it an automated and sustainable technology. This nuanced debate left Frances with a deep appreciation for the subtleties of balancing technological progress with environmental responsibility.

She wondered what she and others could do to use this powerful technology sustainably and began looking for examples of AI models trained on renewable energy. She joined forums where creative communities shared tips to reduce the environmental impact of their work, looked into using more energy-efficient hardware, and signed up for services that run on renewable energy, among other ways of reducing the carbon footprint.

What do you think?