As concerns about the environmental impact of emerging technologies continue to grow, a recent study has shed light on the carbon emissions associated with AI-driven writing and illustration. 

The findings suggest that AI emits significantly less carbon than humans when performing similar tasks, raising questions about the role of technology in mitigating climate change.

Co-authored by Andrew Torrance, Paul E. Wilson Distinguished Professor of Law at the University of Kansas, along with researchers from the University of California-Irvine, the study compared the carbon emissions of established AI systems such as ChatGPT and DALL-E2 to those of human writers and illustrators.

Torrance emphasised the importance of data-driven analysis in understanding the true efficiency of AI technologies. “Even by conservative estimates, AI is extremely less wasteful,” he stated.

“I like to think of myself as driven by data, not just what I feel is true. We’ve had discussions about something that appears to be true in terms of AI emissions, but we wanted to look at the data and see if it truly is more efficient,” Torrance said. 

The research utilised various metrics to quantify the carbon emissions associated with writing and illustration. By comparing the energy consumption of AI systems to that of humans, the study found that AI emits between 130 and 1,500 times less CO2e per page of text generated and between 310 and 2,900 times less CO2e per image produced.

The comparison involved considering factors such as the energy usage of computers running AI algorithms and the per capita emissions of individuals in different countries. Results indicated that AI technologies, such as Bloom and DALL-E2, significantly outperformed humans in terms of carbon efficiency, with emissions reductions ranging from 180 to 2,900 times less than those of human counterparts.

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However, the study’s authors cautioned against viewing AI as a complete replacement for human creativity. While AI may offer environmental benefits, it currently lacks the nuanced capabilities of human writers and artists. Moreover, concerns regarding job displacement and the ethical use of AI-trained models remain significant considerations.

Torrance and his colleagues advocate for a collaborative approach, where AI complements human efforts rather than replacing them entirely. They suggest that AI could enhance efficiency and productivity while allowing humans to retain control over the final creative output. 

Additionally, addressing legal and ethical issues surrounding AI usage is crucial for ensuring responsible deployment and minimising negative impacts.

As societies continue to evolve and technologies improve, Torrance believes that AI has the potential to empower human potential while minimising its environmental impact. 

“We don’t say AI is inherently good or that it is empirically better, just that when we looked at it in these instances, it was less energy consumptive,” Torrance said.

“This is not a curse; it’s a boon,” Torrance said of AI. “I think this will help make good writers great, mediocre writers good, and democratise writing. It can make people more productive and can be an empowerment of human potential. I’m hugely optimistic that technology is getting better in most respects and lightening the effects we have on the Earth. We hope this is just the beginning and that people continue to dig into this issue further.”