Three steps for businesses to make AI data and compute more sustainable

In an article on the OECD.AI website, Professors Tom Jackson and Ian Hodkingson discuss the environment impact of AI and outline three steps that can reduce the environmental impact of AI computing.

Concerns about Generative AI are fueling global discussions about the need for guardrails to protect against biases, discriminatory outcomes, safety, reliability, and the potential impacts on children and labour markets. Generative AI is a category of artificial intelligence (AI) techniques and models that generate new and original content, such as images, text, music, or even videos. Unlike traditional AI systems that rely on pre-programmed rules or explicit instructions, generative AI models are trained to learn and mimic patterns from vast amounts of data.

Data is a critical input into training AI models, and few have considered the carbon cost involved simply because many believe data to be carbon neutral. Over the last decade, there has been an explosion of data. While AI has been identified as a mechanism to manage the currently estimated doubling of global data every two years, there has been little consideration given to how AI itself is contributing to this growth and the environmental impacts associated with this.