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AI can reduce fast fashion's carbon footprint: UNSW Research

Submitted by webmaster on 20 May 2024
AI can reduce fast fashion's carbon footprint: UNSW Research


AI-driven technologies can be harnessed for climate action and significantly advance environmental and market performance, according to the findings of a new study, co-authored by the UNSW Institute for Climate Risk & Response.

The fast fashion industry is one of the world’s biggest polluters. Employing some 75 million people and valued at over $2.5 trillion (A$3.8 trillion), it is responsible for about 10 per cent of global carbon emissions.

Bangladeshi manufacturers are recognised for their worldwide exports. They produce most of the apparel for leading fast-fashion brands such as Primark, Nike, H&M, and others in 150 countries. In recent years, consumers and governments have pressured these brands to reduce emissions and the environmental impact of their global supply chains.

“H&M has committed to a 56 per cent reduction in emissions and 100 per cent renewable electricity in its supply chain and operations by 2030. A larger number of clothing brands, such as Calvin Klein, Tommy Hilfiger, and Next, also require their supplying factories to be green, complying with environmental and safety regulations,” said Grant.

“AI-powered climate service solutions are technologies like big data and machine learning that can reduce routine, repetitive, simple, and standardised tasks,” explained Professor Grant. “These include emission measurement, calculating individual products' carbon footprint, identifying risk factors, forecasting demand to reduce waste, and climate education."

“A key feature of the model discussed in the paper is that it points to how AI can enhance the firm's environmental, social, and governance (ESG) performance and credentials as well as market performance in terms of productivity, efficiency, quality assurance, and overall competitiveness. AI can improve a business's long-term sustainability, growth, and profitability.