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“Artificial Intelligence (AI), especially deep learning (DL) and generative AI (GenAI), has led to faster, more accurate and powerful solutions than ever before by using large amounts of data, deep neural networks, and supercomputing facilities. However, this rapid progress brings both opportunities and challenges. While AI holds great potential to support sustainable development for the benefit of society, latest industry trends highlight environmental and social concerns that cannot be overlooked.

“Many reports show that the increase in training and development of more advanced, larger AI models requires more resources, such as energy, water, and rare materials, which are becoming harder to provide. When considering the whole spectrum of the sustainability of AI, we must also consider its social sustainability, including the potential for job displacement, algorithmic biases and fairness issues that can worsen societal inequalities and create a bigger digital divide. 

"Moving forward, it is imperative to develop and deploy more sustainable and people-centred AI solutions that are less resource-hungry while continuing to deliver superior performance.”