Making AI Less 'Thirsty'

Artificial intelligence (AI) has enabled remarkable breakthroughs in numerous areas of critical importance, including tackling global challenges such as climate change. On the other hand, many AI models, especially large generative ones like GPT-4, are trained and deployed on energy-hungry servers in warehouse-scale datacenters, accelerating the datacenter energy consumption at an unprecedented rate.25 As a result, AI's carbon footprint has been undergoing scrutiny, driving the recent progress in AI carbon efficiency.24,31 However, AI's water footprint--many millions of liters of freshwater consumed for cooling the servers and for electricity generation--has largely remained under the radar and keeps escalating. If not properly addressed, AI's water footprint can potentially become a major roadblock to sustainability and create social conflicts, as freshwater resources suitable for human use are extremely limited and unevenly distributed.