AI for Climate & Social Good

While AI has an environmental footprint, it's also a powerful tool for addressing climate change and other societal challenges. Climate scientists use AI to improve weather forecasting, model climate scenarios, optimise energy grids, and monitor deforestation and biodiversity loss. AI-driven materials science is accelerating the development of better batteries and more efficient solar cells. In agriculture, AI helps optimise irrigation, predict crop diseases, and reduce pesticide use. Beyond climate, AI is being applied to drug discovery, epidemic prediction, disaster response, educational access, and poverty reduction. The challenge is ensuring these applications reach the people and places that need them most, not just well-funded institutions in wealthy countries. Many "AI for good" initiatives have been criticised for being more about corporate marketing than meaningful impact - pilot projects that generate positive press coverage but don't scale. The most effective applications tend to be those developed in partnership with the communities they serve, addressing problems those communities have identified, using data they've contributed. For organisations interested in using AI for positive social or environmental impact, the key is moving beyond showcase projects to sustained, funded programmes with measurable outcomes and genuine community engagement.