Advancing environmental justice with AI

Climate change is undoubtedly the defining challenge of our time, but its effects are not equally distributed. In both developed and developing countries, environmental degradation disproportionately affects communities marginalized because of race, ethnicity, religion, and poverty. More often than not, these communities are already confronting systemic inequalities such as water scarcity and greater exposure to pollution and extreme weather events – all of which are exacerbated by the climate crisis.

It is a reality with which I am intimately familiar. As a child, my family had a farm on Dominica, a small Caribbean island state that faces the threat of hurricanes each year. One tropical storm could knock out power grids and wipe out entire harvests, destroying local livelihoods.

According to the World Bank, climate-related disasters push 26 million people into poverty annually. And because the world’s poorest people often depend on agriculture – a sector highly dependent on favourable weather conditions – to support themselves, they urgently need access to technical, financial, and institutional resources to prepare for and respond to ever more frequent and intense extreme weather events.

Given its capacity to innovate climate solutions, the technology sector could provide the tools we need to understand, mitigate, and even reverse the damaging effects of global warming. In fact, addressing longstanding environmental injustices requires these companies to put the newest and most effective technologies into the hands of those on the front lines of the climate crisis.

Tools that harness the power of artificial intelligence, in particular, could offer unprecedented access to accurate information and prediction, enabling communities to learn from and adapt to climate challenges in real time. The IBM Sustainability Accelerator, which we launched in 2022, is at the forefront of this effort, supporting the development and scaling of projects such as the Deltares Aquality App, an AI-powered tool that helps farmers assess and improve water quality. As a result, farmers can grow crops more sustainably, prevent runoff pollution, and protect biodiversity.

Consider also the challenges that smallholder farmers face, such as rising costs, the difficulty of competing with larger producers that have better tools and technology, and, of course, the devastating effects of climate change on biodiversity and weather patterns. Accurate information, especially about soil conditions and water availability, can help them address these issues, but has historically been hard to obtain.

One could imagine regional officials in a developing country deploying a machine learning algorithm to forecast future population growth and corresponding change in energy demand using temporal and spatial data. With this forecasting model, policymakers could optimize the country’s energy network, redirecting supply to where it will be needed most. That is also something that we are supporting today.

Developing AI-powered mobile apps and virtual assistants, and making them widely available, promotes equitable access to data and technical insights. With highly accurate weather forecasting, advanced agronomy techniques, and carbon-footprint calculations, as well as other predictions generated by AI, smallholder farmers can build greater climate resilience and boost both production and income by adapting to changing conditions more quickly and managing crops more sustainably.