On a grey Saturday morning, my colleague, fellow researcher Dona Mathew, and I hosted a day-long workshop at the SCIENCE Gallery, Bengaluru engaging 18-23-year-olds in exploring the role of AI in climate action. We were pleasantly surprised by how enthusiastically and clearly these young adults engaged with the material and futuring activities. Some participants even mentioned that while they’d signed up for a more technical session, they were glad to have experienced something more imaginative. For us, this highlights that youth are eager to partake in serious conversations about the forces shaping their futures; and it’s up to us to make room for that.
Climate change and AI are two of the most significant factors shaping Asia’s future.
In India alone, we see
There’s a growing convergence between these technologies - their development and deployment - and climate action efforts, including mitigating and preventing climate change and related consequences. AI can enhance resource efficiency, forecast risks, and drive research. Yet, the interaction between digital and green transitions—and their impacts on sectors like food systems, city planning, and transportation—needs better understanding.
AI technologies can support more efficient and innovative resource use, forecast potential risks, and advance research and discovery. Pursuing a green transition, and putting climate action at the centre of policy and business decisions, could also transform the digital sector through, for example, a switch to alternative energy sources. But, these digital and green transitions could also negatively affect each other - given the environmental impacts of AI, inequities in data access and access to tech resources amongst nations, etc.
During our icebreaker, participants shared anxieties about rising temperatures, data centers encroaching on land rights, Western-dominated climate narratives, and the growing carbon footprint. They are also open to AI and its potential in areas like climate pattern analysis and targeted agricultural interventions. However, they voiced concerns about conflicts of interest in funding climate tech by corporate-linked entities and the state's potential misuse of AI for surveillance.
Our workshop was designed to give participants a deeper understanding of AI’s potential in tackling climate change, while also encouraging them to think critically and creatively about the future. We kicked off with an overview of various AI use-cases in climate action, from predicting natural disasters to optimising resource use. Dona presented insights from DFL’s research on AI and climate futures in Asia, emphasising how AI technologies can support more efficient and innovative resource use, forecast potential risks, and drive groundbreaking research and discovery.
The second half of the workshop featured interactive sessions that introduced foresight methodologies, including identifying signals of change, world-building, and back-casting. These methodologies aimed to equip participants with tools to think beyond the present, fostering an understanding of how current actions could shape future scenarios. The world-building and back-casting exercises were particularly well-received, as they allowed participants to actively engage with the material and think beyond traditional approaches to climate action.
In the world-building activity, we divided the participants into two groups:
In the dystopian world, participants depicted a future dominated by technology companies that have taken over almost every aspect of life, driving society deeper into consumerism and capitalism.
Natural resources were extensively commodified, and AI was utilised for invasive surveillance, from tracking genetic footprints to monitoring social media for involuntarily shared information. Even waste was scrutinised by AI waste segregators to extract consumer trends, turning climate change into a profitable enterprise for tech conglomerates. This vision also highlighted an exacerbated class divide, where the wealthy controlled most resources while the impoverished struggled to survive in a world where every aspect of their lives was controlled, down to the amount of time they could spend in the shower. The dystopian group chose to centre their narrative on an indigenous person displaced from ancestral lands, forced into a life of modern slavery in resource extraction industries, underscoring the deep societal impacts of unchecked AI deployment.
Conversely, the utopian group painted a picture of a harmonious society where institutions are transparent and accountable, and policies prioritise environmental and societal well-being.
Poverty had been eradicated, universal healthcare was accessible, and political leaders enacted policies that put the planet first.
In this vision, AI was widely adopted, not as a tool of control, but as an enabler of positive change—predicting natural disasters with high accuracy, improving urban resilience with earthquake-proof buildings, and providing exceptional healthcare and mental health support, including free therapy after natural calamities.
Their world emphasised renewable energy, equitable access to resources, and a commitment to reducing carbon footprints, creating a balanced ecosystem where technology and nature coexisted in synergy.