On trees and robots: How AI can serve climate solutions

Towards a digital commons for evidence-based action
Des Chercheurs Ghanéens suivent la croissance des arbres à l’aide de l’application ReGreening Africa. Photo de Kelvin/CIFOR-ICRAF.

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Advances in artificial intelligence (AI) have been top of many minds lately. It’s estimated that the sector could contribute USD 10-15 trillion to the global economy by 2030, while tough ethical questions are also being raised by the rapidly-expanding potential of the technology. 

But the possibilities that AI presents for the climate mitigation, adaptation, and ecosystem restoration space are as yet undersung. As UN Secretary-General António Guterres said in July this year, AI has the potential to “supercharge climate action”, but it also carries some climate – and social – risks itself, and this increases the urgency to develop it in reliable, safe, and equitable ways. 

For instance, we can use AI to develop responsive and effective early warning systems for extreme climate events, better predict which crops to grow as conditions change, and understand leverage points where long-term climate resilience can be built while also ensuring immediate risk mitigation. 

But as a global community, we don’t yet have a great track record of ensuring that technological advances are shared with those who need them most. The unique contexts and challenges faced by communities at the forefront of climate risks are often ignored, and algorithmic bias can deepen inequity and reinforce discrimination. 

As the Global Partnership on AI noted in a recent report, “a growing body of evidence suggests that the least-well-resourced actors (such as those in the Global South) stand to suffer most from both climate change (they bear the brunt of climate impacts) and digital transformation-related transfers of power (loss of agency and control).”  

This means that research community, private investment, and the public sector urgently needs to work together to pinpoint where AI might be applied to landscape and climate challenges, and frame how to do so equitably and responsibly. As science fiction has always warned us, the key to maximizing positive impacts from this technology – that is, those that are equitable for the widest population set – is ensuring that it is human-centered, justly applied, and attuned to manifest actual impact at the individual and community levels. 

Developments in this arena must be ethically sound, user-friendly, and equitably built with the Global South in mind. This means that policymakers, funders, investors, and researchers must prioritize the needs, rights, and voices of communities, ensuring that technological and policy innovations are aligned with human values, ethical considerations, and social justice. 

We need thoughtful design that tasks AI with making sure systems are governed and evolve in ways that enable more inclusion and fairness, with communities and local action at the center. Far from trending toward techno-fixes, we can instead leverage AI’s formidable potential in collating, analyzing, and distributing data to promote and amplify grassroots initiatives, Indigenous knowledge, local wisdom, and community-led actions as powerful catalysts for scalable, impactful, and sustainable global climate solutions.

Better and broader access to robust evidence, data, and localized insights can improve decision making on forest, tree, and agroforestry strategies for communities, countries, civil society, and the private sector. When such solutions show broader promise, AI can help facilitate their scaling across contexts and scales. 

It can also play a key role in informing and improving financial policies in biodiversity and carbon markets, ensuring they are strategically optimized for impact and sustainability. Such initiatives, however, will likely require research institutions and governments make the relevant data openly available as public goods (as CIFOR-ICRAF does with its own research).

This behooves us to foster a democratized ‘commons’ approach and reduce data silos, ensuring interoperability in data and AI systems. A unified and cohesive ecosystem facilitates other research and public and private players to build on what has been done and utilize known and proven techniques. It encourages swift learning and adaptation, enabling the identification of effective strategies and the rejection of less fruitful ones.

AI can also help us to bridge critical data gaps that currently exacerbate inequities and hinder decision-making processes on climate and restoration issues, particularly in lower-income countries. For instance, it can collate data to help policymakers understand the impacts of policies to incentivize emissions cuts and boost climate resilience. 

It also facilitates continuous data sampling, of which CIFOR-ICRAF is a strong advocate. Our Land Degradation Surveillance Framework (LDSF), under which we regularly gather data from a number of key locations, has substantially improved our comprehension of, and strategies related to, landscape health and restoration in contrast to what would have been gained through a one-off data collection approach. Building on this approach further, the Regreening Africa app combines AI and citizen science to serve hundreds of thousands of farmers and reverse land degradation across eight countries in sub-Saharan Africa.

As the AI revolution continues, our organization is committed to human-centered leadership on its use in the climate and biodiversity space, and to nurturing partnerships, dialogues, and initiatives that resonate with global sustainability visions. Will you join us?

Éliane Ubalijoro is the CEO of the Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF).

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Topic(s) :   Climate change