An innovative method based on the principles of evolutionary artificial intelligence (AI) is transforming into an effective means to achieve worldwide climate targets and generate a thriving economy.
More and more, industry leaders and policymakers are recognizing the unparalleled capacity of this branch of AI to balance intricate trade-offs and find creative solutions that support both the environment and the economy.
Based on natural selection, evolutionary AI uses a computational method to produce, evaluate against the predefined parameters, and refine a number of potential solutions.
The less successful solutions are eliminated, while the more successful ones “reproduce” and “mutate,” giving rise to highly-efficient and sometimes unconventional solutions.
Recent research has shown that evolutionary AI is a useful tool for solving complex problems at the nexus of climate action and sustainable economic development. For example, a team at the University of Texas at Austin worked with Cognizant AI Labs to create an evolutionary AI system to help optimize land use policies.
This approach successfully weighted the goals of maximizing carbon storage against minimizing economic disruptions, and it delivered complex recommendations that occasionally ran counter to conventional wisdom.
The AI found that cropland-to-forest change is far more efficient for carbon sequestration as compared to rangeland-to-forest change, and that the optimal land management is location specific.
The range of applications for such evolutionary AI are enormous in sectors vital for climate mitigation and economic development sectors. For the energy industry, it could be used on the integration of renewables in the electricity network, improving efficiency and lowering the dependance on fossil fuels.” This not only supports the decarbonization movement but also offers new business opportunities in the green energy markets.
In agriculture, evolutional AI can help accelerate the evolution of climate smart practices that increase productivity with less environmental footprint, leading to food security and robust rural economies. And in urban planning and infrastructure, it can point to sustainable options that bolster economic activity and environmental resilience alike.
Regarding the potential of evolutionary AI, it is stressed that its added value is that it is able to explore large solution spaces and find nontrivial complementarities between climate and economic goals.
As opposite to conventional optimization techniques, which can be trapped in local optima, the evolutionary process enables a lingering exploration and adaptation, thus more holistic and efficient results are achieved.
Although the sub-field is still in its early formative years, the early successes of evolutionary AI at addressing complex sustainability issues provides a promising model for how climate action and economic growth need not be in competition, but that we can, and should, instead aim to do well in one area while doing good in another.
Further R&D will leverage more exploration in that context with potential to be even greater for serving the world in the cause of sustainable prosperity.
