A new scientific journal is calling for artificial intelligence to be more deeply integrated into environmental research
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For most people, discussions about artificial intelligence tend to focus on productivity gains, the risk of job losses and concerns about privacy. But a new journal, Artificial Intelligence & Environment, is exploring another possibility: that AI could become one of the most powerful tools for tackling climate change, pollution and resource sustainability.
The authors outline how environmental challenges are increasingly interconnected and global in scale. ‘Humanity faces environmental crises that are complex, systemic, and deeply intertwined,’ they said. ‘Addressing them requires new scientific approaches capable of extracting meaning from vast and diverse data sources.’
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The belief is that AI can help fight significant environmental challenges which threaten ecosystems, public health, and economic stability worldwide. The processing of massive datasets from satellites, sensors, and environmental monitoring networks, can allow scientists to detect patterns which would otherwise remain hidden. It is the unmasking of hidden patterns which can lead to great strides in pollution tracking, climate impact modelling, and agricultural planning.
In agriculture, AI driven models can predict crop yields and guide precision farming strategies which improve productivity while reducing environmental impact. Algorithms can also improve the real time monitoring of air and water quality, optimise waste management systems, and improve renewable energy planning.
AI can help to close the gap between research findings and policy decisions which would be welcomed, as environmental regulations often lag behind scientific evidence. ‘AI can provide tools that clarify the consequences of different choices and support more informed, equitable decision making,’ the authors said. Ultimately, AI driven modelling can relay potential policy outcomes more clearly, helping decision makers to weigh up trade offs and foresee unintended consequences
The article’s launch represents a growing recognition that we need to delve far away from traditional methods in order to solve environmental challenges. Much of AI’s power and success as a potential tool to address global environmental problems stem from the improvements it provides in precision as well as its own aptitudes in facing up to the inherent complexities of environmental challenges. Deeper collaboration between data scientists, environmental researchers and policymakers may just be the best chance we’ve got.
This intense nexus of power and capabilities – if harnessed correctly – can be a solution to the most pressing global environmental crises.
AI’s environmental woes
Far from being purely a solution, AI can also be an exacerbator of crises themselves. In order to power the AI transition that is undoubtedly underway, huge amounts of data centres need to be built and become operational. These data centres consume vast amounts of electricity in addition to water for cooling purposes.
According to the International Energy Agency, global electricity consumption for data centres is predicted to double to reach around 945 terawatt hours by 2030. Although this may still mean a (relatively) small share of total global electricity consumption originating from data centres, this is a big step from a world previously without data centres at the scale we are now witnessing globally.
