With environmental applications for artificial intelligence broadening, the
question arises on how AI might influence economic growth and the global ambition to reduce emissions between now and 2030.
AI can be harnessed in a wide range of economic sectors and situations to contribute to managing environmental impacts and climate change. From AI-infused clean distributed energy grids to precision agriculture, sustainable supply chains to environmental monitoring and enforcement, and enhanced weather and disaster prediction and response, artificial intelligence has undeniably become one of Nature’s allies.
And as the field of AI continues to thrive, companies with large ecological impressions are leveraging the field’s power to make serious changes to our world as we know it.
Big Data - Mitigation and Adaptation
With advancements in Big Data, Hardware, and emerging powerful AI Algorithms, it seems like all the pieces are coming together to make huge changes to our everyday lives. Artificial intelligence can apply powerful predictive capabilities and intelligent grid systems to manage the supply and demand of renewable energy, accurate weather forecasts can optimize efficiency, cut costs, and unnecessary carbon pollution generation.
It can improve energy storage, efficiency, and load management, and assist in the integration and reliabilities of renewables. In turn, this will facilitate dynamic pricing and trading, resulting in market incentives. A multitude of companies tracking the ever-increasing extreme weather systems are now helping better understand, forecast and mitigate environmental impact and economic cost of weather patterns.
Sustainable Land Use
Artificial intelligence integrated with satellite imagery can sense changes in land use, vegetation, forest cover, and the fallout of natural disasters. Early detection of crop diseases and issues is possible through the use of AI-augmented agriculture via robotics.
This system involves automated corrective measures, automated data collection, and decision-making. It also helps with streamlining agricultural inputs and returns based on supply and demand resulting in an improved resilience to climate extremes, increased resource efficiency of the industry, and a reduction in the use of water, fertilizers, and pesticides – all things that devastate important ecosystems.
Environmental Intelligence - Regulations & Enforcements
AI and machine learning is currently being used to automate environmental inspections through AI analysis of images obtained by satellite or drone, extending the reach and efficiency of environmental inspections and significantly enhance regulatory effectiveness. Machine learning methods can also help optimize resource allocation by predicting where on-the-ground manual inspection resources would be most beneficial. Businesses are subject to greater scrutiny and regulatory supervision, because the authorities are able to detect or predict potential violations in a cost-effective manner. As a result, there is a higher risk of potential violations being detected and respective sanctions materialising.
AI is increasingly being used for the purpose of environmental law enforcement, as demonstrated by the recent example of a large British company that received billions of pounds in green energy subsidies from UK taxpayers, which was proven to be cutting down environmentally important forests in Canada, using satellite image analysis, traced logging licenses and drone filming.
AI & Economic Impact
A recent study commissioned by Microsoft has modelled the economic impact of AI’s application to manage the environment, across four sectors – agriculture, water, energy and transport. The study demonstrated that the application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e – equivalent to the 2030 annual emissions of Australia, Canada and Japan combined.
The study suggests that on top of productivity improvements, AI could create 38.2 million net new jobs across the global economy, increasing the offer of skilled occupations as part of this transition.
Follow the link to learn more on how Laconic uses environmental intelligence to monitor environmental restoration, identifying patterns of progress or regress and quantifying both.