One of the most prominent issues humankind needs to address is climate change. It is exacerbating in front of our eyes as we see the ecosystem changing for the worse. Storms, droughts, fires, and floods have grown more frequent and increasing in severity as time passes. An intergovernmental report done in 2018 has estimated that the world will be facing catastrophic climate changes in 30 years.

It is possible that humans can gradually overcome this complex issue with the help of machine learning algorithms and artificial intelligence, which are capable of gathering, compiling, and interpreting large and complex datasets on carbon emissions and climate change.

The rising threat of climate change

A report conducted by IPCC (Intergovernmental Panel on Climate Change) in 2018 has estimated that in 30 years we will face catastrophic climate change unless we are able to reduce greenhouse gas emissions.

A report from the United Nations’ Intergovernmental Panel on Climate Change published this April makes it clear that it is “now or never” for the planet. We are “firmly on track toward an unlivable world,” U.N. Secretary-General Antonio Guterres said when releasing the report. There is a high chance that global temperatures will rise by three degrees Celsius per year, twice as much as the agreed-upon 1.5 degrees Celsius limit if things do not improve. Unless we take more drastic steps and cut down carbon emissions by 43 percent within this decade, the full force of climate change will be upon us. (You can read more about climate change predictions here.)

How AI can help combat climate change

A report released by BCG discussed how companies can help fight climate change. Below is a chart from BCG that shows how most public and private sector leaders support using AI in combating climate change but are not familiar with how to use it. AI can contribute to climate change mitigation in a variety of ways, including reducing global greenhouse gas emissions from transportation, agriculture, and industry. Additionally, machine learning can help us predict weather patterns and identify patterns from climate data.

They came up with a framework on how humans can reduce greenhouse gas emissions and combat climate changes by using AI in five ways. This acts as a tool for shareholders and companies to use AI in a more efficient, informed, and driven way to create a difference in the years ahead.

The drawbacks of using AI to fight climate change

While the tools for a solution we have discussed in this article are course-changing, the available resources are scattered and unconventional. Most organizations are not yet active in supporting AI for climate change and even those who are, are not educated enough and face many obstacles in implementation.

A report by Horizon, the EU’s Research and Innovation Magazine shows that AI can also have problems in the fight against climate change. In this report, it states that we must also consider AI’s carbon footprint and the ethics behind the tool. It has been raised that machine learning applications and the use of AI could lead to misuse of public surveillance. This might lead to transparency problems and discriminatory data use.

“It is part of a wider ethics debate in the EU about how to use AI for the benefit of human beings, the challenges that the technology poses, and how best to tackle them.”

The future of AI

On top of combating climate change, climate change AI technology can be revolutionary in terms of the tech ecosystem. The use of AI could lead to a more resilient future for us all.

“The most urgent need in this context is not to have more powerful AI but to become smarter at where and how we use Artificial Intelligence. There are so many unexplored opportunities,” states Lambert Hogenhout, Chief of Data Analytics, Partnerships, and Technology Innovation at the Office for Information and Communications Technology (OICT).

As climate change’s effects become more widespread and severe, it is vital that we continue to support and invest in climate-tech companies that use artificial intelligence and machine learning.

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