How can Artificial Intelligence enable climate action?
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How can Artificial Intelligence enable climate action?

Published: 20 Nov 2023


AI and climate change may not seem as a very obvious combination when thinking about how to tackle climate change. Some might say the two can be polar opposites. Yet, AI can help scientists and policymakers inform their decisions when it comes to implementing new regulations. Indeed, UN Secretary-General António Guterres says that it has the “potential to turbocharge global development such as monitoring the climate crisis”. Following this speech, UN Climate Change launched #AI4ClimateAction, which looks at the ways AI can be used as a powerful tool to scale up climate action.


AI has the “potential to turbocharge global development such as monitoring the climate crisis” - UN Secretary-General António Guterres -

Climate action

What is AI?

Artificial Intelligence, also known as AI, has become a central topic of discussion and research today. Many of you have heard of ChatGPT, an artificial intelligence bot used to produce information on any subject. Or AI in robots. "AI is the simulation of human intelligence processes by machines, which is developed using machine learning techniques" says Dr Mark Elshaw. In essence it is humans who put data into the system that allows the software to generate outputs. This enables computers to think like human beings and execute complex tasks as human do. The industry is growing, with the financial sector predicting that the AI industry will contribute $10 to $15 trillion to worldwide economy by 2030. Specialists warns that AI must be used as a tool rather than an alternative, in that sense fears about job losses must not be taken too dramatically.


More and more universities are including AI courses into their curriculum to attract new students and raise awareness of AI, which will become very important to our day-to-day life in the future. However, tech giant Elon Musk recently warned about the risks of AI, and the potential creation of a world where no job is needed. Therefore, AI needs to be regulated or else many will use it will ill intent.

Climate action

AI to monitor plastic movement in Oceans.

Despite this warning, there are reasons to hope that AI tools can be used for the greater good. Microsoft Azure is a perfect example of how these tools can be used in the context of data collection for climate action. It is a platform used to detect plastic pollution in rivers and oceans. Every year more than 430 million tonnes of plastic are produced, and a staggering two-thirds are single use plastics. This means that around 286 million tons of plastic are not recycled and thrown away. The United Nations Environment Programme has sounded the alarm about the scale and impact of this crisis. Not only are the seas increasingly polluted by plastics, but as a result, so is our food. Nikola Simpson, the Head of the UN Development Programme’s Barbados and Eastern Caribbean Blue Economy Accelerator Lab warned that ‘at the current rate of production, there will be more plastic than fish in the ocean by 2050’.


This is where Microsoft’s AI for Earth initiative comes in. It provides information on how Microsoft’s partners are working on the front line of sustainability development. The Ocean Cleanup project partnered with Microsoft to use an AI machine learning to spot plastic pollutions in rivers. This algorithm carries out simulations to predict the movements of plastics in water. The aim of this project is to inform passive clean up systems and to support the removal of plastic in our oceans. This project assesses plastic movements across both rivers and oceans. The project aims to reduce ocean plastic by 90% by 2040. A wide range of different solutions are being and will be developed to collect plastic in rivers and oceans. The installation of floating barriers across rivers has already proved their success across the world. Interceptor tenders are then set up to collect the plastic and offload it into a dumpster onshore.

Climate action

Monitoring and predicting initiatives


Other initiatives aimed at using AI to predict environment activities have also been launched. The roll out of Satlas by AI2, also known as the Allen Institute for AI, has demonstrated that a radical change is taking place in the way satellite imagery is used. This platform provides geospatial data analysis from satellite imagery to assess global trends in the use of renewable energy. It provides evidence of national and international to switch to offshore or solar power.


Innovative AI-powered models can also be used to provide early warning alerts to local communities in regions most vulnerable to climate change. An example of this, is Be-Resilient South Africa, an initiative led by UNESCO Regional Office for Southern Africa. This project uses AI to predict flooding trends in Mozambique. Most of these regions are located in emerging or developing countries, where the risk of natural disasters is high. The consequences of these events are catastrophic.


"Be aware of the biased effects that AI can cause in climate predictions".

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Yet, even though AI can be used to track climate developments, climate action in response to these analysis must comply with national and international regulations. One must be weary when using satellites to assess renewable projects worldwide that the images are used for a positive purpose. Therefore, despite, the hope that artificial intelligence can help provide data to support the works of climate scientists, certain rules need to be put in place. Uncontrolled development of artificial intelligence poses a threat for security and ethical reasons. Scientists specialising in climate data warn of the biased effects that AI can cause in climate predictions. This is caused to the introduction into systems of data derived from past observed events. Dr Kasia Tokarska, a climate data scientist specialised in AI, suggests that any organisation using AI should regularly add data from new events into the AI’s system. This will allow to keep the program updated with more recent data and trends to better adapt to new cycles.






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