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Climate Consequences of AI: Risks and Solutions

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Chioma Obinagwam

The official mission statement of the United Nations Sustainable Development Goal (UNSDG) 13 is to “Take urgent action to combat climate change and its impacts”.

Confiance News gathered that the role Artificial Intelligence (AI) in achieving this great task cannot be over-emphasised.

Artificial intelligence (AI) is a powerful tool that can transform various aspects of human society, from health care and education to business and entertainment. However, AI also has a significant role to play in addressing one of the most urgent and complex challenges of our time: climate change.

 

Climate change is humans major concern

Climate change is caused by human activities that emit greenhouse gases into the atmosphere, leading to global warming and its associated impacts, such as rising sea levels, melting ice caps, biodiversity loss, and more frequent and intense natural disasters. To prevent the worst-case scenarios of climate change, the world needs to take urgent and ambitious action to reduce emissions and achieve net-zero by 2050. At the same time, the world also needs to adapt to and build resilience against the inevitable effects of climate change that are already occurring or will occur in the near future.

 

AI as climate change ally

AI can be a valuable ally in both mitigation and adaptation efforts, as it can help gather, complete, and interpret large, complex, and disparate datasets on emissions, climate impacts, and more. AI can also help optimize processes and systems across various sectors, such as energy, transport, agriculture, and manufacturing, to reduce their carbon footprint and increase their efficiency. Furthermore, AI can help enhance disaster preparedness and response, as well as support long-term planning and policy-making for climate resilience. However, AI is not a silver bullet for climate action. It also carries risks and challenges that need to be addressed carefully. For instance, AI itself is energy-intensive and requires a lot of computing power and data storage, which can contribute to emissions if not powered by renewable sources. Moreover, AI depends on materials that are scarce or harmful to the environment, such as rare earth metals and electronic waste. Additionally, AI can have social and ethical implications that could affect the distribution of benefits and burdens of climate action among different groups of people.

 

 

 

Risks of AI-Induced Climate Consequences

1. Energy Consumption: AI systems, especially deep learning models, demand enormous computational power. Training a single model can consume as much electricity as an entire household does in years. This heightened energy consumption significantly contributes to greenhouse gas emissions, exacerbating the climate crisis.

 

2. Data Center Footprint: The massive data centers that support AI operations require extensive energy for both computing and cooling. In 2020, data centers were estimated to consume 1% of the world’s total electricity, with this number expected to rise as AI applications continue to expand.

 

3. E-Waste: The rapid evolution of AI technology renders older hardware obsolete, leading to an increase in electronic waste. Disposing of this equipment responsibly is a pressing challenge.

 

4. Resource-Intensive Components: The production of AI hardware involves the extraction of rare minerals and resources, often associated with environmental degradation and human rights concerns. This process further compounds AI’s ecological impact.

 

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