Can AI Save Climate Change?

Technological advancements change many aspects of our lives. Sometimes technology can have a global impact. Most of the time, when we think about world-changing technology, we aren’t talking about the planet. Maybe we should. The path to a solution for some of our climate change challenges may reside with advanced technologies like Artificial Intelligence (AI).

 Science and climate technology experienced significant advances over the last few decades. With these advances comes a massive amount of climate data. Climate scientists, meteorologists, and climatologists analyze this data to understand the impact of climate change better. They create advanced weather models and better prediction tools. However, leveraging AI and Machine Learning to aid this effort is a newer concept. 

 Some may still debate whether humans are responsible for significant changes in the global climate. However, it is hard to dispute the Earth’s changing climate. Disruptions to historical weather patterns, an uptick in dangerous weather, and melting glaciers are but a few data-proven climate changes. As a prominent Los Angeles iPhone app developer, we intimately understand the potentially devastating impact of climate change.

 No matter the side of the debate, we can leverage technology to understand climate change better and discover ways to reduce the impact of climate change.

AI and Climate Science

AI, and its subset of machine learning, have the power to analyze data and images at a speed and scale beyond human capabilities. From this analysis comes better prediction models and algorithms to detect patterns. These results help make informed decisions, find efficiencies, or solve complex problems. When applied to the challenges of climate change, AI and machine learning prove exceptionally beneficial. 

 Partnerships between data science and climate science create a new dynamic to combat climate change. Until recently, climate scientists relied on information collected from simulations and observations, which followed predetermined rules. With AI, and specifically machine learning, the data and imagery collected from around the planet feed into AI learning models. The process uses machine learning to ‘train’ algorithms using large amounts of climate-based datasets.

 Successful implementations of AI and climate change nationally include Japan and Brazil. Japan employs AI as an early warning against natural disasters. In the Amazon, AI monitors and predicts deforestation.

 When applied to climate change, advances in AI and machine learning create exciting opportunities for companies to innovate. Kayrros is one such example. They are a data analytics company that provides insight into climate risk by monitoring energy, natural resource, and industrial markets.

AI’s Use to Reduce Carbon Emissions

Of all the ways that AI could positively impact climate change, the goal of zero-carbon emissions may be the best bet. Many world governments and leaders across global economies pledged a goal of net-zero carbon emission by 2050. This pledge is a needed yet ambitious objective to bring global energy-related carbon dioxide emissions to a net-zero solution.

 The energy sector will have the most significant impact on the success or failure of this goal. Electric power produces 25% of greenhouse gases worldwide. Using AI to gain efficiencies by optimizing energy grids is a short-term application that could provide immediate benefits. AI can integrate and increase the use and efficiency of renewable energy sources combined with current energy grids.

 AI solutions return immediate benefits on a slightly smaller scale. The successful application of AI to operate commercial buildings’ heating, ventilation, and air conditioning (HVAC) is one such example. On average, nearly 50% of a commercial building’s energy usage comes from HVAC systems, with more than half going to waste. Large warehouses, factories, or industrial centers see significant cost savings and emissions reduction from AI-controlled HVAC operations.

Potential Diminishing Returns Using AI

The energy and carbon emissions to power AI on the scale needed could be counterintuitive. Some analysis predicts that the data centers used to power AI could consume upwards of 25% of the world’s electricity.

 However, large tech companies are aware, and some have taken steps to mitigate the impact.  Google successfully deployed AI to mitigate excessive heat loss. Partnering with DeepMind to develop an AI recommendation system, AI systems control data center cooling. The results produced a near-immediate 30% energy savings.

Conclusion

Applying AI and machine learning could be a turning point against climate change. The collaboration of data science and climate science is still in the early stages. However, the positive impact already felt by AI’s use to run the heating and cooling of commercial buildings is a reality today. 

 AI and machine learning applications focused on combating climate change that impacts the environment are a field brimming with opportunities. If you or your company have a climate-focused idea for an AI or machine learning application, Dogtown Media is your partner to develop and deploy it. Take advantage of our free consultation to see how we can partner together to positively impact the environment.