AI is increasingly seen as a potential weapon in the fight against climate change. Yet, there are a number of issues throughout AI’s lifecycle that can harm the environment and contribute to a warming planet.
For example, energy-intensive AI technologies require large data farms and processing centers, which create emissions that contribute to global warming. Some also use rare minerals such as lithium and tantalum that can cause conflict in developing countries.
AI is being used to send natural disaster alerts in Japan, monitor deforestation in the Amazon, and design greener smart cities in China. It’s being used by scientists, engineers, and industry experts from a variety of disciplines to tackle a global emergency that threatens all life on Earth.
But can AI solve climate change? The answer is a bit complicated. It has to do with a phenomenon called Earth’s climate system, which is a complex and dynamic network of interactions between various atmospheric, oceanic, and terrestrial factors. It also has to do with a massive amount of data that needs to be collected and analyzed in order to understand how the climate system is changing. This is a huge challenge that requires people of all backgrounds, including scientists, engineers, and industry experts from countless sectors of the economy to work together in order to find solutions.
In addition to the need for collaboration across multiple sectors, many experts believe that AI is going to be an important tool in fighting climate change. AI can help in a number of ways, from providing better hazard forecasts for both regionalized long-term events like sea level rise and ice sheet movement and immediate extreme weather events such as hurricanes. It can also be used to reduce the risk of climate-related catastrophes for businesses, by identifying operational vulnerabilities and highlighting potential risks in visual risk maps.
Another area in which AI can be helpful is in the mitigation of greenhouse gas emissions, by reducing energy consumption and making energy more efficient. It can also be used in monitoring and analyzing the performance of various mitigation and adaptation measures to assess their effectiveness. In addition, it can be used to improve the accuracy of climate models by integrating and evaluating different types of data and modeling algorithms.
It can also be used to develop new technologies that reduce the emission of carbon dioxide and other greenhouse gases, such as solar technology, biofuels, and other low-carbon alternatives. It can also be used to evaluate and test the impact of climate policies, such as carbon taxes or market-based mechanisms.
Artificial intelligence consumes vast amounts of energy, and at present and in the near future, this energy is mostly derived from fossil fuels. This leads to substantial greenhouse gas emissions. Hence, it is important to consider how the deployment of AI can be done in an environmentally friendly way.
One possibility is that AI could help to reduce the amount of energy used in power plants, through increased efficiency and a better use of existing resources. Another option is that AI could help to reduce the amount energy consumed in households, through smarter appliances and energy-saving policies.
The third possible application is that AI can help to detect environmental crises and respond to them effectively. This would involve the use of sensors, cameras, and other devices to monitor natural patterns and raise alarms when something unusual is observed. Examples could include rainfall anomalies in arid regions, temperature spikes in a city, or sea-level rise.
Ultimately, AI can make it easier for governments and businesses to focus their adaptation efforts. One of the dangers of climate change is that governments, firms, and households invest enormous resources in adaptation but cannot quickly evaluate which of these efforts are most effective. In addition, a lack of clear policy incentives can lead to market failures, where companies and individuals emit warming gases without paying for their global externalities. AI can improve the ability of markets to identify and correct these market failures.
It can also be a powerful tool for finding solutions to climate change, especially if it is combined with sensors and other monitoring systems that can measure the physical effects of warming in real time. These can be coupled with predictive models to forecast the consequences of various policy options.
Finally, AI can also be used to build new infrastructure that is more resilient in the face of extreme weather events. This includes building more disaster-resistant buildings, and locating safer evacuation routes. In addition, AI can be used to train sensors that can tell when natural environments are under threat. The sensors can then alert the authorities so that measures can be taken to protect them.
In the future, farmers may use artificial intelligence to grow healthier crops that can withstand climate change. But it is crucial that AI-related solutions are vetted for ethical and environmental impact.
For example, at the start of a new growing season, an AI-powered system could monitor crops and identify pests faster than human eyes. It would then send the data to a farmer’s mobile phone and recommend what action should be taken. If the crop needed a pesticide application, it could even automate this through a connected sprayer.
This is one of many ways that technology can help us feed the world, despite increasing droughts and floods that disrupt growing seasons and destroy once-fertile land. It is also a critical tool for helping us cope with food insecurity and the threat of a global hunger crisis, which is already affecting more than 1 billion people.
AI is also being used to help reduce the carbon footprint of agriculture and address climate change, in addition to its role in improving productivity and efficiency. But many of these AI-related climate solutions are still in the early stages and require investment, especially in resources and networks.
At BCG, we believe that promising solutions must earn the confidence of climate leaders by ensuring they use AI responsibly, employ granular and reliable underlying datasets, and emphasize results that can be interpreted and understood. They must also provide an opportunity for collaboration with other actors to develop innovative and cost-effective approaches to climate mitigation, adaptation, and resilience.
The good news is that a growing number of entrepreneurs are working on these kinds of solutions, and we expect to see accelerated progress in all three themes of the Adaptability and Resilience framework in the next few years. However, this progress is unlikely to be enough to prevent a catastrophic rise in temperatures, so we must continue to invest in research, development, and testing.
With the right support and resources, the power of AI can be used to help humanity confront one of its greatest challenges—feeding 2 billion more people by 2050, while reducing agricultural emissions and addressing climate change. AI is an essential part of this solution, and the sooner we begin to leverage it, the better.
In the realm of transportation, AI can be used to reduce carbon emissions and improve traffic flow. For example, an AI-based system developed by Siemens Mobility has been adopted in Bengaluru, India, to monitor traffic conditions with smart cameras, adjust traffic lights and facilitate smooth flow. This has led to a 25% reduction in travel time and emissions. The same technology is also being utilized in Pittsburgh, US, to manage motorway tolls and traffic flow.
Other uses for AI in transportation include reducing fuel use, improving energy efficiency and optimizing renewable energy deployment by sending power from electric vehicles back to the grid when demand is low. AI can also help to prevent natural disasters by analyzing data about climate patterns and warning of abnormal ones, such as high temperatures in arid forests or rising sea levels. It can then offer evacuation and rescue routes or design more disaster-resistant infrastructures to mitigate damage when such events occur.
However, the use of AI in fighting climate change poses several ethical challenges. First, AI can produce its own emissions during training and operation that contribute to climate change. To address this issue, most would agree that AI companies should improve the energy efficiency of their systems and shift to fossil-free energy sources.
Second, the use of AI in tackling climate change requires collaboration with researchers and climate activists alike. This collaboration can be facilitated by the development of AI chatbots that communicate with stakeholders in a meaningful and understandable way, providing information about climate-change mitigation options and recommending actions. Such AI bots could be a vast improvement over the profit-driven, bias-amplifying and misinformation-spreading algorithmic regime currently in place.
The challenge of using artificial intelligence in addressing climate change is complex and requires multiple disciplines, including engineering, computing, biology, psychology and social science. In the end, it will be up to governments to ensure that these technologies are used wisely in order to curb the worst effects of climate change. Despite the fact that some may argue that the responsibility of high-income countries in undertaking mitigation and adaptation measures is higher than that of low-income nations, it will be vital for all states to cooperate in these efforts.
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