AI can also help us adapt to the effects of climate change, improve our ability to predict extreme weather events, and provide decision-support tools to help us respond more effectively. AI can also play a key role in improving our resilience to the effects of climate change by helping us identify risk factors and develop plans to mitigate the effects of climate change.
Public and private sector leaders see greatest business value in reducing emissions and measuring emissions (Source: BCG Climate AI Survey, May 2022)
Lambert Hogenhout, chief data analyst for partnerships and technology innovation at the Office of Information and Communication Technology (OICT), said, “In this context, the most pressing need is not to have more powerful AI, but to have more powerful AI where and where we use it. Get smarter in ways. There are many untapped opportunities.” This sentiment reflects the consensus of many experts in the field: We need to be more strategic about where and how we deploy AI to have the greatest impact .
Hence the need for a new climate AI framework, which is essential to focus discussions on investment and innovation in this area. James Hodson, CEO of the AI for Good Foundation, said, “To effectively address the fundamental drivers and risks of our overreliance on fossil fuels, we need to embrace a framework of multiple innovative solutions. Artificial intelligence is at the center of that framework, and AI has already Faster progress in increasing transparency at scale, efficient power generation and storage, and renewed confidence in large-scale investment have contributed.”
The “Framework for Using Artificial Intelligence to Address Climate Change,” pictured below, was developed by BCG for the latest Global Artificial Intelligence report, which includes views from experts on the Global Artificial Intelligence Advisory Committee. The framework includes three main themes: Mitigation, Adaptation and Resilience, and Fundamentals. Mitigation and fundamentals are critical to our efforts to combat climate change, but adaptation and resilience are necessary to ensure that people and economies can withstand the impacts of climate change today. True resilience requires us to look at the world at a systems level and use artificial intelligence to help us identify risks, vulnerabilities and potential disruptions when it comes to climate change. We must also build the capability and strength to respond quickly to these threats and create a resilient architecture.
A framework for using AI to address climate change (BCG Project Experience, AI for Climate Change, Global Partnership for AI).
“Despite the promise of AI, AI cannot be used to solve the climate crisis in isolation,” said Damien Gromier, founder and co-chair of the AI for the Planet Alliance and co-author of the report. The crisis depends on the willingness of policymakers to act and make the necessary changes, and artificial intelligence and other emerging technologies can provide part of the support.” It must therefore be pointed out that artificial intelligence is not a panacea for climate change, artificial intelligence is a tool that can be used to help We build a more resilient future.
Using artificial intelligence to tackle climate change framework
The Harnessing AI to Climate Change framework is changing the way we think about climate change. In the past, we tended to think of adaptation as something we did after the fact in response to an event that had already happened. But as the frequency and severity of extreme weather events increase, it has become clear that we must take a proactive approach to adaptation. We need to predict the potential impacts of climate change and take steps to mitigate them before they happen. This is critical to ensuring the resilience of our communities and economies and protecting the most vulnerable among us. AI can give us the tools and data we need to make informed decisions and help accelerate mitigation, adaptation and resilience efforts.
Mitigate climate change
The mitigation portion of the Using AI to Address Climate Change Framework is a portfolio that includes both macro- and micro-level measurements, reductions (reducing greenhouse gas emissions intensity, improving energy efficiency, and reducing greenhouse effects) and removals (environmental and technological removals).
Emission measurement
Measurements at the macro level: Overall environmental emissions are an important component of models that predict future climate. AI can help these models by improving measures such as scanning remote sensing data from satellites for further analysis.
Micro-level measurements: Producers can use micro-level emissions measurements to understand the carbon footprint of their products, track their progress towards ESG targets, or identify opportunities to reduce Scope 1, 2 and 3 emissions. Consumers can use this information to make more informed choices when purchasing products and actions to reduce their carbon footprint.
Reduce emissions and the greenhouse effect
Due to the urgency of the global climate, accelerated efforts are necessary to accelerate the reduction of current emissions and their greenhouse gas consequences. It is important to take immediate and large reduction measures. This is important to avoid the catastrophic consequences of climate change. Emission reduction consists of the following three components:
Reducing the emission intensity of greenhouse gases: AI solutions can be used to support the transition to new energy sources. Forecasts of solar energy supply can help us identify areas that have the potential to increase solar energy use, thereby reducing greenhouse gas emissions.
Reducing emissions-generating activities: AI can also reduce emissions by optimizing supply chains by improving demand forecasting (fighting overproduction) or efficient transport of goods (such as shortening lead times and minimizing energy use). It is possible to use data to generate models that forecast demand or optimize transportation routes.
Reducing the Greenhouse Effect: If policymakers turn to geoengineering solutions to curb the effects of climate change, AI will be an important tool in accelerating chemical research that can help us develop new materials and processes that reduce greenhouse gas emissions. In addition, incentives for behavioral change can reduce energy consumption and lower emissions.
remove greenhouse gases
Removing greenhouse gases from the atmosphere is one way to mitigate climate change, either through natural processes, such as increased photosynthesis in trees, or through technological means, such as carbon capture and storage. There are two main cleaning methods:
Environmental removal: Natural ecosystems such as forests, algae and wetlands can play a central role in atmospheric carbon removal. Monitoring these ecosystems requires collecting and processing vast amounts of data, and artificial intelligence is very effective in this context.
Technical removals: Environmental removals can be complemented by industrial processes, but industrial processes are still in their infancy and face scaling issues. AI will be a powerful ally in addressing these issues as quickly as possible.
Having consolidated the mitigation part of the framework, we now need to focus on the adaptation aspect.
Adaptability and Resilience
disaster prediction
Predicting long-term trends in localization: To predict the potential impacts of climate change, we need to be able to predict long-term trends in localization. For example, what is the probability of a major drought in an area in the next 10 years? What are the potential impacts of this drought on agriculture, water supply and human health? AI can help us answer these questions by analyzing historical data and predicting future trends.
Build early warning systems: In addition to predicting long-term trends, AI can also help us build early warning systems that will alert you to impending events in a timely manner. For example, by analyzing data from weather stations, satellite imagery and sensor networks, AI can help us identify conditions that fuel extreme weather events such as hurricanes, floods and wildfires. These early warning systems allow us to take action before these events and mitigate the effects of extreme weather events. For example, the World Economic Forum report on AI helping the world fight wildfires shows that AI can help prevent mountain fires by developing better algorithms for fire detection and spread by using data sources such as satellite imagery, real-time weather data and social media posts. fire occurs. An intelligent framework that integrates all these systems is necessary to build a dynamic wildfire risk map as well as interactively simulate fire spread.
Weakness and Risk Management
Manage crises: Once extreme weather events occur, AI can help us manage crises by providing decision support tools. For example, AI can be used to identify people who are likely to be affected by an event and match them with the resources they need. AI can also monitor the situation in real time and provide information on the location of those affected, the state of infrastructure and the state of rescue efforts.
Strengthening infrastructure: Smart irrigation systems can help reduce the impact of droughts by using weather data and plant sensors to optimize watering schedules. AI flood control systems can help prevent flooding by using real-time data on rainfall, river levels and land elevations. Smart buildings can use sensor data to adjust heating, cooling and ventilation. Can help save energy and reduce emissions. According to the UN project summary, knowledge graphs can store large amounts of data and perform inference, can help identify patterns, associations and dependencies hidden in complex data sets, and ultimately can analyze information such as floods, droughts and other extreme weather events. . These can improve resilience in the face of climate change.
Protecting populations: Mass migration is one of the potential impacts of climate change. AI can help us manage this problem, and AI can provide decision-support tools for managing refugee camps, tracking migrants, and coordinating relief efforts. AI can also be used to monitor the situation in real time and provide information on the location of personnel, the state of infrastructure and the state of rescue efforts.
Protecting biodiversity: The use of machine learning species identification systems can help us track and protect endangered species. And the use of artificial intelligence monitoring systems from satellite imagery and sensor data can help us spot illegal logging, poaching and other activities that threaten biodiversity.
The AI for Climate Change Medium Framework demonstrates ways to build truly resilient and robust systems that can withstand and recover from extreme weather events. The framework also creates a set of essential elements for climate research and modelling of economic and social transitions, climate finance (such as carbon price projections), education and behavioural change.
“Companies that put AI at their core are more likely to make positive contributions to climate resilience, adaptation and mitigation efforts than those that don’t,” Hodson said.
In addition, according to Hamid Maher, managing director and partner at BCG and BCG GAMMA and co-author of the Global Artificial Intelligence Report, “AI’s unique ability to collect, complete and interpret large and complex data sets means that AI can help A more informed and data-driven approach by stakeholders can combat carbon emissions and address climate risks. However, most existing AI-related climate solutions are fragmented, difficult to access, and lack the resources to scale Scaling. These are the things that need to change.” However, some innovative climate technology solutions have used AI and made progress across all three themes of the Adaptation and Resilience Framework.
“Artificial intelligence and other emerging technologies can play a huge role in helping us get back on track with the SDGs,” said Reina Otsuka, UNDP’s natural climate and energy digital innovation expert and member of the Global AI Steering Group. Huge potential. AI can help us move in a sustainable direction, including an emphasis on climate change-related impacts such as mitigating climate change and providing additional resilience and adaptation, especially for those already affected and most vulnerable to climate change The importance of change-related risks to those affected.”
Furthermore, Dr Marielza Oliveria, Director of UNESCO’s Partnerships and Operational Programme Monitoring, Communications and Information Sector and member of the Global Artificial Intelligence Steering Group, said, “It is impossible to solve the urgent and devastating climate crisis we face with old solutions. We have to add massive innovation to this mix. AI can help us identify opportunities to change our current posture on a scale large enough to have a rapid impact. AI is deployed in a human-centred, responsible and ethical way, Bike is a sustainability accelerator. I see every day the transformative power that AI is bringing to the planet, including companies minimizing carbon emissions across their entire value chain and helping governments predict weather patterns and respond effectively Weather patterns affecting vulnerable coastal communities. Here’s what we need: full brain power!”
Blue Sky Analysis
Blue Sky Analytics, based in The Hague, Netherlands, is a climate technology company that transforms satellite data into environmental intelligence. The company’s API-based environmental datasets leverage satellite data, artificial intelligence and the cloud to provide insights on a variety of topics related to the planet and its health. The Global Artificial Intelligence Report features the company as an example of a successful climate technology startup.
One Concern
Headquartered in California, One Concern uses artificial intelligence to estimate damage caused by natural phenomena. The company takes a holistic approach to uncovering risk sources and building resilience, taking into account not only individual buildings but also the networks on which they depend, such as transport connections and power grids, when uncovering the sources of climate risk hazards.
Cloud to Street
New York-based Cloud to Street is a company that uses satellites and artificial intelligence to track floodwaters anywhere on Earth in near real-time. The company runs a global flood database that provides insight into global flood risk. Cloud to Street is committed to helping reduce flood risk and save lives.
Prospera
Prospera is a Tel Aviv-based company developing machine vision technology designed to monitor and analyze plant development, health and stress. The company’s technology captures multiple layers of crop field data, including climate and visual data, to quickly spot anomalies. Prospera technology is implemented in the form of mobile and web dashboards.
EXCI
Based in Maroochydore, Australia, EXCI is a bushfire detection technology company. EXCI uses artificial intelligence models to fuse data from satellite and ground sensors to provide continuous system monitoring of wildfires, which can provide firefighters with the intelligence to effectively manage wildfires and extinguish them.
Kuzi
Kuzi is a Kenyan company. Kuzi uses artificial intelligence to predict the breeding, occurrence and migration routes of desert locusts across the Horn of Africa and East African countries. The company’s AI tools use satellite data, soil sensor data, ground-based weather observations and machine learning to make predictions.
The above solutions are just a few illustrative examples of how today’s AI can address adaptation and mitigate the effects of climate change. Hodson said, “The next frontiers of AI in climate will be decision support tools and behavioral incentives that push people, companies and governments to do the right thing.
because it is in their best interests. ”
call to action
The Global AI Alliance is launching a call for solutions aimed at providing visibility, networking and commercial support for climate AI solutions around the world and moving these solutions forward on a path to scale and impact provide support. Global Artificial Intelligence is an alliance created by Startup Inside. The alliance’s knowledge partners include Boston Consulting Group (BCG) and BCG GAMMA. The alliance partners also include AI for Good Foundation, United Nations Development Program (UNDP), United Nations Education , Scientific and Cultural Organization (UNESCO) and the United Nations Office of Information and Communication Technologies (OICT).
Global AI is a unique, multidisciplinary, and diverse consortium whose mission is to: 1. Promote the application of advanced analytics and artificial intelligence to Innovations for climate challenges; 2. Provide a global platform for identifying and prioritizing key tools and use cases of AI in addressing the climate crisis; 3. Identifying and supporting the most promising AI, identifying and supporting solutions to climate change mitigation, The most promising solutions for adaptation and recovery, especially in the southern half, provide visibility and recognition of the solutions; 4. Ensure generation of Scale effects; 5. Facilitate the development of networks among project teams, investors and experts in the field (including start-ups, corporations and the public sector).
In addition, the Global AI Alliance is currently accelerating the global search for startups that use AI to combat climate change in one or more of the following ways.
Improve our understanding of the natural world and how it changes
Develop new methods for monitoring and measuring environmental phenomena
Help us make better decisions about how to use and protect our natural resources
reduce greenhouse gas emissions
Adapting to and Mitigating the Impact of Climate Change
Artificial intelligence is a key game-changer that has the potential to accelerate humanity’s race against climate change. We have the opportunity to build a more resilient future for all of us by harnessing artificial intelligence. As the impacts of climate change become more widespread and severe, we must continue to invest in and support climate technology companies that are using artificial intelligence to develop solutions.
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