I share some reflections about the role of AI in mitigating climate change. I emphasize the potential for local AI ecosystems in driving innovation and economic growth. I believe that startups should play a prime role in climate mitigation. They will achieve this through tailored AI applications in various sectors.
Large AI and Climate Change
Large AI companies (“Large AI“) are already actively mitigating climate change, for which they are a partial culprit. They are motivated by both economic and environmental factors.
Such initiatives aim to increase renewable energy for AI operations, utilizing sources like wind, solar, nuclear, and hydroelectric. Estimates show that AI could consume about 402 TWh of energy by 2030. This is mainly due to the high energy demands of training large models.
Additionally, large AI companies are heavily investing in climate technology. By improving existing applications and technologies, AI could help reduce greenhouse gas emissions by 5% to 10% by 2030. It could also support climate adaptation and resilience efforts.
AI also enhances the operational efficiency of these Large AI companies. Examples include optimized cooling in data centers, supply chain management, carbon footprint reduction in product design, etc.
This is not enough to effect the significant change needed to fight against climate change at scale. It also does not ensure a fair distribution of the outcomes resulting from implementing such initiatives.
Local AI ecosystems?
The concept of a local AI ecosystem focuses on interactions among stakeholders. Stakeholders include SMEs, academic institutions, and governmental bodies. It also involves civil society and international entities.
Such ecosystems promote community-centered innovation, enhancing entrepreneurship and attracting investments. They forge vital collaborations essential for tailored solutions to environmental challenges.
Supporting local AI ecosystems not only addresses climate change. It also fosters economic growth and resilience in communities. It is crucial to harness AI’s potential in addressing climate issues effectively.
Large AI Call to Action: Collaborative Innovation
Large AI companies, startups, and local ecosystems need to collaborate further. This collaboration will create a synergistic approach to climate change adaptation. This collaboration can lead to more comprehensive and effective solutions that tackle both global and local challenges.
Ai for Climate
The next is a summary overview of the main categories of how AI is currently assisting in climate change adaptation and startups active in this field:
AI-Enabled Strategies for Climate Change Adaptation
Risk Assessment and Prediction
AI can analyze vast amounts of data from climate models, satellite imagery, and other sources. It can identify vulnerable areas. AI can predict future climate scenarios. This capability allows for:
- Identification of high-risk areas prone to climate-related hazards
- Climate Analytics: This institute utilizes AI to analyze climate data and offer insights into future climate scenarios.
- Orbital Insight: This company uses satellite imagery and AI to track changes in the environment. These changes include deforestation and urban sprawl.
- Development of early warning systems for disasters like floods and wildfires
- Tesselo: Tesselo’s country-scale mapping solutions provide important data points. These include forest growth forecasts, crop harvest forecasts, pest prevalence, and natural disaster risk analysis, among others.
- Prediction of sea-level rise impacts on coastal infrastructure
- Earthwave: This company uses AI to analyze satellite imagery and other data sources to monitor coastal erosion and sea-level rise.
Tailored Adaptation Planning
AI tools can help develop targeted adaptation plans by:
- Analyzing local geographical and socioeconomic factors
- Connecting global climate risks with local conditions
- Identifying relevant adaptation measures for specific locations
- Climawise uses machine learning. It creates a global database of adaptation solutions.
Improved Resource Management
AI can enhance resource use and reduce emissions by:
- Enhancing energy efficiency in buildings
- (*) Kapacity.io – smart, automated energy management.
- Improving agricultural practices
- Assolia – multi year planting planner.
- Optimizing water management systems
- (*) AgrowAnalytics – predictive irrigation and automation of irrigation.
Need for Localization, Scalability and Replication
Adaptability allows communities facing similar challenges to gain from shared knowledge and innovations. This approach ultimately enhances local capabilities. It also fosters a collaborative approach.
We can refine these strategies further by leveraging data and insights gathered from diverse environments. This approach ensures they are contextually relevant and effective.
As more regions adopt AI-enabled solutions, a powerful synergy will emerge. This will enable a proactive response to climate change on a much larger scale. This interconnectedness enhances the resilience of individual communities. It also contributes to a more sustainable and equitable global future. In this future, knowledge flows freely, and resources are utilized efficiently.
Final Call to action!
I am interested in connecting with startups working on poverty alleviation and climate change mitigation using AI (**).
I am looking for startups operating in the USA, China, Russia, and/or KSA.
Please do not hesitate to contact me if you seek investment or if you are open to collaboration opportunities. Besides money, this is my value add.
“We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction”.
Bill Gates
(*) I’m an early investor.
(**) Particularly if you are working on afforestation and AI, as we do at Tree Geo Data
Further reading
[1] AI-enabled strategies for climate change adaptation https://link.springer.com/article/10.1007/s43762-023-00100-2
[2] Leveraging AI for climate adaptation: A new era for resilience https://www.preventionweb.net/news/leveraging-ai-climate-adaptation-new-era-resilience
[3] 9 ways AI is helping tackle climate change https://www.weforum.org/stories/2024/02/ai-combat-climate-change/
[4] Five ways local AI ecosystems can foster climate action https://unu.edu/cpr/blog-post/five-ways-local-ai-ecosystems-can-foster-climate-action
[5] How 4 startups are using AI to solve climate change challenges https://blog.google/outreach-initiatives/entrepreneurs/how-4-startups-are-using-ai-to-solve-climate-change-challenges/
Re: recent DeepSeek and Qwen announcements
There is another AI area besides mathematics (algorithms) and IT hardware which could be disrupted very soon. This is IT infrastructure and data center, electronics and chip cooling.
The US is leading AI race with Stargate USD 500 B initiative; China is contender with recent DeepSeek and Qwen announcements; Saudi can support with own PIF USD 600 B investment in USA economy and input in AI industry and infrastructure, including disruptive tech plus retain air cooling innovations for own internal use in many areas domestically and in GCC countries.