"AI refers to systems or machines that perform tasks that typically require human intelligence, and can iteratively improve themselves over time, based on the information they collect," says David Jensen, coordinator of the United Nations Environment Program's (UNEP's) Digital Transformation sub-programme.
Jensen highlights several areas where AI can play a role in tackling environmental challenges, from designing more energy-efficient buildings to monitoring deforestation to optimizing renewable energy deployment.
"This can be on a large scale – such as satellite monitoring of global emissions, or a more granular scale – such as a smart house automatically turning off lights or heat after a certain time," he adds.
source: How artificial intelligence is helping tackle environmental challenges
One and not only direction "Disinformation Detection":
AI can identify and counteract misinformation and propaganda campaigns, helping maintain informed societies.
However, the issue is the modeling of such detection. Statistical tools are used under human supervision, which may bias the AI model.
Given the current geopolitical climate, pollution, natural disasters, global warming, and wars, AI can play a vital role in addressing these challenges. Some of the most practical applications include:
1. Environmental Monitoring
AI can enhance environmental tracking through satellite imagery and data analysis, monitoring emissions, deforestation, and pollution. It enables real-time updates and predictions that support better decision-making in environmental policies.
2. Climate Change Prediction
AI models can predict climate patterns and assess the impacts of global warming, informing strategies for mitigation and adaptation. By analyzing vast climate data, AI aids in designing policies to reduce greenhouse gas emissions.
3. Energy Efficiency
AI optimizes energy use in homes, industries, and grids, promoting renewable energy deployment and improving efficiency. It helps balance energy supply and demand and reduces carbon footprints by targeting specific energy consumption patterns.
4. Disaster Response
AI helps predict natural disasters such as hurricanes and wildfires and optimizes response efforts by analyzing real-time data. AI-driven drones and robotics also assist in disaster recovery and aid delivery to remote areas.
5. Pollution Control
AI monitors and analyzes pollution levels, detecting harmful emissions and optimizing waste management systems. It can also improve recycling processes and develop cleaner production technologies.
6. Sustainable Agriculture:
AI enhances agricultural practices by optimizing water usage, reducing pesticide use, and increasing crop yields, all while minimizing environmental impact through precision farming techniques.
7. Conflict Monitoring and Peacebuilding
AI can predict potential conflicts by analyzing data from various sources, supporting early interventions. It can also help in post-conflict recovery by optimizing resource allocation for rebuilding efforts.
8. Smart Cities:
AI supports the development of sustainable urban environments by optimizing infrastructure, reducing energy consumption, and improving transportation systems, making cities more resilient and eco-friendly.
AI's applications to address current global challenges fall into two critical categories:
1. AI for climate action and disaster response 2. AI for humanitarian aid and crisis management.
Specifically, AI is being deployed for rapid weather prediction and climate modeling to provide early warnings of extreme weather events and natural disasters.
It is also being utilized for humanitarian assistance by detecting damaged buildings from satellite imagery after disasters and supporting missing person identification during crises.
If we are talking about AI helping environmental issues, such as global warming or natural disasters, it is quite the opposite, unfortunately.
AI, as it is currently developed and deployed, is not inherently environmentally safe. It requires substantial resources, both in terms of materials and energy. AI infrastructure, including data centers, servers, and GPUs, depends on materials and mining of silicon, lithium, cobalt, and rare earth metals.
Recently, Google and Microsoft already sparked conversation about using nuclear reactors to scale and maintain their AI data centers. As it stands, this only seems to be growing.
I'd recommend an incredible book called Atlas of AI by Kate Crawford if you wish to know more in-depth about what it takes to build and maintain AI systems.
Eduard Babulak .....Eduard, I don’t know the answer. - I recall you asked a similar question(s) searching and hoping today offers more insight. — On March 20, 2023 Noah M. Kenney posted his insights to your past question. I tend to agree with him. -- In addition, based on mankind’s past use of technology, I believe we won’t have answers but (many) more questions. And, to an extreme extent, unexpected answers & questions. Also, like our past, we won't know how to think about what we find. Though an uncomfortable place to work — I will consider that a worthwhile achievement. No, I'm not ignoring your question, “what are the most practical AI applications to help?” There’s enough people on earth for us to address each one.
However, as we live into the future I believe the best outcomes are not always a specific answer. The best outcome is twofold; (1) we find common needs and work together. Likely conditions will force us into working and sharing what we find. (2) We’re -again- faced with not understanding or knowing how to think about what we discover with our new tools (physical, digital or something else).
Said differently; working to accomplish the tasks at hand and, in addition, finding many unknowns offers avenues to innovation and creativity. Today AI is very new. Moving forward we’ll begin to see AI based on our accumulated past experiences. Like most of our questions, we’ll move forward with our best “guesses” and adjust the way we test them with our experiences (mostly inexperience) with AI & nature.
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