What artificial intelligence has to do with ecology? First, running AI takes up a lot of energy. Therefore, its major challenge concerns supplying itself with power. How to program AI to make itself more sustainable? The second area linking AI to ecology is the application of AI to analyze, create and implement green solutions. Additionally, one of the most urgent tasks for AI to handle concerns increasing corporate social responsibility. Read our article to learn more about green AI and AI for the Earth.
Green AI and AI for the Earth – table of contents:
There is a whole range of obstacles AI has to overcome to become green. One of the key issues is minimizing the amount of energy it consumes. Part of it is the AI-assisted selection of locations for servers and power plants powered by renewable sources, while among the tasks facing green AI is the creation of fully automated agriculture oriented to make the most of local potential. In today’s text, we will consider two issues:
- What is green AI (Green AI) all about? – i.e., how artificial intelligence tools make it possible to deliver greener AI models that require less energy and other resources to operate, and which companies are developing Green AI solutions
- What is AI for the Earth (AI for Green)? – i.e. how to assign AI to make it to find green solutions, and in which areas artificial intelligence already enables optimal use of natural resources in a way it doesn’t harm the environment
“Green AI” is contrasted with so-called “red AI” – that is, solutions that increase the efficiency of operations without looking at the environmental costs they generate. “Red AI” achieves spectacular results, but its environmental footprint is substantial and growing along the skyrocketing progress technology keeps making.
The main challenge facing green AI considers minimizing the carbon footprint. Its implementation relates to maximizing the efficiency of AI algorithms and cutting down on its unjustified application. A good example of the green AI dilemma concerns the moment a household is purchasing a vacuum cleaner robot. Let’s assume that a model without AI cleans with 80% efficiency while taking up 20% less energy. A model with AI vacuums with 95% efficiency, but consumes far more energy and transmits data almost constantly. When picking the right vacuum cleaner, we must therefore decide whether the increase in efficiency is worth the environmental cost.
Green AI is a very promising business area. Paradoxically, this is because apart from scientific as well as business, green AI developers’ key incentives concern ethical issues. Indeed, reducing the amount of energy consumed by green AI has more than just an economic dimension. Economized AI suits smaller companies perfectly well, including those operating in developing countries. This also means democratizing its application opens up its creative potential for more people to employ or even develop it, especially those with tight budgets.
AI for Earth
Artificial intelligence analyzes issues related to the climate crisis. It develops models that provide insight into environmental changes and predict their consequences.
AI also helps in many tasks that evolve around the optimal exploitation of raw materials, as well as in developing more efficient ways of operating existing systems that consume large amounts of energy. Among other things, it enhances the logistics of public transportation reducing fuel consumption. Through AI for Earth, you may reduce energy and water consumption on a large scale – at the street, city, and even regional level – in a relatively simple way. Synchronization of multiple parameters ensures that streetlights only light up when it’s dark and turn off when no one is around.
Moreover, Artificial intelligence also prevents costly and environmentally dangerous failures, such as in hydroelectric or wind power plants. This is possible through software called Digital Twins, which predicts the wear and tear of components in a particular system.
Green AI and AI for the Earth provide a huge creative potential for developing new solutions to the technological complexity of artificial intelligence. This makes these issues increasingly popular with startup developers and promising young researchers. What’s more, it raises hopes not only for the growth of ever-improving technologies in the field of artificial intelligence, but also for their wise maintenance as well as upgrades of existing models to come up with ones that are as planet-friendly as possible.
AI in business:
- Artificial intelligence in business - Introduction
- Threats and opportunities of AI in business (part 1)
- Threats and opportunities of AI in business (part 2)
- AI applications in business - overview
- What is NLP, or natural language processing in business
- Automatic document processing
- AI and social media – what do they say about us?
- Automatic translator. Intelligent localization of digital products
- AI-assisted text chatbots
- The operation and business applications of voicebots
- Virtual assistant technology, or how to talk to AI?
- Business NLP today and tomorrow
- How can artificial intelligence help with BPM?
- Will artificial intelligence replace business analysts?
- The role of AI in business decision-making
- What is Business Intelligence?
- Scheduling social media posts. How can AI help?
- Automated social media posts
- Artificial intelligence in content management
- Creative AI of today and tomorrow
- Multimodal AI and its applications in business
- New interactions. How is AI changing the way we operate devices?
- RPA and APIs in a digital company
- New services and products operating with AI
- The future job market and upcoming professions
- Green AI and AI for the Earth
- EdTech. Artificial intelligence in education