Sustainable Artificial Intelligence

What is Sustainable Artificial Intelligence?

Sustainable Artificial Intelligence is the training and creation of artificial intelligence systems with an effort to be more sustainable. This comes in two different categories; Environmental and Social. Social sustainability includes using training data that is freely available, and bias free, with transparency. Environmental sustainability involves using optimized algorithms and data centers, and efficient implications including heat reuse, edge computing and more, to reduce the environmental impact and energy/water use that comes from artificial intelligence systems.

Why Sustainable Artificial Intelligence?

The powers of Artificial Intelligence are taking over the world. The reach and impact of AI can been seen almost anywhere you look today. This comes with tremendous benefits. Artificial Intelligence can make daily tasks more efficient, help increase creativity, and much more. However, these powerful tools come with a cost as well. Artificial Intelligence is expensive to train. It takes a lot of time, computing power, and water. Also, these generative AI tools use lots of data to train, and to "learn" from this data to create new content. This creates many problems, such as biases in training data, ethical rules regarding who owns generated content, questions regarding what data is okay to use for training, and much more.

This website explore all the important questions, and current answers regarding the dangerous costs of AI. It will talk about how to make AI more sustainable and better for advancing the common good, and divide it into 2 different sections; social and environmental. Both topics are crucial in ensuring safe and beneficial artificial intellence systems. This website will also explore the various ways that AI can help sustainability efforts in a variety of topics. Continue reading and exploring this website to learn more.

Environmentally Sustainable Artificial Intelligence

Optimization

Opitmization of Data Centers and Algorithms used for training AI systems are crucial for reducing the environmental impact.

Renewable Energy

Renewable Energy is required to power the training of AI to reduce the carbon footprint and to battle the large increase of energy consumption caused by AI.

Heat Reuse

The use of hundreds to thousands of GPU's to train AI systems creates a lot of heat. The ability to reuse this heat ensures efficiency and reduces negative environmental impacts.

Edge Computing

Edge Computing is a training process that allows for more efficient training of AI systems and less computer infrastructure.

Artificial Intelligence for Sustainability

One significant benefit of artificial intelligence systems is the ability to help improve sustainable practices across many different fields. In many fields AI can help improve efficiency of operations, decrease cost of production, monitor important variables, and help solve challenging problems. The three main aspects of AI helping sustainability that this website will explore are through resource management, climate monitoring and the supply chain.

Artificial Intelligence can help resource management by predicting resource needs for a project, and assigning tools and resources in the most efficient ways possible. AI may help climate monitoring by noticing important changes within the environment.

Socially Sustainable Artificial Intelligence

Safe AI

Creating safe and aligned AI is crucial for ensuring a future best for humanity. There are many practices being developed to achieve this.

Bias Free AI

AI uses a lot of data to train, and that data contains biases. This could negatively impact various groups and causes bias amplification.

AI Regulaton

There are still many questions on how it is best to regulate AI. Are strict regulations or loose regulations best?