What is Sustainable AI?

Sustainable AI must be about making AI systems that are environmentally friendly, socially responsible, and economically viable in the long run.

AI requires a lot of computational power, which means more energy consumption. Data centers that train AI models use a lot of electricity, often from non-renewable sources, leading to high carbon emissions. So Sustainable AI might involve using renewable energy, optimizing algorithms to be more energy-efficient, or developing hardware that’s less power-hungry.

Social Impact of Sustainable AI

AI can have biases, leading to unfair outcomes. Sustainable AI should address fairness, transparency, and accountability. Ensuring that AI systems are designed with ethical guidelines in mind, so they don’t perpetuate discrimination or inequality.

For example, considering the social impact, like job displacement due to AI automation. Sustainable AI might involve creating systems that augment human work rather than replace it, or investing in education and reskilling programs.

Question

Which of the following practices is important for creating sustainable AI models?

a) Reducing the size and complexity of AI models to decrease energy consumption.
b) Using large amounts of unfiltered data without considering its environmental impact.
c) Training AI models without regard for computational resources or carbon emissions.
d) Ignoring model optimization for the sake of speed and performance.

Correct Answer:

a) Reducing the size and complexity of AI models to decrease energy consumption.

Explanation

Sustainable AI involves practices that minimize the environmental impact of AI models, such as reducing the computational cost and energy consumption required for training and inference.

The first option focuses on optimizing the model’s size and complexity to make it more energy-efficient, which is a key aspect of sustainable AI.