Sustainable artificial intelligence: how to minimise the environmental impact of AI

Artificial intelligence (AI) has become a key technology in multiple sectors, from health and education to industry and environmental management, not to mention the number of citizens who create texts, images or videos with this technology for their own personal enjoyment. It is estimated that in Spain more than half of the adult population has ever used an AI tool.

However, this boom poses challenges in terms of sustainability, both in terms of water and energy consumption and in terms of social and ethical impact. It is therefore necessary to seek solutions that help mitigate the negative effects, promoting efficient, responsible and accessible models for all. In this article we will address this challenge, as well as possible efforts to address it.

What is the environmental impact of AI?

In a landscape where artificial intelligence is all the rage, more and more users are wondering what price we should pay for being able to create memes in a matter of seconds.

To properly calculate the total impact of artificial intelligence, it is necessary to consider the cycles of hardware and software as a whole, as the United Nations Environment Programme (UNEP)indicates. That is, it is necessary to consider everything from raw material extraction, production, transport and construction of the data centre, management, maintenance and disposal of e-waste, to data collection and preparation, modelling, training, validation, implementation, inference, maintenance and decommissioning. This generates direct, indirect and higher-order effects:

• The direct impacts include the consumption of energy, water and mineral resources, as well as the production of emissions and e-waste, which generates a considerable carbon footprint.
• The indirect effects derive from the use of AI, for example, those generated by the increased use of autonomous vehicles.
• Moreover, the widespread use of artificial intelligence also carries an ethical dimension, as it may exacerbate existing inequalities, especially affecting minorities and low-income people. Sometimes the training data used are biased or of poor quality (e.g. under-representing certain population groups). This situation can lead to responses and decisions that favour majority groups.

Some of the figures compiled in the UN document that can help us to get an idea of the impact generated by AI include:

• A single request for information to ChatGPT consumes ten times more electricity than a query on a search engine such as Google, according to data from the International Energy Agency (IEA).
• Entering a single Large Language Model ( Large Language Models or LLM) generates approximately 300.000 kg of carbon dioxide emissions, which is equivalent to 125 round-trip flights between New York and Beijing, according to the scientific paper "The carbon impact of artificial intelligence".
• Global demand for AI water will be between 4.2 and 6.6 billion cubic metres by 2,027, a figure that exceeds the total consumption of a country like Denmark, according to the "Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models" study.

Solutions for sustainable AI

In view of this situation, the UN itself proposes several aspects to which attention needs to be paid, for example:

• Search for standardised methods and parameters to measure the environmental impact of AI, focusing on direct effects, which are easier to measure thanks to energy, water and resource consumption data. Knowing this information will make it easier to take action that will bring substantial benefit.
• Facilitate the awareness of society, through mechanisms that oblige companies to make this information public in a transparent and accessible manner. This could eventually promote behavioural changes towards a more sustainable use of AI.
• Prioritise research on optimising algorithms, for energy efficiency. For example, the energy required can be minimised by reducing computational complexity and data usage. Decentralised computing can also be boosted, as distributing processes over less demanding networks avoids overloading large servers.
• Encourage the use of renewable energies in data centres, such as solar and wind power. In addition, companies need to be encouraged to undertake carbon offsetting practices.

In addition to its environmental impact, and as seen above, AI must also be sustainable from a social and ethical perspective. This requires:

• Avoid algorithmic bias: ensure that the data used represent the diversity of the population, avoiding unintended discrimination.
• Transparency in models: make algorithms understandable and accessible, promoting trust and human oversight.
• Accessibility and equity: develop AI systems that are inclusive and benefit underprivileged communities.

While artificial intelligence poses challenges in terms of sustainability, it can also be a key partner in building a greener planet. Its ability to analyse large volumes of data allows optimising energy use, improving the management of natural resources and developing more efficient strategies in sectors such as agriculture, mobility and industry. From predicting climate change to designing models to reduce emissions, AI offers innovative solutions that can accelerate the transition to a more sustainable future.

National Green Algorithms Programme

 In response to this reality, Spain has launched the National Programme for Green Algorithms (PNAV). This is an initiative that seeks to integrate sustainability in the design and application of AI, promoting more efficient and environmentally responsible models, while promoting its use to respond to different environmental challenges.

The main goal of the NAPAV is to encourage the development of algorithms that minimise environmental impact from their conception. This approach, known as "Green by Design", implies that sustainability is not an afterthought, but a fundamental criterion in the creation of AI models. In addition, the programme seeks to promote research in sustainable IA, improve the energy efficiency of digital infrastructures and promote the integration of technologies such as the green blockchain into the productive fabric.

This initiative is part of the Recovery, Transformation and Resilience Plan, the Spain Digital Agenda 2026 and the National Artificial Intelligence Strategy.. Objectives include the development of a best practice guide, a catalogue of efficient algorithms and a catalogue of algorithms to address environmental problems, the generation of an impact calculator for self-assessment, as well as measures to support awareness-raising and training of AI developers.

Its website functions as a knowledge space on sustainable artificial intelligence, where you can keep up to date with the main news, events, interviews, etc. related to this field. They also organise competitions, such as hackathons, to promote solutions that help solve environmental challenges.

The Future of Sustainable AI

The path towards more responsible artificial intelligence depends on the joint efforts of governments, business and the scientific community. Investment in research, the development of appropriate regulations and awareness of ethical AI will be key to ensuring that this technology drives progress without compromising the planet or society.

Sustainable AI is not only a technological challenge, but an opportunity to transform innovation into a driver of global welfare. It is up to all of us to progress as a society without destroying the planet.