Ethics and AI: Societal and Environmental Wellbeing (6/7)
In 2019, the European Commission's High-Level Expert Group on Artificial Intelligence (AI HLEG) published its "Ethics Guidelines for Trustworthy AI". To this day, it remains one of the foundational documents on the ethical requirements for artificial intelligence.
The Guidelines set out seven key requirements for trustworthy AI that must be met at every stage of a system's lifecycle - from design and development to practical deployment in real-world settings.
These requirements are:
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Human agency and oversight - see our article here
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Technical robustness and safety - see our article here
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Privacy and data governance - see our article here
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Transparency - see our article here
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Diversity, non-discrimination and fairness - see our article here
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Societal and environmental wellbeing
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Accountability - see our article here
Each of them plays a key role in making AI not only technologically advanced, but also ethically sound, sustainable, and beneficial to society. In this series, we will examine each principle in turn, looking at what it means for legal practice and for the future of the legal profession.
Having already covered the first five principles, we now turn to the sixth: societal and environmental wellbeing.
Why this principle is of key importance
The principle of societal and environmental wellbeing focuses on the sustainable and ethical use of AI - use that not only avoids harm, but also promotes long-term benefits for society, ecosystems, and future generations.
It connects fairness (principle 5) and the prevention of harm with long-term sustainable development. AI should support global goals such as sustainable development, environmental protection, and the wellbeing of everyone.
This includes both social aspects (access, health, education) and environmental ones - the responsible use of resources, minimizing harm, and supporting future generations.
What does the principle mean?
According to the principle of societal and environmental wellbeing, AI should be used deliberately to solve social, environmental, and economic problems such as hunger, poverty, education, and climate change. This is the essence of the AI for Social Good (AI4SG) movement, which supports sustainable development through technological solutions.
Existing environmental and social considerations
While AI can solve social and environmental problems (e.g. flood modeling, health, education), there is no guarantee that its resources will be used fairly and sustainably.
Building and maintaining AI infrastructure itself (especially data centers) demands significant resources:
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Energy: The use of artificial intelligence is driving a sharp rise in electricity demand. According to projections, by 2030 data processing in the United States could consume more electricity than all manufacturing industries combined.
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Water: Cooling the equipment consumes enormous quantities of drinking water - global consumption at data centers is expected to reach 6.6 billion m³ by 2027, which is more than half of the United Kingdom's annual consumption.
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Carbon emissions: In 2022 alone, data centers used around 460 TWh of electricity, comparable to the consumption of a country like France.
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The hardware waste (e-waste) and the mining of rare earth elements associated with chip manufacturing and the upkeep of data centers also have a major impact on the environment.
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Overloading the energy grid and tying up large quantities of resources often affects vulnerable communities, which bear the burden of pollution and higher bills.
Examples of using AI for societal benefit.
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Fighting poverty and education NGOs such as Education Above All created the Ferby platform - an AI chatbot that provides personalized learning in India, already used by more than 5 million children. It is a free tool that helps children in resource-limited regions.
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Crises and natural disasters The International Federation of Red Cross and Red Crescent Societies reports that AI can cut disaster response times by up to 50% and save more than 1 billion dollars a year.
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Agriculture and sustainable development AI tools are being used to optimize farming - chatbots such as Saagu Baagu help farmers in India increase their yields, reduce resource consumption, and improve their incomes. In Kenya, SMS-based AI systems deliver weather forecasts to farmers and help them adapt to climate change.
The principle of societal and environmental wellbeing in AI urges us to use technology responsibly - to minimize the burden on energy, water resources, and the carbon footprint, while at the same time ensuring fairness and sustainability
