Reacción a "A UN report details the increasingly serious consequences of AI as it relates to water, land, and carbon emissions"

This is a very comprehensive report that takes a holistic approach to the environmental cost associated with data centre energy consumption, taking into account not only CO₂ emissions but also the water consumption and land use footprints linked to data centres.

To summarise its impact, I would highlight the following statement: ‘If the electricity consumption of data centres were considered that of a country, it would rank eleventh globally in terms of electricity consumption’ (my own translation). The report clearly reflects an economic reality in which the technology sector occupies a dominant position. It is worth noting that nine of the ten companies with the highest market capitalisation in the world belong to this sector, with Nvidia having the highest market value. This company, a manufacturer of the processors used to train and operate AI systems, has a market capitalisation exceeding the GDP of every country in the world, with the exception of the United States and China. In fact, this market capitalisation is equivalent to more than 13% of US GDP.

The report also highlights the growing share of artificial intelligence in data centre electricity consumption, rising from around 20% of the electricity consumed by these facilities in 2025 to a projected 40% in 2030. However, only 16% of countries have specialised AI infrastructure, and within this group, 90% of installed capacity is concentrated in two countries: the United States and China. Consequently, a very significant proportion of the increase in the environmental impact associated with artificial intelligence is also concentrated in these two economies.

Among the principles proposed by the report to move towards a responsible AI ecosystem, I find the principle of efficiency by design particularly relevant. The document highlights that a typical text query to a system such as ChatGPT can require approximately 200 times more energy than text classification tasks, such as spam filtering (the comparison is even greater when considering images or videos). In this context, the development and deployment of smaller, specialised models appears to be a promising way to reduce energy consumption without sacrificing the utility of these technologies.

Another aspect that caught my attention is the comparison of the environmental footprints of data centres in different countries. For example, France, which hosts one of the largest numbers of data centres in Europe, has a significantly lower carbon, water and land-use footprint per kWh than other countries with a high concentration of such infrastructure, such as the United Kingdom, Italy or Germany. Such comparisons highlight that environmental impact depends not only on the scale of installed capacity, but also on the characteristics of the energy system that powers it.