Artificial Intelligence (AI) is emerging as a technological revolution, transforming industries and improving people's lives. However, the growing energy appetite of the data centers that power these systems is generating a worrying echo in public health. While the impact on everyday life and energy consumption is discussed, the influence of AI on human health is often presented as a silenced topic, yet it is critical for building a sustainable future.
We often hear about the benefits of AI, but the conversation often ignores the implications for public health. This omission is a serious error, as the way in which the electricity needed to power the data centers that drive AI algorithms is generated is crucial. The electricity that powers these technological behemoths determines the impact on our health.
If the energy used comes from renewable sources, such as solar, wind, or hydroelectric, the impact is minimal. But if we continue to rely on fossil fuels to power these data centers, environmental pollution becomes a silent enemy. The "silent killer," as some call it, takes its toll in the form of respiratory illnesses, increased cancer cases, and other ailments, resulting in an annual death toll of around 4 million worldwide.
A determining factor is the pollution produced by the generation of that energy. The most harmful particles, known as PM2.5 (particles with a diameter of less than 2.5 micrometers), are microscopic and disperse widely through the air, reaching hundreds of kilometers from their source.
This is the crucial point: the people who suffer the consequences of pollution are not necessarily those who consume the energy. The most vulnerable populations, living in the vicinity of polluting power plants, bear the brunt of environmental pollution, in an unacceptable socio-environmental injustice.
The problem is exacerbated when the exponential growth in the use of AI requires more energy than is currently generated from renewable sources. Technology is advancing by leaps and bounds, but sustainable energy sources are not keeping pace, creating an imbalance that hinders the transition to a healthy future.
What solutions are emerging in this context? The answer is not easy, but a key strategy lies in separating the AI learning process. Instead of centralizing all processes in large, energy-intensive data centers, dedicated infrastructures for algorithm training could be created, located in areas with access to renewable energy sources. This would significantly reduce the carbon footprint associated with AI learning.
Imagine a scenario where data centers dedicated to training AI models are located in areas with high availability of wind or solar energy. This strategic decoupling could reduce the negative impact on public health. This would require significant investments in infrastructure and the development of new technologies, but the cost is less than the price society will pay for deteriorating health as a result of air pollution.
This is not about abandoning AI, but rather integrating it responsibly and sustainably. It is a powerful technology with transformative potential, but its application must not come at a human cost. It is essential to develop strategies that minimize the negative impact on public health, from the energy generation process to the location of the data centers that power it.
Ultimately, the future of AI and public health are intertwined. We cannot ignore the consequences that the widespread use of a technology can have, and we must seek a balance between innovation and sustainability, between progress and people's well-being.
AI is a powerful tool, but not a panacea. Its development and application must be integrated into a global strategy that prioritizes public health and the sustainable use of resources. Doing nothing is not an option. Humanity must find a way to build a future where artificial intelligence is a force for good, not disease.
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