Part 1 of the series “Keep Calm and Count the Kilowatts” showed that AI suggestions account for only a small portion of a person's daily energy consumption. Part 2 looked at how AI's energy, water and carbon footprints stack up on a global scale.
But the real environmental impact here isn't the tiny sip of energy your custom tip uses; it's the massive, concentrated impact that new data centers can have on the specific cities and ecosystems in which they're built.
Disproportional effects
AI-focused data centers leave a larger and messier footprint than other types of data centers and are large industrial facilities that impact power grids, water supplies and air quality.
There are two main problems. Power Density – Using artificial intelligence often means packing a lot of high-power GPUs into a small area, and as a result, a data center can consume much more power than a data center of the same size that simply streams Netflix.
Operators are already finding that this kind of concentrated demand is forcing them to rewire substations and delay building new ones because Expanding data centers with the help of artificial intelligence does not always provide full-fledged operations.
In fact, companies have to Modify power delivery and cooling to suit AI workloadsand AI leads to higher emissions in data centers.
Second, a data center that focuses on training AI models rather than serving content to users can be built where other data centers cannot, and those areas are often less equipped to handle the impact.
Impact as air pollution from portable gas turbines was used when an artificial intelligence data center was built in an area where the grid could only supply 4% of its electricity needs. Such facilities could end up importing diesel, burning gas on site, and competing with local residents for already strained infrastructure.
And although data centers are not large consumers of water compared to other industriesthey often built in areas where they could have serious consequences due to the small amount of resources available.
It's easy to blame these consequences solely on AI, but the underlying problem is weak (and many would argue corrupt) regulations and laws (not to mention responsible politicians) that make it cheaper for companies to harm the environment than to work on sustainability.
In fact, AI (and data centers in general) don't need to use water for cooling, and it can be carbon neutral—it just costs more, which reduces profits.
Can data centers go green?
There is now a race to create new GPU farms wherever possible, which is predicted to lead to triple local energy demand by 2035. Avoiding the negative consequences of this increase is not unknown or even difficult—it is a well-understood engineering challenge.
The key points are things like better network planning so power-hungry data centers don't outgrow their local resources, options like dense but efficient water cooled racks which waste less energy as heat, and regulations/incentives that mean it is more profitable for companies to use renewable energy and rely less on local resources such as water.
Although this is not yet enough, this greener approach is already being implemented. Google he has something of an on-again, off-again relationship with the mantra “Don't be evil,” but the company reports 66% of electricity from renewable sourcesand with offsets it reaches 100%. Google is also experimenting with campuses located near wind and solar power plants.
But now these greener approaches are (mostly) not being implemented out of the kindness of the company's heart – it's because if the network can't keep up AI's growing energy needs future profits may be lost.
And just because they try something doesn't mean they'll stick with it – Microsoft cancels Project Natick undersea data center test despite its success.
The missing step continues to be government regulations and incentives. If done correctly, it's quite reasonable balance data center growth with environmental responsibility and avoid any negative impact on the area.
And despite political oppositionRenewable energy production continues to grow remarkably quickly and is expected to be more than enough to meet new demand (including from AI) over the rest of the decade.
Data centers can also help locally, and waste heat can be a valuable public asset for heating houses and even greenhouses.
What's next?
A sustainable future for AI also involves using this technology to reduce emissions faster than they increase. This could involve training energy-intensive models in regions where green energy is abundant, and then using AI to operate in a way that can help. strengthen and improve existing efforts to reduce environmental impact.
This also means more discussion about the real impact of data centers: right now AI companies rarely talk in detail about energy use even how data centers are quietly becoming a much larger part of global emissions and big players love Google uses more energy every year – and not only for AI.
It's not as simple as spending more money on high-tech solutions, and balancing costs and reducing climate impact is an important and subtle point in the era of artificial intelligence in data infrastructure.
However, AI data centers can be built in areas and in ways that support the local community, but only with appropriate regulations and infrastructure upgrades.
And yes, AI as a technology can have many problematic consequences, but it is also just a sudden new growth that has exposed existing ones. imperfect regulations and energy systems. But recognizing and discussing these underlying issues means we can better focus on creating a truly sustainable future for artificial intelligence.
Conclusion
The point is that one AI tip (or even hundreds) only a small part of daily use by most peopleand small compared to luxuries such as television, games, and even Christmas lights.
On a global scale, The use of AI power is large enough to warrant attention.but it's still only a small part of the collective race to see whether technology will save us from ourselves or simply provide a more interesting apocalypse.
Of course, you don't have to just sit back and wait to see how it all turns out. Take matters into your own hands and compensation of CO2 emissions resulting from the use of artificial intelligence is a rounding error on the already surprisingly low cost of achieving carbon neutrality.
In fact, offsetting all my personal carbon emissions for a year starts at about the same cost as a ChatGPT Plus subscription.
So keep calm, count the kilowatts and focus on where the big benefits lie: just remember to turn off the bathroom light before bed and you'll get 250 guilt-free AI tips.
Don't get me wrong, AI is mired in problems and controlled by problematic people and companies, but the doom and gloom isn't because of electricity use. For the most part.
Not sure AI can go green? Let me know which plan you think is better in the comments!
Artificial Intelligence Skeptics May Also Like
Artificial Intelligence lovers may also like
How we use AI
Here at TechRadar, our coverage is provided by contributors. AI helps with sourcing, research, fact checking, and spelling and grammar recommendations. The person still checks every figure, source and word before anything comes out. Sometimes we use it for important work, like adding dinosaurs to co-workers' photos. See our full list Page of the future and artificial intelligence.
