Artificial Intelligence and Sustainability: The Great Green Paradox

In the grand parade of corporate hypocrisy, few things shine as brightly as the marriage of Artificial Intelligence (AI) and Sustainability.

It’s a match made in heaven, or so the marketing gurus would have us believe.

Picture the scene: sleek tech giants with their shiny logos, strutting down the runway, dressed in the finest buzzwords, “AI-driven innovation,” “sustainable solutions,” “green technology”, all while the audience claps like well-trained seals, oblivious to the power-hungry beast lurking behind the curtain.

Yes, AI is here to save the planet, apparently. But before we get carried away with the fanfare, let’s take a moment to consider the irony of it all.

AI: The Power-Hungry Hero?

Let’s start with the basics, shall we?

AI, the darling of the tech world, is being hailed as the solution to all our environmental woes. It’s like the Swiss Army knife of sustainability: predictive analytics, smart grids, energy optimisation, you name it, AI can do it.

Corporations are tripping over themselves to tell us how their AI-powered solutions will usher in a new era of green living, where carbon footprints are as light as a feather and the planet is saved from the brink of disaster.

But here’s the kicker: AI itself is about as eco-friendly as a coal-fire power station.

Yes, you heard that right!

While the tech moguls are busy patting themselves on the back for their “green” innovations, the reality is that AI requires an obscene amount of computational power. And that power doesn’t come from some magical, sustainable source; it comes from data centres that consume electricity at rates that would make even the most profligate energy hog blush.

Think of AI as the tech equivalent of a sports car. Sure, it’s fast, it’s sleek, and it gets you where you want to go in record time. But it also guzzles fuel like it is going out of fashion, and daily, we are bombarded with the narrative too. Every time you fire up an AI algorithm, you’re essentially feeding it a diet of electricity, and lots of it. Those data centres aren’t exactly running on fairy dust, they’re powered by vast amounts of energy, much of it derived from fossil fuels. So, while we’re busy celebrating AI as the saviour of sustainability, we might want to consider the possibility that we’re simply swapping one environmental problem for another.

The Uncomfortable Truth About AI’s Carbon Footprint

Now, you might be thinking, “Surely, the benefits of AI outweigh the costs, right?”

Well, let’s take a closer look at that, shall we?

The truth is, AI’s carbon footprint is nothing to sneeze at. In fact, training a single AI model can emit as much carbon as five cars over their entire lifetimes. Yes, you read that correctly. Five cars. Over their entire lifetimes. And that’s just for one AI model. Multiply that by the thousands of models being trained every day, and you start to see the problem.

Of course, this inconvenient truth isn’t exactly front and centre in the corporate sustainability reports. No, those reports are all about how AI is revolutionising the energy sector, making everything more efficient, and generally saving the world one algorithm at a time. But the reality is that the energy required to power these AI systems is anything but negligible. And unless we’re getting that energy from 100% renewable sources (spoiler alert: we’re not), then all those AI-powered “sustainability” initiatives are really just adding to the problem.

It’s like trying to lose weight by eating nothing but diet soda and fast food! You might feel like you’re making progress, but you’re really just fooling yourself. AI might be able to optimise energy usage in some areas, but the energy it consumes in the process is a problem that we can’t afford to ignore. And yet, ignore it we do, because, well, it doesn’t quite fit the narrative, does it?

AI and the Echoes of Over-Zealousness

If all this sounds eerily familiar, that’s because it is. Humanity has a long and storied history of rushing headlong into the latest technological fad without stopping to consider the consequences. Remember when asbestos was hailed as a miracle material? Or when leaded petrol was the cutting-edge solution to engine knock? We all know how those stories ended, don’t we? But somehow, we never seem to learn. We’re like a moth to a flame, drawn to the shiny new thing without a thought for the potential downsides.

The current AI craze is just the latest example of this overzealousness. We’re so eager to embrace the promises of AI-driven sustainability that we’re overlooking the very real environmental costs. It’s like we’re sprinting towards the edge of a cliff, blissfully unaware of the drop that awaits us. And when we finally do stop to take stock, it might be too late to turn back.

This headlong rush into AI-powered sustainability is reminiscent of another recent societal obsession: the fervor surrounding woke culture and the ongoing debate over transgender athletes in female sports. Now, don’t get me wrong, there’s nothing inherently wrong with wanting to be progressive or inclusive. But when we start making decisions based on ideology rather than scientific evidence, we’re setting ourselves up for trouble.

Take, for example, the debate over whether transgender women should be allowed to compete in female sports. On the one hand, there’s a strong argument for inclusion and equality. But on the other hand, there’s the uncomfortable reality that biological differences can’t simply be wished away. It’s a complex issue that requires careful consideration and nuanced debate! Yet, much like the AI-sustainability conundrum, there’s a rush to judgment, a tendency to leap before we look.

The result? A debate that’s more divisive than productive, with no clear resolution in sight. And if we’re not careful, we could find ourselves heading down a similar path with AI and sustainability: plunging headfirst into a technological disaster that could have been avoided if only we’d taken the time to ask the right questions.

The Benefits of AI: A Cautionary Tale

Now, before you accuse me of being a Luddite, let me be clear: AI isn’t all bad. In fact, when used thoughtfully and responsibly, it has the potential to bring about significant benefits. AI can optimise energy usage, reduce waste, and help us make better decisions about how we manage our resources. But, and this is a big but, those benefits can only be realised if we approach AI with a healthy dose of skepticism and a willingness to confront the challenges head-on.

Let’s take a closer look at some of the ways AI can actually help us achieve our sustainability goals, if, that is, we’re willing to put in the work.

1. Energy Optimisation: A Double-Edged Sword

One of the most frequently cited benefits of AI is its ability to optimise energy usage. By analysing vast amounts of data, AI systems can identify inefficiencies in power grids, predict energy demand, and even help us transition to renewable energy sources. In theory, this should lead to significant reductions in energy consumption and carbon emissions.

But here’s the catch: the AI systems themselves require a lot of energy to run. It’s a bit like hiring a personal trainer to help you lose weight, only to discover that they’re also making you eat twice as much as before. Sure, you might be getting fitter, but you’re also consuming more resources in the process.

The key, then, is to strike a balance. We need to ensure that the energy savings generated by AI systems outweigh the energy they consume. This means designing AI algorithms that are as energy-efficient as possible and using renewable energy sources to power the data centers where they’re housed. Easier said than done, of course, but it’s a challenge we need to take seriously if we’re to avoid the pitfalls of overzealous AI adoption.

2. Waste Reduction: The Good, the Bad, and the Ugly

AI also holds promise in the realm of waste reduction. From optimising supply chains to predicting equipment failures before they happen, AI can help businesses minimise waste and make better use of their resources. This, in turn, should lead to lower carbon emissions and a more sustainable economy.

But, as with energy optimisation, there’s a darker side to this story. The rapid pace of AI development means that hardware becomes obsolete at an alarming rate. And when old devices are discarded in favour of newer, more powerful models, we’re left with mountains of e-waste that’s difficult, and sometimes impossible to recycle.

It’s the tech equivalent of throwing out your entire wardrobe every season and buying a new one. Sure, you might look stylish, but the environmental cost is staggering. If we’re serious about using AI to reduce waste, we need to address the e-waste problem head-on—by designing hardware that lasts longer, is easier to upgrade, and can be recycled more effectively.

3. Decision-Making: The Devil’s in the Data

Another area where AI can make a significant impact is in decision-making. By analyzing data and identifying patterns that humans might miss, AI can help us make more informed decisions about everything from resource management to urban planning. This should, in theory, lead to more sustainable practices and better outcomes for the environment.

But, and you knew there was going to be a “but”, AI is only as good as the data it’s fed. If that data is flawed, biased, or incomplete, then the decisions made by AI systems will be flawed, biased, and incomplete as well. It’s the classic “garbage in, garbage out” problem, and it’s a real risk in the world of AI-driven sustainability.

The solution?

We need to be vigilant about the quality of the data we’re using and ensure that AI systems are designed to account for biases and uncertainties.

This requires a level of transparency and accountability that’s often lacking in the world of corporate AI development. But if we’re serious about using AI to drive sustainable decision-making, it’s a challenge we can’t afford to ignore.

The Path Forward: Thoughtful Innovation, Not Blind Enthusiasm

So, where does this leave us? On the one hand, AI has the potential to revolutionize the way we approach sustainability. It can help us optimise energy usage, reduce waste, and make better decisions about how we manage our resources. But on the other hand, AI is a power-hungry beast with a significant environmental footprint. And if we’re not careful, we could end up causing more harm than good in our quest for a greener future.

The key, then, is to approach AI with a healthy dose of skepticism and a willingness to ask the hard questions. We need to move beyond the hype and take a clear-eyed look at the environmental costs of AI, and, more importantly, what we can do to mitigate those costs.

1. Prioritise Energy Efficiency

First and foremost, we need to prioritise energy efficiency in AI development. This means designing algorithms that require less computational power and finding ways to make data centers more energy-efficient. It also means transitioning to renewable energy sources wherever possible, so that the electricity used to power AI systems doesn’t come at the expense of the environment.

2. Address the E-Waste Problem

We also need to tackle the e-waste problem head-on. This means designing hardware that lasts longer, is easier to upgrade, and can be recycled more effectively. It also means finding ways to reduce the environmental impact of AI development, whether by using more sustainable materials or by implementing better recycling practices.

3. Ensure Transparency and Accountability

Transparency and accountability are critical when it comes to AI-driven decision-making. We need to be vigilant about the quality of the data we’re using and ensure that AI systems are designed to account for biases and uncertainties. This requires a level of transparency and accountability that’s often lacking in the world of corporate AI development—but it’s a challenge we must meet if we’re serious about using AI to drive sustainable decision-making.

4. Encourage Thoughtful Innovation

Finally, we need to encourage thoughtful innovation in AI development. This means taking the time to consider the potential consequences of new technologies and being willing to ask the hard questions. It also means being open to alternative approaches and recognizing that AI isn’t always the best solution for every problem.

The Final Word: A Cautious Optimism

In the end, the promise of AI in sustainability is a bit like that trendy new superfood that everyone’s raving about. It sounds great in theory, and it might even have some real benefits. But before we jump on the bandwagon, let’s take a moment to consider the facts. Let’s look beyond the hype and the headlines, and make sure that we’re not simply swapping one set of problems for another.

And above all, let’s remember that true sustainability isn’t just about adopting the latest technology or following the latest trend. It’s about making thoughtful, informed choices that balance the needs of the present with the responsibilities of the future. It’s about recognizing that there are no easy answers or quick fixes, and that real progress takes time, effort, and a willingness to confront uncomfortable truths.

So, next time you hear a corporation waxing lyrical about how AI is going to save the planet, take it with a hefty pinch of salt. Remember that for all its potential, AI is not a panacea. It’s a powerful tool, yes, but one that comes with its own set of challenges and risks. And in our rush to embrace the future, let’s not forget the lessons of the past: that overzealousness, whether in technology, social issues, or any other area, rarely leads to good outcomes.

Let’s be realistic about what AI can and cannot do, and let’s make sure that our pursuit of sustainability is grounded in reality, not in wishful thinking or corporate spin. Only then can we hope to build a truly sustainable future—one that’s not just driven by the latest technological fad, but by thoughtful, informed, and responsible decision-making.

After all, as the saying goes, the road to hell is paved with good intentions—and in this case, it’s also littered with discarded servers and mountains of e-waste. So let’s tread carefully, and let’s make sure that our journey towards a sustainable future doesn’t end up taking us somewhere we really don’t want to go.

Minn Tun

September 2024