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⌥ Stories Told About Data Centres

By: Nick Heer

Nathaniel Rich, author of the novel “Cloudthief”, in a non-fiction retelling for New York Times Magazine of a 2007 heist of a London data centre by Terry Ellis and others:

The fixer — Ellis called him Ray and won’t reveal his name — met him in North London near Hampstead Heath for coffee and cakes. When it came time to discuss business, to avoid being overheard, they strolled into the park.

Ray had brought Ellis a few jobs before. But this job, he warned, was of an entirely different order. As Ellis claims in “The Art of Robbery,” a self-published memoir written after his release from prison, he eventually learned that Ray had been contacted by a consultant employed by “some influential bankers from America.” The bankers “were involved in prime mortgages” and had “circumnavigated” certain regulations. Damning evidence of these circumnavigations could be found in banking files held in the King’s Cross area in a giant building known as a data center.

This is a dramatic story, and one I think should be read with a heavy dose of skepticism. It seems that most of the criminal details have been shared by Ellis. For a start, the claim that some bankers ostensibly contracted with “Ray” is just a little too perfect for a recession-era tale. These bankers are pretty much universally loathed, and this justification makes this theft seem more palatable than a simple financial motive. For example, there was a similar data centre theft in October 2006, which would be unrelated to the lending crisis in the following years.

Another problem is that Rich says crimes like these are covered-up in part by a data centre operator because they are loathe to “admit to flaws in its security, [which] would only encourage additional attacks and scare away its clients”. Therefore, the lack of evidence for the specific circumstances of this crime is supposed to be a buttress for its likelihood, not a weakness, which is not reassuring.

The story of the theft was, as far as I can tell, broken by Here is the City, then a gossipy financial news site:

The data center itself is thought to be used by a number of companies, including JPMorgan, which is believed to have told staff that some of its systems could be off-line for parts of the day today as a result of the theft. Fortunately the thieves are thought to have got away with just the computer hardware, and not any sensitive information which may also have been stored at the facility.

Tom Espiner, of ZDNet, a few days later:

Reports circulating on the Internet last week that JPMorgan, a customer of Verizon Business, had been affected by the burglary were incorrect, according to a source at the investment bank. There has been no loss of service or data, said the source.

On the one hand, of course all these parties tried to cover this up. The reading-between-the-lines story implied by these early reports and Rich’s telling is that some banking higher-ups, perhaps from JPMorgan, wanted to cover up some crimes, and denying any meaningful effect is just more cover-up. But little of this is substantiated by contemporary or current reporting — which is, of course, the whole problem with using a lack of evidence as the foundation for a story.

Rich, in the Times:

“The banks knew they were sending mortgages to people who couldn’t pay back,” he says today. “That’s what broke the whole system. That was the big con.” Ellis remains convinced that the bankers who paid for the Verizon job wanted to destroy evidence of their involvement in fraudulent subprime mortgages — the inside information that Ellis received about the data center, he believes, “would have had to come from the top” — but he can’t prove it. He never saw what was on the servers.

“Our job was to get the motherboards,” he says. “We were paid quite handsomely. Whatever happened after that was none of our concern.”

In contemporaneous reports, the Metropolitan Police noted the theft of motherboards and processors. But if these bankers wanted to cover up their fraudulent practices, surely the hard drives would have been the target, right? In Rich’s version, entire servers were taken, so perhaps this is just a misunderstanding.

This story smells fishy. I believe the theft happened, of course, and Ellis’ involvement, but I am not as convinced this had anything to do with covering up some white collar crime. (By the way, the Guardian in 2018 published an interview with Ellis about the interesting prison where he was transferred and which led to his rehabilitation.)

The heist element is only about half of Rich’s story; much of it is a discussion about data centre secrecy:

The public fogginess about data centers is not an accident. It is the product of a willful strategy by the world’s largest tech corporations, whose business models rest on the public assumption that the internet, and all the data it holds, is as immaterial as air — or as a cloud, to borrow the metaphor commonly used to describe the sum of information stored on servers. As the digital-media scholar Tung-Hui Hu writes in “A Prehistory of the Cloud,” the cloud “hides its physical location by design.”

[…]

It was a lot easier to defend data when people didn’t know it existed. The more people learn about data centers, the more they hate them. […]

If you read a website like this one, you were probably aware that data centres were commonplace twenty or more years ago. Like the one near King’s Cross, some were hidden in plain sight, while others were purpose-built facilities that look like hangars stuffed with servers. But the A.I. boom has meant rapid increases in the speed, scale, and quantity of data centres. People quickly learned not only of their existence, but how much pressure they put on local resources. Tech companies, it seemed, were caught by surprise; and as someone who spends a lot of time immersed in this world, so was I.

Much of the consternation I have seen in more general audiences has been about data centres in general. People simply were not aware that Amazon has warehouses full of products, and other warehouses full of computers. As Rich writes, this is deliberate, for business secrecy reasons, security, and environmental costs. But, also, I think some of that unawareness is because of just how boring it is. If nobody wants to know hidden information, is it really a secret? It only became one when the information these companies were hiding had real-life effects.

It does seem that public awareness is putting pressure on corporations to improve data centres and make them more efficient. But that is not a standard. New data centres are powered by petroleum with a pinky promise of renewable offsets. In some regressive regions, like Alberta, new power plants for data centres must be powered by methane gas. In a further complication, Meta’s proposed data centre is scheduled to be completed before the power plant is ready, meaning it will be dependent on existing grid power for perhaps years. Meta’s is just one of the data centres proposed for Alberta. Another one, a gigawatt cluster, would also require a dedicated gas-fired power plant, while Kevin O’Leary’s questionable project is supposed to require over three times the combined power of those other two.

For years, the tech industry told us we did not need to have much concern for how digital products and services worked, and many of us did not bother to find out. But it turns out the demands of our email and Netflix subscription were comparatively easy to hide. At the very least, what we ought to demand from projects with the scale and ambition of these data centres is open disclosure of their power consumption, water use, and emissions.

But we ought to demand more than the bare minimum. Transparency does as much good as a big banner reading we are destroying the planet but we are also creating a lot of value for shareholders. When a single data centre is projected to use about as much power as the entire city of Calgary is currently — Enmax says 1,260 megawatts as of writing — we should have a say in whether that makes sense. A.I. remains a thing that is happening to us rather than with or for us. It is built on assuming consent and asking forgiveness, which has more-or-less worked for the industry and gave it way too much confidence. Tech companies could have spent decades being better corporate citizens. Data centres are just one part, but they are representative of the difference between the stories told by tech companies and the things we can actually know.

The Carbon Footprint Sham

By: Nick Heer

Thinking about the energy “footprint” of artificial intelligence products makes it a good time to re-link to Mark Kaufman’s excellent 2020 Mashable article in which he explores the idea of a carbon footprint:

The genius of the “carbon footprint” is that it gives us something to ostensibly do about the climate problem. No ordinary person can slash 1 billion tons of carbon dioxide emissions. But we can toss a plastic bottle into a recycling bin, carpool to work, or eat fewer cheeseburgers. “Psychologically we’re not built for big global transformations,” said John Cook, a cognitive scientist at the Center for Climate Change Communication at George Mason University. “It’s hard to wrap our head around it.”

Ogilvy & Mather, the marketers hired by British Petroleum, wove the overwhelming challenges inherent in transforming the dominant global energy system with manipulative tactics that made something intangible (carbon dioxide and methane — both potent greenhouse gases — are invisible), tangible. A footprint. Your footprint.

The framing of most of the A.I. articles I have seen thankfully shies away from ascribing individual blame; instead, they point to systemic flaws. This is preferable, but it still does little at the scale of electricity generation worldwide.

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The Energy Footprint of A.I.

By: Nick Heer

Casey Crownhart, MIT Technology Review:

Today, new analysis by MIT Technology Review provides an unprecedented and comprehensive look at how much energy the AI industry uses — down to a single query — to trace where its carbon footprint stands now, and where it’s headed, as AI barrels towards billions of daily users.

We spoke to two dozen experts measuring AI’s energy demands, evaluated different AI models and prompts, pored over hundreds of pages of projections and reports, and questioned top AI model makers about their plans. Ultimately, we found that the common understanding of AI’s energy consumption is full of holes.

This robust story comes on the heels of a series of other discussions about how much energy is used by A.I. products and services. Last month, for example, Andy Masley published a comparison of using ChatGPT against other common activities. The Economist ran another, and similar articles have been published before. As far as I can tell, they all come down to the same general conclusion: training A.I. models is energy-intensive, using A.I. products is not, lots of things we do online and offline have a greater impact on the environment, and the current energy use of A.I. is the lowest it will be from now on.

There are lots of good reasons to critique artificial intelligence. I am not sure its environmental impact is a particularly strong one; I think the true energy footprint of tech companies, of which A.I. is one part, is more relevant. Even more pressing, however, is our need to electrify our world as much as we can, and that will require a better and cleaner grid.

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A.I. Pins Returned to Humane Cannot Be Refurbished

By: Nick Heer

Kylie Robinson, of the Verge, obtained internal sales data from Humane. Not only is the A.I. Pin not selling super well, but many of them are being returned. That is a huge frustration, I imagine, for lots of people who worked on this product. Also, maybe it is simply an indicator it is not very good: for its own reasons, and also perhaps because it is hard to start a new platform, and maybe because integrating with established platforms is often a struggle.

That is what everyone is talking about. I wanted to highlight a different part of Robinson’s thorough report:

Once a Humane Pin is returned, the company has no way to refurbish it, sources with knowledge of the return process confirmed. The Pin becomes e-waste, and Humane doesn’t have the opportunity to reclaim the revenue by selling it again. The core issue is that there is a T-Mobile limitation that makes it impossible (for now) for Humane to reassign a Pin to a new user once it’s been assigned to someone. One source said they don’t believe Humane has disposed of the old Pins because “they’re still hopeful they can solve this problem eventually.” T-Mobile declined to comment and referred us to Humane.

It is inexcusable for a device to be launched in 2024 without considering the environmental effects of its disposal. Perhaps Humane can recover some of the hardware components for reuse or recycling — this is unclear to me — but for a product to be useful only to its original owner is terrible, even for its first generation.

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How Shein and Temu Snuck Up on Amazon

By: Nick Heer

Louise Matsakis, Big Technology:

Shein and Temu’s users aren’t just browsing. Shein reportedly earned roughly $45 billion last year, and is currently trying to go public. PDD Holdings, Temu’s Chinese parent company, reported earlier this week that its revenue surged more than 130% in the first quarter. PDD is now the most valuable e-commerce company in China.

The two startups are sending so many orders from China to the US that it’s causing air cargo rates to spike, and USPS workers have said publicly that they are overwhelmed by the sheer volume of Temu’s signature bright orange packages they have to deliver. “I’m tired of this Temu shit, ya’ll killing me,” one mailman said in a TikTok video last year with over two million likes. “Everyday it’s Temu, Temu, Temu — I’m Temu tired.”

You might recognize how both Shein and Temu grew using the same tactic as TikTok: relentless advertising. (Which is something Snap CEO Evan Spiegel complained about despite TikTok’s huge spending on Snapchat.)

Both these companies are an aggressive distillation of plentiful supply and low cost to buyers. For people with lower incomes or who are economically stressed, the extreme affordability they offer can be a lifeline. Not everybody who shops with either fits that description; Matsakis cites a UBS report finding an average Shein customer earns $65,000 per year and spends more than $100 per month on clothes. But there are surely plenty of people who shop on both sites — and Amazon — because they simply cannot afford to buy anywhere else.

Every time I think about these retailers, I cannot shake a pervasive sadness. Saddened by how some people in rich countries have been compromised so much they rely on stores they may have moral qualms with. Saddened by the ripple effect of exploitation. Saddened by the environmental cost of producing, shipping, and disposing of these often brittle products — a wasteful exercise for many customers who can afford longer-lasting goods, and the many people who cannot.

Derek Guy has written about the brutality of the garment industry in the U.S., but notes how clearly different these fast and ultra-fast fashion brands are from inexpensive clothing:

Given the opacity in the supply chain, your best single measure for whether something is amiss is price. If you are paying $5 for a cut-and-sewn shirt, something bad is happening. Does this mean that every expensive shirt was ethically made? No. But you know the $5 shirt is bad.

Guy also wrote about the difference between cheap and fast fashion.

This whole industry bums me out because I try to appreciate clothing and fashion. I like finding things I like, dressing a particular way, and putting some effort into how I present myself. Yet every peek behind the curtain is a mountain of waste and abuse, and the worst offenders are companies like Shein and Temu — and, for what it is worth, AliExpress and facilitators like Amazon.

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