We’ve never had more data and yet we’ve never had less information architecture skill. Organizations don’t want to invest in the hard and vital work of professionally organizing and managing data. AI is making things worse because it is feeding the idea that humans no longer need to worry about how we create and organize our data—that AI will look after all that. It won’t. It is making things much worse because AI is a great big lying, great big crap-producing machine.

Teachers are finding that students, brought up on Google search, don’t even know what the concept of a file is, let alone where it is saved or how to organize it in a classification hierarchy with other files. To the Google generation, “the concept of file folders and directories, essential to previous generations’ understanding of computers, is gibberish to many modern students,” one professor stated.

Archiving data can significantly reduce overall data pollution because the most important decision in archiving is what not to keep. Bob Clark, director of archives at the US Rockefeller Archive Center, has stated that less than 5% of stuff is worth saving in any situation, while a representative from Library and Archives Canada told me that only 1% to 3% of information in any department has archival or historical value. And yet archiving is not worth the effort, according to most managers.

“Don’t make me think” has been a mantra of modern design and user experience. This philosophy is equally pervasive when it comes to technology in general. Buy this technology, the pitch goes, it does the thinking for you, it does the hard work for you. And it’s always on, always available. Store everything and no matter what time of day or night it is, you can get exactly what you want instantly. In the data center industry, they call it 99.99% uptime. It comes at the same cost to the environment as making silicon 99.99% pure. Huge costs. Massive costs.

In a typical data center, “only 6 to 12 percent of energy consumed is devoted to active computational processes,” Steven Gonzalez Monserrate has estimated. “The remainder is allocated to cooling and maintaining chains upon chains of redundant fail-safes to prevent costly downtime.” Perhaps this has changed somewhat because of the voracious processing demand from AI. However, the basic point remains true. Guaranteeing your convenience, and your access to all that crap data you’re never going to look at again, costs 90% more mining, 90% more materials, 90% more electricity, 90% more water, 90% more waste. All so that you can potentially access that photo or file that there is a 99.99% chance you will never access. A data center is like before the start of an Formula 1 race. All these high-performance, energy-intense cars revving and revving for a race most of them will never run. Here we are. This is us. This is civilization, modernity, progress, innovation. Spending so much energy to create and store crap.