This column will take you five minutes, according to the New York Times website, which now posts an estimated reading time for articles on its home page. You can easily finish it while waiting for your DoorDash, which will arrive in 12 minutes, shortly after your laundry cycle ends in — check the app — seven minutes.
Or this column will take 50 minutes because your kid will text you midway through reading it and you’ll mindlessly toggle to another tab on your browser, then remember the email you were supposed to send first thing this morning. You’ll stop to collect the DoorDash, which didn’t actually come in 12 minutes but instead materialized in 22, just as you’d settled into a Zoom meeting. The laundry, on the other hand, will be ready in 12 minutes.
In a world where everything has a time stamp, everything is still somehow off-kilter.
That the pandemic completely warped our sense of time, leaving us with what feels like a collective case of dyschronometria, has been well documented. Figuring out when something happened has become a kind of a funhouse-mirror guessing game: Did we go to Florida one year ago or three? How long has that blue sofa been there? What happened to eighth grade?
While the specific distortion of pandemic time has passed — at least for now — time still does not seem to be moving forward at a predictable clip. The weather is wonky, disrupting the regular rhythm of the seasons. The workplace is still in flux, blurring the lines between labor time and leisure time. It is harder and harder to tell when we are in the middle of a thing and when the thing is definitively over. As Jenny Odell notes in her recent book “Saving Time,” we are increasingly marked by “a deep suspicion that we are living on the wrong clock.”
All we really want to know is, How much time will this take? When will it be over? And where the hell is my Uber already?
Our digital devices are supposedly here to help. They come with numerical capabilities that far exceed our own. We rely on them. But when each unit of measurement is conspicuously displayed — from the increasing temperature on your preheating oven to the outdoor temperature displayed on your indoor phone — even the slightest mathematical infraction can qualify as a major upset.
And our devices aren’t above lying to us. They may think we don’t notice — and maybe we don’t! We are simultaneously impatient and distracted. We haven’t been counting because the machines have been counting for us — down to the hundredth of a second. We’re already in the middle of a download of that new operating system that just inexplicably leapfrogged from 43 minutes back up to 54 and it’s too late to abort now. The algorithm is too strong for us.
Our meal delivery and ride share apps mess around with us all the time. Take that Uber. On some level, you know it’s not actually coming in two minutes. If you’re lucky, it will be here in five. But that time estimate may keep you hostage in a holding pattern so that you don’t switch over to Lyft or hail a taxi. Uber may consider this part of its “magical customer experience,” but what it can feel like to those of us with mere human intelligence is an app trap. Someone behind that math wall is presumably betting against your giving up and turning to a competitor’s “two minutes.”
The Kindle plays its own number games, offering an average estimated reading time. But that’s for the average reader — who is not necessarily you. Once it homes in on your particular blend of distractedness, the algorithm will adjust these times to what it perceives as your rate of progress. “Within two pages, my Kindle had become increasingly unimpressed with me,” one reader noted on Alphr, a British technology site. “It promptly added 24 minutes to my reading time, like a spurned satnav irritated with me for trying my special alternative route.” Other readers may witness unexpected leaps in the estimate, sometimes from checking out a footnote or flipping around in the book, forward and backward appraisals that make them feel like either a slowpoke or a “superhuman librarian.”
Hold on just a minute — or two — there, HAL.
Does this mean we’re being gaslit by our own technology? Are the machines and devices and digital authorities that are supposed to help us by providing estimated wait times, minutes until completion and expected arrival times deliberately giving us the wrong answers?
If so, they might only be following human orders. People have long manipulated time estimates. Passengers are regularly told their airline flight will take longer than anticipated — only to arrive agreeably “early,” even after a late departure. In 1986, for example, the estimated flying time for an American Airlines flight between Kennedy Airport in New York and Los Angeles Airport was about five hours 30 minutes. Today, the estimated flying time for the same flight averages around six hours 23 minutes. That’s not because planes are flying more slowly but because airlines calculate the flying times based on other variables — largely to improve their on-time arrival statistics, which the Department of Transportation began requiring in 1987 and are now posted online. This is referred to in the industry as schedule padding.
“It is definitely a marketing thing,” Robert W. Mann, an airline consultant and former airline executive, told me. “The results generate a preference for the airline.”
Fudged time can help make people feel better — or worse. Anyone who has been a restaurant hostess knows that there’s a standard lie you feed to waiting diners, whether it’s the eternal “15 minutes” (to keep them waiting) or “at least an hour and a half” (to make them leave), depending on what message you’re trying to impart. Recipe app designers, same thing: Sure, the summer farro salad will take you just 30 minutes to prepare — assuming you have the knife skills of a sous chef. Half an hour in, the farro may be only half cooked, but you’re on hold with the health insurance company, whose automated attendant promises there are only three people ahead of you. At least you are multitasking!
With the digital world becoming ever more artificially clever, perhaps it will start playing nicer with us. Is that too much to hope? We would like to trust in the machine, especially now that we are now engineered by machines at least as much as we are engineering them. I, for one, would like to believe you arrived at this sentence in exactly five minutes.
Discussion about this post