Ode to a Microinteraction: Amazon Kindle’s “Time to Read”

Dan Saffer
4 min readJan 14, 2015

Allan Chochinov, a design professor at SVA, used to have his students do an unusual project: design a solution for picking up dog poop. He called it the Dumbest Smartest Design Problem. One of the purposes of the exercise was this: if you’re going to compete against an existing product in the marketplace, you’ve got to be better in some way. Any solution to the Dumbest Smartest Design Problem had to “Beat The Bag,” meaning it had to be better (more efficient, more effective, less gross, etc.) than just using a plastic bag to pick up dog poop.

As someone whose job it’s been over the last few years to try to replace ordinary objects with “smart” ones or dissolve them into apps, I think about Beat The Bag a lot. Although many companies have tried to do just this, it’s not enough just to connect an appliance or household device to the internet and hope people buy it. It’s gotta Beat The Bag over what they already have and use. Which brings us to Time to Read.

When Amazon launched Kindle in 2007, its value proposition was this: you can have 200 books in the palm of your hand, delivered automatically. It’s still true today, except now you can hold thousands of books on a Kindle, plus improvements like Paperwhite and a backlight. Paperwhite, a high-resolution e-ink display on a white background, is an attempt to reach parity with paper book features, namely high-resolution display on a white background. Backlight, allowing for reading in dim light, is really another parity feature, this time against the iPad, not paper books.

In 2012, with the Kindle Paperwhite, Amazon introduced a real Beat The Bag microinteraction: Time to Read. (It eventually made its way into the Kindle apps as well.) Amazon for a long time had been trying to figure out to replicate the feel of a physical book, its weight and heft. Saying you were in Loc 23 of 2345 or 1% done doesn’t tell you very much, or give you much indication of what kind of commitment you’re in by reading it. Enter Time to Read. Time to Read tells you how much time you have left in a book or a chapter. It’s an excellent example of the design principle Bring The Data Forward: what piece of information is hidden inside your application that is potentially very useful to its users? With Time to Read that information is About how long is it going to take me to read this book (or this chapter)?

But the magic is really in the me part of that last sentence. About how long is it going to take me to read this book? Unlike other (dumber) algorithms that simply convert every 200 words into 1 minute of reading time, Time to Read watches your personal reading speed and adjusts accordingly. It’s a human-powered progress bar.

This Beats The Bag hands down. While I can look at the paper book of, say Infinite Jest and think, wow, that’s going to take me a long time to read (two months, as it turned out), I’d never really have an accurate idea of how long it would really take me. It’s a piece of the quantified self, but the data has real value. Importantly, it has meaning not just as a recording of what you did (I walked 5489 steps today!) but so you can make adjustments as you’re doing the activity. It’s real-time feedback that allows you to make decisions, in much the same way that many video games have indicators of health or score or some other resource that needs to be managed. Here, you’re managing your time. Do I want to finish this chapter before bed? Oh, it’ll only take me 2 more minutes, so sure.

It’s not perfect. Sometimes the algorithm can be thrown off by simply setting the Kindle down for a while. Sharing a Kindle will also change the data. But most of the time, it’s a close enough estimate to be useful. The algorithm is the design.

I’d love to see this data make it’s way back to the Amazon site, so that in the details of the book I’m considering purchasing it’ll show how long it’ll likely take me to read. The information might influence my buying decision. It would also be interesting to know (and I’m not sure if the nuance is there in the algorithm or in the reporting here) what kind of books take me the longest to read. I can guess that a page-turner (thus the name) will take me less time than a dry academic book, but by how much? Hardcore readers might make use of this kind of data, knowing, for one example, how many books they need to download for their vacation.

As more and more of our objects start to become connected or app-ified, we have to consider what value making something digital really brings. Connected objects can tell us things about ourselves we never knew — and maybe never even knew to ask about — like how fast am I reading. And that data can change the decisions we make and thus change how we live and work and think about ourselves.

And maybe even help us pick up dog poop better.