I’m not usually one to freak out about kids and technology use, but Bruce Feiler makes some interesting points in Hey, Kids, Look at Me When We’re Talking:

Dr. [Clifford Nass, a communication professor at Stanford University] told me about research he was doing that suggested young people were spending so much time looking into screens that they were losing the ability to read nonverbal communications and learn other skills necessary for one-on-one interactions. As a dorm supervisor, he connected this development with a host of popular trends among young people, from increased social anxiety to group dating.

That’s pretty alarming.

In The Machines Are Coming, Zeynep Tufekci talks about the kind of tasks that are being automated by machines:

Today, machines can process regular spoken language and not only recognize human faces, but also read their expressions. They can classify personality types, and have started being able to carry out conversations with appropriate emotional tenor.

Machines are getting better than humans at figuring out who to hire, who’s in a mood to pay a little more for that sweater, and who needs a coupon to nudge them toward a sale. In applications around the world, software is being used to predict whether people are lying, how they feel and whom they’ll vote for.

This is not a new topic. Back in 2012, Kevin Kelly proclaimed in Better Than Human: Why Robots Will — And Must — Take Our Jobs:

It may be hard to believe, but before the end of this century, 70 percent of today’s occupations will likewise be replaced by automation.

At the end of last year Claire Cain Miller wrote for the New York Times that As Robots Grow Smarter, American Workers Struggle to Keep Up:

Although fears that technology will displace jobs are at least as old as the Luddites, there are signs that this time may really be different. The technological breakthroughs of recent years — allowing machines to mimic the human mind — are enabling machines to do knowledge jobs and service jobs, in addition to factory and clerical work.

Who knows if this fear is going to turn into reality or not — there are lots of counter-arguments as well (For example, Nicholas Carr has a really interesting historical perspective in Should the Laborer Fear Machines?).

Still, I find the discussion fascinating — especially as it relates to the balance of power in workplaces. Tufekci continues:

Machines aren’t used because they perform some tasks that much better than humans, but because, in many cases, they do a “good enough” job while also being cheaper, more predictable and easier to control than quirky, pesky humans. Technology in the workplace is as much about power and control as it is about productivity and efficiency. […]

This is the way technology is being used in many workplaces: to reduce the power of humans, and employers’ dependency on them, whether by replacing, displacing or surveilling them.

Maybe that’s the real cause for concern here. Not that jobs might go away (although that’s certainly worrisome too), but that power will continue to shift to employers and away from employees.

Benedict Evans wrote a characteristically brilliant analysis in What does Google need on mobile? Here’s a taste of his conclusion about Google’s challenge going forward:

The key change in all of this, I think, is that Google has gone from a world of almost perfect clarity—a text search box, a web-link index, a middle-class family’s home—to one of perfect complexity—every possible kind of user, device, access and data type. It’s gone from a firehose to a rain storm. But on the other hand, no-one knows water like Google. No-one else has the same lead in building understanding of how to deal with this. Hence, I think, one should think of every app, service, drive and platform from Google not so much as channels that might conflict but as varying end-points to a unified underlying strategy, which one might characterize as ‘know a lot about how to know a lot’.

Don’t miss this article, the whole thing is great.

I’m a long-time Pinboard fan, and from the moment I became a paid user I couldn’t shake the feeling that it is one of the most underrated services out there. It’s basically the center of my personal internet. I have years of articles tagged and cached, and available immediately whenever I need to remember something. For me, it represents the best of what technology has to offer as an “external brain”1.

But it’s even more powerful than that. I recently started wondering if Pinboard could become more central in my blogging workflow as well. My flow when I find an article I want to write about used to be two steps: (1) save to Pinboard, and then (2) start a new text file (with an excerpt from the article) and start writing.

Since I don’t always have time to write immediately after I read something, the disjointedness of these two steps means that I forget to post articles sometimes — or that I can’t remember which part I want to write about. So I needed a way to save Pinboard links for later, in a way that lets me pick up writing whenever I have time.

The solution I came up with isn’t rocket science, but it has made such a big difference to the way I write that I wanted to share it here. The key is a simple IFTTT recipe that takes any new link I save to Pinboard and creates a Markdown-formatted text file that I can use to start writing whenever I want to.

Here is a link to the IFTTT recipe: Post any new Pinboard link to a new text file in Dropbox.

And this is what it does:

I always put a pull quote in the “Description” field when I save a Pinboard link, so the recipe creates a text note with a Markdown-formatted URL, the pull quote, and space for me to add a title, slug, and excerpt once I’m ready to post to the site. Putting the note in a Dropbox folder means I can continue typing and editing on any device — I use Editorial on iOS and nvALT on Mac.

As for posting… I still haven’t found a mobile blogging platform that works for me, so even though I write many posts on my iPhone or iPad, I still post exclusively from MarsEdit. So I also went one step further and made a Keyboard Maestro macro (download here) that transfers the text from nvALT to MarsEdit as soon as I’m ready to post.

You know, the internet is pretty cool sometimes.

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1. Clive Thompson discusses the idea of external memory in detail in his excellent book Smarter Than You Think. ↩

Interesting thoughts from Steven Levy in What the Apple Watch Means for The Age of Notifications:

Done right, notifications are a wonderful Feed of Feeds, weeding out the stuff you really need to see from all the usual chaff in the stream.

But it’s hard to do this right when every single app wants to send you notifications. Even given that the system will limit itself to notices worthy of instant notice there are just too many notifications elbowing their way into what should be a narrow passage labeled, “Stuff I absolutely need to see.”

This decreases the value of all notifications.

Gmail has tried, but no one has really figured out the algorithms required to figure out what qualifies as “Stuff I absolutely need to see.” This is the holy grail of notifications at the moment.

Jason Kottke wrote what I guess can be described as a review of Apple Watch reviews. He makes a particularly interesting point about the common assertion that we’ll start using our phones less because of the watch. From Apple Watch and the induced demand of communication:

In the entire history of the world, if you make it easier for people to do something compelling, people don’t do that thing less: they’ll do it more. If you give people more food, they eat it. If you make it easier to get credit, people will use it. If you add another two lanes to a traffic-clogged highway, you get a larger traffic-clogged highway. And if you put a device on their wrist that makes it easier to communicate with friends, guess what? They’re going to use the shit out of it, potentially way more than they ever used their phones.

He also quotes from the same article I had a visceral reaction to in The Apple Watch won’t save you time. In that article I made a similar point:

I’m not saying the Apple Watch won’t be wildly successful, or that I don’t want one — I definitely want one. I just don’t think we should fool ourselves into thinking it will somehow give us more time because we might look at our phones less. If history teaches us anything, it’s that we’ll find a way for the watch to fill up our “saved” time in other ways — and then some.

Judy Wajcman’s Who’s to blame for the digital time deficit? starts off like many similar articles as she ponders the role smart phones play in making us feel time-starved. But then she takes an unexpected and well-reasoned turn:

If technology is going to contribute to a better world, people must think about the world in which they want to live. Put simply, it means thinking about social problems first and then thinking of technological solutions, rather than inventing technologies and trying to find problems they might solve.

We can’t do this while the people who design our technology and decide what is made are so unrepresentative of society. The most powerful companies in the world today—such as Microsoft, Apple and Google—are basically engineering companies and, whether in the US or Japan, they employ few women, minorities or people over 40. […] Such skewed organisational demographics inevitably influence the kind of technology produced.

And later on:

If we want technology to bring us a better future, we must contest the imperative of speed and democratise engineering. We must bring more imagination to the field of technological innovation. Most of all, we must ask bigger questions about what kind of society we want. Technology will follow, as it usually does.

Tim Harford has an excellent critique of the statistical issues with the “big data” trend in Big data: are we making a big mistake? First, there’s this:

But the “big data” that interests many companies is what we might call “found data”, the digital exhaust of web searches, credit card payments and mobiles pinging the nearest phone mast.

I still love the term “digital exhaust”. I first saw Frank Chimero use it in the context of social media when he said (in a post that’s now gone from the internet):

The less engaged I become with social media, the more it begins to feel like huffing the exhaust of other people’s digital lives.

But back to big data. The big problem (see what I did there?) is that statistical problems don’t just go away when you have more data. In fact, they get worse. For example:

Because found data sets are so messy, it can be hard to figure out what biases lurk inside them – and because they are so large, some analysts seem to have decided the sampling problem isn’t worth worrying about. It is.

The article goes into the detail on this, and I think it’s important for us to recognize the limitations of big data before jumping on the bandwagon.

Dave Pell—in the context of Facebook’s plan to host news sites’ content natively—explains what tech people are good at (and usually not good at) in Don’t Take a Flying Leap:

But building a really successful app or site does not mean you know more about education than educators. Disrupting the photo-sharing space does not qualify you to disrupt higher education. Or to understand the health system better than doctors. Or to understand the woes of urban poverty better than those who have spent a career on those corners. […]

This is not the time to give up and it’s not the time to give in to one of the most prevalent myths of the era: that people who can build technology know how to run your business better than you do.

Virginia Heffernan’s A Sucker Is Optimized Every Minute is a deeply cynical, extremely funny rant on our obsession with data:

These days, optimizers of squeeze pages, drawing lessons as much from the labcoats at Optimizely as from the big daddies at Google, recommend creating a three-to-10 minute video that’s introduced by a “magnetic headline” (“Find the Perfect Lampshade for Any Lamp”) and quickly chase it with an “information gap” like “You’re Not Going to Believe the Trick I Use While Lampshade Shopping.” (Article of faith among optimizers: humans find information gaps intolerable and will move heaven and earth to close them.) Next you get specific: “Click the play button to see me do my lampshade trick!” — after which the video unspools, only to stall at the midpoint with a virtual tollbooth. You can’t go on unless you hand over an email address. Presto.

A sucker is optimized every minute.