Poorna Bell’s So Long, FOMO is making the rounds today:

At nearly every restaurant table I saw, there was at least one person (if not most) who spent most of their time taking photos or video to put on Facebook later, or searching for something on the internet, or playing games or just checking for texts. For more and more of us, technology is taking over, invading even our most personal and private of moments.

This idea that technology is turning us into antisocial monkeys is getting pretty old. Putting photos on Facebook helps you connect with others around the experience. Searching for something on the internet helps you move conversations forward (or change direction completely). All these activities are inherently social. Jason Feifer’s impassioned rejection of Sherry Turkle’s doom-and-gloom ideas provides a very good counterargument to all the fear-mongering:

Turkle imagines that any interaction with technology somehow negates all the time spent doing other things. She also imagines that we must devote ourselves in only one way to every task: At a dinner table, we are only serious and focused on conversation; at a memorial service, we are only mournful. That is not the way we live. It’s never been the way we live. And that’s the beauty of technology, which Turkle cannot see: We can use it for all purposes, to express joy and sadness, to have long conversations or send short texts. We made it. It is us.

It’s time for us to realise that we are evolving the way we communicate with each other, and that’s ok. I’m not saying we shouldn’t be mindful about how much time we spend staring at our phones, but we should recognize how much more social our devices are making us. Clive Thompson points this out in his book Smarter Than You Think:

What are the central biases of today’s digital tools? There are many, but I see three big ones that have a huge impact on our cognition. First, they allow for prodigious external memory: smartphones, hard drives, cameras, and sensors routinely record more information than any tool before them. We’re shifting from a stance of rarely recording our ideas and the events of our lives to doing it habitually. Second, today’s tools make it easier for us to find connections—between ideas, pictures, people, bits of news—that were previously invisible. Third, they encourage a superfluity of communication and publishing. This last feature has many surprising effects that are often ill understood.

And we should also remember that it’s not up to us to tell people how to experience the moments that are important to them. As usual, XKCD says it best:

Vijay Sundaram takes the concept of technical debt and applies it to User Experience Design:

You know you’re a subprime borrower when your team decides to “clean this up next release”. But the next release has a backlog of critical bug fixes, must-have feature requests, and of course plenty of new design shortcuts that emerge in the process. What’s more, the usage data for the last release is showing great engagement and no one has complained yet about the shortcuts you took. Fixing those can’t possibly be a priority right now. Before long, the team is grafting one design shortcut onto another, and the only way to unwind them is a wholesale reboot.

The article made me think of Henrik Kniberg’s excellent Good and Bad Technical Debt (and how TDD helps), in which he explains the concepts of a “good mess” and the “technical debt ceiling”:

A fresh mess is not a problem. It’s the old mess that bites you. […]

If you are coding up a new feature, there are lots of different ways to do it. Somewhere there is probably a very simple elegant solution, but it’s really hard to figure it out upfront. It’s easier to experiment, play around, try some different approaches to the problem and see how they work. […]

The problem is, just like in the kitchen, we often forget to clean up before moving on. And that’s how technical debt goes bad. All that “temporary” experimental code, duplicated code, lack of test coverage — all that stuff will really slow you down later when you build the next feature.

So regardless of your reason for accumulating short-term debt, make sure you actually do pay it off quickly.

I’ve been wondering how this applies to UX debt. Is it ok to take some design shortcuts, knowing that you’ll come back later and fix it (up to a “UX debt ceiling”)? My gut feeling is to say no, because design is so path-dependent. Your early choices constrain your later design choices, so if you make the wrong choice it can really hurt down the line. For example, if you skip user research in the beginning of the project, you’re highly likely to make the wrong choice about what to build, which isn’t something you can fix easily later on.

The solution is to have shorter UX (and development) cycles, which is becoming commonplace anyway with the rise of the Lean movement. I’m reminded of IDEO Design Director David Aycan’s 2010 article in HBR, Don’t Let the Minimum Win Over the Viable, in which he explains the importance of taking small steps so that it’s easier to correct course when you realise you’re on the wrong track:

Sketching or mocking up experiential prototypes and then testing them with consumers or potential partners, while also explicitly jotting down your operating and business assumptions and using them to discuss the business with industry experts, allows you both to pick a promising route to invest in the development sprint and to pivot with confidence. For example, by prototyping multiple consumer experiences and business models before investing in an initial MVP, GoGo was able to launch an airline WiFi and in-flight service experience that combined the best of multiple alternative services that might be offered in flight. One might think of this approach as testing multiple MVPs in parallel.

Creating multiple options in tandem creates more confidence in the core variables, which in turn means that pivots may be less drastic or disruptive later on. This approach can be applied beyond product features to business models and operating approaches as well.

He uses this sketch to illustrate the approach:

This makes a lot of sense in the context of UX and technical debt as well. A pragmatic approach to dealing with software debt seems to be something like this:

1. Create different possible paths (variation)
2. Pick a direction and work towards it (iteration)
3. Get feedback, address debt and other issues, correct course if necessary
4. Repeat cycle

The trick is to be ok with the early messes, but not let them deteriorate so much that you’re unable to clean things up when you finally decide it’s time. Remember the broken windows theory: “maintaining and monitoring urban software environments in a well-ordered condition may stop further vandalism neglegence and escalation into more serious crime technical issues.”

It took me a while to get through Michael Pepi’s The Postmodernity of Big Data. It’s dense, and the premise seemed so far-fetched that I wasn’t sure it would be worth the time investment:

But beyond economic motivations for Big Data’s rise, are there also epistemological ones? Has Big Data come to try to fill the vacuum of certainty left by postmodernism? Does data science address the insecurities of the postmodern thought?

Yes, I know, that sounds like a bit of a stretch. But I’m glad I stuck with it. The essay brings up some really interesting thoughts around the certainty promised by Big Data (even though some view it as nothing more than a clever marketing campaign for something that has been around a long time), and how that might be a response to the relativism of postmodernism:

Though both are projects that address positions about empiricism and meaning making, postmodernism and Big Data are in some senses opposites: Big Data is an empirically grounded quest for truth writ large, accelerated by exponentially expanding computing power. Postmodernism casts doubt on the very idea that reason can unearth an inalienable truth. Whereas Big Data sees a plurality of data points contributing to a singular definition of the individual, postmodernism negates the idea that a single definition of any entity could outweigh its contingent relations. Big Data aims for certainties — sometimes called “analytic insights” — that fly in the face of postmodernist doubt about knowledge. Postmodernism was confined to the faculty lounge and the academic conference, but Big Data has the ability to dictate new rules of behavior and commerce. An e-commerce outfit is almost foolish not to analyze browsing data and algorithmically determine likely future purchases, or as Jaron Lanier put it in Who Owns the Future, “your lack of privacy is someone else’s wealth.”

Consider this your difficult but satisfying weekend reading project.

Jeffrey Zeldman in a strong defense of web standards:

While many of us prefer to concentrate on design, content, and experience, it continues to be necessary to remind our work comrades (or inform younguns) about web standards, accessibility, and progressive enhancement. When a site like Facebook stops functioning when a script forgets to load, that is a failure of education and understanding, and all of us have a stake in reaching out to our fellow developers to make sure that, in addition to the new fancy tricks they’ve mastered, they also learn the basics of web standards, without which our whole shared system implodes.

I’ll add this to the ever-growing case for progressive enhancement.

I recently switched from Reeder to Mr. Reader as my default RSS app on my iPad¹. The main reason is that I wanted an easier workflow to post article snippets to my text editor so that I can either post it to the site, or come back to it later and expand more before posting. Mr. Reader allows for the creation of custom workflows, which makes this possible.

The ultimate article on using Mr. Reader’s custom workflows is Federico Viticci’s characteristically insightful Mr. Reader And The Services Menu for iOS. He goes over several useful workflows, but the one he uses for Notesy doesn’t quite do what I want it to do, so I made my own and thought I might as well share in case anyone else is interested.

I want to have an action that lets me select some text in Mr. Reader, and then create a new note in Notesy with the article title as the note’s title, followed by a markdown-formatted excerpt that includes the author, the title/url, as well as the quoted text — like so:

To set this up, go into the services menu in Mr. Reader, and configure it as follows:

If you want to copy and paste the URL scheme text, here it is:

notesy://x-callback-url/append?name={[TITLE]}&text={[AUTHOR] in *}%5B{[TITLE]}%5D{([URL])*:

> [TEXT-SELECTED]}

Make sure the “Text Selection Menu” toggle is on. Then, all you have to do is a select a piece of text, tap on “More actions”, and call the Notesy action. You can then either keep writing in Notesy, or come back to it later in nvALT on your Mac (see an overview of my plain text setup here).

And if you’re really lazy, just download this file on your iPad and select “Open In Mr. Reader” to set it up automatically: Notesy services configuration for Mr. Reader.

Craig Mod’s Goodbye, Cameras kicked off an interesting discussion on the future of photography and connected devices:

As I’ve become a more network-focussed photographer, I’ve come to love using the smartphone as an editing surface; touch is perfect for photo manipulation. There’s a tactility that is lost when you edit with a mouse on a desktop computer. Perhaps touch feels natural because it’s a return to the chemical-filled days of manually poking and massaging liquid and paper to form an image I had seen in my head.

Yet if the advent of digital photography compressed the core processes of the medium, smartphones further squish the full spectrum of photographic storytelling: capture, edit, collate, share, and respond. I saw more and shot more, and returned from the forest with a record of both the small details — light and texture and snippets of life — and the conversations that floated around them on my social networks.

Also see Camera makers are desperately trying to stay a step ahead of smartphones—and failing and Connectedness for some interesting follow-up discussions.

Mark O’Connell wrote a very interesting article about a fairly unsettling iOS app called Days of Life — “a counter for the days you have left to live.” In Deathwatch he explores just how weird and absurd this app turns out to be:

Days of Life is one of those technologies that seems to incidentally satirize our relationship with technology more broadly. It sits in the “Productivity” folder on my iPhone’s home screen, along with my calendar and a to-do list app called Remember the Milk, but it would be as appropriately housed in a folder called “Existential Terror.”

So much of what we value in technology is its promise to upgrade the hardware of our lives, to make us more useful to ourselves — more productive, more profitable, more effective. Days of Life functions like a reductio ad absurdum of the logic of personal productivity. The pie chart becomes a special way of being afraid: an image of the self as a micro-economy of numbered days.

We sometimes have such a warped view of what it means to be “productive”, and this essay does a good job of shining a spotlight on that.

Alexis Madrigal — who is turning into one of the most interesting journalists of our time — goes deep on Netflix’s 76,897 (often bizarre) micro-genres in How Netflix Reverse Engineered Hollywood:

Netflix has meticulously analyzed and tagged every movie and TV show imaginable. They possess a stockpile of data about Hollywood entertainment that is absolutely unprecedented.

Netflix is putting in a staggering amount of effort on the structured data of their TV shows and movies. And of course, it’s all for one reason — to get to know you better:

They capture dozens of different movie attributes. They even rate the moral status of characters. When these tags are combined with millions of users’ viewing habits, they become Netflix’s competitive advantage. The company’s main goal as a business is to gain and retain subscribers. And the genres that it displays to people are a key part of that strategy. “Members connect with these [genre] rows so well that we measure an increase in member retention by placing the most tailored rows higher on the page instead of lower,” the company revealed in a 2012 blog post. The better Netflix shows that it knows you, the likelier you are to stick around.

And now, they have a terrific advantage in their efforts to produce their own content: Netflix has created a database of American cinematic predilections. The data can’t tell them how to make a TV show, but it can tell them what they should be making. When they create a show like House of Cards, they aren’t guessing at what people want.

What’s interesting is that similar things are happening in other forms of media as well. Spotify and Rdio’s knowledge of our listening data can be used to inform record labels what type of albums they should invest in. And as David Streitfeld reports in As New Services Track Habits, the E-Books Are Reading You, a new crop of companies are helping authors figure out what type of books they should write:

The move to exploit reading data is one aspect of how consumer analytics is making its way into every corner of the culture. Amazon and Barnes & Noble already collect vast amounts of information from their e-readers but keep it proprietary. Now the start-ups — which also include Entitle, a North Carolina-based company — are hoping to profit by telling all.

“We’re going to be pretty open about sharing this data so people can use it to publish better books,” said Trip Adler, Scribd’s chief executive. […]

Scribd is just beginning to analyze the data from its subscribers. Some general insights: The longer a mystery novel is, the more likely readers are to jump to the end to see who done it. People are more likely to finish biographies than business titles, but a chapter of a yoga book is all they need. They speed through romances faster than religious titles, and erotica fastest of all.

All of this raises familiar questions about the loss of serendipity — finding interesting things we’re not looking for. But I still think this is an unnecessary fear.