Cap Watkins is switching from RSS to Twitter, and so far he is very happy:

Now that I’ve started using Twitter for feeds, I’m unlikely to ever go back. The ease of sharing, Favoriting, Retweeting, sending to Instapaper, etc. not only match, but at times surpass even Reeder in terms of ease and simplicity. One less app to deal with is a win, not to mention that the links are ordered exactly as I like them (and holy crap, Tweetbot iCloud sync. So good).

Cap goes over the pros and cons of his decision, but I think there’s one major con that he left out: Twitter is a river, RSS is a filing cabinet. Ok, I apologize for the mixed metaphor, but hear me out.

Twitter updates flow by you in a never-ending stream of links. This means that if you choose to follow RSS feeds in this way, all the separate article feeds flow into that one river, and there’s no stopping it. If you happen to be offline for a day or two, it’s extremely likely that you’ll miss an update from an infrequently-updated website you love.

With RSS, that problem doesn’t exist. Since article feeds are separate, there isn’t one giant river (you can choose to view “All feeds” in most readers, but that’s optional). So, I just open the filing cabinet whenever I want, and I can immediately see how many updates my favourite sites have received. I can decide to nuke the unread counts on a site with 50 new items. I can seek out the content I really want. I don’t have to worry that the river will keep flowing and I’ll miss the boat completely (ok, now I’ve really killed this metaphor).

So, although I agree with the pros Cap highlights in his post, and I’m glad he found a reading flow that works for him, I’m not ready to give up RSS. It’s still my favorite way to discover good content.

I’d like to thank Xero for sponsoring Elezea’s RSS feed this week.

Xero is online accounting software that’s simple, beautiful and smart. With Xero, your financial data is displayed visually on the dashboard so you get a clear picture of your finances — anywhere, anytime, on any device.

It connects to your bank, and with over a hundred apps such as Harvest, Batchbook & Quoteroller, to give you all the information you need to run your business — without any manual data entry.

Xero’s online so you can start using it right away, no need for installation or updates — you’re always using the latest version.

For your free trial or to find out more, visit xero.com/creatives.

Sign up to Xero before June 30, 2013 and get 60 days free.

Sponsorship by The Syndicate.

About a year ago I wrote an article for Smashing Magazine called A Dad’s Plea To Developers Of iPad Apps For Children. It was generally well received, but some of the comments were inevitably judgemental about parents who let their kids use iPads.

With that as backdrop, I really enjoyed Gary Marshall’s post Don’t fear your kids’ tech tantrums. He starts by making this point:

Let’s start by separating the “lazy parent” argument from the “kids shouldn’t have devices” argument. You can be a good parent and let your kids play on the iPad, and you can be a bad parent with a house full of encyclopaedias.

Gary’s main point is that giving kids appropriate exposure to technology — as part of a wider mix of non-tech activities — is essential to help prepare them for the digitally-focused world they are growing up in:

These are all valuable skills, critical skills, and the older she gets and the more tech-saturated the world becomes the more important digital literacy will become. I want my daughter to be ready for that world, not to be afraid of it or to be manipulated by it.

So thank you, Gary. I feel a little bit better about those comments now.

I was going to write about the Google Reader shutdown but Brent Simmons beat me to the argument I was going to make. In Why I love RSS and You Do Too he sums up why we should all care about Google Reader’s demise:

Even if you don’t use an RSS reader, you still use RSS. If you subscribe to any podcasts, you use RSS. Flipboard and Twitter are RSS readers, even if it’s not obvious and they do other things besides. Lots of apps on the various app stores use RSS in at least some way. […] And those people you follow on Twitter who post interesting links? They often get those links from their RSS reader. One way or another, directly or indirectly, you use RSS. Without RSS all we’d have is pictures of cats and breakfast.

Killing Google Reader doesn’t kill RSS, for sure, but it’s such a big part of the ecosystem that we should be concerned about the health of the platform. From the perspective of a guy with a blog this is pretty depressing news. RSS subscribers are extremely difficult to grow, but they are, by far, the best kind of readers. I’ve written about this before, but to reiterate: they’re loyal, they read almost everything, and they share your stuff. It’s the best way to build an audience. Hunter Walk makes this point succinctly:

Google Reader impact also undercounted if you strictly look at # users bec many power-curators/sharers use it as a discovery system

— Hunter Walk (@hunterwalk) March 14, 2013

But Scott Stein has perhaps the best TL;DR version of the whole debacle:

Google Reader is to Twitter as a well-labeled filing cabinet is to a bag of insane cats.

— Scott Stein (@jetscott) March 14, 2013

So, what now? For a bit of nostalgia, Buzzfeed has a great history of Google Reader. It’s a fascinating story, worth reading. And then, Om Malik has an interview with the original creator of Google Reader. Once you’re done grieving and ready to move on, Lifehacker has a very comprehensive post on the alternatives.

Frank Chimero has a great follow-up to Tino Arnall’s excellent post No to NoUI. In The Cloud is Heavy and Design Isn’t Invisible Frank explores what’s appropriate (and what’s not) about using “The Cloud” as a metaphor, and then he makes a great point about the Invisible Design trend:

Sometimes I wonder if the desire to obfuscate production and make the resulting design invisible or seamless to users diminishes their appreciation for the craft of building systems. I think there’s a strong likelihood that metaphors like “The Cloud” and sayings like “It Just Works™” reduce a user’s appreciation of the software/hardware they are using. “Magic” is a great word for selling product, but it also can cheapen all the sweat it takes to get there. If the seams have been covered, you can’t admire how things connect.

I completely agree with Frank on this. As I’ve mentioned before, I think our goal shouldn’t be NoUI (or YesUI or AlwaysUI or whatever we want to label the other extreme). Our goal should be appropriate visibility.

In The Guardian Tom Meltzer asks, Are our household appliances getting too complicated? Despite violating Betteridge’s law of headlines he makes some good points:

“The innovation is obviously being driven by manufacturers’ desire to add value and to differentiate themselves,” says analyst Neil Mason, head of retail research at market research company Mintel. “But from a consumer’s point of view, what they want is convenience and simplicity. When you run into trouble is when you add all these extra functions and consumers just get perplexed as to how to actually use them.”

He cites some classic examples of technology-driven innovation — asking “What more can we do with this technology?” as opposed to “What goals do our customers want to accomplish with our product?”

Figuring out what to read (and what to believe) about Big Data is becoming a Big Data problem in and of itself1. I wrote The hype, benefits, and dangers of Big Data a while ago to give an overview of what’s out there, but there are two more interesting articles from the last week that I’d like to highlight as well.

First, on the HBR blog Jake Porway talks about Big Data and social entrepreneurship and makes the point that You Can’t Just Hack Your Way to Social Change:

Any data scientist worth their salary will tell you that you should start with a question, NOT the data. Unfortunately, data hackathons often lack clear problem definitions. Most companies think that if you can just get hackers, pizza, and data together in a room, magic will happen. This is the same as if Habitat for Humanity gathered its volunteers around a pile of wood and said, “Have at it!” By the end of the day you’d be left with half of a sunroom with 14 outlets in it.

And on Wired, Does ‘Big Data’ Mean the Demise of the Expert — And Intuition? is a very interesting excerpt from Viktor Mayer-Schönberger and Kenneth Cukier’s new book on the topic:

In the same spirit, the biggest impact of big data will be that data-driven decisions are poised to augment or overrule human judgment.

The subject-area expert, the substantive specialist, will lose some of his or her luster compared with the statistician and data analyst, who are unfettered by the old ways of doing things and let the data speak. This new cadre will rely on correlations without prejudgments and prejudice. To be sure, subject-area experts won’t die out, but their supremacy will ebb. From now on, they must share the podium with the big-data geeks, just as princely causation must share the limelight with humble correlation.

It seems like an obvious conclusion, but everything I’ve read so far about Big Data confirms that if we think cutting the “messiness” of human decision-making out of data analysis will result in better decisions, we’re sorely mistaken.

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1. Sorry, I didn’t get much sleep last night, so even though I know this isn’t a particularly funny joke, I just can’t help myself. ↩

In Students to e-textbooks: no thanks Nicholas Carr reflects on a recent study (PDF link) out of Ryerson University in Toronto which shows that students still prefer paper textbooks over electronic textbooks:

What’s most revealing about this study is that, like earlier research, it suggests that students’ preference for printed textbooks reflects the real pedagogical advantages they experience in using the format: fewer distractions, deeper engagement, better comprehension and retention, and greater flexibility to accommodating idiosyncratic study habits. Electronic textbooks will certainly get better, and will certainly have advantages of their own, but they won’t replicate the particular advantages inherent to the tangible form of the printed book.

What makes this interesting is that it’s not the usual “I want to smell the pages” argument we see in most stories about the yearning for paper books. This study shows that paper textbooks help students learn better. That’s not to say that electronic textbooks won’t eventually catch up — they will — but it’s a reminder that in some spaces, e-books still have a long way to go.

A Readlist of all the articles referenced in this post is available here. Readlists allow you to send all the articles to your Kindle, read them on your iOS device, or download it as an e-book.

Despite the overly alarmist title, Andrew Leonard’s How Netflix is turning viewers into puppets1 is a fascinating article on how Netflix uses Big Data in their programming decisions:

“House of Cards” is one of the first major test cases of this Big Data-driven creative strategy. For almost a year, Netflix executives have told us that their detailed knowledge of Netflix subscriber viewing preferences clinched their decision to license a remake of the popular and critically well regarded 1990 BBC miniseries. Netflix’s data indicated that the same subscribers who loved the original BBC production also gobbled down movies starring Kevin Spacey or directed by David Fincher. Therefore, concluded Netflix executives, a remake of the BBC drama with Spacey and Fincher attached was a no-brainer, to the point that the company committed $100 million for two 13-episode seasons.

The article also asks what this approach means for the creative process, something I’ve written about before in The unnecessary fear of digital perfection, so I won’t rehash that argument here.

What’s interesting to me about the rise in Big Data approaches to decision-making is the high levels of inaccuracy inherent to the analysis process. Of course, this is something we don’t hear about often, but Nassim N. Taleb recently wrote a great opinion piece about it for Wired called Beware the Big Errors of ‘Big Data’, in which he states:

Big-data researchers have the option to stop doing their research once they have the right result. In options language: The researcher gets the “upside” and truth gets the “downside.” It makes him antifragile, that is, capable of benefiting from complexity and uncertainty — and at the expense of others.

But beyond that, big data means anyone can find fake statistical relationships, since the spurious rises to the surface. This is because in large data sets, large deviations are vastly more attributable to variance (or noise) than to information (or signal). It’s a property of sampling: In real life there is no cherry-picking, but on the researcher’s computer, there is. Large deviations are likely to be bogus.

He gets into more detail on the statistical problems with Big Data in the article, and his book Antifragile looks really interesting too.

Since I haven’t written about Big Data before, I also want to reference a few articles on the topic that I enjoyed. Sean Madden gives some interesting real world examples in How Companies Like Amazon Use Big Data To Make You Love Them2. But over on the skeptical side, Stephen Few argues in Big Data, Big Deal that “interest in big data today is a direct result of vendor marketing; it didn’t emerge naturally from the needs of users.” He also makes the point that data has always been big, and that by focusing on the “bigness” of it, we’re missing the point:

A little more and a little faster have always been on our wish list. While information technology has struggled to catch up, mostly by pumping itself up with steroids, it has lost sight of the objective: to better understand the world—at least one’s little part of it (e.g., one’s business)—so we can make it better. Our current fascination with big data has us looking for better steroids to increase our brawn rather than better skills to develop our brains. In the world of analytics, brawn will only get us so far; it is better thinking that will open the door to greater insight.

Alan Mitchell makes a similar point in Big Data, Big Dead End, a case for what he calls Small Data:

But if we look at the really big value gap faced by society nowadays, it’s not the ability to crunch together vast amounts of data, but quite the opposite. It’s the challenge of information logistics: of how to get exactly the right information to, and from, the right people in the right formats at the right time. This is about Very Small Data: discarding or leaving aside the 99.99% of information I don’t need right now so that I can use the 0.01% of information that I do need as quickly and efficiently as possible.

What I think we should take from all of this is that our ability to collect vast amounts of data comes with enormous predictive and analytical upside. But we’d be foolish to think that it makes decision-making easier. Because Big Data does not take away the biggest challenge of data analysis: figuring how to turn data into information, and information into knowledge. In fact, Big Data makes this harder. To quote Nassim again:

I am not saying here that there is no information in big data. There is plenty of information. The problem — the central issue — is that the needle comes in an increasingly larger haystack.

In other words: proceed with caution.

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1. Link via @mobivangelist ↩

2. It’s interesting that the phrasing of both this headline and the Netflix one implies that companies are using Big Data to persuade us to do things against our will. But I can’t figure out if that’s a real fear, or just clever linkbait. ↩

Mark Boulton argues that we need to think further than breakpoints in responsive design, and also spend time figuring out the “optimization points”. From The In-Between:

I think we’re missing a trick for using breakpoints to make lots of subtle design optimisations. […] Content-out design means defining your underpinning design structure from your content, and then focusing on what happens in between ‘layouts’. This approach of optimising your design by adding media queries (I like to call these optimisation points rather than break points, because nothing is broken without them, just better), means you are always looking at your content as you’re working. You become more aware of the micro-details of how the content behaves in a fluid context because your focus shifts from controlling the design in the form of pages, to one of guiding the design between pages.

He shares some examples and also links to more resources on how to accomplish this. One good example of this subtle optimization approach is Responsive Typography, a concept by Marko Dugonjić where the size of the typography displayed on the screen is based on the viewing distance of the reader, calculated via webcam.