UI Design Trend Cycles

A little while ago, Brent Simmons wrote about standard UI controls and their advantages in comparison to custom UI controls. This is in large part due to iOS 7, which leveled the UI design playing field last year: Where previously iOS user interfaces were expected to feature lavish graphical details such as photorealistic textures, lighting and shadows, iOS 7’s streamlined appearance reduces the necessity of a dedicated photoshop artist in UI design.

User interfaces adopting iOS 7’s new, minimal appearance look modern and fresh, whereas iOS 6 apps look dated and old fashioned in comparison. This begs one question: How long will it take until iOS 7’s appearance starts to look dated and old fashioned? Greg Cox speculates that just as standard controls and the default look & feel of iOS 7 are a useful differentiator right now, history is bound to repeat itself once the novelty of iOS 7 wears off and designers have to find new ways to differentiate:

So at some point in the cycle custom controls start to become valuable again. Apps that use them effectively will stand out and will be hard to copy. Consider the discussions about TweetBot’s famously custom UI, or the raving about Loren Brichter’s beautifully simple Letterpress design. In the latter half of the life of the original iOS design it became positively passé to rely on standard controls for your app.

Which reminds me of a theory recently put forth by Joel Unger:

Design ecosystems mimic biological ecosystems: Whenever a new trend takes hold or an old one reemerges in the world of design, patterns emulate competitive systems in nature. Resource-intensive adaptations often achieve substantial competitive advantages.

Alan Kay says that Xerox PARC bought its way into the future by paying lots of money for each computer. Today, you can almost buy your way into the future of mobile computers by paying small amounts of money for lots of computers.

PADDs, not the iPad

Visualizing Algorithms

Mike Bostock adapted his talk on visualizing algorithms from Eyeo 2014 for the web. He writes:

Algorithms are a fascinating use case for visualization. To visualize an algorithm, we don’t merely fit data to a chart; there is no primary dataset. Instead there are logical rules that describe behavior. This may be why algorithm visualizations are so unusual, as designers experiment with novel forms to better communicate. This is reason enough to study them.

But algorithms are also a reminder that visualization is more than a tool for finding patterns in data. Visualization leverages the human visual system to augment human intellect: we can use it to better understand these important abstract processes, and perhaps other things, too.

I’m also reminded of a video I came across some time ago, visualizing the inner workings of 15 different sorting algorithms:

A Better Place on Twitter

A Better Place is a positivity filter bubble. It uses terrible sentiment analysis to strip out negative Twitter posts from your timeline; hopefully leaving you with a few morsels that make your day tolerable.

A pleasant response to those Facebook mood experiments.

“Her pitch was pretty genius. She would go to chapters of her sorority, do her presentation, and have all the girls at the meetings install the app. Then she’d go to the corresponding brother fraternity—they’d open the app and see all these cute girls they knew.” Tinder had fewer than 5,000 users before Wolfe made her trip, Munoz says; when she returned, there were some 15,000.

The Truth About Tinder and Women Is Even Worse Than You Think – Businessweek.

Clever.