TAOI: Searching for iTunes in macOS Catalina

The architecture of information:

Starting with macOS Catalina, Apple deprecated its long-standing iTunes media management app. In its stead, we got three new applications: Music.app, Podcasts.app, and TV.app.

I just upgraded my laptop to Catalina. After cleaning up some random post-upgrade changes, I set out to do some work. Before starting, I thought I’d get some music going in the background. So I did what I always do to play music on the computer: I typed CMD-space to open the system Spotlight search field and then itun-RETURN. This sequence of keystrokes usually launches the iTunes application. I’ve done it so many times I now do it reflexively, without even looking at what the system is doing.

Which is why I was confused when I saw an unfamiliar app welcome dialog pop up. I knew iTunes had changed in this release, but the dialog wasn’t what I expected: I was onboarding onto the Podcasts app. My first thought was that perhaps the Music app opened with a description of the new apps that replaced previous iTunes functionality so that I wouldn’t be lost entirely. But the welcome dialog said nothing about Music or TV — it was all about Podcasts. When I closed it, I realized I had actually opened the Podcasts app. I was baffled.

So I typed CMD-space again and then the word itunes:

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TAOI: Incompatible Apps in the Microsoft Store

The architecture of information:

A month ago, Microsoft introduced several new computers to its Surface line. While some of the new devices were incremental advances, one of them — the Surface Pro X — is a modern reinterpretation of the product line. It’s physically sleeker than previous Surface tablets. It features a new stylus that can be stored in the tablet’s keyboard. And, most importantly, it uses a new ARM processor architecture, like the one used by smartphones.

This last point is worth noting. One of the advantages of using Windows tablets over iPads is that the latter lack the breadth of software available for Windows. But in many cases, software “for Windows” really means “for Windows on traditional Intel processors.” Some of the apps that run “on Windows” are incompatible with the new ARM processors in the Surface Pro X tablets, even though they, too, run Windows. In other words, it’s complicated.

In his review of the device for The Verge, Dieter Bohn calls out app compatibility issues as one of the downsides of the new device. The review is worth reading for details into the complexities of this processor transition. The challenges are nuanced: some apps will run slowly, others won’t run at all. One issue stood out to me:
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TAOI: Facebook’s Electoral Interference Changes

The architecture of information:

The Verge reports on a set of changes to Facebook aimed at counteracting misinformation on its platform. The changes come ahead of next years’ elections in the U.S., and include tools to protect candidates’ accounts, more transparency about the entities that manage Facebook pages, and new advertiser guidelines.

Reading through this list reminds me of the role television has played in influencing electoral outcomes. Compared to an information environment like Facebook, television — even in its current state, with hundreds of channels to choose from — has limited bandwidth. As a result, both actors and gatekeepers must be selective about what they publish on TV.

Compared to television, publishing on digital social platforms is cheap and easy. Anyone can publish anything, including variations on ads so they can be optimized for effectiveness. Additionally, on a social platform like Facebook, the people who are being influenced can also be publishers — that is, they can help spread messages “virally.” As a result, digital is a more effective platform for persuasion than TV.

I’m glad to see Facebook making structural changes to increase transparency and trustworthiness of their platform. Given its scale and reach, these changes could have an impact on the fairness of elections.

Facebook will label false posts more clearly as part of an effort to prevent 2020 election interference

TAOI: Facebook Hiding Likes

The Architecture of Information:

Likes are one of the most important concepts of the Facebook experience. Giving users the ability to cast their approval (or disapproval) on a post or comment — and to see how others have “voted” — is one of the most engaging aspects of the system, both for users and content authors. Facebook even uses the Like icon as a symbol of the company as a whole:

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The sign outside the main entrance to Facebook headquarters. (Photo: Facebook.)

However, according to a report in the NY Times, Facebook is experimenting with hiding post measurements:

On [September 26], the social network said it was starting a test in Australia, where people’s Likes, video view counts and other measurements of posts would become private to other users. It is the first time the company has announced plans to hide the numbers on its platform.

Why would they do this? Because seeing these metrics may have an impact on users’ self-esteem. According to a Facebook spokesperson quoted in the article, the company will be testing the change to see if it helps improve people’s experiences. A noble pursuit. But, I wonder: How would this impact user engagement? If it benefits users but hurts advertising revenue, will Facebook discontinue the experiment?

Facebook Tests Hiding ‘Likes’ on Social Media Posts

TAOI: Personalized Yelp Results

The architecture of information:

Per TechCrunch, Yelp announced earlier this week that it will allow users to personalize search results:

Once you’ve made your selections, those preferences will start affecting the search results you see. The personalization should be obvious because the results will be identified as having “many vegetarian options” or “because you like Chinese food.” The homepage will also start highlighting locations that it thinks you would like.

Seems like an obvious feature, especially for a system like Yelp that aims to connect users with places they will like. A short video explains how it works:

A baseline 21st Century tech literacy skill: Training the algorithms that personalize your search results. (For designers: Watch for emerging user interface standards for such training mechanisms. I was intrigued by Yelp’s use of the heart icon to signify personalization.)

Yelp will let users personalize their homepage and search results

TAOI: Following Topics on Twitter

The architecture of information:

According to a report on The Verge, Twitter is testing a means for users to follow topics in much the same way that they follow Twitter accounts. Topics would include sports and entertainment, and would be determined algorithmically.

Why is Twitter doing this?

The move represents Twitter’s latest effort to help users find the best content on the platform even if they don’t know which accounts to follow. For years, the company has sought to make it easier for people to find value in Twitter, which can be foreboding for newcomers.

This sounds like something you can already do with hash tags. However, as the report points out, this feature may not be easily discoverable for new users. It makes sense to surface topics over (or at least in parallel) to accounts, since “interests” can be as much (or more) fodder for conversation than what we traditionally think of as accounts. (I.e., Loci representative of — and curated by — either individuals or organizations.) Still, this sounds like an important change to Twitter’s conceptual model.

Twitter tests letting users follow topics in the same way they follow accounts

TAOI: Disneyland App

The architecture of information:

Digital experiences are changing our understanding of physical environments. Google Maps gives you the ability to walk around a new city as though you’d known it for a long time. And should you develop a sudden hankering for ice cream, Yelp allows you to locate the nearest gelateria. The most noticeable change comes from layering information on the environment. For example, when trying to decide between two neighboring restaurants you’re no longer constrained to judging them solely by their appearance; you can also peruse their reviews in Yelp. Restaurant A has four-and-a-half stars, whereas restaurant B has three — A it is!

The number of stars is information about the place. You won’t find it in the physical place itself, but in its representation in an information environment which you access through your magical pocket-sized slab of glass. We’ve grown used to these augmented interactions with physical space, and mostly take them for granted. But recently I had one such interaction with an app I hadn’t used before, and which stood out to me for 1) its clarity of purpose and 2) the degree to which that purpose changed the experience of the place. I’m referring to the Disneyland app.

My family and I visited Disneyland a few weeks ago. We hadn’t been in five years, and the Disneyland app was one of the novelties since our last visit. The app presents a map of the Disney theme parks. As such it mostly replaced the parks’ old (and sometimes beautiful) paper-based maps. Thanks to the phone’s sensors, the Disneyland app makes it easy to figure out where you are, where to go next, and how to get there. But the app adds an additional key piece of information to the experience that can’t be had with paper-based maps: attraction wait times. Over every representation of an attraction in the park, you see a little callout that indicates how long you’ll have to wait in line to experience that ride or show:

Disneyland app

This piece of information is always available at all levels of zoom in the map. It’s the definitive element of the experience: in these maps, attraction wait times have the highest visual priority. As a result, wait times become the defining factor in sequencing the exploration of the park. The apps preferred answer to the question “What should we do next?” is always “Whatever is closest that has the shortest lines.”

This is an interesting choice that recalls the park’s old ticket levels. A long time ago, each Disneyland attraction required a separate ticket. Not all attractions used the same tickets; there were several levels ranging from A to E. “E-tickets,” such as the Haunted Mansion, were the most popular and desirable. These were considered the park’s premium attractions; their tickets were worth more than the others. This economic scheme influenced how visitors experienced the park. Ticket “coupon books” only included a limited number of E-tickets as compared to the lower denominations. Guests could buy more tickets inside the park, but having a limited number of the various level tickets affected choices. (I remember visiting Walt Disney World when it had a similar scheme, and hearing things like, “let’s visit this ride next, we have to use up our C-tickets.”)

The Disneyland app creates a similar economy by making attraction wait times the key informational element of the experience. When you’re trying to decide between two rides, knowing you’ll have to wait 65 minutes in line in one versus 15 minutes in another could be the key factor in your choice. (It was for my wife and me. Children get very cranky after waiting in long lines all day!) Our choosing to go on the ride with the lower wait times would contribute to slightly increasing that ride’s wait times and lowering the wait times for the more popular rides. I don’t have data, but my expectation is that this would help even out wait times throughout the park.

That is, of course, if all other things are equal — which they aren’t. The Haunted Mansion is a much more elaborate and compelling experience than Dumbo the Flying Elephant. Also, some rides have higher throughput than others. So the choice of riding one rather than the other doesn’t come down solely to which has the shortest waits.

That said, for someone like myself, who knows Disneyland very well, having this extra bit of information made the experience of visiting the park much better. In our two days at Disneyland, my family and I experienced more of the park than we’d ever been able to before. We also had more fun, since we spent a lower percentage of our time there in queues. But I wonder about the effect on folks who are less familiar with the parks. Will the emphasis on wait times drive them to prioritize less popular attractions over the park’s highlights? Adding feedback mechanisms to a system influences the way the system works. In what unexpected ways does this app change the experience of visiting Disneyland?

TAOI: The “Agony” of Browsing Amazon

The architecture of information:

As I’ve noted before, as software eats more of the world we’re likely to see more stories about how poor information architecture is hurting businesses. Along these lines, a recent opinion piece in Bloomberg claims browsing for products in Amazon is “agonizing”:

Try clicking through Amazon’s beauty products section to the pages for foundation, one of the (ahem) foundations of any makeup line. It’s a notoriously tricky item to buy online or in stores because people must match the shade to their skin tone. I found hunting for foundation on Amazon comically impossible.

There are 200 pages of products grouped seemingly with little reason. It’s not possible to narrow the product listings by liquid or powder foundation — equivalent to not giving people the choice between boxers or briefs.

Today is the second of two “Amazon Prime Days,” when the retailer presents many products at a deep discount. I’m in search of a new pair of sunglasses, so I’ve perused the site’s offers a couple of times since yesterday. The findings in the Bloomberg piece correspond with my experience: Amazon is relatively easy to use if you know what you’re looking for, less so if you’re browsing.

As the piece notes, it’s hard to state precisely how much (if any) this is hurting Amazon’s business. Speaking from my own experience, I find myself using other information environments as my first resort for browsing for products more often than not. (It’s not just bad IA; lately I also find Amazon’s UI slow to load and clumsy to operate.)

Amazon Shopping Is Easy. Browsing Is Agonizing.

TAOI: Podcasts on Spotify

The architecture of information:

Last week, Apple announced the end of its venerable iTunes application on the Mac. In its stead, the next version of macOS will feature three applications: Music, Podcasts, and TV.

This change is long-coming. Managing media such as music, podcasts, and movies is one of the uses of computers that requires regular folks to think like information architects; they must consider categorization schemes, the nomenclature of artist names, the integrity of their metadata, and so on. (Most people lack the language to describe the challenges in these terms, of course.) By separating media types into their own applications (as has long been the case in iOS), Apple eliminates the confusion inherent in presenting different types of stuff that nevertheless share similar structural underpinnings.

Now Spotify seems to be moving in a similar direction. According to an article on The Verge, an upcoming release of the app will more clearly separate podcasts from other types of audio types. It will also introduce a clearer structure for podcasts:

Podcasts on Spotify are currently only organized by shows that users follow, unplayed shows, and downloaded shows, which is to say it’s chaotic. In the new design, the podcast category will be broken up into three sections: episodes, downloads, and shows.

Image: Spotify
Image: Spotify

I haven’t yet seen the new design myself (nor am I a Spotify user.) However, this strikes me as yet another example of how businesses are using information architecture as a way of making their products and services more competitive. As I’ve said before, good IA is good business.

Spotify’s officially separating podcasts and music in premium users’ libraries