Chuck Jones and the Power of Discipline

Every Frame a Painting has a fantastic analysis of the work of master animator Chuck Jones:

As the video points out, Jones’s work has stood the test of time. Why? The video teases apart the elements that make Jones’s Looney Tunes cartoons work:

  • A two-part gag structure that 1) leads the viewer to make an assumption, and 2) proves that assumption wrong.
  • An emphasis on building character.
  • The discipline to abide by “the challenges and restrictions you set for yourself.”
  • Being open to inspiration from the real world.

The combination of these simple rules led to some most effective — and funniest — short films ever made. (Including my all-time favorite, One Froggy Evening.)

While all the rules are important for storytelling​, I consider discipline paramount since it transcends the medium. When creating a complex work (be it a book, a website, or an animated cartoon), you’re establishing a little universe with its own logic and rules. One of the central concerns of the creator is ensuring that this logic is internally coherent. While can sometimes be tempting to make exceptions for the sake of expediency, such exceptions often point to structural deficiencies, which left unresolved can ruin the work.

Having the discipline to abide by constraints (self-imposed and otherwise) is key to producing good work. Chuck Jones’s cartoons ultimately stand the test of time because of his insistence on abiding by the rules.

Chuck Jones – The Evolution of an Artist

Artificial Intransigence

Me: Ooh, X looks interesting. I wonder if I can find a short video about X. [Finds a video on X and watches to the end.]

Recommendation algorithm: Oh, s/he watched X! I know what s/he likes. X! Like? Nay! X is the bread on his/her table, the air s/he breathes, his/her raison d’être. S/he has a visible X tattoo on his/her body. His/her firstborn will be/is named after X. X in continuous rotation, 24 x 7! More X! More X! MORE X!

Me: Whoa, whoa! [Looks around for a way to say “no more X.” Finds a link to hide video about X. Clicks it. The video disappears from the recommendations feed.]

TIME PASSES

Me: [Idly visits video site.]

Recommendation algorithm: New X video! Oh, and here are three others you may have missed. And these two are kinda like X.

Me: Hmmm. I thought I said no more X. How does this thing work? [Clicks on hide links for three other videos about X. Reloads page.]

Recommendation algorithm: New X video! Oh, and here are three others you may have missed. And these two are kinda like X. Oh, and here are some about Y and Z, just in case.

Me: Really?! [Clicks on hide link for another X video. Reloads page.]

Recommendation algorithm: New X video! Oh, and here are three others you may have missed. And these two are kinda like X. Oh, and here are some Ys and Zs, just in case.

Me: Sigh. [Clicks on video about Z. Watches to the end.]

Recommendation algorithm: Oh, s/he watched Z! I know what s/he likes. Z! Like? Nay! Z is the bread on his/her table, the air s/he breathes, his/her raison d’être. S/he has a visible Z tattoo on his/her body. His/her firstborn will be/is named after Z. Z in continuous rotation, 24 x 7. More Z! More Z! MORE Z!

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?

Neal Stephenson on Social Media

Speaking in an interview with Tyler Cowen, Neal Stephenson offers an excellent analysis of how social media has hurt civic discourse:

COWEN: You saw some of the downsides of social media earlier than most people did in Seveneves. It’s also in your new book, Fall. What’s the worst-case scenario for how social media evolved? And what’s the institutional failure? Why do many people think they’re screwing things up?

STEPHENSON: I think we’re actually living through the worst-case scenario right now, so look about you, and that’s what we’ve got. Our civil institutions were founded upon an assumption that people would be able to agree on what reality is, agree on facts, and that they would then make rational, good-faith decisions based on that. They might disagree as to how to interpret those facts or what their political philosophy was, but it was all founded on a shared understanding of reality.

And that’s now been dissolved out from under us, and we don’t have a mechanism to address that problem.

Mr. Stephenson’s observation corresponds to my experience of social media (especially Twitter): It’s not that folks are talking past each other, it’s that they’re not even interacting with people who don’t share their mental models. The mere hint of the possibility of an alternate take can lead to ostracism — or worse. Amplified through continuous validation and a complete lack of pushback, opinions replace facts as the basis for worldviews. To talk of filter bubbles is misleading: these aren’t tenuous membranes; they’re thick, hardened shells.

The interview continues:

COWEN: But what’s the fundamental problem there? Is it that decentralized communications media intrinsically fail because there are too many voices? Is there something about the particular structure of social media now?

STEPHENSON: The problem seems to be the fact that it’s algorithmically driven, and that there are not humans in the loop making decisions, making editorial, sort of curatorial decisions about what is going to be disseminated on those networks.

As such, it’s very easy for people who are acting in bad faith to game that system and produce whatever kind of depiction of reality best suits them. Sometimes that may be something that drives people in a particular direction politically, but there’s also just a completely nihilistic, let-it-all-burn kind of approach that some of these actors are taking, which is just to destroy people’s faith in any kind of information and create a kind of gridlock in which nobody can agree on anything.

In other words, it’s a structural problem. As such, it’s also systemic. Unmentioned in the interview is the driving force behind these algorithmic constructs: business models based on monetizing users’ attention. Incentivizing engagement leads to systems that produce fragmentation and conflict.

Neal Stephenson on Depictions of Reality (Ep. 71)

Are Your Navigation Structures Working?

One of the most important elements of a digital product is its navigation structures. By this, I mean the sets of links that allow users to move from one part of the environment to another. This includes global navigation bars, hamburger menus, contextual navigation blocks, etc. At its most basic, a well-designed navigation structure will help your users find the stuff they’re looking without fussing about. They’ll look at the choices before them, pick one, and find themselves faced with the information they’re looking for.

Achieving this best-case scenario is easier said than done; there are many ways to mess up navigation structures. I’ve experienced broken structures in major websites that leave me scratching my head. Often, the problem is that the structure reflects the organization’s conceptual model of its business without considering that the user may bring to the interaction a different mental model. Labels that may be clear to people in the organization can be ambiguous to outsiders.

Fortunately, it’s relatively easy to gauge​ the effectiveness of navigation structures. For example, studying site log files can reveal patterns of use that reveal navigational gaps. Observing users interacting with the environment (whether in production or using prototypes) is also a very effective way of revealing issues with navigation. Interviewing users is also valuable​ since it can help you understand​ how they see the domain. When examining the outcomes of such studies, you should ask questions such as:

  • Are we offering users the choices they expect?
  • Are choices labeled clearly? (By this I mean that they’re understandable to users.)
  • Are choices clearly distinct from one another? Or are some possibly ambiguous?
  • Are we offering users too much or too little choice?
  • Are choices presented at the right level of granularity for this part of the environment?
  • Is the set of choices helping bridge the user’s mental model of the business domain?

This last question is particularly important to me. Users bring to the interaction expectations of how the domain is organized. These expectations may or may not match reality. Situations in which users come to the experience with a clear, accurate understanding of the domain are relatively easy to deal with. But in some cases, users’ understanding may be off the mark. What then?

Navigation plays an important role not just in helping users move around, but also in educating them on the options available to them. Options in don’t exist in a void; people read them as sets. Users will understand the domain not through individual labels, but through the groups of choices they represent.

Defining these choices, the distinctions​ between them, and the labels that represent them​ is a design act that requires understanding the people who will be using them. In particular, understanding users’ mental models of the domain — and the degree to which those mental models differ from the organization’s conceptual models — is essential for designing navigation structures that work. This calls for research: understanding how folks think about your business’ domain, what they expect from you, and how they talk about those choices.

What I Unlearned From Architecture

I got an interesting question via Twitter:

“What were some of the mindsets, habits of thinking you had to unlearn transitioning from [architecture] to [information architecture]?”

The answer that comes immediately to mind is: “not that many!” I consider architecture a perfect training ground for information architecture. There are many more architectural mindsets that apply to information architecture than mindsets that require unlearning. That said, as I’ve thought about it I’ve realized there is, in fact,​ a mindset I picked up from architecture that I’ve had to unlearn over time: the idea of the architect as the central element of the design process.

Architecture is rife with what are referred to as starchitects — practitioners whose work and style is known around the world, and whose fame influences the work. Clients seek out Frank Gehry because they want a Frank Gehry building. Gehry’s office is bound to produce buildings in the Gehry style regardless of what contextual conditions call for.

When I was a student, most of the works we looked at were produced by starchitects. The implication was that that’s what we ought to aspire to. The first few years of my career, I labored under the delusion that I was at the center of the work. Over time, I came to realize that effective designers (in any field!) primarily serve not themselves or their architectural ideologies, but the work. I came to suspect the idea of having a “house style” — something I longed for at first.

To put it bluntly, I left architecture school with an inflated ego. The main mindset I had to unlearn as I transitioned to information architecture was the centrality of my own ideas, desires, and “style” in the design process. Instead, the core of what I aspire to now is form-context fit. This calls for understanding through collaboration; it calls for research and open-mindedness. Experience is primarily in service to the process, not the other way around. Getting my ego out of the way — embracing beginner’s mind — took many years of practice.

The Informed Life With Lis Hubert

Episode 14 of The Informed Life podcast features an interview with information architecture/digital strategy/customer experience consultant Lis Hubert. Over the past year, Lis has been living around the world as what some folks refer to as a “digital nomad.” She’s using this time to “architect [her] best life:”

I want to be the best person I can be and I want to take the and I’m one of the best life I can have and I’m going to take all of the knowledge that I acquire along the way and create a life that gives me the most purpose.

In this show, we discuss what this means for Lis. It’s an inspiring conversation for anyone who’s ever thought about structuring their lives more intentionally.

An ask: if you’re enjoying these conversations, please rate or review the show in Apple’s podcast directory. This helps other folks find it. Thanks!

The Informed Life Episode 14: Lis Hubert on Living Intentionally

Apollo 11 at Fifty

Today is the fiftieth anniversary of one of the most important achievements in human history: the Apollo 11 moon landing. I find the project incredibly inspiring. I tear up every time I think of the words inscribed in the base of the Eagle lander, which was left behind on the lunar surface:

Here men from the planet Earth first set foot upon the Moon July 1969, A.D. We came in peace for all mankind.

Some people speak dismissively of Apollo, saying we ought to spend money on problems here on Earth rather than going to space. I wasn’t alive when Armstrong and Aldrin walked on the moon, but from what I gather it was a momentous event that brought the whole world together. I’ve only experienced that degree of global cohesion in my lifetime due to tragic events (E.g., 9/11, the 2004 Indonesian tsunami, etc.) Apollo stands out as a positive achievement that united the world. We need more challenges like it — especially in our polarized times.

There are lots of lessons in the moon program for anyone tasked with aligning and motivating people towards wickedly complex goals. (That’s why we refer to particularly gnarly challenges as “moonshots.”) Over the last few weeks I’ve been reading books, watching documentaries, and listening to podcasts about Apollo. If you’d like to look into it, here are a few resources that are worth your while:

  • APOLLO 11 (2019) – A breathtaking new documentary assembled from contemporary (yet astonishingly clear) footage and audio sources. I also loved the synthesized soundtrack; like the film, it manages to sound both modern and of its time.
  • 13 Minutes to the Moon – A podcast from the BBC World Service that features interviews with surviving members of the Apollo program, including astronauts, mission controllers, and more.
  • Carrying the Fire: An Astronaut’s Journeys – A memoir by Apollo astronaut Michael Collins. I’m still working through this one, but can already recommend it due to the quality of the writing and the level of detail it provides. (I’ve also posted a few things I learned from it already.)

What Did I Learn?

Like many other people, I have a morning routine. Journaling is an important part of this routine. Every morning, at the start of my day, I set aside a few minutes to reflect on the previous day and what today holds.

I’ve written before about the structure of this journal. Recently, I’ve added a new section: What did I learn? Specifically, what did I learn the day before? (And by implication: How do I need to change my behavior?) I sit with it for a little while, replaying the previous day. These are some other questions that help with this exploration:

  • What did I try that didn’t play out as I expected?
  • What expectations did I have that weren’t met?
  • What expectations were exceeded?
  • What information would help reduce the gap between these expectations and actual outcomes in the future?
  • How can I procure this information?
  • What patterns have I noticed?
  • What happened unexpectedly/serendipitously?
  • What resonances/synchronicities did I notice?

This last question may seem weird; it requires unpacking. Sometimes I’ll be thinking about something and the next day (or sometimes, the same day), I’ll come across the same idea in a podcast, book, article, etc. An echo of sorts. Sometimes these resonances are very peculiar ideas, to the point where I’m startled by the coincidence.

I don’t think there’s anything supernatural at work. The fact that the concept stood out merely suggests that I’m paying attention to it on some deep level. It’s like when you’re thinking of buying a particular model of car and suddenly you see the same model everywhere. Those cars were always out there, but now your mind is primed to pay attention. These could be important signals.

Note these are questions about things that are under my control: my attitudes, expectations, plans, etc. I don’t bother to document things I learned due to events happening in the outside world, out of my control. (E.g., stuff in the news.) Rather, I’m trying to establish a feedback loop that allows me to become more effective over time. Growth calls for introspection; What did I learn? is a useful trigger.