Album art didn’t always exist. In the early 1900s, recorded music was still a novelty, overshadowed by sales of sheet music. Early vinyl records were vastly different from what we think of today: discs were sold individually and could only hold up to four minutes of music per side. Sometimes, only one side of the record was used. One of the most popular records of 1910, for example, was “Come, Josephine, in My Flying Machine”: it clocked in at two minutes and 39 seconds. via Wikipedia The packaging of these records was strictly utilitarian: a brown paper sleeve to protect the record from dust, printed with the name of the record label or the retailer. Rarely did the packaging include any information on the disc inside; the label on the center of the disc was all there was to differentiate one record from another. But as record sales started to show signs of life, music publishers took note. Columbia Records, one of the first companies to sell music on discs, was especially successful. They pioneered the sale of songs in bundles: the individual discs were bound together in packages resembling photo albums, partly to protect the delicate shellac that the records were made of, partly to increase their sales. They resembled photo albums, so Columbia called them “record albums.” There were many more technological breakthroughs that made it possible to mass-manufacture and distribute music throughout the world at affordable prices. The five-minute-long 78 rpm discs were replaced by 20-minute discs that ran at 33 ⅓ rpm, which were replaced by the hour-long 12″ LP we know today. Delicate shellac was replaced by the more resilient (and cheaper) vinyl. Both recording technology and consumer electronics were always evolving, allowing more dynamic music to fit into smaller packages and be played on smaller, higher-fidelity stereos. The invention of album art can get lost in the story of technological mastery. But among all the factors that contributed to the rise of recorded music, it stands as one of the few that was wholly driven by creators themselves. Album art — first as marketing material, then as pure creative expression — turned an audio-only medium into a multi-sensory experience. This is the story of the people who made music visible. The prophet: Alex Steinweiss Alex Steinweiss was born in 1917, the son of eastern European immigrants. Growing up in Brooklyn, New York, Steinweiss took an early interest in art and earned a scholarship to Parsons School of Design. On graduating, he worked for Austrian designer Joseph Binder, whose bold, graphic posters had influenced design for the first decades of the 1900s. The Most Important Wheels in America, Association of American Railroads (1952) via Moma Joseph Binder, Österreichs Wiederaufbau Ausstellung Salzburg (1933) via Moma Joseph Binder, Air Corps U.S. Army (Winning entry for the MoMA National Defense Poster Competition [Army Air Corps Recruiting]) via Moma After his work with Binder, Steinweiss was hired by Columbia Records to produce promotional displays and ads, but the job didn’t stick. At the outbreak of World War II, he went to work for the Navy’s Training and Development Center in New York City, designing teaching material and cautionary posters. When the war ended, Steinweiss went back to freelancing for Columbia. At a lunch meeting in 1948, company president Ted Wallerstein mentioned that Columbia would soon introduce a new kind of record that, spinning at a slower speed of 33 ⅓ rpm, could hold more music than the older 78 rpm discs. But there was a problem: the smaller, more intricate grooves on the discs were being damaged by the heavy paper sleeves used for the 78s. After the lunch, Steinweiss went to work to create a new, safer jacket for the records. But his vision for the new packaging went beyond just its construction. “The way records were sold was ridiculous,” Steinweiss said. “The covers were brown, tan or green paper. They were not attractive, and lacked sales appeal.” He suggested that Columbia should spend more money on packaging, convinced that eye-catching designs would help sell records.1 His first chance to prove his case was a 1940 compilation by the songwriters Rodgers and Hart — one of the first releases on the new microgroove 33 ⅓ records. For it, he asked the Imperial Theater (located one block west of Times Square) to change the lettering on their marquee to read “SMASH SONG HITS BY RODGERS & HART." Steinweiss had a photographer take a photo, and back in his studio, superimposed “COLUMBIA RECORDS’’ on the image to match the perspective and style of the signage. The last touch, a nod to the graphic abstraction of his mentor Joseph Binder, were orange lines arcing around the marquee in the exact size of the record underneath. Album art was born. Smash Song Hits by Rodgers & Hart via RateYourMusic Steinweiss would go on to design hundreds of covers for Columbia from 1940 to 1945. His methodology was rigorous; the covers went beyond nice pictures to be visual representations of the music itself. Before most people owned a TV set, Steinweiss’s album covers were affordable multi-sensory entertainment. Looking at the album cover and listening to the music created an experience that was more than the sum of its parts. “I tried to get into the subject,” he explains, "either through the music, or the life and times of the composer. For example, with a Bartók piano concerto, I took the elements of the piano—the hammers, keys, and strings—and composed them in a contemporary setting using appropriate color and rendering. Since Bartók is Hungarian, I also put in the suggestion of a peasant figure.” via RateYourMusic Steinweiss was prophetic: His colorful compositions sold records. Newsweek reported that sales of Bruno Walter’s recording of Beethoven’s “Eroica” symphony increased 895% with its new Steinweiss cover.” 2 Eroica The challenger: Reid Miles From 1940 to 1950, Columbia Records was the dominant force in music sales. Buoyed by Steinweiss’s initial successes, Columbia hired more artists and designers to produce album art. Jim Flora led the charge from 1947–1950 with irreverent illustrations and more daring explorations of typography, and like Steinweiss, his work mirrored the music on the records. During the era, Columbia began to focus much more on popular music. Flora’s campy compositions screamed “this isn’t your parent’s music.” Gene Krupa and His Orchestra via JimFlora.com Jim Flora's cover for Bix and Tram via JimFlora.com Jim Flora's cover for Kid Ory and His Creole Jazz Band via JimFlora.com But while Columbia was focusing on making it into the hit parade, an upstart label was honing in on a sound that would come to define the era; Blue Note Records, founded in 1939, was fixated on the jazz underground. From its founding and throughout the 1950s, Blue Note focused on “hot jazz,” a mutant strain of jazz descending from the big band swing era, often including twangy banjoes, wailing clarinets, and rambunctious New Orleans second-line-style drumming. Founder Alfred Lion wrote the label’s manifesto: Blue Note Records are designed simply to serve the uncompromising expressions of hot jazz or swing, in general. Any particular style of playing which represents an authentic way of musical feeling is genuine expression. … Blue Note records are concerned with identifying its impulse, not its sensational and commercial adornments.3 One way Blue Note stood out from labels like Columbia was their dedication to their artists. Many of the working musicians of the ’50s lived like vampires, waking up after dusk and playing gigs into the early hours of the morning, then rehearsing until dawn. Blue Note would record their artists in the pre-dawn hours, giving musicians time to rest up before their next night’s gigs started. Art Blakey, Thelonius Monk, Charlie Parker, Dizzy Gillespie, and John Coltrane are household names now; but then, because of their drinking, drug use, and frenetic schedules, labels wouldn’t work with them. Blue Note embraced them, feeding their fires of creative innovation and creating an updraft for the insurgency of jazz to come. Album art was one more revolutionary way for Blue Note to explore “genuine expression.” Just as they fostered talented musicians, they’d give young designers a chance to shine. Alfred Lion’s childhood friend Francis Wolff had joined the label as a producer and photographer; he’d shoot candid portraits of the musicians as they worked. Then, designers like Paul Bacon, Gil Mellé (himself a musician), and John Hermansader would pair Wolff’s black-and-white photos with a single, bright color, then juxtapose them with stark, sans-serif type. Genius of Modern Music Vol. 1 via Deep Groove Mono Gil Mellé's cover featuring Francis Wolff's photography for his band's New Faces — New Sounds via Deep Groove Mono John Hermansader's cover featuring Francis Wolff's photography for George Wallington's Showcase via Deep Groove Mono As the 1960s approached, the musicians Blue Note worked so hard to cultivate were forging new styles, leaving behind the swing-era pretense of jazz as dance music. Charlie Parker and Bud Powell kept speeding up the tempo and stuffing more chords into progressions. Max Roach started playing the drums like a boxer, bobbing and weaving around the beat with skittering cymbals, waiting for the right moment to land a single monumental “thud” of a kick drum. Without the drums keeping a steady rhythm, bass players like Milt Hinton and Gene Ramey had to furiously mark out time with eighth notes, traversing chords by plucking up and down the scale. This was bebop, and it was musicians’ music. Blue Note’s ethos of artistic integrity was the perfect Petri dish for virtuosic musicians to develop innovative sounds — they worked in small ensembles, often just five players, constantly scrambling and re-arranging instrumentation, playing harder and faster and louder. Then, around 1955, just as Blue Note was hitting its stride, Wolff met a 28-year-old designer named Reid Miles. Miles had recently moved to New York and had been working for John Hermansader at Esquire magazine. He was a big fan of classical music but wasn’t so interested in jazz. Wolff convinced Miles to start designing covers for Blue Note all the same and kicked off one of the most influential partnerships in modern design. The first cover Miles created was for vibraphone player Milt Jackson; it picked up from the established art style, with Wolff’s photos and a single bright hue. But the type was even more exaggerated, and the photo took up more than half the cover. White dots overlayed on Jackson’s mallets were the perfect abstraction of the staccato tones of the vibraphone. It’s a great cover, but it was just a hint of what was to come. via Ariel Salminen A common theme of Miles’ covers was the emphasis on Wolff’s photography. We’re familiar with these iconic images today, but at the time they were revolutionary; before, black musicians like Louis Armstrong and Ella Fitzgerald were portrayed in tuxedos and evening gowns, posed smiling genially or laughing, rendered so as to not offend the largely white listening audience. Wolff’s portraits were candid, realistic, showing black musicians at work. For example, the cover for Art Blakey’s The Freedom Rider shows Blakey lost in a moment, almost entirely obscured by a cymbal. The drummer is smoking a cigarette, but it’s barely hanging onto the corner of his lip — his mouth is half-open, his brows clenched in a moment of agony or ecstasy. Miles would let the photo fill up the entire cover, cramming the name of the record into whatever empty space was available. The Freedom Rider via London Jazz Collector Miles sometimes reversed this relationship, pioneering the use of typography to convey the spirit of the music. His cover for Jackie McLean’s It’s Time! is composed of an edge-to-edge grid of 243 exclamation marks; a postage stamp picture of McLean graces the upper corner, almost a punchline. Lee Morgan’s The Rumproller is another type-only cover, this time with the title smeared out from corner to corner, like it was left on a hot dashboard for the day. Larry Young’s Unity has no photo at all; the four members of the quartet become orange dots resting in (or bubbling out of) the bowl of the U. It's Time via Ariel Salminen Reid Miles' cover for Lee Morgan's The Rumproller via Fonts in Use Reid Miles' cover for Larry Young's Unity Miles fulfilled the Blue Note manifesto. His album covers pushed the envelope of graphic design just as the artists on the records inside continued to break new ground in jazz. With the partnership of Miles and Wolff, alongside Alfred Lion’s commitment to artistic integrity, Blue Note became the standard-bearer for jazz. Columbia Records couldn’t help but notice. Even though Blue Note wasn’t nearly as commercially successful as Columbia, their willingness to take risks had established them as a much more sophisticated, innovative, and creative label; to compete for the best talent, Columbia would need to find a way to win the attention of both artists and listeners. The master: S. Neil Fujita Sadamitsu Fujita was born in 1921 in Waimea, Hawaii. He was assigned the name Neil in boarding school — leading up to World War II, anti-Japanese sentiment was rampant, especially in Hawaii. Fujita moved to LA to attend art school, but his studies were cut short in 1942 when Franklin Roosevelt signed executive order 9066, allowing the imprisonment of Japanese Americans living on the west coast. Fujita was sent to Wyoming, where he enlisted in the 442nd Regimental Combat Team. Before the war was over, he’d see combat in Italy, France, and the Pacific theater. After the war, Fujita finished his studies in LA. He quickly made a name for himself in the advertising world; his résumé landed on the desk of Bill Golden, the art director for CBS, which owned Columbia Records. Alex Steinweiss, the first album artist and Columbia’s ace in the hole, had moved on to RCA. Columbia needed a new direction. Golden called Fujita and asked him to run the art department. Fujita would be building a whole new team, replacing the relationships that Columbia had built with art studios for hire. This wasn’t going to be the hardest part of Fujita’s work; when offering him the job, Golden warned him that he’d experience a lot of racist attitudes still simmering in the wake of World War II.4 Still, Fujita agreed to take the job. Fujita’s first covers fit in with the work that Reid Miles was doing at Blue Note: single-color accents set against black-and-white photography. The Jazz Messengers via Discogs Fujita's cover for Miles Davis' 'Round About Midnight via Discogs In 1959, jazz was leaving the stratosphere. Ornette Coleman was performing what he called “free jazz,” frenetic, inscrutable compositions that drew backlash and praise in equal parts. John Coltrane recorded Giant Steps with a level of virtuosity that even his own bandmates struggled to keep up with. Miles Davis recorded Kind of Blue, which would go on to be regarded as one of the best recordings of all time. Fujita was also breaking ground at Columbia. He was one of the first directors to hire both men and women in a racially integrated office.5 He delegated work, tapping painters, illustrators, and photographers to contribute to covers. Fujita himself trained to be a painter before starting his career in design; he started looking for ways to incorporate his own original paintings into the covers: “We thought about what the picture was saying about the music,” Fujita recalled, “and how we could use that to sell the record. And abstract art was getting popular so we used a lot more abstraction in the designs—with jazz records especially.” He got the perfect opportunity to make his mark with two albums released in 1959: Charles Mingus’s Mingus Ah Um and Dave Brubeck’s Time Out. Mingus Ah Um Fujita's cover for Dave Brubeck's Time Out Fujita’s abstract paintings reflected the pure exuberance of Mingus’ and Brubeck’s music. In the case of Mingus Ah Um, the divisions and intersections spanning the cover read like a beam of light passing through exotic lenses, magnifiers, refractors, and prisms; through his music, Mingus was reflecting on the transition of jazz from popular entertainment to mind-expanding creative exercise. For Time Out, the wheels and rollers spooling out across the page echo the way that Brubeck’s quartet was experimenting with how time signatures could be interlocked, multiplied, and divided to create completely new textures and musical patterns. Fujita’s covers made it plain: Jazz was art. ’59 turned out to be a watershed for both jazz and album art. Brubeck’s Time Out went to #2 on the pop charts in 1961, and was the first jazz LP to sell more than a million copies; “Take Five,” the album’s standout hit, would also become the first jazz single to sell a million copies. For a unique moment in time, the music and art worlds were being propelled forward by a commercially successful record. Fujita’s paintings were making their way into millions of homes, driving sales of records by the vanguards of jazz. Fujita left Columbia records shortly after these major successes. “I wanted to be something other than just a record designer,” he said, “so I left to go on my own.” He’d go on to design the book covers for Truman Capote’s In Cold Blood and Mario Puzo’s The Godfather — when the latter was turned into Francis Coppola’s breakthrough film, Fujita’s design was used for its title and promotional art. But he’d continue to design album covers, creating paintings for each one. Far Out, Near In Fujita's cover for Dony Byrd and Gigi Gryce's Modern Jazz Perspective Fujita's cover for Columbia's recording of Glenn Gould performing Berg, Křenek, and Schoenberg. The next generation As jazz continued to evolve throughout the ’60s and ’70s, melding with rock ’n roll to produce punk, electronic, R&B, and rap, album art evolved alongside. Packaging became more sophisticated: multi-disc albums came in folding cases called gatefolds, accompanied by booklets of photography and art. New printing techniques allowed for brighter colors, shiny foil stamps, and textured finishes. Budgets for production grew larger and larger. The Beatles’ Sgt. Pepper’s Lonely Hearts Club Band featured an elaborate photo of the band members, 57 life-sized photograph cutouts, and nine wax sculptures. For the first time for a rock EP, the lyrics to the songs were printed on the back of the cover. In another first, the paper sleeve inside was not white but a colorful abstract pattern instead. Also inside was a sheet of cardboard cutouts, including a postcard portrait of Sgt. Pepper, a fake mustache, sergeant stripes, lapel badges, and a stand-up cutout of the Beatles themselves. The zany campiness of Sgt. Pepper’s could only be matched by an absurd gift box full of toys and games. The stark loneliness of the Beatles’ next album would be paired with a plain white cover, without even ink to fill in the impression of the words “The Beatles” on the front. Sgt. Pepper's Lonely Hearts Club Band, designed by Jann Haworth and Peter Blake and photographed by Michael Cooper The cover of The Beatles, designed by Richard Hamilton via Reddit The most famous artists and designers of each generation would try their hand at album art. Salvador Dali, Andy Warhol, Saul Bass, Keith Haring, Annie Leibovitz, Jeff Koons, Shepard Fairey, and Banksy would all create work for albums. Some of those pieces would become the most recognizable ones in an artist’s catalog. Greatest Hits by The Modern Jazz Quartet Andy Warhol's cover for The Velvet Underground & Nico via Leo Reynolds Saul Bass's cover for Frank Sinatra Conducts Tone Poems of Color via Moma Keith Haring's cover for David Bowie's Without You Annie Leibovitz and Andrea Klein's cover for Bruce Springsteen's Born In The USA Jeff Koons' cover for Lady Gaga's Artpop Shepard Fairey's cover for The Smashing Pumpkins' Zeitgeist Banksy's cover for Blur's Think Tank None of this would have been possible without the contributions of Alex Steinweiss, Jim Flora, Paul Bacon, Gil Mellé, John Hermansader, Reid Miles, S. Neil Fujita, and others. If not for the arms race between Columbia Records and Blue Note for the best art and the best artists of the ’50s, many artists would never have found their career. And in some cases, an album like The Rolling Stones’ Sticky Fingers would be remembered more for its art than for its music. When music was first pressed into discs, design was less than an afterthought. Today, album art is an extension of music itself. Footnotes & References https://www.nytimes.com/2011/07/20/business/media/alex-steinweiss-originator-of-artistic-album-covers-dies-at-94.html ↩︎ https://web.archive.org/web/20120412033422/http://www.adcglobal.org/archive/hof/1998/?id=318 ↩︎ https://web.archive.org/web/20080503055603/https://www.bluenote.com/History.aspx ↩︎ https://www.hellerbooks.com/pdfs/voice_s_neil_fujita.pdf ↩︎ https://www.nationalww2museum.org/war/articles/s-neil-fujita ↩︎

Interfaces are becoming less dense. I’m usually one to be skeptical of nostalgia and “we liked it that way” bias, but comparing websites and applications of 2024 to their 2000s-era counterparts, the spreading out of software is hard to ignore. To explain this trend, and suggest how we might regain density, I started by asking what, exactly, UI density is. It’s not just the way an interface looks at one moment in time; it’s about the amount of information an interface can provide over a series of moments. It’s about how those moments are connected through design decisions, and how those decisions are connected to the value the software provides. I’d like to share what I found. Hopefully this exploration helps you define UI density in concrete and useable terms. If you’re a designer, I’d like you to question the density of the interfaces you’re creating; if you’re not a designer, use the lens of UI density to understand the software you use. Visual density We think about density first with our eyes. At first glance, density is just how many things we see in a given space. This is visual density. A visually dense software interface puts a lot of stuff on the screen. A visually sparse interface puts less stuff on the screen. Bloomberg’s Terminal is perhaps the most common example of this kind of density. On just a single screen, you’ll see scrolling sparklines of the major market indices, detailed trading volume breakdowns, tables with dozens of rows and columns, scrolling headlines containing the latest news from agencies around the world, along with UI signposts for all the above with keyboard shortcuts and quick actions to take. A screenshot of Terminal’s interface. Via Objective Trade on YouTube Craigslist is another visually dense example, with its hundreds of plain links to categories and spartan search-and-filter interface. McMaster-Carr’s website shares similar design cues, listing out details for many product variations in a very small space. Screenshots of Craigslist's homepage and McMaster-Carr's product page circa 2024. You can form an opinion about the density of these websites simply by looking at an image for a fraction of a second. This opinion is from our subconsciousness, so it’s fast and intuitive. But like other snap judgements, it’s biased and unreliable. For example, which of these images is more dense? Both images have the same number of dots (500). Both take up the same amount of space. But at first glance, most people say image B looks more dense.1 What about these two images? Again, both images have the same number of dots, and are the same size. But organizing the dots into groups changes our perception of density. Visually density — our first, instinctual judgement of density — is unpredictable. It’s impossible to be fully objective in matters of design. But if we want to have conversations about density, we should aim for the most consistent, meaningful, and useful definition possible. Information density In The Visual Display of Quantitative Information, Edward Tufte approaches the design of charts and graphs from the ground up: Every bit of ink on a graphic requires reason. And nearly always that reason should be that the ink presents new information. Tufte introduces the idea of “data-ink,” defined as the useful parts of a given visualization. Tufte argues that visual elements that don’t strictly communicate data, whether it’s a scale value, a label, or the data itself — should be eliminated. Data-ink isn’t just the space a chart takes up. Some charts use very little extraneous ink, but still take up a lot of physical space. Tufte is talking about information density, not visual density. Information density is a measurable quantity: to calculate it, you simply divide the amount of “data-ink” in a chart by the total amount of ink it takes to print it. Of course what is and is not data-ink is somewhat subjective, but that’s not the point. The point is to get the ratio as close to 1 as possible. You can increase the ratio in two ways: Add data-ink: provide additional (useful) data Remove non-data-ink: erase the parts of the graphic that don’t communicate data Tufte's examples of graphics with a low data-ink ratio (first) and a high one (second). Reproduced from Edward Tufte's The Visual Display of Quantitative Information There’s an upper limit to information density, which means you can subtract too much ink, or add too much information. The audience matters, too: A bond trader at their 4-monitor desk will have a pretty high threshold; a 2nd grader reading a textbook will have a low one. Information density is related to visual density. Usually, the higher the information density is, the more dense a visualization will look. For example, take the train schedule published by E.J. Marey in 18852. It shows the arrival and departure times of dozens of trains across 13 stops from Paris to Lyon. The horizontal axis is time, and the vertical axis is space. The distance between stops on the chart reflects how far apart they are in the real world. The data-ink ratio is close to 1, allowing a huge amount of information — more than 260 arrival and departure times — to be packed into a relatively small space. The train schedule visualization published by E.J. Marey in 1885. Reproduced from Edward Tufte's The Visual Display of Quantitative Information Tufte makes this idea explicit: Maximize data density and the [amount of data], within reason (but at the same time exploiting the maximum resolution of the available data-display technology). He puts it more succinctly as the “Shrink Principle”: Graphics can be shrunk way down Information density is clearly useful for charts and graphs. But can we apply it to interfaces? The first half of the equation — information — applies to screens. We should maximize the amount of information that each part of our interface shows. But the second half of the equation — ink — is a bit harder to translate. It’s tempting to think that pixels and ink are equivalent. But any interface with more than a few elements needs separators, structural elements, and signposts to help a user understand the relationship each piece has to the other. It’s also tempting to follow Tufte’s Shrink Principle and try to eliminate all the whitespace in UI. But some whitespace has meaning almost as salient as the darker pixels of graphic elements. And we haven’t even touched on shadows, gradients, or color highlights; what role do they play in the data-ink equation? So, while information density is a helpful stepping stone, it’s clear that it’s only part of the bigger picture. How can we incorporate all of the design decisions in an interface into a more objective, quantitative understanding of density? Design density You might have already seen the first challenge in defining density in terms of design decisons: what counts as a design decision? In UI, UX, and product design, we make many decisions, consciously and subconsciously, in order to communicate information and ideas. But why do those particular choices convey the meaning that they do? Which ones are superlative or simply aesthetic, and which are actually doing the heavy lifting? These questions sparked 20th century German psychologists to explore how humans understand and interpret shapes and patterns. They called this field “gestalt,” which in German means “form.” In the course of their exploration, Gestalt psychologists described principles that describe how some things appear orderly, symmetrical, or simple, while others do not. While these psychologists weren’t designers, in some sense, they discovered the fundamental laws of design: Proximity: we perceive things that are close together a comprising a single group Similarity: objects that are similar in shape, size, color, or in other ways, appear related to one another. Closure: our minds fill in gaps in designs so that we tend to see whole shapes, even if there are none Symmetry: if we see shapes that are symmetrical to each other, we perceive them as a group formed around a center point Common fate: when objects move, we mentally group the ones that move in the same way Continuity: we can perceive objects as separate even when they overlap Past experience: we recognize familiar shapes and patterns even in unfamiliar contexts. Our expectations are based on what we’ve learned from our past experience of those shapes and patterns. Figure-ground relationship: we interpret what we see in a three-dimensional way, allowing even flat 2d images to have foreground and background elements. Examples of the princples of proximity (left), similarity (center), and closure (right). Gestalt principles explain why UI design goes beyond the pixels on the screen. For example: Because of the principle of similarity, users will understand that text with the same size, font, and color serves the same purpose in the interface. The principle of proximity explains why when a chart is close to a headline, it’s apparent that the headline refers to the chart. For the same reasons, a tightly packed grid of elements will look related, and separate from a menu above it separated by ample space. Thanks to our past experience with switches, combined with the figure-ground principle, a skeuomorphic design for a toggle switch will make it obvious to a user how to instantly turn on a feature. So, instead of focusing on the pixels, we think of design decisions as how we intentionally use gestalt principles to communicate meaning. And like Tufte’s data-ink ratio compares the strictly necessary ink to the total ink used to print a chart, we can calculate a gestalt ratio which compares the strictly necessary design decisions to the total decisions used in a design. This is design density. Four different treatments of the same information, using different types and amounts of gestalt principles. Which is the most dense? This is still subjective: a design decision that seems necessary to some might be superfluous to others. Our biases will skew our assessment, whether they’re personal tastes or cultural norms. But when it comes to user interfaces, counting design decisions is much more useful than counting the amount of data or “ink” alone. Design density isn’t perfect. User interfaces exist to do work, to have fun, to waste time, to create understanding, to facilitate personal connections, and more. Those things require the user to take one or more actions, and so density needs to look beyond components, layouts, and screens. Density should comprise all the actions a user takes in their journey — it should count in space and time. Density in time Just like the amount of stuff in a given space dictates visual density, the amount of things a user can do in a given amount of time dictates temporal — time-wise — density. Loading times are the biggest factor in temporal density. The faster the interface responds to actions and loads new pages or screens, the more dense the UI is. And unlike 2-dimensional whitespace, there’s almost no lower limit to the space needed between moments in time. Bloomberg’s Terminal loads screens full of data instantaneously With today’s bloated software, making a UI more dense in time is more impactful than just squeezing more stuff onto each screen. That’s why Bloomberg’s Terminal is still such a dominant tool in the financial analysis space; it loads data almost instantaneously. A skilled Terminal user can navigate between dozens of charts and graphs in milliseconds. There are plenty of ways to cram tons of financial data into a table, but loading it with no latency is Terminal’s real superpower. But say you’ve squeezed every second out of the loading times of your app. What next? There are some things that just can’t be sped up: you can’t change a user’s internet connection speed, or the computing speed of their CPU. Some operations, like uploading a file, waiting for a customer support response, or processing a payment, involve complex systems with unpredictable variables. In these cases, instead of changing the amount of time between tasks, you can change the perception of that time: Actions less than 100 milliseconds apart will feel simultaneous. If you tap on an icon and, 100ms later, a menu appears, it feels like no time at all passed between the two actions. So, if there’s an animation between the two actions — the menu slides in, for example — the illusion of simultaneity might be broken. For the smallest temporal spaces, animations and transitions can make the app feel slower.3 Between 100 milliseconds and 1 second, the connection between two actions is broken. If you tap on a link and there’s no change for a second, doubt creeps in: did you actually tap on anything? Is the app broken? Is your internet working? Animations and transitions can bridge this perceptual gap. Visual cues in these spaces make the UI feel more dense in time. Gaps between 1 and 10 seconds can’t be bridged with animations alone; research4 shows that users are most likely to abandon a page within the first 10 seconds. This means that if two actions are far enough apart, a user will leave the page instead of waiting for the second action. If you can’t decrease the time between these actions, show an indeterminate loading indicator — a small animation that tells the user that the system is operating normally. Gaps between 10 seconds and 1 minute are even harder to fill. After seeing an indeterminate loader for more than 10 seconds, a user is likely to see it as static, not dynamic, and start to assume that the page isn’t working as expected. Instead, you can use a determinate loading indicator — like a larger progress bar — that clearly indicates how much time is left until the next action happens. In fact, the right design can make the waiting time seem shorter than it actually is; the backwards-moving stripes that featured prominently in Apple’s “Aqua” design system made waiting times seem 11% shorter.5 For gaps longer than 1 minute, it’s best to let the user leave the page (or otherwise do something else), then notify them when the next action has occurred. Blocking someone from doing anything useful for longer than a minute creates frustration. Plus, long, complex processes are also susceptible to error, which can compound the frustration. In the end, though, making a UI dense in time and space is just a means to an end. No UI is valuable because of the way it looks. Interfaces are valuable in the outcomes they enable — whether directly associated with some dollar value, in the case of business software, or tied to some intangible value like entertainment or education. So what is density really about, then? It’s about providing the highest value outcomes in the smallest amount of time, space, pixels, and ink. Density in value Here’s an example of how value density is manifested: a common suggestion for any form-based interface is to break long forms into smaller chunks, then put those chunks together in a wizard-type interface that saves your progress as you go. That’s because there’s no value in a partly-filled-in-form; putting all the questions on a single page might look more visually dense, but if it takes longer to fill out, many users won’t submit it at all. This form is broken up into multiple parts, with clear errors and instructions for resolution. Making it possible for users to get to the end of a form with fewer errors might require the design to take up more space. It might require more steps, and take more time. But if the tradeoffs in visual and temporal density make the outcome more valuable — either by increasing submission rate or making the effort more worth the user’s time — then we’ve increased the overall value density. Likewise, if we can increase the visual and temporal density by making the form more compact, load faster, and less error-prone, without subtracting value to the user or the business, then that’s an overall increase in density. Channeling Tufte, we should try to increase value density as much as possible. Solving this optimization problem can have some counterintuitive results. When the internet was young, companies like Craigslist created value density by aggregating and curating information and displaying it in pages of links. Companies like Yahoo and Altavista made it possible to search for that information, but still put aggregation at the fore. Google took a radically different approach: use information gleaned by the internet’s long chains of linked lists to power a search box. Information was aggregating itself; a single text input was all users needed to access the entire web. Google and Yahoo's approach to data, design, and value density hasn't changed from 2001 (when the first screenshots were archived) to 2024 (when the second set of screenshots were taken). The value of the two companies' stocks reflect the result of these differing approaches. The UI was much less visually dense, but more value-dense by orders of magnitude. The results speak for themselves: Google went from a $23B valuation in 2004 to being worth over $2T today — closing in on a 100x increase. Yahoo went from being worth $125B in 2000 to being sold for $4.8B — less than 3% of its peak value.6 Conclusion Designing for UI density goes beyond the visual aspects of an interface. It includes all the implicit and explicit design decisions we make, and all the information we choose to show on the screen. It includes all time and the actions a user takes to get something valuable out of the software. So, finally, a concrete definition of UI density: UI density is the value a user gets from the interface divided by the time and space the interface occupies. Speed, usability, consistency, predictability, information richness, and functionality all play an important role in this equation. By taking account of all these aspects, we can understand why some interfaces succeed and others fail. And by designing for density, we can help people get more value out of the software we build. Footnotes & References This is a very unscientific statement based on a poll of 20 of my coworkers. Repeatability is questionable. ↩︎ The provenance of the chart is interesting. Not much is known about the original designer, Charles Ibry; but what we do know points to even earlier iterations of the design. If you’re interested, read Sandra Rendgen’s fascinating history of the train schedule. ↩︎ I have no scientific backing for this claim, but I believe it’s because a typical blink occurs in 100ms. When we blink, our brains fill in the gap with the last thing we saw, so we don’t notice the blink. That’s is why we don’t notice the gap between two actions that are less than 100ms apart. You can read more about this effect here: Visual Perception: Saccadic Omission — Suppression or Temporal Masking? ↩︎ Nielsen, Jakob. “How Long Do Users Stay on Web Pages?” Nielsen Norman Group, 11 Sept. 2011, https://www.nngroup.com/articles/how-long-do-users-stay-on-web-pages/ ↩︎ Harrison, Chris, Zhiquan Yeo, and Scott E. Hudson. “Faster Progress Bars: Manipulating Perceived Duration with Visual Augmentations.” Carnegie Mellon University, 2010, https://www.chrisharrison.net/projects/progressbars2/ProgressBarsHarrison.pdf ↩︎ HackerNews has pointed out that this is a ridiculous statement. And it is. Of course, value density isn’t the only reason why Google succeeded where Yahoo failed. But as a reflection of how each company thought about their products, it was a good leading indicator. ↩︎

There’s a lot of fear in the air. As AI gets better at design, it’s natural for designers to be worried about their jobs. But I think the question — will AI replace designers? — is a waste of time. Humans have always invented technology to do their work for them and will continue to do so as long as we exist. Let’s use our curiosity and creativity to imagine how technology will help us be better, more efficient, and more impactful. So, in that spirit, I’d like to share a metaphor that I think paints a picture of how the job of design will change in the next decade. Flying by wire Commercial airplanes are some of the most complicated machines humans have ever built. It took all of Wilbur Wright’s skill to fly the first powered airplane for a minute, just 10 feet off the ground. That plane, the Wright Flyer, could carry one person; it weighed 745 pounds with fuel and could reach a height of 30 feet at a maximum speed of 30 miles per hour.1 The Airbus A380, currently the world’s largest commercial airliner, weighs over a million pounds when fully loaded. It can carry up to 853 people, flying up to 43,000 feet at a cruising speed of 561 mph — 85% the speed of sound. Just two people pilot the A380.2 The cockpit of an Airbus A380. Photo by Steve Jurvetson, CC BY 2.0 The A380, and all modern commercial airplanes, wouldn’t exist without something called “fly-by-wire.” Fly-by-wire is a system that translates a pilot’s inputs — changing the throttle to speed up or slow down, controlling pitch and roll with the yoke, turning knobs and dials in the cockpit — into coordinated movements of the airplane’s engines and control surfaces. The first fly-by-wire systems were a veritable nervous system of electric relays and motors; today, they’re sophisticated computers in the belly of the plane. Originally, fly-by-wire had nothing to do with automation. As airplanes got larger, the cables, rods, and hydraulic links connecting the cockpit to the rest of the plane became a monumental design challenge. By replacing those complex, bulky components with electrical wires and switches, airplanes would be lighter and easier to maintain, with more room for passengers and cargo. The first commercial airplane with a fly-by-wire system was the supersonic Concorde jet. At speeds of over Mach 1, it would be almost impossible for a pilot to move the control surfaces of the airplane through sheer mechanical force; fly-by-wire allowed pilots to smoothly operate the plane at any speed. And because sudden changes at top speed could be catastrophic, the fly-by-wire system could use analog circuitry to smooth out a pilot’s inputs. An experimental fly by wire system in the Vought F-8 Crusader using data-processing equipment adapted from the Apollo Guidance Computer As fly-by-wire systems became more common, they went from faithfully transferring pilot’s inputs to interpreting and adjusting them. The Airbus A320, introduced in 1988, featured the first digital (computerized) fly-by-wire system; it included “flight envelope protection,” a system that prevents pilots from taking any action that would cause damage to the airplane. Depending on the speed, altitude, and phase of flight, the fly-by-wire system will ignore certain pilot inputs altogether. Fly-by-wire has been the focus of both scrutiny and praise since its introduction. On one hand, it has saved lives: When US Airways Flight 1549 (an Airbus A320) flew through a flock of birds on takeoff, it lost all power. The pilots had to make an emergency landing in the Hudson river, flying the airplane unusually low and slow, risking putting the plane into an uncontrollable stall. The fly-by-wire system, with its flight envelope protection, ensured the plane could maneuver at the very edge of its capability, leading to a controlled landing with only a few serious injuries for those aboard. On the other hand, fly-by-wire has been criticized for replacing parts of pilots’ expertise. In 2009, Air France Flight 447 (another Airbus A320), crashed in the Atlantic Ocean, killing all 228 passengers and crew. An investigation into the cause of the crash concluded that the autopilot and fly-by-wire protections started to malfunction when ice crystals interfered with the aircraft’s sensors; the pilots, used to flying with the safety of flight envelope protection, couldn’t correct for the errors, stalled the plane, and crashed into the ocean. Whether you think fly-by-wire is a crucial innovation or a crutch, its effect on the airline industry is easy to demonstrate. Bigger planes that fly farther can carry more passengers to more destinations. From 1970 to 2019, the number of airline passengers worldwide has grown over 1,400%, from 310 million to 4.4 billion.3 In the same time period, the number of commercial pilots — pilots holding “commercial” or “airline transport” licenses — has increased 27%, from 208,027 in 1969 to 265,810 in 2019. Pilots’ salaries have stayed consistently high: an average airline captain made about $51,750 a year in 19754, the equivalent to $287,770 in 20235. An airline captain with six years of experience can expect to make $285,460 today.6 Designing by wire Just as fly-by-wire systems have made pilots more efficient (not redundant), AI and automation will make designers more effective. Imagine a design-by-wire system. The job of the designer is to indicate what they want the desired outcome to be. Like a pilot pushing the throttle to make the airplane accelerate, a designer could assemble a wireframe or configure a screen to enable a user to accomplish a task. The design-by-wire system could then interpret the designer’s instructions. The system could change aspects of the design to use the latest design systems components in the correct way. The system could optimize the design to make implementation cheaper, faster, or less prone to bugs. The system could automatically fix accessibility issues, or add information to address accessibility concerns like keyboard shortcuts, screen reader labels, or high-contrast and reduced-motion variations. A designer could list out hypotheses about the design (like “will this convert the most users to paid plans?”), and the system could provide designs for multivariate testing, along with test or research plans. The system could automate QA by testing designs against simulated user behavior, adjusting the designs to cover the wide and unpredictable cases of real user interaction. You can already see these kinds of systems taking shape. Noya promises to take wireframes and turn them into production code using an existing design system. Galileo AI claims to be able to create fully-editable designs from a single text description. Diagram’s Genius aims to provide contextual suggestions in Figma, filling out designs with the click of a button. These are just early tech previews, but they paint a picture of AI becoming a core component of our design tools. At the end of the day, design-by-wire systems are centered around the designer. Like the pilot of an Airbus A380, the designer becomes the operator of a fantastically complicated machine. There is a risk in designing by wire. If designers don’t understand how the system works, they risk losing control, becoming less effective than they were before. That’s why it’s important that we become experts in AI; we don’t have to be able to write the code that drives these tools, but we need to understand the way the systems work. To use the machine to its full potential, the designer has to understand the intricacies of its operation: Pilots, by analogy, train for years in simulators before they step foot in the cockpit of a real airliner. Here’s a few resources you can use to learn more about GPTs, the systems driving the current boom in AI: Stephen Wolfram’s “What is ChatGPT Doing … and Why Does It Work?” is an incredibly in-depth exploration of the technology and concepts, with interactive code. Ted Chiang’s “ChatGPT Is a Blurry JPEG of the Web” uses analogies to explain the strengths and weaknesses of GPT technology. 3Blue1Brown has a 5-part video series explaining the basics of neural networks, including how they are trained. The Coding Train has 26 videos on neural networks, in which Daniel Schiffman builds and explains various components and variations of neural nets. There’s also an accompanying chapter in Schiffman’s book The Nature of Code. All four of the above authors are amazing teachers who mix mathematical depth with intuitive analogies and mental models. Conclusion AI will change our jobs in ways we can’t imagine. This has been happening to airline pilots since the advent of fly-by-wire systems. In the transition to newer, faster, larger, and more efficient airplanes, pilots have needed more and more technical understanding and skill in interacting with the computers that fly their planes. But pilots are still needed. Likewise, designers won’t be replaced; they’ll become operators of increasingly complicated AI-powered machines. New tools will enable designers to be more productive, designing applications and interfaces that can be implemented faster and with less bugs. These tools will expand our brains, helping us cover accessibility and usability concerns that previously took hours of effort from UX specialists and QA engineers. It’ll take years of training to become an expert at designing with these new AI-powered systems. Start now, and you’ll stay ahead of the curve. Wait, and the challenge won’t come from the AI itself; it’ll be other designers — ones who are skilled at AI-powered design — who will come for your job. Footnotes & References “Wright Flyer.” In Wikipedia, February 19, 2023. https://en.wikipedia.org/w/index.php?title=Wright_Flyer&oldid=1140234161. ↩︎ “Airbus A380.” In Wikipedia, February 10, 2023. https://en.wikipedia.org/w/index.php?title=Airbus_A380&oldid=1138648822. ↩︎ “Top 15 Countries with Departures by Air Transport - 1970/2020 -.” Accessed February 20, 2023. https://statisticsanddata.org/data/top-15-countries-with-departures-by-air-transport-1970-2020/. ↩︎ “Industry Wage Survey. Scheduled Airlines.” Scheduled Airlines, Bulletin / Bureau of Labor Statistics, 1977 1972, 2 v. https://catalog.hathitrust.org/Record/009881222. ↩︎ Calculated with https://www.in2013dollars.com/us/inflation/1975?amount=51750 ↩︎ “Major Airline Pilot Salary: First Officer and Captain Pay in 2023 / ATP Flight School.” Accessed February 18, 2023. https://atpflightschool.com/become-a-pilot/airline-career/major-airline-pilot-salary.html. ↩︎

After four months of parental leave, I came back to work and noticed something different. Many of the words, phrases, acronyms, and figures of speech I took for granted no longer held the same meanings. Specifically, the word “platform:” before my time off, I would breeze over it in any presentation or document without a second thought. Now, I find it totally devoid of any meaning. I decided to start sketching out some possible defintions, and quickly uncovered something exciting: platform design isn’t just another flavor of UX or product design. There are challenges, mental models, and requisite skills that set platform design apart. I lead the platform design team;the work that we can do as platform designers gives us extreme leverage in solving user problems. We have the opportunity to make an outsize difference in the experience of our users. What follows is the result of my exploration of what sets platform design apart. If you are a platform designer, too, I hope it gives you an idea of the potential of your work. Interfaces Application designers fit components, modules, containers, and data together to create the best user experience possible. Platform designers additionally focus on the layers between all those elements — the interfaces — to ensure that everything that can be possibly built on the platform has the same high bar of quality. Developers use the concept of an API to plan the way two things fit together (“interface” is the I in API). Good APIs can change the world: TCP/IP enables every computer in the world to communicate with every other. Stripe’s famous “7 lines of code” could connect any piece of software to the complex global banking system. Jeff Bezos’ insistence on API design at Amazon allowed the company to turn its own infrastructure into its most profitable product (AWS). Platform designers have to understand and plan experience APIs: interfaces both in space (how elements appear beside each other, in front of or behind each other, inside or surrounding each other) and in time (how elements or entire screens appear before or after each other, how to communicate causal relationships). With the right interfaces, any application built on the platform will have a great user experience. Incentives Designing applications requires understanding the balance between motivation and friction. It’s almost mathematical: if a user’s motivation is greater than the friction they experience, the user will complete a task. If users aren’t completing a task, you can increase the motivation through marketing and guidance, or decrease the friction through usability improvements or automation. Designing a platform involves the same balancing act, but with an additional variable: whether we intend to or not, we influence the incentives for both application builders and end users. Platform incentives are complex. Take Spotify, for example: they create incentives for artists in the form of paying for each stream of a song. So, in 2014, funk band Vulfpeck released an album on Spotify called Sleepify consisting entirely of 30-second-long silent “songs”. Vulfpeck encouraged fans to play the album on repeat while they slept. After it garnered 5 million streams, Spotify removed the album, but paid the band accordingly; Vulfpeck used the $20,000 it earned to go on tour.1 Incentives are a powerful tool unique to platform design. To create a successful platform, we need to think deeply about all the ways in which incentives can lead to desired outcomes, or ways in which they motivate bad — or, in Vulfpeck’s case, merely mischievous — actors. Emergence Application users usually behave in predictable ways. We can study their tendencies and preferences, then create experiences to fit our observations. Data like task success, retention rate, user sentiment, and engagement tells us how our predictions matched the real world. Over time, by researching and iterating, we come closer to meeting business goals. We can’t always predict platform users’ behavior. The people building applications on the platform and the people using those applications form a feedback loop; both groups develop creative and unexpected ways to use (or abuse) the platform. Think of Twitter users inventing hashtags and @-mentions, or early bulletin board users using punctuation to create emoticons. These ideas spread far beyond their original application, becoming deeply-embedded cross-platform features. This is called emergence. Emergence presents a unique opportunity in design. When behavior is predictable, we design tightly-tuned experiences (“happy paths”) to realize the best outcomes for users. When behavior is emergent, users’ creativity becomes a multiplier on top of our own, exponentially increasing the best outcomes for both users and business. Second-order thinking Application design is all about first-order thinking. A user interacts with the application, and something happens as a result — cause and effect. Causes and effects can be separated by space and time, but their constant tick and tock drives the crucial engagement loop of every successful product. Platform design requires second-order thinking, where first-order effects are causes, too. A great example of this is attributed to Warren Buffett: imagine a crowd watching a parade. A few people stand on their tiptoes — that’s a first-order cause. Now, they can see better — the first-order effect. What happens next? All the people behind them have to stand on their tiptoes, too — that’s the second-order effect. In the end, everyone is worse off, and nobody can see any better.2 Second-order thinking requires creativity. Platform designers have to ask: how will interfaces and incentives create emergent behavior? How will those behaviors change the incentives? What can we build to channel these feedback loops towards our goals? Though these thought exercises will never fully predict the outcomes, without them, a platform is doomed. Case study: Lego Let’s put all these pieces together.3 Lego is one of the most successful toy companies of all time due to their rigorous approach to platform design. Lego bricks are clearly fun to play with, but Lego’s multi-generational success story goes deeper than that — to interfaces, incentives, emergence, and second-order thinking . Interfaces Lego didn’t invent interlocking plastic bricks; Hilary Page, owner of Kidicraft, secured a patent for injection-molded building blocks in 1940. But Lego succeeded, and Kidicraft didn’t. It wasn’t the bricks themselves that mattered. It’s was the way they fit together — their interfaces. The level of precision of a Lego brick is mesmerizing. Manufacturing tolerances (exact to 2 microns, less than the width of a human hair) are so rigorously maintained that every lego brick ever manufactured attaches to every other brick. Pieces fit together and lock tightly, but can be pulled apart easily by a child. Instructions for lego sets also keep children in mind, only using pictures to communicate.4 But the simplicity of the design is misleading: if you have 6 standard lego bricks, you can put them together in 915,103,765 different ways.5 The ingenious design of standard interfaces, together with an ironclad commitment to precise adherence to those standards, is why Lego succeeds. Incentives Lego incentivizes play. Specifically, they encourage builders to (literally) think outside the box, combining pieces from widely different sets to produce new and inventive designs. They do this in both direct and indirect ways, and through both positive and negative interventions: Direct Indirect Positive Sponsored events like Lego Build Day, where builders are encouraged to explore ideas like “take a space ship and rebuild it into a panda bear hammock.” Allowing third parties to sell and resell individual Lego pieces, enabling builders in any part of the world to find any piece they want. Negative Setting clear rules for first-party designers of Lego sets that set the tone for builders: for example, sets can’t require bricks to be assembled in ways that can’t be disassembled later Using trade protections to keep low-quality third-party parts from entering the market, keeping the guarantee of quality for lego bricks high. We can imagine a Lego that allows for parts with unique pieces that don’t fit with others, incentivizing consumers to constantly buy new kits, and locking third parties out of the market. But it’s hard to see how this version of Lego would be as successful. Emergence There are many examples of how Lego users have adapted the system to do things the original designers never intended. In some cases, Lego has even brought those innovations back into the core system. In 1985, a group of computer scientists had a big idea. What if they connected a programming language to physical machines, like Lego creations? Partnering with Lego through the MIT Media Lab, the researchers created Lego Logo, a beginner-friendly robotics programming language that was optimized for creativity. Since then, programmable Legos — “Mindstorms” and “Technics,” offshoots of the original Lego Logo products — have been used to build everything from a Rubik’s Cube-solving robot to customizable prosthetics for children. Lego also encourages emergence in passive ways. Take Brickit, an app created by Leonid Aleksandrov. Snap a photo of your Lego pieces and it’ll show you what you can build, with 3D instructions. You can even scan finished creations and Brickit will reverse-engineer the instructions so you can share your ideas with others. Surprisingly, Lego hasn’t sued Aleksandrov – they’ve allowed Brickit and its community of creators to flourish. Second-order thinking Lego is no stranger to second-order thinking. As a toy company, they are aware of the impact their decisions have on the lives of children and the planet. Specifically, Lego has avoided selling sets that include military equipment or vehicles. No tanks, no bomber planes, no soldiers with guns. The ban extends beyond finished designs — for a long time, the company didn’t even sell gray-colored bricks, the first choice for making military machines. This self-imposed restriction is especially impressive in the light of how profitable war-like toys can be; think of Nerf guns, green army men, and first-person shooter video games.6 Another example of second-order thinking lies in Lego’s plans for the future. Lego bricks are made of ABS, a petroleum-derived plastic. ABS can’t be recycled, meaning Lego produces more than 100,000 metric tons of single-use plastic every year. To reduce their environmental impact, Lego has invested hundreds of millions of dollars in sustainability, resulting in plant-derived plastic flora, and fully recycled paper packaging. And in 2021, after 3 years of research and 250 material tests, a fully recycled brick — made of PET from used water bottles — was ready for mass production.7 tl;dr Interfaces, incentives, emergence, and second-order thinking constitute the biggest differences between platform and application design. Interfaces are the points of contact between elements, where simplicity and flexibility can lead to efficiency at scale. Incentives drive the motivation of both platform- and end- users. By designing incentives, we can re-invest users’ energy, amplifying desired outcomes and preventing undesired results. Emergence is the open-ended feedback loop that platforms can create and maintain. By designing for emergence, not against it, we enable users to discover applications we never imagined. Second-order thinking lets us plan for, and potentially tame, the complexities that threaten to turn platforms into dead ends — or worse. By putting these concepts together, designers can take advantage of the unique leverage platform design provides, efficiently solving thorny problems at scale. Footnotes & References “How Funk Band Vulfpeck Took on Spotify.” CNBC, 2 Apr. 2018, www.cnbc.com/video/2018/04/02/how-funk-band-vulfpeck-took-on-spotify.html. ↩︎ “Second-Order Problem.” Farnam Street, April 7, 2019. https://fs.blog/second-order/. ↩︎ Pun fully intended. ↩︎ The instructions for the largest lego set (The Millennium Falcon) run over 450 pages, all without a single word. ↩︎ Eilers, Søren. “A Lego Counting Problem.” University of Copenhagen, April 7, 2005. https://web.math.ku.dk/~eilers/lego.html. ↩︎ Lendon, Brad. “Lego Won’t Make Modern War Machines, but Others Are Picking up the Pieces.” CNN, December 13, 2020. https://www.cnn.com/style/article/lego-military-sets-intl-hnk-dst/index.html. ↩︎ White, Jeremy. “How Lego Perfected the Recycled Plastic Brick.” Wired, July 11, 2021. https://www.wired.com/story/lego-recycled-plastic-brick/. ↩︎