The Flash and Barry Allen, the fastest man dead, raced into venues on June 16, 2023. He stayed put long enough for the film to recover its manufacturing budget, but not its advertising budget, and it quickly vanished, officially putting an end to the pre-James Gunn DCEU. It [ …] according to director Andy Muschietti.
The Flash’s Flop’s Fragrances are the subject of the blog Den of Geek Next Batman Director Blames Bandwagons.
Madeleine McGraw portrays a young girl in The Black Phone and its new movie with great role. And she’s prepared to play a second time. McGraw spoke with The Hollywood Reporter about taking the lead role in Black Phone 2, and she launched her demand like she was launching a web. ]… ]
On Den of Geek, the second article Black Phone Star Stakes Her Claim for a Marvel Role.
The Witcher winter 4 will feature significant changes, the most obvious of which being that the show will no longer have its lead actor for the movie’s last two months, with Liam Hemsworth, the Hunger Games professional, actually taking over the role of Geralt of Rivia from Henry Cavill. No single truly knows […]…
The Witcher’s Geralt is really going to smile now, according to Den of Geek‘s first article.
Although I’m not certain when I first heard this statement, it has over the centuries stuck in my mind. How do you generate solutions for scenarios you can’t think? Or create items that are functional on products that have not yet been created?
When I first started designing sites, my go-to technology was Photoshop. I started by making a structure for a 960px canvas that I would later add willing to. The growth phase was about attaining pixel-perfect precision using set widths, fixed levels, and absolute setting.
All of this was altered by Ethan Marcotte’s 2010 content in A List Off entitled” Responsive Web Design.” I was sold on responsive pattern as soon as I heard about it, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.
My first encounter with flexible style didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. You can’t really put responsiveness at the end of a job, which I learned the hard way. To make smooth design, you need to prepare throughout the style phase.
Making flexible or smooth websites has always been about removing restrictions and creating content that can be viewed on any system. It relies on the use of percentage-based design, which I immediately achieved with local CSS and power groups:
.column-span-6 { width: 49%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-4 { width: 32%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-3 { width: 24%; float: left; margin-right: 0.5%; margin-left: 0.5%;}Therefore using Sass to re-use repeated slabs of code and transition to more semantic premium:
.logo { @include colSpan(6);}.search { @include colSpan(3);}.social-share { @include colSpan(3);}The next ingredient for flexible design is press queries. Without them, content would shrink to fit the available space, regardless of whether it remained readable ( The exact opposite issue resulted from the development of a mobile-first approach ).
Media concerns prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on.
For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.
String premium was a mainstay of early flexible design, present in all the frequently used systems like Bootstrap and Skeleton.
1 of 7 2 of 7 3 of 7 4 of 7 5 of 7 6 of 7 7 of 7 Another difficulty arose as I moved from a design firm building websites for smaller- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those capacities, I began to work many more with washable pieces.
Our rely on multimedia queries resulted in parts that were tied to frequent screen sizes. If the goal of part libraries is modify, then this is a real problem because you can just use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process never really hitting that “devices that don’t already occur” goal.
Then there’s the problem of space. Media concerns allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?
Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. There are workarounds for JavaScript, but they can lead to dependencies and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.
One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is an important step in moving toward a form of component-based design that works at any size on any device.
In other words, responsive elements are meant to replace responsive layouts.
Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.
My issue is that layout is still used to determine when a design needs to adapt. This approach will always be restrictive, as we will still need pre-defined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component?
A component library that is disconnected from context and real content is probably not the best place to make that choice.
As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?
In this example, the dimensions of the container are not what should dictate the design, rather, the image is.
Without having strong cross-browser support for them, it’s difficult to say for certain whether container queries will be a success story. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might need to modify these elements in order to fit our content.
Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.
.wrapper { display: grid; grid-template-columns: repeat(auto-fit, 450px); gap: 10px;}The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space.
.wrapper { display: flex; flex-wrap: wrap; justify-content: space-between;}.child { flex-basis: 32%; margin-bottom: 20px;}You don’t need to wrap elements in container rows, which is the biggest benefit of all of this. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.
This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid.
Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?
Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.
.wrapper { display: grid; grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); grid-template-rows: auto 1fr auto; gap: 10px;}.sub-grid { display: grid; grid-row: span 3; grid-template-rows: subgrid; /* sets rows to parent grid */}CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. Subgrid is only supported in Firefox at the time of writing, but the above code can be implemented behind an @supports feature query.
I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional CSS features used to create layouts that respond to available space.
Responsive layouts have flexible columns using percentages. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.
frunits is a statement that says,” I want you to distribute the extra space in this way, but… don’t ever make it smaller than the content that is inside of it.”
—Jen Simmons,” Designing Intrinsic Layouts”
Intrinsic layouts can also make use of a mix of fixed and flexible units, letting the content choose how much space it occupies.
What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Without having the same breakpoints or the same amount of content as in the previous implementation, components and patterns can be lifted and reused.
We can now create designs that adapt to the space they have, the content within them, and the content around them. We can create responsive components without relying on container queries using an intrinsic approach.
This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. It’s another “everything changed” moment for me.
But it doesn’t seem to be moving quite as fast, I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention.
One possible explanation for that is that I now work for a sizable company, which is quite different from the role I held as a design agency in 2010! In my agency days, every new project was a clean slate, a chance to try something new. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase.
Another possibility is that I now feel more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s about applying existing skills and CSS knowledge in a unique way.
Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change.
Ten years ago, responsive grid systems were everywhere. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.
Because having a selection of units is a hindrance when creating layout templates, intrinsic design and frameworks do not work together quite as well. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.
And then there are design tools. We probably all used Photoshop templates for desktop, tablet, and mobile devices to drop designs into and demonstrate how the site would look at all three stages at some point in our careers.
How do you do that now, with each component responding to content and layouts flexing as and when they need to? Personally, I’m a big fan of this kind of design in the browser.
The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. It’s not ideal to implement this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it continue to function? Is the design too reliant on the current content?
Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.
Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account changes in content, like in our earlier Subgrid card illustration, which allowed the cards to modify both their own content and that of their sibling components.
Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.
Instead of the dated markup tricks below,
First line of text with different styling...
—we can target content based on where it appears.
.element::first-line { font-size: 1.4em;}.element::first-letter { color: red;}Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().
This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.
Directional variables must be set in the Sass version.
$direction: rtl;$opposite-direction: ltr;$start-direction: right;$end-direction: left;These variables can be used as values—
body { direction: $direction; text-align: $start-direction;}—or as real estate.
margin-#{$end-direction}: 10px;padding-#{$start-direction}: 10px;However, now we have native logical properties, removing the reliance on both Sass ( or a similar tool ) and pre-planning that necessitated using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.
margin-block-end: 10px;padding-block-start: 10px;There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.
Like the earlier examples, these properties help to build out designs that aren’t constrained to one language, the design will reflect the content’s needs.
We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative.
For min() this means setting a fluid minimum value and a maximum fixed value.
.element { width: min(50%, 300px);}The element in the figure above will be 50 % of its container as long as the element’s width doesn’t exceed 300px.
For max() we can set a flexible max value and a minimum fixed value.
.element { width: max(50%, 300px);}Now the element will be 50 % of its container as long as the element’s width is at least 300px. This means we can set limits but allow content to react to the available space.
The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.
.element { width: clamp(300px, 50%, 600px);}This time, the element’s width will be 50 % of its container’s preferred value, with no exceptions for 300px and 600px.
With these techniques, we have a content-first approach to responsive design. We can separate content from markup, meaning the changes users make will not affect the design. By making plans for unanticipated changes in language or direction, we can begin to future-proof designs. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.
Thanks to what we’ve discussed so far, we can cover device flexibility by changing our approach, designing around content and space instead of catering to devices. But what about that last bit of Jeffrey Zeldman’s quote,”… situations you haven’t imagined”?
Rather than someone using a mobile phone and moving through a crowded street in glaring sunshine, it’s a very different design to be done for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.
This is why making a choice is so crucial. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.
Thankfully, there is a lot we can do to provide choice.
” There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure”.
” I Used the Web for a Day on a 50 MB Budget.”
Chris Ashton
One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. However, our users may be commuters using smaller mobile devices that may experience disconnects in connectivity in the real world. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.
The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.
The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience.
There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.
With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make.
So how can we put users in control?
Media concerns have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.
We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. These checks allow us to provide options that suit more than one scenario, it’s less about one-size-fits-all and more about serving adaptable content.
The Level 5 spec for Media Queries is still being developed at this writing. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.
For instance, a light-level feature allows you to alter a user’s style when they are in the sun or in the dark. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.
@media (light-level: normal) { --background-color: #fff; --text-color: #0b0c0c; }@media (light-level: dim) { --background-color: #efd226; --text-color: #0b0c0c;}Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable.
Media concerns like this go beyond choices made by a browser to grant more control to the user.
In the end, we should always anticipate that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.
We can design for content, but we can’t do it the same way we have for this constantly changing landscape. By putting content first and allowing that content to adapt to whatever space surrounds it, we can create more robust, flexible designs that increase the longevity of our products.
A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. There is so much more we can do to adopt a more intrinsic approach, from responsive components to fixed and fluid units. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.
When it comes to unexpected circumstances, we need to make sure our goods are accessible whenever and wherever needed. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries.
Good design for the unexpected should allow for change, provide choice, and give control to those we serve: our users themselves.
We’ve been conversing for a long time. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have conversations started to be written, and only recently have we outsourced them to the system, a system that exhibits a significantly higher affinity for written communications than for the vernacular rigors of spoken language.
Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the complexity of human statement, including the disfluencies and pauses, the gestures and body speech, and the variations in expression choice and spoken dialect, which may impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.
In contrast, written language develops its own fossil record of dated terms and phrases as we report it and keep utilization long after they are no longer needed in spoken communication ( for example, the welcome” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for machines to interpret and know.
Spoken language is not a luxury in this regard. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Our spoken language reaches far beyond what the written word can ever deliver, whether it’s rapid-fire, low-pitched, high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.
We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too ( ). We typically strike up a discussion by:
These three categories, which I refer to as transactional, informational, and prosocial, also apply to virtually every voice interaction: a single conversation that begins with the voice interface’s first greeting and ends with the user leaving the interface. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but it may not always be one voice interaction.
Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. Users are also debating whether or not they prefer the kind of organic human conversation that starts with a prosocial voiceover and progresses seamlessly into other types. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users ‘ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ( ).
A voice interface can also have two types of conversations we can have with one another that are both transactional and informational, each learning something new ( “discuss a musical” ).
When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza ( generously topped with pineapple, as it should be ).
Alison: Hey, how are things going?
Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?
Alison: Can I get a pizza from Hawaii with extra pineapple.
Burhan: Sure, what size?
Large, Alison.
Burhan: Anything else?
Alison: No thanks, that’s it.
Burhan: Something to drink?
Alison, I’ll have a bottle of Coke.
Burhan: You got it. It will cost about$ 15 and take fifteen minutes to complete.
Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Conversations that are transactional have certain characteristics: they are direct, concise, and cost-effective. They quickly dispense with pleasantries.
Meanwhile, some conversations are primarily about obtaining information. Alison might only want to place an order at Crust Deluxe, but she might not want to leave without a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.
Alison: Hey, how are things going?
Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?
Alison: Can I ask a few questions?
Burhan: Of course! Go right ahead.
Do you have any halal options on the menu, Alison?
Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you considering any additional dietary restrictions?
Alison: What about gluten-free pizzas?
Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you, without a problem. Anything else I can answer for you?
Alison: That’s it for now. Good to know. Thank you!
Burhan: Anytime, come back soon!
This dialogue is entirely different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions that seek the truth through information gathering. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses are typically longer, more in-depth, and carefully communicated to ensure that the customer understands the main ideas.
Voice interfaces, in essence, use speech to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned with pure voice interfaces, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with because multimodal voice interfaces can lean on visual components like screens as crutches.
Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.
Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech ( TTS ) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. We became familiar with the first real voice interfaces that could actually be spoken to without having to deal with overburdened customer service representatives as a result of the development of interactive voice response ( IVR ) systems.
IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Similar to the corporate world, these systems were primarily created as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), and chances are you’ll have a conversation with one when you call an airline or hotel conglomerate. Despite their functional issues and users ‘ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).
IVR systems have a reputation for having less scintillating conversations than we’re used to in real life ( or even in science fiction ), despite being extremely repetitive and monotonous.
The invention of the screen reader, a tool that converts visual content into synthesized speech, was a development of IVR systems in parallel. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Perhaps the closest thing we have today to an out-of-the-box implementation of content delivered through voice is represented by screen readers.
Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 ( ). In the same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, which was later reworked for computers with graphical user interfaces ( GUIs ) ( ).
With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Screen readers started facilitating quick interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one with the introduction of semantic HTML and especially ARIA roles in 2008, enabling speedy interactions with the pages. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. —into useful information,” according to Aaron Gustafson in A List Apart. ” At least they do when documents are authored thoughtfully” ( ).
There’s a big deal with screen readers: they’re difficult to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. Working with web-based interfaces is a cognitive burden for many screen reader users.
In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:
I hated the way Screen Readers operated from the beginning. Why are they designed the way they are? It makes no sense to present information visually and then only to have that information translated into audio. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information, ignoring areas that are unimportant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.
Many of us immediately associate voice assistants with the subset of voice interfaces that are now commonplace in living rooms, smart homes, and offices with the film HAL from 2001: A Space Odyssey or Majel Barrett’s voice as the omniscient computer in Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And because of their assistive potential, they are quickly receiving more attention from accessibility advocates.
Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.
There is a significant variation in how programmable and customizable some voice assistants are compared to others due to the sheer number of voice assistants available today ( Fig 1 ). At one extreme, everything except vendor-provided features is locked down, for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.
At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, developers who feel stifled by the limitations of Siri and Cortana are increasingly using programmable voice assistants that allow for customization and extensibility. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Users of the Amazon Alexa and Google Assistant ecosystems can choose from among the thousands of custom-built skills available today.
As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they are also selling and open-sourcing an unheard array of tools and frameworks for designers and developers, aiming to make creating voice interfaces as simple as possible, even without code.
Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. In contrast, many development platforms, like Google’s Dialogflow, now support omnichannel features, allowing users to create a single conversational interface that then becomes a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.
Simply put, voice content is content delivered through voice. Voice content must be free-flowing, organic, contextless, and concise in order to preserve what makes human conversation so compelling in the first place.
Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. We’re most concerned with the audiobook content being delivered as a requirement rather than an option.
For many of us, our first foray into informational voice interfaces will be to deliver content to users. One issue is that any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice movements?
Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, colossal vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window, like microfilm viewers of newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:
An example of microcontent can be a day’s weather forecast [sic], the arrival and departure times for an airplane flight, an abstract from a lengthy publication, or a single instant message. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. Informing delivery channels both established and novel, Microcontent provides the best opportunity to find out how your content can be stretched to the limits of its potential.
As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly look at a digital sign for an instant and be informed when the next train is coming, but voice interfaces keep our attention captive for so long that we can’t quickly evade or skip, a feature that screen reader users are all too familiar with.
Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.
Our voice content’s legibility and discoverability in general both depend on how it manifests in terms of perceived space and time.
Many wealthy runners had come to the conclusion that it was impossible to run a mile in less than four hours in the 1950s. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.
However, on May 6, 1956, Roger Bannister caught people by shock. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.
The world then knew that the four-minute hour was possible because of this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Therefore, in the same race, three athletes managed to cross the four-minute challenge up. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.
We do a lot more when we think something is possible, and we only think it can be done when we see someone else doing it once more. As for individual running speed, we also think there are strict guidelines for how a website should do.
The key environmental performance indicators for the majority of major industries are pretty well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. But, we are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods to do so.
The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the amount of CO2 that a website item produces. We can’t measure the pollutants coming out of the exhaust valves on our devices. Our websites ‘ emissions are far away, out of mind, and out of sight when fuel and fuel are burned in power plants. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. So what do we accomplish then?
If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as coal pollution gauges:
Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.
Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a reliable indicator of how much power is being consumed and how much coal is being released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.
The easiest way to calculate data transfer for a single visit for web pages is to measure the page weight, which is the page’s transfer size in kilobytes when someone first visits the page. It’s fairly easy to measure using the developer tools in any modern web browser. Frequently, any web application’s overall data transfer statistics will be included in your web hosting account ( Fig. 2.1 ).
The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes.
A large scope is required to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for roughly half of this data transfer, making them the single biggest contributor to carbon emissions on the typical website.
History clearly shows us that our web pages can be smaller, if only we set our minds to it. While the majority of technologies, including the underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.
You might be aware of the project team’s focus on creating faster user experiences using the concept of performance budgeting. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than vague suggestions, much like speed limits while driving, so the goal should always be to come within budget.
Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Page weight and transfer size are more objective and reliable benchmarks for sustainable web design, but web performance is frequently more about the subjective perception of load times than it is about the underlying system’s true efficiency.
We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use competitor page weight to compare the new website to the old one. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.
If we want to take it to the next level, we could start looking at how much more popular our web pages are when people visit them frequently. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, visitors who load the same page more frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all the files on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Moving away from the first visit and allowing us to determine page weight budgets for scenarios other than this one can help us learn even more about how to optimize efficiency for users who regularly visit our pages.
Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose their data on energy consumption and carbon emissions, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.
In summary, less data transfer leads to more energy efficiency, which is a crucial component of reducing web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some.
Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” (gCO2/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity produced. This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO2/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO2/k Wh.
The majority of electricity is produced by national or state grids, where different levels of carbon intensity are combined with energy from a variety of sources. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.
Although we have some control over where our projects are hosted, we do not have complete control over the energy supply of web services. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps the user-provided data, and a look at their map demonstrates how, for instance, choosing a data center in France will have significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).
However, we don’t want to move our servers too far away from our users because it requires energy to transmit data through the telecom’s networks, and the more energy is used. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.
We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance between that location and the data center that our hosting company uses as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.
For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could calculate the distance between San Francisco and London, which is 5,300 miles. That’s a long way! We can see how hosting it somewhere in North America, ideally on the West Coast, would significantly shorten the distance and the amount of energy needed to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.
If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. A tool my team created accomplishes this by measuring the data transfer over the wire when a web page is loaded, calculating the associated electricity consumption, and then converting that data into a CO2 figure ( Fig. 2.4). It also factors in whether or not the web hosting is powered by renewable energy.
The Energy and Emissions Worksheet that comes with this book teaches you how to take it to the next level and tailor the data more accurately to the individual aspects of your project.
We could even expand our page weight budget by establishing carbon budgets as well with the ability to calculate carbon emissions for our projects. CO2 is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds a layer of abstraction that isn’t as intuitive, carbon budgets do focus our minds on the main thing we’re trying to reduce, which supports the main goal of sustainable web design: reducing carbon emissions.
Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.
One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React make it possible to create applications where the” thinking” process is performed either partially or completely in the browser.
All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more computation in a web browser requires more energy to be used by the user’s devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally exclude those who have older, slower devices and make the batteries on phones and laptops drain more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only hurts the environment, but it also places a disproportionate financial burden on society’s poorest.
In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the developer console of the Safari browser is one of the tools we currently have ( Fig. 2.5 ).
You know what happens when your computer’s cooling fans start spinning so frantically that you suspect it might take off when you load a website? That’s essentially what this tool is measuring.
It uses these figures to create an energy impact rating and shows how much CPU is used and how long it takes to load the web page. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.
This book will provide you with that plan of action. It covers how to incorporate safety principles into your design work in order to make tech that’s secure, how to persuade your stakeholders that this work is important, and how to respond to the critique that what we really need is more diversity. ( Spoiler: we do, but diversity alone is not the solution to fixing unethical, unsafe technology. )
Your objectives when designing for protection are as follows:
The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). It’s a method I developed in 2018 to better understand the different methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. The Process includes five public areas of action:
The Process is meant to be flexible; in some situations, it didn’t make sense for groups to adopt every step. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.
And once you use it, if you have an idea for making it better or simply want to give perspective of how it helped your staff, please get in touch with me. It’s a dwelling report that I hope technicians can use as a practical and useful resource in their day-to-day work.
If you’re working on a product especially for a resilient team or survivors of some form of injury, such as an application for survivors of domestic violence, sexual abuse, or drug addiction, be sure to read Section 7, which covers that position directly and should be handled a bit different. The principles set forth here are for putting safety first when creating a more general product with a broad user base ( which, as we already know from statistics, will include some groups that should be protected from harm ). Chapter 7 is focused on products that are specifically for vulnerable groups and people who have experienced trauma.
A thorough analysis of how your technology might be used for abuse as well as specialized insights into the experiences of those who have witnessed and perpetrated that kind of abuse should be included in design research. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.
Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. For example, a team building a smart home device would do well to understand the multitude of ways that existing smart home devices have been used as tools of abuse. If you’re creating an AI product, be aware of the potential for racism and other issues that have been reported in other AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. Google Scholar is a useful resource for locating these studies.
When possible and appropriate, include direct research ( surveys and interviews ) with people who are experts in the forms of harm you have uncovered. In order to gain a better understanding of the subject and avoid retraumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.
It is crucial to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. As an alternative to paying, you can donate to a group fighting against the violence the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.
It’s unlikely that teams aiming to design for safety will be able to interview self-proclaimed abusers or people who have broken laws around things like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Attempt to understand how abusers or bad actors use technology to harm others, how they use it against others, and how they justify or explain the abuse.
Use your research after you’ve finished conducting it to create abuser and survivor archetypes. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they’re based on your research into likely safety issues, much like when we design for accessibility: we don’t need to have found a group of blind or low-vision users in our interview pool to create a design that’s inclusive of them. Instead, we base those designs on existing research and what this group requires. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.
The abuser archetype is defined as someone who views a product as a means of harm ( Fig. 5.2 ). They may be trying to harm someone they don’t know through surveillance or anonymous harassment, or they may be trying to control, monitor, abuse, or torment someone they know personally.
Someone who is being abused with the product is the survivor archetype. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted ( Fig 5.3 )?
You may want to make multiple survivor archetypes to capture a range of different experiences. They may be aware of the abuse is occurring but not be able to stop it, such as when a stalker keeps figuring out where they are from ( Fig 5.4), or they may be aware that it is happening but not know how ( for example, when an abuser locks them out of IoT devices ). Include as many of these scenarios as you need to in your survivor archetype. These suggestions will be used later when creating solutions to assist your survivor archetypes in achieving their objectives of preventing and ending abuse.
It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic information we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and prevent the abuser’s goals.
And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For example, if you uncovered an issue with security, such as the ability for someone to hack into a home camera system and talk to children, the malicious hacker would get the abuser archetype and the child’s parents would get survivor archetype.
After creating archetypes, brainstorm novel abuse cases and safety issues. You’re trying to identify entirely new safety issues that are unique to your product or service by using the term” Novel” in terms of things you’ve not found in your research. The goal with this step is to exhaust every effort of identifying harms your product could cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.
What other uses could your product be used for besides what you’ve already identified in your research? I recommend setting aside at least a few hours with your team for this process.
Try conducting a Black Mirror brainstorming session if you want to start somewhere. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out how your product would be used in an episode of the show—the most wild, awful, out-of-control ways it could be used for harm. Participants in Black Mirror brainstorming typically end up having a lot of fun ( which I believe is great because having fun when designing for safety! ). I recommend time-boxing a Black Mirror brainstorm to half an hour, and then dialing it back and using the rest of the time thinking of more realistic forms of harm.
You may still not feel confident that you have found every possible source of harm after identifying as many opportunities for abuse as possible. A healthy amount of anxiety is normal when you’re doing this kind of work. It’s common for teams designing for safety to worry,” Have we really identified every possible harm? What if something is missing, then? If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.
It’s impossible to say for sure that you’ve done everything, but instead of striving for 100 % assurance, acknowledge that you’ve done everything, and pledge to prioritize safety going forward. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.
You should now be able to identify potential harm-causing uses for your product as well as survivor and abuser archetypes describing opposing user objectives. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This is a good idea to include this one alongside other areas of your design process where you’re offering solutions to the various issues your research has identified.
Some questions to ask yourself to help prevent harm and support your archetypes include:
In some products, it’s possible to proactively detect harm that is occurring. For example, a pregnancy app might be modified to allow the user to report that they were the victim of an assault, which could trigger an offer to receive resources for local and national organizations. Although it’s not always possible to be this proactive, it’s worthwhile to spend a half hour talking about how your product could help the user receive help in a safe manner if any kind of user activity would indicate some form of harm or abuse.
That said, use caution: you don’t want to do anything that could put a user in harm’s way if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll walk through a good illustration of this.
The final step is to evaluate the prototypes against the perspectives of your archetypes, who wants to harm the product or the victim of the harm who needs to regain control of the technology. Just like any other kind of product testing, at this point you’ll aim to rigorously test out your safety solutions so that you can identify gaps and correct them, validate that your designs will help keep your users safe, and feel more confident releasing your product into the world.
Ideally, safety testing happens along with usability testing. If you work for a company that doesn’t conduct usability testing, you might be able to use safety testing to deftly perform both. A user who uses your design while trying to use it against someone else can also be encouraged to point out interactions or other design details that don’t make sense to them.
You’ll want to conduct safety testing on either your final prototype or the actual product if it’s already been released. It’s okay to test an existing product that wasn’t created with safety goals in mind right away; “etrofitting” it for safety is a good thing to do.
Remember that testing for safety involves testing from the perspective of both an abuser and a survivor, though it may not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.
You as the designer are most likely too closely connected to the product and its design by this point to be a valuable tester, you know the product too well, as with other forms of usability testing. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.
The goal of this testing is to understand how easy it is for someone to weaponize your product for harm. Unlike with usability testing, you want to make it impossible, or at least difficult, for them to achieve their goal. Use your product in an effort to achieve the goals in the abuser archetype you created earlier.
For example, for a fitness app with GPS-enabled location features, we can imagine that the abuser archetype would have the goal of figuring out where his ex-girlfriend now lives. You’d make every effort to track down another user’s location who has their privacy settings turned on with this in mind. You might try to see her running routes, view any available information on her profile, view anything available about her location ( which she has set to private ), and investigate the profiles of any other users somehow connected with her account, such as her followers.
If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Reverting to step 4 and figuring out how to stop this from occurring is your next step. You may need to repeat the process of designing solutions and testing them more than once.
Survivor testing involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. The survivor archetype’s goal of not being stalked is satisfied by preventing an attempt by an abuser archetype to stalk someone, so separate testing wouldn’t be required from the survivor’s perspective.
However, there are cases where it makes sense. For instance, a survivor archetype’s goal would be to discover who or what causes the temperature to change when they aren’t altering it themselves. You could test this by looking for the thermostat’s history log and checking for usernames, actions, and times, if you couldn’t find that information, you would have more work to do in step 4.
Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Are there any instructions that explain how to remove a user and change the password, and are they simple to locate? For your test, this would involve trying to figure out how to do this. This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.
To make your product more inclusive and compassionate, consider adding stress testing. This concept comes from Design for Real Life by Eric Meyer and Sara Wachter-Boettcher. The authors noted that personas typically focus on happy people, but that happy people are frequently anxious, stressed out, unhappy, or even go through a bad day. These are called” stress cases”, and testing your products for users in stress-case situations can help you identify places where your design lacks compassion. More information about how to incorporate stress cases into your design can be found in Design for Real Life, as well as in many other effective methods for designing with compassion.
However, how can a content management system ( CMS ) be set up to reach your audience both now and in the future? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing content versions that are lexical and even join related content, you can avoid that result.
I just had the opportunity to direct the CMS application for a Fortune 500 company. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.
A content type is essential to an holistic content strategy, and it required conceptual types to be given names that don’t depend on how the content is presented. Our aim was to allow writers to write articles and use it where necessary. But as the job proceeded, I realized that supporting material utilize at the range that my client needed required the whole group to identify a new pattern.
Despite our best efforts, we remained influenced by design systems, which we were more comfortable with. An holistic content strategy cannot rely on WYSIWYG equipment for design and layout, unlike web-focused material strategies. Our tendency to approach the material model with our common design-system thinking frequently led us to veer away from one of the main purposes of a material model: delivering content to audiences on various marketing channels.
We needed to explain to our designers, developers, and stakeholders that we were doing something completely different from their previous web projects, where everyone assumed that content would fit into layouts as visual building blocks. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. We discovered two guiding principles that helped the team understand how a content model and the design processes we were familiar with were:
Type and attribute names for semantic content models are used to reflect the content’s intended purpose and not its intended display. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. Although these types might make it simple to present content, they don’t aid in understanding the meaning of the content, which would have opened the door to the content presented in each marketing channel. In contrast, a semantic content model employs type names like product, service, and testimonial to allow for each delivery channel to interpret the content and use it as necessary.
When you’re creating a semantic content model, a great place to start is to look over the types and properties defined by Schema. a curated resource for type definitions that are understandable on platforms like Google search, type definitions .org
A semantic content model has a number of advantages:
For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.
Instead of slicing up related content across disparate content components, I’ve come to the realization that the best models are those that are semantic and also connect related content components ( such as a FAQ item’s question and answer pair ). A good content model connects content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.
Write an essay or article about it. The meaning and usefulness of an article depend on how well its components are kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. This had a similar effect to an article that had had its headline removed. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.
Let’s take a look at how connecting related content works in a real-world setting to illustrate. A complex layout for a software product page that included multiple tabs and sections was presented by the client’s design team. Our instincts were to follow suit with the content model. Shouldn’t we make adding any number of tabs in the future as simple and as flexible as possible?
We felt like we needed a “tab section” content type because our design-system instincts allowed for the addition of multiple tab sections to a page because they were so well-versed. Each tab section would display various types of content. The software’s overview or specifications might be available in one tab. A list of resources might be found under another tab.
Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. How would a different system have been able to determine which “tab section” referred to a product’s specifications or resource list, for instance? Would that system have had to have used tab sections and content blocks to calculate this? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.
Our customer had a breakthrough when we realized that for each tab, a specific purpose in mind would be revealed, such as the software product’s overview, specifications, related resources, and pricing. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. It wasn’t long after a little digging that the content model didn’t like the idea of tabs. What was important was the meaning of the information that was intended to be displayed in the tabs.
In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. Based on the meaningful attributes the customer had desired to display on the web, we created content types for the software product. There were rich attributes like screenshots, software requirements, and feature lists as well as obvious semantic attributes like name and description. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel, including those that follow, could comprehend and display this content.
In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic ( with type and attribute names that reflected the meaning of the content ) and that it kept content together that belonged together ( instead of fragmenting it ). These two ideas made it easier for us to decide what to do with the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure Google and other interfaces understand your content, remember:
You’ll help your team understand these principles by firmly defending them in their efforts to give content the attention it deserves as both your most valuable resource and your most effective way to engage with your audience.
Here’s the key. To find stakeholders to determine high-risk assumptions and buried complexity, you must first convince them to do so so that they become just as motivated as you are to receive user-response. Essentially, you need to make them think it’s their plan.
By bringing the group up around two straightforward issues, I’ll show you how to collectively introduce alignment and cracks in the group’s shared understanding in this article.
These two issues correlate to the first two methods of the ORCA approach, which may be your new best friend when it comes to reducing speculation. Delay, what’s ORCA? Glad you asked.
ORCA stands for Things, Relationships, CTAs, and Values, and it outlines a process for creating good object-oriented user experience. My style idea is oriented UX. ORCA is an iterative strategy for synthesizing person study into an elegant fundamental foundation to help monitor and conversation design. My work as a UX designer has become more creative, successful, fun, proper, and important thanks to OOUX and ORCA.
The ORCA approach has four incremental shells and a staggering fifteen steps. In each round we get more precision on our System, Rupees, Computer, and As.
I occasionally refer to ORCA as a “garbage in, garbage out” procedure. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. The beginning of the ORCA process, however, serves another purpose: it helps you sell the need for research if you don’t have a ton of research.
In other words, the ORCA process serves as a gauntlet between research and design. You can gracefully ride the killer whale from research to design with good research. But without good research, the process effectively spits you back into research and with a cache of specific open questions.
What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.
Mark Twain
The first two steps of the ORCA process—Object Discovery and Relationship Discovery—shine a spotlight on the dark, dusty corners of your team’s misalignments and any inherent complexity that’s been swept under the rug. It begins to reveal what this timeless comic so skillfully demonstrates:
This is one reason why so many UX designers are frustrated in their job and why many projects fail. Every decision-maker is confident in their own mental picture, which is another reason why we frequently can’t sell research.
Once we expose hidden fuzzy patches in each picture and the differences between them all, the case for user research makes itself.
However, how we go about doing this is crucial. However much we might want to, we can’t just tell everyone,” YOU ARE WRONG”! Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders accept responsibility for their beliefs and understanding gaps, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.
Let’s say you have doctors on your staff. And you have no idea how doctors use the system you are tasked with redesigning.
You might try to sell research by honestly saying:” We need to understand doctors better! What are the issues they face? How do they use the current app”? Here’s the issue with that, though. Those questions are vague, and the answers to them don’t feel acutely actionable.
Instead, you want your stakeholders themselves to ask super-specific questions. This conversation is more similar to what you need to facilitate. Let’s listen in:
” Wait a sec, how frequently do doctors share patients?” Does a patient in this system have primary and secondary doctors”?
” Can a patient even have more than one primary doctor”?
Is it a “primary doctor” or “primary caregiver” ?Can’t that position be considered a nurse practitioner?
” No, caregivers are something else… That’s the patient’s family contacts, right”?
” So are caregivers in scope for this redesign”?
” Yeah, because if a caregiver is present at an appointment, the doctor needs to note that. Like, tag the caregiver on the note… Or on the appointment”?
We are currently traveling somewhere. Do you see how powerful it can be getting stakeholders to debate these questions themselves? The diabolical goal is to gently and diplomatically shake their confidence.
When these kinds of questions bubble up collaboratively and come directly from the mouths of your stakeholders and decision-makers, suddenly, designing screens without knowing the answers to these questions seems incredibly risky, even silly.
If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And most likely as a result, this software product will become more confusing, complicated, and unintuitive.
But how do we approach these types of contentious inquiries diplomatically, effectively, collaboratively, and reliably?
We can do this by starting with those two big questions that align to the first two steps of the ORCA process:
In practice, getting to these answers is easier said than done. I’m going to demonstrate how these two straightforward questions can serve as the Object Definition Workshop’s starting point. During this workshop, these” seed” questions will blossom into dozens of specific questions and shine a spotlight on the need for more user research.
In the next section, I’ll show you how to run an Object Definition Workshop with your stakeholders ( and entire cross-functional team, hopefully ). But first, you need to do some prep work.
In essence, look for nouns that are specific to the subject matter of your project’s business or industry and use at least a few sources. I call this noun foraging.
Just a few excellent noun foraging sources can be found here:
Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. Use those if all you have is a marketing website, some screenshots of the current legacy system, and access to customer service chat logs.
As you peruse these sources, watch for the nouns that are used over and over again, and start listing them ( preferably on blue sticky notes if you’ll be creating an object map later! …
You’ll want to focus on nouns that might represent objects in your system. If you are having trouble determining if a noun might be object-worthy, remember the acronym SIP and test for:
Consider a library app, for instance. Is “book” an object?
Can you think of a few attributes for this potential object? Title, author, publish date … Yep, it has structure. Check!
What are some illustrations of this potential “book” object, for instance? Can you name a few? Check! The Alchemist, Ready Player One, Everybody Poops, OK!
Purpose: why is this object important to the users and business? Well, “book” is what our library client is providing to people and books are why people come to the library … Check, check, check!
Concentrate on capturing the nouns with SIP as you go noun foraging. Avoid capturing components like dropdowns, checkboxes, and calendar pickers—your UX system is not your design system! Components are just the packaging for objects—they are a means to an end. No one is using your dropdown to play in your digital space! They are coming for the VALUABLE THINGS and what they can do with them. These things, or objects, are what we are trying to identify.
Let’s say we work for a startup disrupting the email experience. This is how I’d start my noun foraging.
I’d like to take a look at my own email client, which is Gmail. I’d then look at Outlook and the new HEY email. I would examine Hotmail, Yahoo, and even Basecamp and other’email replacers’. I’d read some articles, reviews, and forum threads where people are complaining about email. While doing all this, I would look for and write down the nouns.
( Before moving on, feel free to go noun foraging for this fictitious product as well, and then scroll down to see how closely our lists correspond. Just don’t get lost in your own emails! Rejoice back to me!
Drumroll, please…
Here are a few nouns I came up with during my noun foraging:
Scan your list of nouns and pick out words that you are completely clueless about. It might be a client or automation in our email example. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.
Aside: Here are some real nouns that I needed my stakeholders to understand during my own past project work:
A list of nouns that represent potential objects and a short list of nouns that need to be further defined are really all you need to prepare for the workshop session.
Noun foraging can be used as a starting point for your workshop; it can be done in concert. If you have five people in the room, pick five sources, assign one to every person, and give everyone ten minutes to find the objects within their source. When the time’s up, come together and find the overlap. Here, affinity mapping is your friend!
If your team is short on time and might be reluctant to do this kind of grunt work ( which is usually the case ) do your own noun foraging beforehand, but be prepared to show your work. I enjoy showing screenshots of documents and screens that have all the highlighted nouns. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.
HOT TIP: before jumping into the workshop, frame the conversation as a requirements-gathering session to help you better understand the scope and details of the system. We’ll keep that a secret; you just need to let them know that you‘re looking for gaps in the team’s understanding so that you can demonstrate the need for more user research. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers.
Let the whack-a-mole question then start.
Want some genuine fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Then, have everyone present their cards at once, and see if you get different definitions (you will ). This is gold for exposing misalignment and starting great conversations.
As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty strikes, ostensibly start an “open questions” parking lot. � �
Here’s a fantastic follow-up to solidify definitions:
Stakeholder 1: They probably call email clients “apps”. But I’m not certain.
Stakeholder 2: Automations are often called “workflows”, I think. Or, maybe users think workflows are something different.
Ask the group to decide whether to use only that term in the near future if it becomes more user-friendly. This way, the team can better align to the users ‘ language and mindset.
Okay, let’s get to the next part.
If you have two or more objects that seem to overlap in purpose, ask one of these questions:
You: Is a saved response the same as a template?
Stakeholder 1: Yes! Without a doubt.
Stakeholder 2: I don’t think so… A saved response is text with links and variables, but a template is more about the look and feel, like default fonts, colors, and placeholder images.
Continually expand your expanding glossary of terms. And continue to capture areas of uncertainty in your “open questions” parking lot.
If you successfully determine that two similar things are, in fact, different, here’s your next follow-up question:
You: Do saved responses and templates have any connection to each other?
Stakeholder 3: Yeah, a template can be applied to a saved response.
You, always with the follow-ups: When is the template applied to a saved response? When the user is creating the saved response, does that occur? Or when they apply the saved response to an email? How does that actually function?
Listen. Capture uncertainty. When the number of “open questions” reaches a critical mass, pause to begin asking questions of groups or individuals. Some questions might be for the dev team ( hopefully at least one developer is in the room with you ). Someone who couldn’t make it to the workshop might have a question. And many questions will need to be labeled “user”.
Do you see how we are building up to our UXR sales pitch?
Your next query makes it easier for the team to concentrate on what your users are most interested in. You can simply ask,” Are saved responses in scope for our first release”?, but I’ve got a better, more devious strategy.
By now, you should have a list of clearly defined objects. Ask participants to arrange these items either in small breakout groups or independently according to their importance. Then, like you did with the definitions, have everyone reveal their sort order at once. Unsurprisingly, it’s not unusual for the VP to place something like” saved responses” at the top of the list while everyone else places it at the bottom. Try not to look too smug as you inevitably expose more misalignment.
I did this for a startup a few years ago. The three groups ‘ wildly different sort orders were displayed on the whiteboard.
The CEO nodded his head and said,” This is why we haven’t been able to move forward in two years.”
Admittedly, it’s tragic to hear that, but as a professional, it feels pretty awesome to be the one who facilitated a watershed realization.
Once you have a good idea of in-scope, clearly defined things, this is when you move on to doing more relationship mapping.
We’ve already tried to figure out what two things are different, but this time, we wanted to ask the team about every possible relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? Pull out your dependable boxes and arrows technique to see all the connections. Here, we are connecting our objects with verbs. I prefer to use simple statements like “has a” and “has many.”
This system modeling activity brings up all sorts of new questions:
The workshop participants might provide solid responses directly. Great! Capture that new shared understanding. However, as uncertainty arises, keep adding new questions to your expanding parking lot.
You’ve set up the explosives strategically along the floodgates. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.
Have the group reflect on the list of open questions before the workshop ends. Make plans for getting answers internally, then focus on the questions that need to be brought before users.
Your final step is now. Take those questions you’ve compiled for user research and discuss the level of risk associated with NOT answering them. Ask, “if we design without an answer to this question, if we make up our own answer and we are wrong, how bad might that turn out”?
With this approach, we are cornering our decision-makers into supporting user research because they themselves categorize questions as high-risk. Sorry, not sorry.
This is your moment of truth. With everyone in the room, ask for a reasonable budget of time and money to conduct 6–8 user interviews focused specifically on these questions.
HOT TIP: if you are new to UX research, please note that you’ll likely need to rephrase the questions that came up during the workshop before you present them to users. Make sure your questions are non-ending and don’t force the user to choose any default responses.
Seriously, if you’re ever going to design screens again, make sure you first address these fundamental inquiries: what are the objects and how do they relate?
I promise you this: if you can secure a shared understanding between the business, design, and development teams before you start designing screens, you will have less heartache and save more time and money, and ( it almost feels like a bonus at this point! ) users will be more receptive to what you put out into the world.
I sincerely hope this will give you the time and money to spend talking to your users and getting a clear understanding of what you are designing before you begin creating screens. If you find success using noun foraging and the Object Definition Workshop, there’s more where that came from in the rest of the ORCA process, which will help prevent even more late-in-the-game scope tugs-of-war and strategy pivots.
Wish you the best of luck! Now go sell research!
CSS involves creating containers. In fact, the whole website is made of containers, from the website viewport to components on a webpage. However, every now and then a new function emerges that prompts us to reevaluate our design philosophy.
Square features, for instance, make it fun to play with round picture areas. Mobile display holes and electronic keyboards offer issues to best manage content that stays clear of them. And having two or more portable devices forces us to reevaluate how to make the most of the available space in a variety of various device positions.
These latest changes to the website platform have made it both more difficult and fascinating to create products. They’re wonderful opportunities for us to break out of our triangular containers.
I’d like to talk about a new feature similar to the above: the Window Controls Overlay for Progressive Web Apps ( PWAs ).
Liberal Web Apps are bridging the gap between websites and apps. They combine the best of both worlds. On the one hand, they are flexible, shareable, and stable, just like websites. On the other hand, they provide more effective features, work online, and read documents just like local apps.
As a style area, PWAs are really exciting because they challenge us to think about what mixing online and device-native user interface can get. We have more than 40 years of experience telling us what software may look like, especially on desktop computers, and it’s challenging to get out of this psychological design.
At the end of the day though, PWAs on desktops are constrained to the glass they appear in: a square with a name bar at the top.
What a standard pc PWA app looks like:
Sure, as the author of a PWA, you get to choose the color of the title bar (using the Web Application Manifest theme_color home ), but that’s about it.
What if we could assume differently and regain the full glass of the app? Doing so would give us a chance to create our programs more wonderful and feel more included in the operating system.
This is exactly what the Window Controls Overlay provides. This innovative PWA operation makes it possible to take advantage of the full floor area of the app, including where the name bar usually appears.
Let’s get started with an explanation of the screen and title table settings.
The title bar is the place displayed at the top of an game windows, which frequently contains the phone’s name. The buttons or buttons that are displayed at the top of an app’s window are the ones that allow it to reduce, increase, or close its window.
Window Controls Overlay removes the natural barrier of the name bar and windows controls areas. The title bar and glass control buttons can be overlayed on top of the user’s internet information, allowing it to free up the entire height of the game window.
If you are reading this article on a desktop computer, take a quick look at other apps. Chances are they’re already doing something similar to this. In fact, the web browser you are using uses the top area to display tabs.
Spotify displays album artwork to the top of the application window all the way up.
Microsoft Word uses the available title bar space to display the auto-save and search functionalities, and more.
The whole point of this feature is to allow you to make use of this space with your own content while providing a way to account for the window control buttons. And it makes it possible to offer this modified experience on a variety of platforms without having a negative impact on the experience on browsers or other devices that don’t support Window Controls Overlay. After all, PWAs are all about progressive enhancement, so this feature is a chance to enhance your app to use this extra space when it’s available.
For the rest of this article, we’ll be working on a demo app to learn more about using the feature.
The demo app is called 1DIV. Users can create designs using CSS and a single HTML element in a simple CSS playground.
The app has two pages. The first lists the CSS designs you’ve already created:
The second page enables you to create and edit CSS designs:
We can install the app as a PWA on the desktop because I added a straightforward web manifest and service representative. Here is what it looks like on macOS:
And on Windows:
Our app is looking good, but the white title bar in the first page is wasted space. It would be really nice if the design area extended to the top of the app window on the second page.
Let’s use the Window Controls Overlay feature to improve this.
The feature is still experimental at the moment. To try it, you need to enable it in one of the supported browsers.
It has currently been implemented in Chromium as a result of a collaboration between Microsoft and Google. We can therefore use it in Chrome or Edge by going to the internal about: //flags page, and enabling the Desktop PWA Window Controls Overlay flag.
To use the feature, we need to add the following display_override member to our web app’s manifest file:
{ "name": "1DIV", "description": "1DIV is a mini CSS playground", "lang": "en-US", "start_url": "/", "theme_color": "#ffffff", "background_color": "#ffffff", "display_override": [ "window-controls-overlay" ], "icons": [ ... ]}On the surface, the feature is really simple to use. The only thing we need to change is this manifest change, which will make the title bar disappear and convert the window controls into an overlay.
However, to provide a great experience for all users regardless of what device or browser they use, and to make the most of the title bar area in our design, we’ll need a bit of CSS and JavaScript code.
What the current state of the app is:
Our logo, search field, and NEW button are now partially covered by the window controls, but the title bar has been removed, which is what we wanted. Our layout now begins at the top of the window.
It’s similar on Windows, with the difference that the close, maximize, and minimize buttons appear on the right side, grouped together with the PWA control buttons:
New CSS environment variables have also been added in addition to the feature:
titlebar-area-xtitlebar-area-ytitlebar-area-widthtitlebar-area-heightYou use these variables with the CSS env ( ) function to position your content where the title bar would have been while ensuring it won’t overlap with the window controls. We’ll position our header, which includes the logo, search bar, and NEW button, using two of the variables in our case.
header { position: absolute; left: env(titlebar-area-x, 0); width: env(titlebar-area-width, 100%); height: var(--toolbar-height);}The titlebar-area-x variable gives us the distance from the left of the viewport to where the title bar would appear, and titlebar-area-width is its width. (Remember, this is not equivalent to the width of the entire viewport, just the title bar portion, which as noted earlier, doesn’t include the window controls.)
By doing this, we make sure our content remains fully visible. We’re also defining fallback values (the second parameter in the env() function) for when the variables are not defined (such as on non-supporting browsers, or when the Windows Control Overlay feature is disabled).
Now our header adapts to its surroundings, and it doesn’t feel like the window control buttons have been added as an afterthought. The interface resembles a native app much more.
Now let’s take a closer look at our second page: the CSS playground editor.
Not very good. Our CSS demo area does go all the way to the top, which is what we wanted, but the way the window controls appear as white rectangles on top of it is quite jarring.
We can fix this by changing the app’s theme color. There are a few ways to define it:
theme_color.In our case, we can set the manifest theme_color to white to provide the right default color for our app. The OS will read this color value when the app is installed and use it to make the window controls background color white. This color works great for our main page with the list of demos.
The theme-color meta tag can be changed at runtime, using JavaScript. So we can do that to override the white with the right demo background color when one is opened.
Here is the method we’ll employ:
function themeWindow(bgColor) { document.querySelector("meta[name=theme-color]").setAttribute('content', bgColor);}With this in place, we can imagine how using color and CSS transitions can produce a smooth change from the list page to the demo page, and enable the window control buttons to blend in with the rest of the app’s interface.
Now, getting rid of the title bar entirely does have an important accessibility consequence: it’s much more difficult to move the application window around.
Users can drag and click their way to a sizable area in the title bar, but when using the Window Controls Overlay feature, they are limited to where the control buttons are, and must carefully place their fingers in between these buttons to move the window.
Fortunately, this can be fixed using CSS with the app-region property. This property is, for now, only supported in Chromium-based browsers and needs the -webkit- vendor prefix.
We can use the following to animate any aspect of the app so that the window can drag it toward any point:
-webkit-app-region: drag;
It is also possible to explicitly make an element non-draggable:
-webkit-app-region: no-drag;
These choices might be beneficial to us. We can make the entire header a dragging target, but make the search field and NEW button within it non-draggable so they can still be used as normal.
However, because the editor page doesn’t display the header, users wouldn’t be able to drag the window while editing code. Let’s take a different approach, then. We’ll create another element before our header, also absolutely positioned, and dedicated to dragging the window.
... .drag { position: absolute; top: 0; width: 100%; height: env(titlebar-area-height, 0); -webkit-app-region: drag;}With the above code, we’re making the draggable area span the entire viewport width, and using the titlebar-area-height variable to make it as tall as what the title bar would have been. This way, our draggable area is aligned with the window control buttons as shown below.
And, now, to make sure our search field and button remain usable:
header .search,header .new { -webkit-app-region: no-drag;}Users can click and drag where the title bar used to be with the above code. It is an area that users expect to be able to use to move windows on desktop, and we’re not breaking this expectation, which is good.
It may be useful for an app to know both whether the window controls overlay is visible and when its size changes. In our situation, there wouldn’t be enough room for the search field, logo, and button to fit because the user made the window very narrow. We would want to push them a little lower.
The Window Controls Overlay feature comes with a JavaScript API we can use to do this: navigator.windowControlsOverlay.
The API offers three intriguing features:
navigator.windowControlsOverlay.visiblelets us know whether the overlay is visible.navigator.windowControlsOverlay.getBoundingClientRect()lets us know the position and size of the title bar area.navigator.windowControlsOverlay.ongeometrychangelets us know when something changes in size or visibility.Let’s use this to be aware of the size of the title bar area and move the header down if it’s too narrow.
if (navigator.windowControlsOverlay) { navigator.windowControlsOverlay.addEventListener('geometrychange', () => { const { width } = navigator.windowControlsOverlay.getBoundingClientRect(); document.body.classList.toggle('narrow', width < 250); });}In the example above, we set the narrow class on the body of the app if the title bar area is narrower than 250px. We could do something similar with a media query, but using the windowControlsOverlay API has two advantages for our use case:
.narrow header { top: env(titlebar-area-height, 0); left: 0; width: 100%;}When the window is too small, we can move the header down using the above CSS code to avoid hitting the window control buttons, and we can also lower the thumbnails accordingly.
We were able to convert our simple demo app to something that felt much more connected to desktop devices by using the Window Controls Overlay feature. Something that reaches out of the usual window constraints and provides a custom experience for its users.
In reality, this feature only gives us about 30 more pixels of room, and it presents challenges for using the window controls. And yet, this extra room and those challenges can be turned into exciting design opportunities.
More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. To make it easier for us web authors to integrate more and more fully with those devices, new features are added to the web platform. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. Nowadays, web building enables us to think outside the rectangular box.
So let’s embrace this. Let’s use the standard technologies already at our disposal, and experiment with new ideas to provide tailored experiences for all devices, all from a single codebase!
You can report bugs to the spec’s repository if you have the chance to try the Window Controls Overlay feature and have feedback on it. It’s still early in the development of this feature, and you can help make it even better. Or you can look at this demo app and its source code, the feature’s existing documentation, or the feature’s existing documentation.