Ed Boon doesn’t care that imaginary heroes have to deal with their deaths. Boon plays a strong position in the name “fatality” as the co-creator of the 1992 O. G. Mortal Kombat square fighting game that he developed alongside John Tobias. becoming slang in nerd culture for a particularly offensive obliteration or disembowelment. The MK guru]…]
Mortal Kombat II Expands Franchise to New Realms With No One In Safe appeared initially on Den of Geek.
It seems like The New Mutants ‘ difficult path to success on display was difficult on the writer-director. Josh Boone discusses the difficulties and emotions he faced while creating the disturbed X-Men subsidiary in a fresh interview. Boone was ultimately left to [ …] until it was finally released under the Marvel banner in 2020.
The first article Marvel Director Shows” Distressing” Movie Production Journey appeared initially on Den of Geek.
Director Jon M. Chu had to create a two-decade-old stage music based on a book from 30 years ago that felt contemporary and adapted a text from 1900. He did that by using a roll legend as one of the prospects and [Putting Ariana Grande]…
On Den of Geek, the second article Wicked Director Wants to Make a Britney Spears Movie was originally published.
The Next Jedi in Star Wars: The Last Jedi teaches how to let go of the franchise. It ininfamously presented Luke Skywalker as a terrible old recluse and rejected the notion that Rey was important because of her heritage, as well as insisting that the collection was all about change. The Last Jedi demonstrates that [ …]]…]] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ]
Rian Johnson also loves Star Wars, yet after all, appeared initially on Den of Geek.
Their most recent scenario has been closed by Ed and Lorraine Warren. No, not just the Labyrinths in the real world, the scheming criminals whose career came to an end with Ed’s passing in 2006. Instead, the much more endearing imaginary Lairs that Patrick Wilson and Vera Farmiga in The Conjuring play. The Conjuring has been a shocking film since that 2013 film, which was directed by James Wan.
The first article on Den of Geek was Next Customs Director confirms that The Conjuring Universe has ended.
Daredevil is the Gentleman Without Concern, a say he’s going to innovative, extraterrestrial measures. Marvel is eager to release the Ultimate Daredevil in Ultimate Universe: Two Times In# 1, which was written by Deniz Camp and was illustrated by some artists, including Javier Pulido. Where is the Devil [instead of Daredevil’s preferred form]…]
The second article on Den of Geek was Ultimate Daredevil Sends the Street Level Hero into Deep Space.
The Peacemaker period 2 episode has clues in this post. James Gunn makes the announcement about the future of the DCU in the final moments of the Peacemaker winter 2 episode. A strategy to transport all metahumans to an extra-dimensional world called Salvation has been put forth by ARGUS mind Rick Flag Jr. [ARGUS’s abduction]
The first article on Den of Geek was George R. R. Martin Had a Black Perception for the Comic That Inspired Superman 2.
Although I’m not sure when I first heard this statement, it has stuck with me over the centuries. How do you generate solutions for scenarios you can’t think? Or create materials 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 design for a 960px canvas that I would later add willing to. The growth phase was about attaining pixel-perfect reliability using set widths, fixed levels, and absolute placement.
All of this was altered by Ethan Marcotte’s speak at An Event Apart and the subsequent article in A Checklist Off in 2010. 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 design didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. I quickly realized that you didn’t just put responsiveness at the end of a job. To make smooth design, you need to prepare throughout the style stage.
Removing restrictions and creating content that can be viewed on any system has always been the goal of designing responsive or liquid websites. 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 html:
.logo { @include colSpan(6);}.search { @include colSpan(3);}.social-share { @include colSpan(3);}The next ingredient for reactive 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 tiny- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those positions, I began to work more frequently with recyclable parts.
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. Workarounds for JavaScript exist, 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 layouts are to be replaced by responsive components.
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?
The best place to make that choice is probably not a component library that is disconnected from context and real content.
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 reliable cross-browser support for them, it’s difficult to say for certain whether container queries will be successful. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might always need to modify these elements 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. The above code can be implemented behind an @supports feature query even though Firefox is the only browser that supports subgrid at the time of writing.
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 never make it smaller than the content that is inside.”
—Jen Simmons,” Designing Intrinsic Layouts”
Additionally, intrinsic layouts can mix and match both fixed and flexible units, letting the content choose how much space is taken up.
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 to have the same breakpoints or content as in the previous implementation, components and patterns can be removed 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 using an intrinsic approach without relying on container queries.
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 design agency position I held 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 all-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 the benefit of having a selection of units is a hindrance when it comes to creating layout templates, intrinsic design and frameworks do not go hand in hand 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 show how the site would appear throughout our careers at some point.
How do you do that now, with each component responding to content and layouts flexing as and when they need to? This kind of design must take place in the browser, which is something I’m very fond of.
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 content modifications, such as the earlier Subgrid card example, which allowed the cards to adjust both their own content and that of their sibling elements.
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 dated markup tricks like this —
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 decision 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”.
On a 50 MB budget, I spent a day surfing the web.
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, in the real world, our users may be commuters using smaller mobile devices that may experience drops in connectivity while traveling on trains or other modes of transportation. 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, there is a light-level feature that enables you to alter a user’s style when they are in the sun or the darkness. 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, the one thing we should always anticipate is 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 do 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 usable when people need them, whenever and wherever that may be. 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 scenario, spoken language also has the privilege of face-to-face contact, where we can readily interpret nonverbal social cues.
In contrast, written language develops its own fossil record of dated terms and phrases as we record it and keep usages long after they are no longer needed in spoken communication ( for example, the salutation” To whom it may concern” ). Because it tends to be more consistent, polished, and formal, written text is fundamentally much easier for machines to parse and understand.
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 conveys much more than the written word could ever contain, whether it be rapid-fire, low-pitched, or 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 essentially every voice interaction: a single conversation that starts 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 must not be one particular 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 ).
How are things going, Alison?
Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?
Alison, can I get a pineapple-onion pizza in Hawaii?
Burhan: Sure, what size?
Large, Alison.
Burhan: Anything else?
Alison: No, that’s it.
Burhan: Something to drink?
I’ll have a bottle of Coke, Alison.
Burhan: You got it. That will cost$ 13.55 and take about fifteen minutes.
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.
How are things going, Alison?
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 a lot different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions to gather data, news, or facts in search of the truth. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. In order for the customer to understand the key takeaways, responses are typically longer, more in-depth, and carefully communicated.
Voice-based user interfaces use speech at the core 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 in this book with pure voice interfaces because multimodal voice interfaces can lean on visual components like screens as crutches, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with.
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 engaged in authentic conversation with the advent of interactive voice response ( IVR ) systems, which were created as an alternative to overburdened customer service representatives.
IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. These systems, which are commonplace in the corporate world, were primarily intended as metaphorical switchboards to direct customers to real phone agents (” Say Reservations to book a flight or check an itinerary” ), and it is likely that when you call an airline or hotel conglomerate, you will have the opportunity to have a conversation with one. 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 conversations that typically don’t veer from a single format.
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 delivery of content via 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 ( ). The first IBM Screen Reader for text-based computers was created by Jim Thatcher in the same year, which was later recreated 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, allowing them to do so in an aural and temporal space. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. in A List Apart, writes Aaron Gustafson, “into useful information.” ” At least they do when documents are authored thoughtfully” ( ).
There is a big draw for screen readers: they’re challenging 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 before converting it to audio only after that. 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 without worrying about it. 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 popular subset of voice interfaces found in living rooms, smart homes, and offices with the film A Space Odyssey or with Majel Barrett’s voice as the omniscient computer from 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, so even now it isn’t possible to program Siri to perform arbitrary functions.
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 today have the option to choose from among the thousands of custom-built skills available in the Google Assistant and Amazon Alexa ecosystems.
As businesses like Amazon, Apple, Microsoft, and Google continue to dominate their markets, they are also selling and open-sourcing an unmatched range of tools and frameworks for designers and developers, aiming to make creating voice interfaces as simple as possible, even without the use of any 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, such as Google’s Dialogflow, have omnichannel capabilities that allow 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. There is only one issue: 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, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while being viewed in microfilm format in 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], an airplane flight’s arrival and departure times, 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 goes beyond 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. The best way to learn how to stretch your content to the limits of its potential is through microcontent, which will inform both established and new delivery methods.
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 see when the next train is coming from a digital sign underground, 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.
Fundamentally, how voice content manifests in perceived time and space both affect the legibility and discoverability of our voice content.
In the 1950s, some members of the elite running group had come to accept the idea that it was impossible to run a hour in less than four hours. 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 anyone by surprise. 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 today knew that the four-minute hour could be accomplished thanks to this change in the criterion. 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 all managed to cross the four-minute challenge. 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 human running speed, we also think there are strict guidelines for how a website should do.
The essential 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. However, 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 assess the pollutants coming out of the exhaust valves on our laptops. Our websites ‘ emissions are far away, out of mind, and out of sight when fuel and oil 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 carbon 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 energy is being consumed and how much carbon is being released. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.
The most accurate way to calculate data transfer for a single visit for web pages is to measure the page weight, which is the first time a user visits the page in kilobytes. 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, whereas web performance often depends more on the user’s perception of load times than it does on how effective the underlying system is.
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.
We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. 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, repeat users who load the same page frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all of the files back 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. We can learn even more about how to optimize efficiency for users who regularly visit our pages by measuring transfer size at this next level of detail, which will also enable us to establish page weight budgets for situations that extend beyond the initial visit.
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 ). 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 energy from a variety of sources is combined with various levels of carbon intensity. 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. This user-provided data is reported and mapped by Danish startup Tomorrow, and a look at their map demonstrates how, for instance, choosing a data center in France will result in 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 from that location to the data center used by our hosting company by using the distance itself 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 look up the travel distance between London and San Francisco, 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 lessen the distance and the amount of energy required 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. The method my team developed converts the amount of electricity transferred when loading a web page into a CO2 figure ( Fig. 2.4), and then converts that data into a figure for the tool. 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 improve it and tailor the data more appropriately to your project’s unique features.
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, and this is in line with 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 energy is used by the user’s devices as a result of the user’s web browser’s increased computation. 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 make them use older, slower devices and make their phones and laptops ‘ batteries discharge 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 Safari browser’s developer console ( Fig. 2.5 ) is one of the tools we currently use.
You know 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 based on the percentage of CPU used and how long it took the web page to load. 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.