Star Trek is all about exploring the final frontier. But its also about how you can’t explore it alone. From the naval trappings that inform its starship setting to the utopian United Federation of Planets, Star Trek offers a fundamentally communal vision, a depiction of the future in which humanity has overcome its petty differences […]

The post Star Trek Crews Ranked from Worst to the Real Number Ones appeared first on Den of Geek.

Star Trek is all about exploring the final frontier. But its also about how you can’t explore it alone. From the naval trappings that inform its starship setting to the utopian United Federation of Planets, Star Trek offers a fundamentally communal vision, a depiction of the future in which humanity has overcome its petty differences and work together.

That vision begins on the bridge of each ship in the respective Star Trek series. Yet, as anyone who’s ever visited a Trek-centric website knows well, not all crews are created equal. So here’s our attempt to rank the ten main crews across the Star Trek franchise.

10. Sirena (Picard)

Even if the third and final season of Star Trek: Picard didn’t reunite the TNG crew on a reconstituted Enterprise-D, the crew of the Sirena would be in last place. How could they not be? Owing to Patrick Stewart‘s reluctance to repeat too much of what he previously did as Jean-Luc Picard, the first two seasons of Picard didn’t have a proper crew. Instead, he gathered a rag-tag group to go on an unauthorized mission.

Some of those members did make for compelling characters. Jeri Ryan has made Seven of Nine only more nuanced over the years, Santiago Cabrera is endlessly watchable as Chris Rios, and Alison Pill manages to find something compelling in the disastrously-written Agnes Jurati. But with duds like Raffi and Elnor on board, Picard shows that rag-tag teams don’t work when audiences don’t enjoy watching the misfits interact. If only the current Trek producers learned that lesson before making Section 31…

9. NX-01 (Enterprise)

Certainly, some will point out that other, more recent shows deserve to be lower than the team on the NX-01, because Enterprise gave each member of its bridge crew at least one character trait. However, this writer contends that it would be better to know nothing about a character than to know that they’re insufferable jerks, which is too often the case aboard the NX-01.

This isn’t to say that Enterprise was completely devoid of interesting figures. Trip Tucker managed to embody the fighter-pilot mentality that the series wanted to harness, T’Pol’s arc showed just how hard it was to build the alliance between Earth and Vulcan, and Phlox is the best doctor on the show. But compared to Archer’s confused belligerence and Reed’s constant whining or creepiness, Mayweather becomes one of the best characters on the show because we can’t hate someone that we know nothing about.

8. Discovery (Discovery)

Discovery belongs toward the bottom because it eschews the ensemble approach that became the franchise’s trademark. Michael Burnham is a solo protagonist in the way Star Trek had not had since TOS (and even then, it was only a one-man show when Shatner got his way). One episode reveals that that Owosekun comes from a planet of space Luddites, another shows that Detmer is mad a Michael for a while about the hunk of mettle in her face, and one of the other guys says he likes to surf… I don’t remember which.

That said, there are some gems in Discovery‘s crew, even in its unusual structure. Sonequa Martin-Green’s considerable charisma isn’t quite enough to make Michael someone worth so much attention, but Mary Wiseman’s earnest and annoying Tilly helped bring out the best in the eventual captain. Doug Jones is incredible as Saru, adding a layered vocal performance to his remarkable-as-usual physical acting. Stamets and Culber sometimes suffered from uneven writing, but they managed to show how a marriage could work on a starship. And Tig Notaro may have just been playing herself in space, but Tig Notaro is great, and she killed every line.

7. Voyager (Voyager)

Voyager very much wanted to return to Next Generation-style storytelling after the more experimental Deep Space Nine. At first, that meant not just a return to episodic storytelling, but also a focus on the ensemble crew. Even better, the series’ premise gave Voyager a great storytelling engine with which to work, as getting stranded in the Delta Quadrant required members of the Maquis, ex-Starfleet officers who rebelled against the organization, to fall in under Janeway’s command.

In an incredibly frustrating move, the producers of Voyager decided to ignore the potential stories in such a conflict. Outside of a handful of episodes here and there, the former Maquis and the Starfleet officers had no issues. Sadly, missed opportunities became the hallmark of the show’s approach to the ensemble, especially once Seven of Nine. From that point on, Harry Kim, B’Elanna Torres, and Tuvok took a back seat to Janeway, Seven, and the Doctor. That trio got plenty of great episodes, and it was always nice when attention turned to some of the other members of crew. But it’s hard to give Voyager special condemnation for its ensemble work.

6. Protostar (Prodigy)

From this point on, all of the Star Trek shows do a good job with their ensembles, and all of the crews are good—the only question is about how good they are. And, for certain, the group of alien children who escape the confines of an alien overlord from the Delta Quadrant and become Starfleet cadets are very good. Prodigy somehow manages to be a kid’s show, a sequel to Discovery, and a darn good Star Trek show, all at once.

That said, the narrative of Prodigy demands that they aren’t quite on the level of the other more professional and seasoned crews on this list. Dal has all the makings of a great captain, Gwyndala will be a great linguist, Jankom Pog will be a great engineer, and so on. But they aren’t there quite yet, because they’re still kids learning about how Starfleet works. That fact makes for fantastic viewing, and we better get at least one more season of Prodigy to see how they develop. But it also puts the crew at the bottom of the good groups on this list.

5. Cerritos (Lower Decks)

At first, it seemed like Lower Decks would be a two-hander with a couple supporting characters, surrounded by thinly-sketched others. Ensigns Mariner and Boimler were the stars, Ensigns Rutherford and Tendi were their friends, and everyone else existed for jokes. But as Lower Decks developed, it became about more than just laughing about horga’hns and Spock Helmets. It became a proper Star Trek show, about exploration and discovery.

As it did so, the characters developed and the crew became more distinct. Mariner and Boimler evolved past just slacker and try-hard, into good Starfleet officers, just like Rutherford and Tendi became more than just players in the leads’ adventures. Even better were the rest of the Cerritos‘s crew, especially Mariner’s mother Carol Freeman. Neither a once-in-a-generation adventurer like Kirk nor a perfect diplomat like Picard, Captain Freeman is just trying to do her job, and she does it well. It’s Freeman’s no-nonsense watch over the Cerritos that allows her crew of goofballs to shine.

4. Enterprise (Strange New Worlds)

The Strange New Worlds crew aboard the pre-Kirk Enterprise is fun to watch. Beginning with Anson Mount’s take on Captain Pike as a cool, supportive older brother, Strange New Worlds feels less like the return to exploration suggested by its title and more of a romp across space starring familiar characters. While the individual episodes may not be to everyone’s tastes, such as the infamous musical episode or the self-parodying proto-holodeck episode, no one can help but smile while watching the cast interact.

Some of that fun comes from the compelling new characters added to the series, the security officer La’an or the cooky engineer Pelia. Likewise, the show has done remarkably well acting as a prequel, giving us belivably younger versions of Uhura, Scotty, and Spock. But the real pleasure of Strange New Worlds has been the way it develops characters we knew only by name. Number One, M’Benga, and Chapel have gone from being footnotes in Trek history to fully-formed characters who deserve mention alongside their more famous counterparts.

3. Enterprise (The Original Series)

I know, I know. The Original Series set the stage! Star Trek wouldn’t be Star Trek without Scotty and Uhura and Sulu and Chekov! While this is true, it’s also true that everyone who wasn’t in the central trio of Kirk, Spock, and McCoy never got much character development, even in films that purported to give them more to do. As director, Leonard Nimoy made a point of spreading the attention to his co-stars in Star Trek IV: The Voyage Home, but that attention still resulted in single bits: Scotty talking into a mouse, Chekov looks for nuclear ‘wessels,’ Sulu checks out a chopper.

However, the fact that the crew is so beloved despite their relatively small amount of screentime makes them all the more impressive. None of the side characters displace the main three, but Nichelle Nichols, James Doohan, Walter Koenig, and George Takei manage to make the most of the attention they get, so that they feel far more fleshed out than they actually are. Thanks to the supporting cast’s work, TOS set the stage for the crews to come.

2. Deep Space Nine (Deep Space Nine)

Deep Space Nine has a bit of an unfair advantage, as its central cast isn’t the crew of a starship; they’re the staff on a space station. That difference allows us to include barkeep Quark and constable Odo, characters that otherwise might not fit on the main crew. But the real secret to DS9‘s success comes down to its commander-turned-captain, Benjamin Sisko. From the very beginning, Sisko was a different type of character than the other leads, a single father who was skeptical of Starfleet and thrust into the position of religious figure.

Because of this distinction, Sisko was able to have different types of interactions with those around him, making for unique interactions with the crew. He saw Dax as both a subordinate and a mentor, thanks to the symbiote she carried. He bonded with O’Brien over feeling like an outsider, while he recognized Garak as a necessary evil. From the top down, DS9 offered new team dynamics, all part of its groundbreaking approach to the franchise.

1. Enterprise (The Next Generation)

The Original Series crew felt like a group of compelling characters who worked and lived together. The Next Generation crew was a a group of compelling characters who worked and lived together. Well, eventually they became that. Part of the problem in the famously uneven first two seasons of TNG is that it tries to replicate the focus on three characters—originally, Picard, Data, and Geordi. But as the series went on (and Stewart gave into playing along with his co-stars), the Enterprise-D became a proper ensemble.

Several episodes demonstrate these dynamics, from the delightful holodeck romps to the gripping two-parters. But none illustrate it better than the series finale, “All Good Things…” Watching Picard check in with the crew across time, only to finally join them in a card game at the end puts the perfect capper on the show. These are explorers and scientists and military personnel, yes. But most of all, these are friends.

The post Star Trek Crews Ranked from Worst to the Real Number Ones appeared first on Den of Geek.

Feedback, in whichever form it takes, and whatever it may be called, is one of the most effective soft skills that we have at our disposal to collaboratively get our designs to a better place while growing our own skills and perspectives.

Feedback is also one of the most underestimated tools, and often by assuming that we’re already good at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Poor feedback can create confusion in projects, bring down morale, and affect trust and team collaboration over the long term. Quality feedback can be a transformative force. 

Practicing our skills is surely a good way to improve, but the learning gets even faster when it’s paired with a good foundation that channels and focuses the practice. What are some foundational aspects of giving good feedback? And how can feedback be adjusted for remote and distributed work environments? 

On the web, we can identify a long tradition of asynchronous feedback: from the early days of open source, code was shared and discussed on mailing lists. Today, developers engage on pull requests, designers comment in their favorite design tools, project managers and scrum masters exchange ideas on tickets, and so on.

Design critique is often the name used for a type of feedback that’s provided to make our work better, collaboratively. So it shares a lot of the principles with feedback in general, but it also has some differences.

The content

The foundation of every good critique is the feedback’s content, so that’s where we need to start. There are many models that you can use to shape your content. The one that I personally like best—because it’s clear and actionable—is this one from Lara Hogan.

While this equation is generally used to give feedback to people, it also fits really well in a design critique because it ultimately answers some of the core questions that we work on: What? Where? Why? How? Imagine that you’re giving some feedback about some design work that spans multiple screens, like an onboarding flow: there are some pages shown, a flow blueprint, and an outline of the decisions made. You spot something that could be improved. If you keep the three elements of the equation in mind, you’ll have a mental model that can help you be more precise and effective.

Here is a comment that could be given as a part of some feedback, and it might look reasonable at a first glance: it seems to superficially fulfill the elements in the equation. But does it?

Not sure about the buttons’ styles and hierarchy—it feels off. Can you change them?

Observation for design feedback doesn’t just mean pointing out which part of the interface your feedback refers to, but it also refers to offering a perspective that’s as specific as possible. Are you providing the user’s perspective? Your expert perspective? A business perspective? The project manager’s perspective? A first-time user’s perspective?

When I see these two buttons, I expect one to go forward and one to go back.

Impact is about the why. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

The question approach is meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s a viable option for feedback in general, for design critiques, in my experience, defaulting to the question approach usually reaches the best solutions because designers are generally more comfortable in being given an open space to explore.

The difference between the two can be exemplified with, for the question approach:

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

Or, for the request approach:

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

Choosing the question approach or the request approach can also at times be a matter of personal preference. A while ago, I was putting a lot of effort into improving my feedback: I did rounds of anonymous feedback, and I reviewed feedback with other people. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. Until I changed teams. To my shock, my next round of feedback from one specific person wasn’t that great. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. But now in this other team, there was one person who instead preferred specific guidance. So I adapted my feedback for them to include requests.

One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. No… but also yes. Let’s explore both sides.

No, this style of feedback is actually efficient because the length here is a byproduct of clarity, and spending time giving this kind of feedback can provide exactly enough information for a good fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just, “Let’s make sure that all screens have the same two forward and back buttons.” The designer receiving this feedback wouldn’t have much to go by, so they might just apply the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. Without the why, the designer might imagine that the change is about consistency… but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

Yes, this style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (“The font used doesn’t follow our guidelines”) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

So the equation above isn’t meant to suggest a strict template for feedback but a mnemonic to reflect and improve the practice. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

The tone

Well-grounded content is the foundation of feedback, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. Tone alone can make the difference between content that’s rejected or welcomed, and it’s been demonstrated that only positive feedback creates sustained change in people.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. Over the years, I’ve tried to summarize the required soft skills in a formula that mirrors the one for content: the receptivity equation.

Respectful feedback comes across as grounded, solid, and constructive. It’s the kind of feedback that, whether it’s positive or negative, is perceived as useful and fair.

Timing refers to when the feedback happens. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. Questioning the entire high-level information architecture of a new feature when it’s about to ship might still be relevant if that questioning highlights a major blocker that nobody saw, but it’s way more likely that those concerns will have to wait for a later rework. So in general, attune your feedback to the stage of the project. Early iteration? Late iteration? Polishing work in progress? These all have different needs. The right timing will make it more likely that your feedback will be well received.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. That means checking before we write to see whether what we have in mind will truly help the person and make the project better overall. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Hopefully that’s not the case, but that can happen, and that’s okay. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I be more constructive?

Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. There might be many reasons for this: sometimes certain words might trigger specific reactions; sometimes nonnative speakers might not understand all the nuances of some sentences; sometimes our brains might just be different and we might perceive the world differently—neurodiversity must be taken into consideration. Whatever the reason, it’s important to review not just what we write but how.

A few years back, I was asking for some feedback on how I give feedback. I received some good advice but also a comment that surprised me. They pointed out that when I wrote “Oh, […],” I made them feel stupid. That wasn’t my intent! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. I was horrified… but also thankful. I made a quick fix: I added “oh” in my list of replaced words (your choice between: macOS’s text replacement, aText, TextExpander, or others) so that when I typed “oh,” it was instantly deleted. 

Something to highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. It’s important to remember here that a positive attitude doesn’t mean going light on the feedback—it just means that even when you provide hard, difficult, or challenging feedback, you do so in a way that’s respectful and constructive. The nicest thing that you can do for someone is to help them grow.

We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. I found that the best, most insightful moments for me have happened when I’ve shared a comment and I’ve asked someone who I highly trusted, “How does this sound?,” “How can I do it better,” and even “How would you have written it?”—and I’ve learned a lot by seeing the two versions side by side.

The format

Asynchronous feedback also has a major inherent advantage: we can take more time to refine what we’ve written to make sure that it fulfills two main goals: the clarity of communication and the actionability of the suggestions.

Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. There are many ways to do this, and of course context matters, but let’s try to think about some elements that may be useful to consider.

In terms of clarity, start by grounding the critique that you’re about to give by providing context. Specifically, this means describing where you’re coming from: do you have a deep knowledge of the project, or is this the first time that you’re seeing it? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s perspective are you taking when providing your feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

Providing context is helpful even if you’re sharing feedback within a team that already has some information on the project. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

We often focus on the negatives, trying to outline all the things that could be done better. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. This might seem superfluous, but it’s important to keep in mind that design is a discipline where there are hundreds of possible solutions for every problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. As a bonus, positive feedback can also help reduce impostor syndrome.

There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo (compared to a previous iteration, competitors, or benchmarks) and why, and then on that foundation, you can add what could be improved. This is powerful because there’s a big difference between a critique that’s for a design that’s already in good shape and a critique that’s for a design that isn’t quite there yet.

Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. It’s “This button isn’t well aligned” versus “You haven’t aligned this button well.” This is very easy to change in your writing by reviewing it just before sending.

In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. For longer pieces of feedback, you might also consider splitting it into sections or even across multiple comments. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. So a red square 🟥 means that it’s something that I consider blocking; a yellow diamond 🔶 is something that I can be convinced otherwise, but it seems to me that it should be changed; and a green circle 🟢 is a detailed, positive confirmation. I also use a blue spiral 🌀 for either something that I’m not sure about, an exploration, an open alternative, or just a note. But I’d use this approach only on teams where I’ve already established a good level of trust because if it happens that I have to deliver a lot of red squares, the impact could be quite demoralizing, and I’d reframe how I’d communicate that a bit.

Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

• 🔶 Navigation—When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
• 🟢 Overall—I think the page is solid, and this is good enough to be our release candidate for a version 1.0.
• 🟢 Metrics—Good improvement in the buttons on the metrics area; the improved contrast and new focus style make them more accessible.
•  🟥  Button Style—Using the green accent in this context creates the impression that it’s a positive action because green is usually perceived as a confirmation color. Do we need to explore a different color?
• 🔶Tiles—Given the number of items on the page, and the overall page hierarchy, it seems to me that the tiles shouldn’t be using the Subtitle 1 style but the Subtitle 2 style. This will keep the visual hierarchy more consistent.
• 🌀 Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the thinking in using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? In general, I find these difficult to use because they hide discussions and they’re harder to track, but in the right context, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

One final note: say the obvious. Sometimes we might feel that something is obviously good or obviously wrong, and so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it—that’s okay. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

There’s another advantage of asynchronous feedback: written feedback automatically tracks decisions. Especially in large projects, “Why did we do this?” could be a question that pops up from time to time, and there’s nothing better than open, transparent discussions that can be reviewed at any time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved. 

Content, tone, and format. Each one of these subjects provides a useful model, but working to improve eight areas—observation, impact, question, timing, attitude, form, clarity, and actionability—is a lot of work to put in all at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others) and start there. Then the second, then the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

“Any comment?” is probably one of the worst ways to ask for feedback. It’s vague and open ended, and it doesn’t provide any indication of what we’re looking for. Getting good feedback starts earlier than we might expect: it starts with the request. 

It might seem counterintuitive to start the process of receiving feedback with a question, but that makes sense if we realize that getting feedback can be thought of as a form of design research. In the same way that we wouldn’t do any research without the right questions to get the insights that we need, the best way to ask for feedback is also to craft sharp questions.

Design critique is not a one-shot process. Sure, any good feedback workflow continues until the project is finished, but this is particularly true for design because design work continues iteration after iteration, from a high level to the finest details. Each level needs its own set of questions.

And finally, as with any good research, we need to review what we got back, get to the core of its insights, and take action. Question, iteration, and review. Let’s look at each of those.

The question

Being open to feedback is essential, but we need to be precise about what we’re looking for. Just saying “Any comment?”, “What do you think?”, or “I’d love to get your opinion” at the end of a presentation—whether it’s in person, over video, or through a written post—is likely to get a number of varied opinions or, even worse, get everyone to follow the direction of the first person who speaks up. And then… we get frustrated because vague questions like those can turn a high-level flows review into people instead commenting on the borders of buttons. Which might be a hearty topic, so it might be hard at that point to redirect the team to the subject that you had wanted to focus on.

But how do we get into this situation? It’s a mix of factors. One is that we don’t usually consider asking as a part of the feedback process. Another is how natural it is to just leave the question implied, expecting the others to be on the same page. Another is that in nonprofessional discussions, there’s often no need to be that precise. In short, we tend to underestimate the importance of the questions, so we don’t work on improving them.

The act of asking good questions guides and focuses the critique. It’s also a form of consent: it makes it clear that you’re open to comments and what kind of comments you’d like to get. It puts people in the right mental state, especially in situations when they weren’t expecting to give feedback.

There isn’t a single best way to ask for feedback. It just needs to be specific, and specificity can take many shapes. A model for design critique that I’ve found particularly useful in my coaching is the one of stage versus depth.

“Stage” refers to each of the steps of the process—in our case, the design process. In progressing from user research to the final design, the kind of feedback evolves. But within a single step, one might still review whether some assumptions are correct and whether there’s been a proper translation of the amassed feedback into updated designs as the project has evolved. A starting point for potential questions could derive from the layers of user experience. What do you want to know: Project objectives? User needs? Functionality? Content? Interaction design? Information architecture? UI design? Navigation design? Visual design? Branding?

Here’re a few example questions that are precise and to the point that refer to different layers:

• Functionality: Is automating account creation desirable?
• Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
• Information architecture: We have two competing bits of information on this page. Is the structure effective in communicating them both?
• UI design: What are your thoughts on the error counter at the top of the page that makes sure that you see the next error, even if the error is out of the viewport? 
• Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Are there any suggestions to address this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is about how deep you’d like to go on what’s being presented. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially useful from one iteration to the next where it’s important to highlight the parts that have changed.

There are other things that we can consider when we want to achieve more specific—and more effective—questions.

A simple trick is to remove generic qualifiers from your questions like “good,” “well,” “nice,” “bad,” “okay,” and “cool.” For example, asking, “When the block opens and the buttons appear, is this interaction good?” might look specific, but you can spot the “good” qualifier, and convert it to an even better question: “When the block opens and the buttons appear, is it clear what the next action is?”

Sometimes we actually do want broad feedback. That’s rare, but it can happen. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or maybe just say, “At first glance, what do you think?” so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

Sometimes the project is particularly expansive, and some areas may have already been explored in detail. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. It’s not something that I’d recommend in general, but I’ve found it useful to avoid falling again into rabbit holes of the sort that might lead to further refinement but aren’t what’s most important right now.

Asking specific questions can completely change the quality of the feedback that you receive. People with less refined critique skills will now be able to offer more actionable feedback, and even expert designers will welcome the clarity and efficiency that comes from focusing only on what’s needed. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Yet a lot of design tools with inline commenting tend to show changes as a single fluid stream in the same file, and those types of design tools make conversations disappear once they’re resolved, update shared UI components automatically, and compel designs to always show the latest version—unless these would-be helpful features were to be manually turned off. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That’s probably not the best way to approach design critiques, but even if I don’t want to be too prescriptive here: that could work for some teams.

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. Any platform that can accommodate this structure can use this. By the way, when I refer to a “write-up or presentation,” I’m including video recordings or other media too: as long as it’s asynchronous, it works.

Using iteration posts has many advantages:

• It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
• It makes decisions visible for future review, and conversations are likewise always available.
• It creates a record of how the design changed over time.
• Depending on the tool, it might also make it easier to collect feedback and act on it.

These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. And other feedback approaches (such as live critique, pair designing, or inline comments) can build from there.

I don’t think there’s a standard format for iteration posts. But there are a few high-level elements that make sense to include as a baseline:

1. The goal
2. The design
3. The list of changes
4. The questions

Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. So this is something that I’d repeat in every iteration post—literally copy and pasting it. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. If I want to know about the latest design, the latest iteration post will have all that I need.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. So having posts that repeat information is actually very effective toward making sure that everyone is on the same page.

The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. In short, it’s any design artifact. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture. 

It can also be useful to label the artifacts with clear titles because that can make it easier to refer to them. Write the post in a way that helps people understand the work. It’s not too different from organizing a good live presentation. 

For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

And finally, as noted earlier, it’s essential that you include a list of the questions to drive the design critique in the direction you want. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not all iterations are the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then later, the iterations start settling on a solution and refining it until the design process reaches its end and the feature ships.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be a draft—just a concept to get a conversation going—or it could be a cumulative list of each feature that was added over the course of each iteration until the full picture is done.

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. This might look like a minor labelling tip, but it can help in multiple ways:

• Unique—It’s a clear unique marker. Within each project, one can easily say, “This was discussed in i4,” and everyone knows where they can go to review things.
• Unassuming—It works like versions (such as v1, v2, and v3) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Iterations must be able to be exploratory, incomplete, partial.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files named “final final complete no-really-its-done.” Within each project, the largest number always represents the latest iteration.

To mark when a design is complete enough to be worked on, even if there might be some bits still in need of attention and in turn more iterations needed, the wording release candidate (RC) could be used to describe it: “with i8, we reached RC” or “i12 is an RC.”

The review

What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This approach is particularly effective during live, synchronous feedback. But when we work asynchronously, it’s more effective to use a different approach: we can shift to a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

This shift has some major benefits that make asynchronous feedback particularly effective, especially around these friction points:

1. It removes the pressure to reply to everyone.
2. It reduces the frustration from swoop-by comments.
3. It lessens our personal stake.

The first friction point is feeling a pressure to reply to every single comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s easy, and it doesn’t feel like a problem. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Sometimes replying to all comments can be effective, but if we treat a design critique more like user research, we realize that we don’t have to reply to every comment, and in asynchronous spaces, there are alternatives:

• One is to let the next iteration speak for itself. When the design evolves and we post a follow-up iteration, that’s the reply. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement. 
• Another is to briefly reply to acknowledge each comment, such as “Understood. Thank you,” “Good points—I’ll review,” or “Thanks. I’ll include these in the next iteration.” In some cases, this could also be just a single top-level comment along the lines of “Thanks for all the feedback everyone—the next iteration is coming soon!”
• Another is to provide a quick summary of the comments before moving on. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

The second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements—or of the previous iterations’ discussions. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments often trigger the simple thought “We’ve already discussed this…”, and it can be frustrating to have to repeat the same reply over and over.

Let’s begin by acknowledging again that there’s no need to reply to every comment. If, however, replying to a previously litigated point might be useful, a short reply with a link to the previous discussion for extra details is usually enough. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting can still be useful for two reasons: they might point out something that still isn’t clear, and they also have the potential to stand in for the point of view of a user who’s seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

The third friction point is the personal stake we could have with the design, which could make us feel defensive if the review were to feel more like a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego (because yes, even if we don’t want to admit it, it’s there). And ultimately, treating everything in aggregated form allows us to better prioritize our work.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer. 

As the designer leading the project, you’re in charge of that decision. Ultimately, everyone has their specialty, and as the designer, you’re the one who has the most knowledge and the most context to make the right decision. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

I’m not sure when I first heard this quote, but it’s something that has stayed with me over the years. How do you create services for situations you can’t imagine? Or design products that work on devices yet to be invented?

Flash, Photoshop, and responsive design

When I first started designing websites, my go-to software was Photoshop. I created a 960px canvas and set about creating a layout that I would later drop content in. The development phase was about attaining pixel-perfect accuracy using fixed widths, fixed heights, and absolute positioning.

Ethan Marcotte’s talk at An Event Apart and subsequent article “Responsive Web Design” in A List Apart in 2010 changed all this. I was sold on responsive design as soon as I heard about it, but I was also terrified. The pixel-perfect designs full of magic numbers that I had previously prided myself on producing were no longer good enough.

The fear wasn’t helped by my first experience with responsive design. My first project was to take an existing fixed-width website and make it responsive. What I learned the hard way was that you can’t just add responsiveness at the end of a project. To create fluid layouts, you need to plan throughout the design phase.

A new way to design

Designing responsive or fluid sites has always been about removing limitations, producing content that can be viewed on any device. It relies on the use of percentage-based layouts, which I initially achieved with native CSS and utility classes:

.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%;
}

Then with Sass so I could take advantage of @includes to re-use repeated blocks of code and move back to more semantic markup:

.logo {
  @include colSpan(6);
}

.search {
  @include colSpan(3);
}

.social-share {
  @include colSpan(3);
}

Media queries

The second ingredient for responsive design is media queries. Without them, content would shrink to fit the available space regardless of whether that content remained readable (The exact opposite problem occurred with the introduction of a mobile-first approach).

Media queries 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.

Row markup was a staple of early responsive design, present in all the widely used frameworks 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 problem arose as I moved from a design agency building websites for small- to medium-sized businesses, to larger in-house teams where I worked across a suite of related sites. In those roles I started to work much more with reusable components. 

Our reliance on media queries resulted in components that were tied to common viewport sizes. If the goal of component libraries is reuse, then this is a real problem because you can only use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process not really hitting that “devices that don’t yet exist”  goal.

Then there’s the problem of space. Media queries 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: our savior or a false dawn?

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 JavaScript workarounds, but they can create dependency 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 components 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 concern is that we are still using layout 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 removed from context and real content is probably not the best place for that decision. 

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.

It’s hard to say for sure whether container queries will be a success story until we have solid cross-browser support for them. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. But maybe we will always need to adjust these components to suit our content.

CSS is changing

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;
}

The biggest benefit of all this is you don’t need to wrap elements in container rows. 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 at the time of writing is only supported in Firefox but the above code can be implemented behind an @supports feature query. 

Intrinsic layouts 

I’d be remiss not to mention intrinsic layouts, the term created by Jen Simmons to describe a mixture of new and old 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.

fr units is a way to say I want you to distribute the extra space in this way, but…don’t ever make it smaller than the content that’s inside of it.

—Jen Simmons, “Designing Intrinsic Layouts”

Intrinsic layouts can also utilize a mixture of fixed and flexible units, allowing the content to dictate the space it takes 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. Components and patterns can be lifted and reused without the prerequisite of having the same breakpoints or the same amount of content as in the previous implementation. 

We can now create designs that adapt to the space they have, the content within them, and the content around them. With an intrinsic approach, we can construct responsive components without depending on container queries.

Another 2010 moment?

This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. For me, it’s another “everything changed” moment. 

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 reason for that could be that I now work in a large organization, which is quite different from the design agency role I had 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 could be that I feel more prepared for change now. In 2010 I was new to design in general; the shift was frightening and required a lot of learning. Also, an intrinsic approach isn’t exactly all-new; it’s about using existing skills and existing CSS knowledge in a different way. 

You can’t framework your way out of a content problem

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. 

Responsive grid systems were all over the place ten years ago. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

Intrinsic design and frameworks do not go hand in hand quite so well because the benefit of having a selection of units is a hindrance when it comes to creating layout templates. 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, at some point in our careers, used Photoshop templates for desktop, tablet, and mobile devices to drop designs in and show how the site would look at all three stages.

How do you do that now, with each component responding to content and layouts flexing as and when they need to? This type of design must happen in the browser, which personally I’m a big fan 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. To do this in a graphics-based software package is far from ideal. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it still work? 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 first 

Content is not constant. After all, to design for the unknown or unexpected we need to account for content changes like our earlier Subgrid card example that allowed the cards to respond to adjustments to their own content and the content of 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 old markup hacks 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.

In the Sass version, directional variables need to be set.

$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 properties.

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.

Fixed and fluid 

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% (the preferred value) of its container but never less than 300px and never more than 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. We can start to future-proof designs by planning for unexpected changes in language or direction. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

Situation first

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”?

It’s a very different thing to design for someone seated at a desktop computer as opposed to someone using a mobile phone and moving through a crowded street in glaring sunshine. 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 choice is so important. 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.

Responsible design 

“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. But in the real world, our users may be commuters traveling on trains or other forms of transport using smaller mobile devices that can experience drops in connectivity. 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?

The return of media queries 

Media queries 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. 

As of this writing, the Media Queries Level 5 spec is still under development. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

For example, there’s a light-level feature that allows you to modify styles if a user is in sunlight or 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 queries like this go beyond choices made by a browser to grant more control to the user.

Expect the unexpected

In the end, the one thing we should always expect is for things to change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

We can’t design the same way we have for this ever-changing landscape, but we can design for content. 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. From responsive components to fixed and fluid units, there is so much more we can do to take a more intrinsic approach. 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 situations, we need to make sure our products are usable when people need them, whenever and wherever that might 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 having conversations for thousands of years. Whether to convey information, conduct transactions, or simply to check in on one another, people have yammered away, chattering and gesticulating, through spoken conversation for countless generations. Only in the last few millennia have we begun to commit our conversations to writing, and only in the last few decades have we begun to outsource them to the computer, a machine that shows much more affinity for written correspondence than for the slangy vagaries of spoken language.

Computers have trouble because between spoken and written language, speech is more primordial. To have successful conversations with us, machines must grapple with the messiness of human speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that can stymie even the most carefully 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 immediately concretizes as we commit it to record and retains usages long after they become obsolete in spoken communication (the salutation “To whom it may concern,” for example), generating its own fossil record of outdated terms and phrases. Because it tends to be more consistent, polished, and formal, written text is fundamentally much easier for machines to parse and understand.

Spoken language has no such luxury. 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. Whether rapid-fire, low-pitched, or high-decibel, whether sarcastic, stilted, or sighing, our spoken language conveys much more than the written word could ever muster. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice Interactions

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 (). Generally, we start up a conversation because:

• we need something done (such as a transaction),
• we want to know something (information of some sort), or
• we are social beings and want someone to talk to (conversation for conversation’s sake).

These three categories—which I call transactional, informational, and prosocial—also characterize essentially every voice interaction: a single conversation from beginning to end that realizes some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting 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 a conversation is not necessarily a single 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. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts 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 ().

That leaves two genres of conversations we can have with one another that a voice interface can easily have with us, too: a transactional voice interaction realizing some outcome (“buy iced tea”) and an informational voice interaction teaching us something new (“discuss a musical”).

Transactional voice interactions

Unless you’re tapping buttons on a food delivery app, you’re generally having a conversation—and therefore a voice interaction—when you order a Hawaiian pizza with extra pineapple. 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’s it going?

Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

Alison: Can I get a Hawaiian pizza with extra pineapple?

Burhan: Sure, what size?

Alison: Large.

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. That’ll be $13.55 and 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. Transactional conversations have certain key traits: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Here, though we again have a prosocial mini-conversation at the beginning to establish politeness, we’re after much more.

Alison: Hey, how’s it going?

Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

Alison: Do you have any halal options on the menu?

Burhan: Absolutely! We can make any pie halal by request. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you thinking about any other dietary restrictions?

Alison: What about gluten-free pizzas?

Burhan: We can definitely do a gluten-free crust for you, no problem, for both our deep-dish and thin-crust pizzas. Anything else I can answer for you?

Alison: That’s it for now. Good to know. Thanks!

Burhan: Anytime, come back soon!

This is a very different dialogue. Here, the goal is to get a certain set of facts. Informational conversations are investigative quests for the truth—research expeditions to gather data, news, or facts. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses tend to be lengthier, more informative, and carefully communicated so the customer understands the key takeaways.

Voice Interfaces

At their core, voice interfaces employ speech to support users in reaching their goals. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. Because multimodal voice interfaces can lean on visual components like screens as crutches, we’re most concerned in this book with pure voice interfaces, which depend entirely on spoken conversation, lack any visual component whatsoever, and are therefore much more nuanced and challenging to tackle.

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.

Interactive voice response (IVR) systems

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. With the advent of interactive voice response (IVR) systems, intended as an alternative to overburdened customer service representatives, we became acquainted with the first true voice interfaces that engaged in authentic conversation.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Commonplace in the corporate world, these systems were primarily designed as metaphorical switchboards to guide customers to a real phone agent (“Say Reservations to book a flight or check an itinerary”); chances are you will enter 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).

While IVR systems are great for highly repetitive, monotonous conversations that generally don’t veer from a single format, they have a reputation for less scintillating conversation than we’re used to in real life (or even in science fiction).

Screen readers

Parallel to the evolution of IVR systems was the invention of the screen reader, a tool that transcribes visual content into synthesized speech. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Screen readers represent perhaps the closest equivalent we have today to an out-of-the-box implementation of content delivered through voice.

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 (). That same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, 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. Thanks to the introduction of semantic HTML and especially ARIA roles beginning in 2008, screen readers started facilitating speedy 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. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc.—into useful information,” writes Aaron Gustafson in A List Apart. “At least they do when documents are authored thoughtfully” ().

Though deeply instructive for voice interface designers, there’s one significant problem with screen readers: they’re difficult to use and unremittingly verbose. 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. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

From the beginning, I hated the way that Screen Readers work. Why are they designed the way they are? It makes no sense to present information visually and then, and only then, translate that 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, visual interface users have the benefit of darting around the viewport freely to find information, ignoring areas irrelevant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Disabled users who have long had no choice but to employ clunky screen readers may find that voice interfaces, particularly more modern voice assistants, offer a more streamlined experience.

Voice assistants

When we think of voice assistants (the subset of voice interfaces now commonplace in living rooms, smart homes, and offices), many of us immediately picture HAL from 2001: A Space Odyssey or hear 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 they’re rapidly gaining more attention from accessibility advocates for their assistive potential.

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 formulated their vision for a Semantic Web “agent” that would perform typical errands like “checking calendars, making appointments, and finding locations” (, behind paywall). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others (Fig 1.1). 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. Even today, it isn’t possible to program Siri to perform arbitrary functions, because there’s no means by which developers can interact with Siri at a low level, apart from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and certain others.

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, programmable voice assistants that lend themselves to customization and extensibility are becoming increasingly popular for developers who feel stifled by the limitations of Siri and Cortana. 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. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant ecosystems.

As corporations like Amazon, Apple, Microsoft, and Google continue to stake their territory, they’re also selling and open-sourcing an unprecedented array of tools and frameworks for designers and developers that aim to make building voice interfaces as easy 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. By contrast, many development platforms like Google’s Dialogflow have introduced omnichannel capabilities so users can build a single conversational interface that then manifests as 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.

Voice Content

Simply put, voice content is content delivered through voice. To preserve what makes human conversation so compelling in the first place, voice content needs to be free-flowing and organic, contextless and concise—everything written content isn’t.

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. In this book, we’re most concerned with content delivered auditorily—not as an option, but as a necessity.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. So how do we make the content trapped on our websites more conversational? And how do we write new copy that lends itself to voice interactions?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many respects, colossal vaults of what I call macrocontent: lengthy prose that can extend for infinitely scrollable 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:

A day’s weather forcast [sic], the arrival and departure times for an airplane flight, an abstract from a long publication, or a single instant message can all be examples of microcontent. ()

I’d update Dash’s definition of microcontent to include all examples of bite-sized content that go well 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. Microcontent offers the best opportunity to gauge how your content can be stretched to the very edges of its capabilities, informing delivery channels both established and novel.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can glance at a digital sign underground for an instant and know when the next train is arriving, but voice interfaces hold our attention captive for periods of time that we can’t easily escape or skip, something 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, the legibility and discoverability of our voice content both have to do with how voice content manifests in perceived time and space.

In the 1950s, many in the elite running community had begun to believe it wasn’t possible to run a mile in less than four minutes. Runners had been attempting it since the late 19th century and were beginning to draw the conclusion that the human body simply wasn’t built for the task. 

But on May 6, 1956, Roger Bannister took everyone by surprise. It was a cold, wet day in Oxford, England—conditions no one expected to lend themselves to record-setting—and yet Bannister did just that, running a mile in 3:59.4 and becoming the first person in the record books to run a mile in under four minutes. 

This shift in the benchmark had profound effects; the world now knew that the four-minute mile was possible. Bannister’s record lasted only forty-six days, when it was snatched away by Australian runner John Landy. Then a year later, three runners all beat the four-minute barrier together in the same race. Since then, over 1,400 runners have officially run a mile in under four minutes; the current record is 3:43.13, held by Moroccan athlete Hicham El Guerrouj.

We achieve far more when we believe that something is possible, and we will believe it’s possible only when we see someone else has already done it—and as with human running speed, so it is with what we believe are the hard limits for how a website needs to perform.

Establishing standards for a sustainable web

In most major industries, the key metrics of environmental performance are fairly well established, such as miles per gallon for cars or energy per square meter for homes. The tools and methods for calculating those metrics are standardized as well, which keeps everyone on the same page when doing environmental assessments. In the world of websites and apps, however, we aren’t held to any particular environmental standards, and only recently have gained the tools and methods we need to even make an environmental assessment.

The primary goal in sustainable web design is to reduce carbon emissions. However, it’s almost impossible to actually measure the amount of CO₂ produced by a web product. We can’t measure the fumes coming out of the exhaust pipes on our laptops. The emissions of our websites are far away, out of sight and out of mind, coming out of power stations burning coal and gas. We have no way to trace the electrons from a website or app back to the power station where the electricity is being generated and actually know the exact amount of greenhouse gas produced. So what do we do? 

If we can’t measure the actual carbon emissions, then we need to find what we can measure. The primary factors that could be used as indicators of carbon emissions are:

1. Data transfer 
2. Carbon intensity of electricity

Let’s take a look at how we can use these metrics to quantify the energy consumption, and in turn the carbon footprint, of the websites and web apps we create.

Data transfer

Most researchers use kilowatt-hours per gigabyte (kWh/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 provides a great reference point for energy consumption and carbon emissions. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.

For web pages, data transfer for a single visit can be most easily estimated by measuring the page weight, meaning the transfer size of the page in kilobytes the first time someone visits the page. It’s fairly easy to measure using the developer tools in any modern web browser. Often your web hosting account will include statistics for the total data transfer of any web application (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. 

Reducing page weight requires a large scope. 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). Roughly half of this data transfer is image files, making images the single biggest source of carbon emissions on the average website. 

History clearly shows us that our web pages can be smaller, if only we set our minds to it. While most technologies become ever more energy efficient, including the underlying technology of the web such as data centers and transmission networks, websites themselves are a technology that becomes less efficient as time goes on.

You might be familiar with the concept of performance budgeting as a way of focusing a project team on creating faster user experiences. 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. Much like speed limits while driving, performance budgets are upper limits rather than vague suggestions, so the goal should always be to come in under budget.

Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Web performance is often more about the subjective perception of load times than it is about the true efficiency of the underlying system, whereas page weight and transfer size are more objective measures and more reliable benchmarks for sustainable web design. 

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 benchmark page weight against competitors or the old version of the website we’re replacing. 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, then we could also start looking at the transfer size of our web pages for repeat visitors. 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 example, visitors who load the same page multiple times will likely have a high percentage of the files cached in their browser, meaning they don’t need to transfer all of 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. Measuring transfer size at this next level of detail can help us learn even more about how we can optimize efficiency for users who regularly visit our pages, and enable us to set page weight budgets for additional scenarios beyond the first visit.

Page weight budgets are easy to track throughout a design and development process. Although they don’t actually tell us carbon emission and energy consumption analytics directly, they give us a clear indication of efficiency relative 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, reduced data transfer translates to energy efficiency, a key factor to reducing carbon emissions of web products. 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. But as we’ll see next, since all web products demand some power, it’s important to consider the source of that electricity, too.

Carbon intensity of electricity

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. Carbon intensity is a term used to define the grams of CO₂ produced for every kilowatt-hour of electricity (gCO₂/kWh). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/kWh (even when factoring in their construction); whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO₂/kWh. 

Most electricity comes from national or state grids, where energy from a variety of different sources is mixed together with varying 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.

We don’t have control over the full energy supply of web services, but we do have some control over where we host our projects. 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 this user-contributed data, and a glance at their map shows how, for example, choosing a data center in France will have significantly lower carbon emissions than a data center in the Netherlands (Fig 2.3).

That said, we don’t want to locate our servers too far away from our users; it takes energy to transmit data through the telecom’s networks, and the further the data travels, the more energy is consumed. 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.

Using the distance itself as a benchmark, we can use website analytics to identify 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. 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 example, if a website is hosted in London but the primary user base is on the West Coast of the USA, then we could look up the distance from London to San Francisco, which is 5,300 miles. That’s a long way! We can see that hosting it somewhere in North America, ideally on the West Coast, would significantly reduce the distance and thus the energy used 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.

Converting it back to carbon emissions

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 does this by measuring the data transfer over the wire when loading a web page, calculating the amount of electricity associated, and then converting that into a figure for CO₂ (Fig 2.4). It also factors in whether or not the web hosting is powered by renewable energy.

If you want to take it to the next level and tailor the data more accurately to the unique aspects of your project, the Energy and Emissions Worksheet accompanying this book shows you how.

With the ability to calculate carbon emissions for our projects, we could actually take a page weight budget one step further and set carbon budgets as well. 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. Translating that into carbon adds a layer of abstraction that isn’t as intuitive—but carbon budgets do focus our minds on the primary thing we’re trying to reduce, and support the core objective of sustainable web design: reducing carbon emissions.

Browser Energy

Data transfer 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. As front-end web technologies become more advanced, the computational load is increasingly moving from the data center to users’ devices, whether they be phones, tablets, laptops, desktops, or even smart TVs. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Furthermore, JavaScript libraries such as Angular and React allow us to create applications where the “thinking” work is done partly or entirely 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 the user’s web browser means more energy used by their devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a heavy processing load on the user’s device can inadvertently exclude users with older, slower devices and cause batteries on phones and laptops to drain faster. 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 isn’t just bad for the environment, but it puts a disproportionate financial burden on the poorest in society.

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. One tool we do currently have is the Energy Impact monitor inside the developer console of the Safari browser (Fig 2.5).

You know when you load a website and your computer’s cooling fans start spinning so frantically you think it might actually take off? That’s essentially what this tool is measuring. 

It shows us the percentage of CPU used and the duration of CPU usage when loading the web page, and uses these figures to generate an energy impact rating. 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.

Antiracist economist Kim Crayton says that “intention without strategy is chaos.” We’ve discussed how our biases, assumptions, and inattention toward marginalized and vulnerable groups lead to dangerous and unethical tech—but what, specifically, do we need to do to fix it? The intention to make our tech safer is not enough; we need a strategy.

This chapter will equip you with that plan of action. It covers how to integrate safety principles into your design work in order to create tech that’s safe, how to convince your stakeholders that this work is necessary, and how to respond to the critique that what we actually need is more diversity. (Spoiler: we do, but diversity alone is not the antidote to fixing unethical, unsafe tech.)

The process for inclusive safety

When you are designing for safety, your goals are to:

• identify ways your product can be used for abuse,
• design ways to prevent the abuse, and
• provide support for vulnerable users to reclaim power and control.

The Process for Inclusive Safety is a tool to help you reach those goals (Fig 5.1). It’s a methodology I created in 2018 to capture the various techniques I was using when designing products with safety in mind. Whether you are creating an entirely new product or adding to an existing feature, the Process can help you make your product safe and inclusive. The Process includes five general areas of action:

• Conducting research
• Creating archetypes
• Brainstorming problems
• Designing solutions
• Testing for safety

The Process is meant to be flexible—it won’t make sense for teams to implement every step in some situations. Use the parts that are relevant to your unique work and context; this is meant to be something you can insert into your existing design practice.

And once you use it, if you have an idea for making it better or simply want to provide context of how it helped your team, please get in touch with me. It’s a living document that I hope will continue to be a useful and realistic tool that technologists can use in their day-to-day work.

If you’re working on a product specifically for a vulnerable group or survivors of some form of trauma, such as an app for survivors of domestic violence, sexual assault, or drug addiction, be sure to read Chapter 7, which covers that situation explicitly and should be handled a bit differently. The guidelines here are for prioritizing safety when designing a more general product that will have a wide user base (which, we already know from statistics, will include certain 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.

Step 1: Conduct research

Design research should include a broad analysis of how your tech might be weaponized for abuse as well as specific insights into the experiences of survivors and perpetrators of that type of abuse. 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.

Broad research

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 your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing 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 tool for finding these studies.

Specific research: Survivors

When possible and appropriate, include direct research (surveys and interviews) with people who are experts in the forms of harm you have uncovered. Ideally, you’ll want to interview advocates working in the space of your research first so that you have a more solid understanding of the topic and are better equipped to not retraumatize survivors. 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.

Especially when interviewing survivors of any kind of trauma, it is important to pay people for their knowledge and lived experiences. 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. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

Specific research: Abusers

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. Aim to understand how abusers or bad actors weaponize technology to use against others, how they cover their tracks, and how they explain or rationalize the abuse.

Step 2: Create archetypes

Once you’ve finished conducting your research, use your insights 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 into what this group needs. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

The abuser archetype is someone who will look at the product as a tool to perform 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.

The survivor archetype is someone who is being abused with the product. 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 know that the abuse is happening but not be able to stop it, like when an abuser locks them out of IoT devices; or they know it’s happening but don’t know how, such as when a stalker keeps figuring out their location (Fig 5.4). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later on when you design solutions to help your survivor archetypes achieve their goals 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. Instead of focusing on the demographic information we often see in personas, focus on their goals. 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 brainstorm how to prevent the abuser’s goals and assist the survivor’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.

Step 3: Brainstorm problems

After creating archetypes, brainstorm novel abuse cases and safety issues. “Novel” means things not found in your research; you’re trying to identify completely new safety issues that are unique to your product or service. 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.

How could your product be used for any kind of abuse, outside of what you’ve already identified in your research? I recommend setting aside at least a few hours with your team for this process.

If you’re looking for somewhere to start, try doing a Black Mirror brainstorm. 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. When I’ve led Black Mirror brainstorms, participants usually end up having a good deal of fun (which I think is great—it’s okay to have 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.

After you’ve identified as many opportunities for abuse as possible, you may still not feel confident that you’ve uncovered every potential form of harm. 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 we’ve missed something?” 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 guarantee you’ve thought of everything; instead of aiming for 100 percent assurance, recognize that you’ve taken this time and have done the best you can, and commit to continuing to prioritize safety in the future. Once your product is released, your users may identify new issues that you missed; aim to receive that feedback graciously and course-correct quickly.

Step 4: Design solutions

At this point, you should have a list of ways your product can be used for harm as well as survivor and abuser archetypes describing opposing user goals. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This step is a good one to insert alongside existing parts of your design process where you’re proposing solutions for the various problems your research uncovered.

Some questions to ask yourself to help prevent harm and support your archetypes include:

• Can you design your product in such a way that the identified harm cannot happen in the first place? If not, what roadblocks can you put up to prevent the harm from happening?
• How can you make the victim aware that abuse is happening through your product?
• How can you help the victim understand what they need to do to make the problem stop?
• Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product help the user access support?

In some products, it’s possible to proactively recognize that harm is happening. 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. This sort of proactiveness is not always possible, but it’s worth taking a half hour to discuss if any type of user activity would indicate some form of harm or abuse, and how your product could assist the user in receiving help in a safe manner.

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. We’ll walk through a good example of this in the next chapter.

Step 5: Test for safety

The final step is to test your prototypes from the point of view of your archetypes: the person who wants to weaponize the product for harm and the victim of the harm who needs to regain control over 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’re at a company that doesn’t do usability testing, you might be able to use safety testing to cleverly perform both; a user who goes through your design attempting to weaponize the product against someone else can also be encouraged to point out interactions or other elements of the design 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. There’s nothing wrong with testing an existing product that wasn’t designed with safety goals in mind from the onset—“retrofitting” 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.

As with other sorts of usability testing, you as the designer are most likely too close to the product and its design by this point to be a valuable tester; you know the product too well. 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.

Abuser testing

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. Reference the goals in the abuser archetype you created earlier, and use your product in an attempt to achieve them.

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. With this goal in mind, you’d try everything possible to figure out the location of another user who has their privacy settings enabled. 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. Your next step is to go back to step 4 and figure out how to prevent this from happening. You may need to repeat the process of designing solutions and testing them more than once.

Survivor testing

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. Thwarting the attempt of an abuser archetype to stalk someone also satisfies the goal of the survivor archetype to not be stalked, so separate testing wouldn’t be needed from the survivor’s perspective.

However, there are cases where it makes sense. For example, for a smart thermostat, a survivor archetype’s goals would be to understand who or what is making the temperature change when they aren’t doing 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. Your test would involve attempting to figure out how to do this: are there instructions that explain how to remove another user and change the password, and are they easy to find? 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.

Stress testing

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 pointed out that personas typically center people who are having a good day—but real users are often anxious, stressed out, having a bad day, or even experiencing tragedy. 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. Design for Real Life has more details about what it looks like to incorporate stress cases into your design as well as many other great tactics for compassionate design.

Do you find yourself designing screens with only a vague idea of how the things on the screen relate to the things elsewhere in the system? Do you leave stakeholder meetings with unclear directives that often seem to contradict previous conversations? You know a better understanding of user needs would help the team get clear on what you are actually trying to accomplish, but time and budget for research is tight. When it comes to asking for more direct contact with your users, you might feel like poor Oliver Twist, timidly asking, “Please, sir, I want some more.” 

Here’s the trick. You need to get stakeholders themselves to identify high-risk assumptions and hidden complexity, so that they become just as motivated as you to get answers from users. Basically, you need to make them think it’s their idea. 

In this article, I’ll show you how to collaboratively expose misalignment and gaps in the team’s shared understanding by bringing the team together around two simple questions:

1. What are the objects?
2. What are the relationships between those objects?

A gauntlet between research and screen design

These two questions align to the first two steps of the ORCA process, which might become your new best friend when it comes to reducing guesswork. Wait, what’s ORCA?! Glad you asked.

ORCA stands for Objects, Relationships, CTAs, and Attributes, and it outlines a process for creating solid object-oriented user experiences. Object-oriented UX is my design philosophy. ORCA is an iterative methodology for synthesizing user research into an elegant structural foundation to support screen and interaction design. OOUX and ORCA have made my work as a UX designer more collaborative, effective, efficient, fun, strategic, and meaningful.

The ORCA process has four iterative rounds and a whopping fifteen steps. In each round we get more clarity on our Os, Rs, Cs, and As.

I sometimes say that ORCA is a “garbage in, garbage out” process. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. But if you don’t have a ton of research, the beginning of the ORCA process serves another purpose: it helps you sell the need for research.

In other words, the ORCA process serves as a gauntlet between research and design. With good research, you can gracefully ride the killer whale from research into design. But without good research, the process effectively spits you back into research and with a cache of specific open questions.

Getting in the same curiosity-boat

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 expose what this classic comic so beautifully illustrates:

This is one reason why so many UX designers are frustrated in their job and why many projects fail. And this is also why we often can’t sell research: every decision-maker is confident in their own mental picture. 

Once we expose hidden fuzzy patches in each picture and the differences between them all, the case for user research makes itself.

But how we do this is important. 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 take ownership of assumptions and gaps in understanding, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Say your users are doctors. 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 their pain points? How do they use the current app?” But here’s the problem with that. 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 is more like the kind of conversation you need to facilitate. Let’s listen in:

“Wait a sec, how often 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 just a ‘primary caregiver’… Can’t that role be 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?”

Now we are getting somewhere. Do you see how powerful it can be getting stakeholders to debate these questions themselves? The diabolical goal here is to shake their confidence—gently and diplomatically.

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 this will, hands down, result in a more confusing, more complex, and less intuitive software product.

The two questions

But how do we get to these kinds of meaty questions diplomatically, efficiently, 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:

1. What are the objects?
2. What are the relationships between those objects?

In practice, getting to these answers is easier said than done. I’m going to show you how these two simple questions can provide the outline for an Object Definition Workshop. During this workshop, these “seed” questions will blossom into dozens of specific questions and shine a spotlight on the need for more user research.

Prep work: Noun foraging

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.

Basically, look for nouns that are particular to the business or industry of your project, and do it across at least a few sources. I call this noun foraging.

Here are just a few great noun foraging sources:

• the product’s marketing site
• the product’s competitors’ marketing sites (competitive analysis, anyone?)
• the existing product (look at labels!)
• user interview transcripts
• notes from stakeholder interviews or vision docs from stakeholders

Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. If all you have is a marketing website, some screenshots of the existing legacy system, and access to customer service chat logs, then use those.

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:

1. Structure
2. Instances
3. Purpose

Think of a library app, for example. Is “book” an object?

Structure: can you think of a few attributes for this potential object? Title, author, publish date… Yep, it has structure. Check!

Instance: what are some examples of this potential “book” object? Can you name a few? The Alchemist, Ready Player One, Everybody Poops… OK, check!

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!

As you are noun foraging, focus on capturing the nouns that have SIP. 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 coming to your digital place to play with your dropdown! They are coming for the VALUABLE THINGS and what they can do with them. Those 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.

First I’d look at my own email client, which happens to be Gmail. I’d then look at Outlook and the new HEY email. I’d look at Yahoo, Hotmail…I’d even look at Slack and Basecamp and other so-called “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 hypothetical product, too, and then scroll down to see how much our lists match up. Just don’t get lost in your own emails! Come back to me!)

Drumroll, please…

Here are a few nouns I came up with during my noun foraging:

• email message
• thread
• contact
• client
• rule/automation
• email address that is not a contact?
• contact groups
• attachment
• Google doc file / other integrated file
• newsletter? (HEY treats this differently)
• saved responses and templates

Scan your list of nouns and pick out words that you are completely clueless about. In our email example, it might be client or automation. 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 foraged during my own past project work that I needed my stakeholders to help me understand:

• Record Locator
• Incentive Home
• Augmented Line Item
• Curriculum-Based Measurement Probe

This is really all you need to prepare for the workshop session: a list of nouns that represent potential objects and a short list of nouns that need to be defined further.

Facilitate an Object Definition Workshop

You could actually start your workshop with noun foraging—this activity can be done collaboratively. 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. Affinity mapping is your friend here!

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 love presenting screenshots of documents and screens with all the nouns already highlighted. 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. You don’t need to let them know that you’re looking for gaps in the team’s understanding so that you can prove the need for more user research—that will be our little secret. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers. 

Then, let the question whack-a-mole commence.

1. What is this thing?

Want to have some real 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 show their cards at the same time 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 emerges, quietly (but visibly) start an “open questions” parking lot. 😉

After definitions solidify, here’s a great follow-up:

2. Do our users know what these things are? What do users call this thing?

Stakeholder 1: They probably call email clients “apps.” But I’m not sure.

Stakeholder 2: Automations are often called “workflows,” I think. Or, maybe users think workflows are something different.

If a more user-friendly term emerges, ask the group if they can agree to use only that term moving forward. This way, the team can better align to the users’ language and mindset.

OK, moving on. 

If you have two or more objects that seem to overlap in purpose, ask one of these questions:

3. Are these the same thing? Or are these different? If they are not the same, how are they different?

You: Is a saved response the same as a template?

Stakeholder 1: Yes! Definitely.

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. 

Continue to build out your growing glossary of objects. 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:

4. What’s the relationship between these objects?

You: Are saved responses and templates related in any way?

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? Does that happen when the user is constructing the saved response? Or when they apply the saved response to an email? How does that actually work?

Listen. Capture uncertainty. Once the list of “open questions” grows to a critical mass, pause to start assigning questions to groups or individuals. Some questions might be for the dev team (hopefully at least one developer is in the room with you). One question might be specifically for someone who couldn’t make it to the workshop. And many questions will need to be labeled “user.” 

Do you see how we are building up to our UXR sales pitch?

5. Is this object in scope?

Your next question narrows the team’s focus toward what’s most important to your users. 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 sort these objects from most to least important, either in small breakout groups or individually. Then, like you did with the definitions, have everyone reveal their sort order at once. Surprisingly—or not so surprisingly—it’s not unusual for the VP to rank something like “saved responses” as #2 while everyone else puts it at the bottom of the list. Try not to look too smug as you inevitably expose more misalignment.

I did this for a startup a few years ago. We posted the three groups’ wildly different sort orders on the whiteboard.

The CEO stood back, looked at it, 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.

6. Create a visual representation of the objects’ relationships

We’ve already done a bit of this while trying to determine if two things are different, but this time, ask the team about every potential relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? To visualize all the connections, pull out your trusty boxes-and-arrows technique. Here, we are connecting our objects with verbs. I like to keep my verbs to simple “has a” and “has many” statements.

This system modeling activity brings up all sorts of new questions:

• Can a saved response have attachments?
• Can a saved response use a template? If so, if an email uses a saved response with a template, can the user override that template?
• Do users want to see all the emails they sent that included a particular attachment? For example, “show me all the emails I sent with ProfessionalImage.jpg attached. I’ve changed my professional photo and I want to alert everyone to update it.” 

Solid answers might emerge directly from the workshop participants. Great! Capture that new shared understanding. But when uncertainty surfaces, continue to add questions to your growing parking lot.

Light the fuse

You’ve positioned the explosives all along the floodgates. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.

Before your workshop wraps up, have the group reflect on the list of open questions. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

Here’s your final step. 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 methodology, we are cornering our decision-makers into advocating for user research as they themselves label questions as high-risk. Sorry, not sorry. 

Now 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 open-ended and don’t lead the user into any default answers.

Final words: Hold the screen design!

Seriously, if at all possible, do not ever design screens again without first answering these fundamental questions: 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 helps you win time and budget to go talk to your users and gain clarity on what you are designing before you start building 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. 

All the best of luck! Now go sell research!

CSS is about styling boxes. In fact, the whole web is made of boxes, from the browser viewport to elements on a page. But every once in a while a new feature comes along that makes us rethink our design approach.

Round displays, for example, make it fun to play with circular clip areas. Mobile screen notches and virtual keyboards offer challenges to best organize content that stays clear of them. And dual screen or foldable devices make us rethink how to best use available space in a number of different device postures.

These recent evolutions of the web platform made it both more challenging and more interesting to design products. They’re great opportunities for us to break out of our rectangular boxes.

I’d like to talk about a new feature similar to the above: the Window Controls Overlay for Progressive Web Apps (PWAs).

Progressive Web Apps are blurring the lines between apps and websites. They combine the best of both worlds. On one hand, they’re stable, linkable, searchable, and responsive just like websites. On the other hand, they provide additional powerful capabilities, work offline, and read files just like native apps.

As a design surface, PWAs are really interesting because they challenge us to think about what mixing web and device-native user interfaces can be. On desktop devices in particular, we have more than 40 years of history telling us what applications should look like, and it can be hard to break out of this mental model.

At the end of the day though, PWAs on desktop are constrained to the window they appear in: a rectangle with a title bar at the top.

Here’s what a typical desktop 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 property), but that’s about it.

What if we could think outside this box, and reclaim the real estate of the app’s entire window? Doing so would give us a chance to make our apps more beautiful and feel more integrated in the operating system.

This is exactly what the Window Controls Overlay offers. This new PWA functionality makes it possible to take advantage of the full surface area of the app, including where the title bar normally appears.

About the title bar and window controls

Let’s start with an explanation of what the title bar and window controls are.

The title bar is the area displayed at the top of an app window, which usually contains the app’s name. Window controls are the affordances, or buttons, that make it possible to minimize, maximize, or close the app’s window, and are also displayed at the top.

Window Controls Overlay removes the physical constraint of the title bar and window controls areas. It frees up the full height of the app window, enabling the title bar and window control buttons to be overlaid on top of the application’s web content. 

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 very web browser you are using to read this uses the top area to display tabs.

Spotify displays album artwork all the way to the top edge of the application window.

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 enables you to offer this modified experience on a range of platforms while not adversely affecting the experience on browsers or 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.

Let’s use the feature

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. It’s a simple CSS playground where users can create designs using CSS and a single HTML element.

The app has two pages. The first lists the existing CSS designs you’ve created:

The second page enables you to create and edit CSS designs:

Since I’ve added a simple web manifest and service worker, we can install the app as a PWA on desktop. 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. In the second page, it would be really nice if the design area went all the way to the top of the app window.

Let’s use the Window Controls Overlay feature to improve this.

Enabling Window Controls Overlay

The feature is still experimental at the moment. To try it, you need to enable it in one of the supported browsers.

As of now, it has been implemented in Chromium, as 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.

Using Window Controls Overlay

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. This manifest change is the only thing we need to make the title bar disappear and turn 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.

Here is what the app looks like now:

The title bar is gone, which is what we wanted, but our logo, search field, and NEW button are partially covered by the window controls because now our layout starts 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:

Using CSS to keep clear of the window controls

Along with the feature, new CSS environment variables have been introduced:

• titlebar-area-x
• titlebar-area-y
• titlebar-area-width
• titlebar-area-height

You 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. In our case, we’ll use two of the variables to position our header, which contains the logo, search bar, and NEW button. 

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 app looks a lot more like a native app.

Changing the window controls background color so it blends in

Now let’s take a closer look at our second page: the CSS playground editor.

Not great. 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 couple of ways to define it:

• PWAs can define a theme color in the web app manifest file using the theme_color manifest member. This color is then used by the OS in different ways. On desktop platforms, it is used to provide a background color to the title bar and window controls.
• Websites can use the theme-color meta tag as well. It’s used by browsers to customize the color of the UI around the web page. For PWAs, this color can override the manifest 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 function we’ll use:

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.

Dragging the window

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.

The title bar provides a sizable area for users to click and drag, but by using the Window Controls Overlay feature, this area becomes limited to where the control buttons are, and users have to very precisely aim 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. 

To make any element of the app become a dragging target for the window, we can use the following: 

-webkit-app-region: drag;

It is also possible to explicitly make an element non-draggable: 

-webkit-app-region: no-drag; 

These options can be useful for 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. So let’s use a different approach. 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;
}

With the above code, users can click and drag where the title bar used to be. 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.

Adapting to window resize

It may be useful for an app to know both whether the window controls overlay is visible and when its size changes. In our case, if the user made the window very narrow, there wouldn’t be enough space for the search field, logo, and button to fit, so we’d want to push them down a bit.

The Window Controls Overlay feature comes with a JavaScript API we can use to do this: navigator.windowControlsOverlay.

The API provides three interesting things:

• navigator.windowControlsOverlay.visible lets us know whether the overlay is visible.
• navigator.windowControlsOverlay.getBoundingClientRect() lets us know the position and size of the title bar area.
• navigator.windowControlsOverlay.ongeometrychange lets us know when the size or visibility changes.

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:

• It’s only fired when the feature is supported and used; we don’t want to adapt the design otherwise.
• We get the size of the title bar area across operating systems, which is great because the size of the window controls is different on Mac and Windows. Using a media query wouldn’t make it possible for us to know exactly how much space remains.

.narrow header {
  top: env(titlebar-area-height, 0);
  left: 0;
  width: 100%;
}

Using the above CSS code, we can move our header down to stay clear of the window control buttons when the window is too narrow, and move the thumbnails down accordingly.

Thirty pixels of exciting design opportunities

Using the Window Controls Overlay feature, we were able to take our simple demo app and turn it into something that feels so much more integrated on desktop devices. 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 pixels of extra room and comes with challenges on how to deal with 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. New features get added to the web platform to allow us, web authors, to integrate more and more deeply with those devices. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. Building for the web now lets us 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!

If you get a chance to try the Window Controls Overlay feature and have feedback about it, you can open issues on the spec’s repository. It’s still early in the development of this feature, and you can help make it even better. Or, you can take a look at the feature’s existing documentation, or this demo app and its source code. 

About two and a half years ago, I introduced the idea of daily ethical design. It was born out of my frustration with the many obstacles to achieving design that’s usable and equitable; protects people’s privacy, agency, and focus; benefits society; and restores nature. I argued that we need to overcome the inconveniences that prevent us from acting ethically and that we need to elevate design ethics to a more practical level by structurally integrating it into our daily work, processes, and tools.

Unfortunately, we’re still very far from this ideal. 

At the time, I didn’t know yet how to structurally integrate ethics. Yes, I had found some tools that had worked for me in previous projects, such as using checklists, assumption tracking, and “dark reality” sessions, but I didn’t manage to apply those in every project. I was still struggling for time and support, and at best I had only partially achieved a higher (moral) quality of design—which is far from my definition of structurally integrated.

I decided to dig deeper for the root causes in business that prevent us from practicing daily ethical design. Now, after much research and experimentation, I believe that I’ve found the key that will let us structurally integrate ethics. And it’s surprisingly simple! But first we need to zoom out to get a better understanding of what we’re up against.

Influence the system

Sadly, we’re trapped in a capitalistic system that reinforces consumerism and inequality, and it’s obsessed with the fantasy of endless growth. Sea levels, temperatures, and our demand for energy continue to rise unchallenged, while the gap between rich and poor continues to widen. Shareholders expect ever-higher returns on their investments, and companies feel forced to set short-term objectives that reflect this. Over the last decades, those objectives have twisted our well-intended human-centered mindset into a powerful machine that promotes ever-higher levels of consumption. When we’re working for an organization that pursues “double-digit growth” or “aggressive sales targets” (which is 99 percent of us), that’s very hard to resist while remaining human friendly. Even with our best intentions, and even though we like to say that we create solutions for people, we’re a part of the problem.

What can we do to change this?

We can start by acting on the right level of the system. Donella H. Meadows, a system thinker, once listed ways to influence a system in order of effectiveness. When you apply these to design, you get:

• At the lowest level of effectiveness, you can affect numbers such as usability scores or the number of design critiques. But none of that will change the direction of a company.
• Similarly, affecting buffers (such as team budgets), stocks (such as the number of designers), flows (such as the number of new hires), and delays (such as the time that it takes to hear about the effect of design) won’t significantly affect a company.
• Focusing instead on feedback loops such as management control, employee recognition, or design-system investments can help a company become better at achieving its objectives. But that doesn’t change the objectives themselves, which means that the organization will still work against your ethical-design ideals.
• The next level, information flows, is what most ethical-design initiatives focus on now: the exchange of ethical methods, toolkits, articles, conferences, workshops, and so on. This is also where ethical design has remained mostly theoretical. We’ve been focusing on the wrong level of the system all this time.
• Take rules, for example—they beat knowledge every time. There can be widely accepted rules, such as how finance works, or a scrum team’s definition of done. But ethical design can also be smothered by unofficial rules meant to maintain profits, often revealed through comments such as “the client didn’t ask for it” or “don’t make it too big.”
• Changing the rules without holding official power is very hard. That’s why the next level is so influential: self-organization. Experimentation, bottom-up initiatives, passion projects, self-steering teams—all of these are examples of self-organization that improve the resilience and creativity of a company. It’s exactly this diversity of viewpoints that’s needed to structurally tackle big systemic issues like consumerism, wealth inequality, and climate change.
• Yet even stronger than self-organization are objectives and metrics. Our companies want to make more money, which means that everything and everyone in the company does their best to… make the company more money. And once I realized that profit is nothing more than a measurement, I understood how crucial a very specific, defined metric can be toward pushing a company in a certain direction.

The takeaway? If we truly want to incorporate ethics into our daily design practice, we must first change the measurable objectives of the company we work for, from the bottom up.

Redefine success

Traditionally, we consider a product or service successful if it’s desirable to humans, technologically feasible, and financially viable. You tend to see these represented as equals; if you type the three words in a search engine, you’ll find diagrams of three equally sized, evenly arranged circles.

But in our hearts, we all know that the three dimensions aren’t equally weighted: it’s viability that ultimately controls whether a product will go live. So a more realistic representation might look like this:

Desirability and feasibility are the means; viability is the goal. Companies—outside of nonprofits and charities—exist to make money.

A genuinely purpose-driven company would try to reverse this dynamic: it would recognize finance for what it was intended for: a means. So both feasibility and viability are means to achieve what the company set out to achieve. It makes intuitive sense: to achieve most anything, you need resources, people, and money. (Fun fact: the Italian language knows no difference between feasibility and viability; both are simply fattibilità.)

But simply swapping viable for desirable isn’t enough to achieve an ethical outcome. Desirability is still linked to consumerism because the associated activities aim to identify what people want—whether it’s good for them or not. Desirability objectives, such as user satisfaction or conversion, don’t consider whether a product is healthy for people. They don’t prevent us from creating products that distract or manipulate people or stop us from contributing to society’s wealth inequality. They’re unsuitable for establishing a healthy balance with nature.

There’s a fourth dimension of success that’s missing: our designs also need to be ethical in the effect that they have on the world.

This is hardly a new idea. Many similar models exist, some calling the fourth dimension accountability, integrity, or responsibility. What I’ve never seen before, however, is the necessary step that comes after: to influence the system as designers and to make ethical design more practical, we must create objectives for ethical design that are achievable and inspirational. There’s no one way to do this because it highly depends on your culture, values, and industry. But I’ll give you the version that I developed with a group of colleagues at a design agency. Consider it a template to get started.

Pursue well-being, equity, and sustainability

We created objectives that address design’s effect on three levels: individual, societal, and global.

An objective on the individual level tells us what success is beyond the typical focus of usability and satisfaction—instead considering matters such as how much time and attention is required from users. We pursued well-being:

We create products and services that allow for people’s health and happiness. Our solutions are calm, transparent, nonaddictive, and nonmisleading. We respect our users’ time, attention, and privacy, and help them make healthy and respectful choices.

An objective on the societal level forces us to consider our impact beyond just the user, widening our attention to the economy, communities, and other indirect stakeholders. We called this objective equity:

We create products and services that have a positive social impact. We consider economic equality, racial justice, and the inclusivity and diversity of people as teams, users, and customer segments. We listen to local culture, communities, and those we affect.

Finally, the objective on the global level aims to ensure that we remain in balance with the only home we have as humanity. Referring to it simply as sustainability, our definition was:

We create products and services that reward sufficiency and reusability. Our solutions support the circular economy: we create value from waste, repurpose products, and prioritize sustainable choices. We deliver functionality instead of ownership, and we limit energy use.

In short, ethical design (to us) meant achieving wellbeing for each user and an equitable value distribution within society through a design that can be sustained by our living planet. When we introduced these objectives in the company, for many colleagues, design ethics and responsible design suddenly became tangible and achievable through practical—and even familiar—actions.

Measure impact 

But defining these objectives still isn’t enough. What truly caught the attention of senior management was the fact that we created a way to measure every design project’s well-being, equity, and sustainability.

This overview lists example metrics that you can use as you pursue well-being, equity, and sustainability:

There’s a lot of power in measurement. As the saying goes, what gets measured gets done. Donella Meadows once shared this example:

“If the desired system state is national security, and that is defined as the amount of money spent on the military, the system will produce military spending. It may or may not produce national security.”

This phenomenon explains why desirability is a poor indicator of success: it’s typically defined as the increase in customer satisfaction, session length, frequency of use, conversion rate, churn rate, download rate, and so on. But none of these metrics increase the health of people, communities, or ecosystems. What if instead we measured success through metrics for (digital) well-being, such as (reduced) screen time or software energy consumption?

There’s another important message here. Even if we set an objective to build a calm interface, if we were to choose the wrong metric for calmness—say, the number of interface elements—we could still end up with a screen that induces anxiety. Choosing the wrong metric can completely undo good intentions. 

Additionally, choosing the right metric is enormously helpful in focusing the design team. Once you go through the exercise of choosing metrics for our objectives, you’re forced to consider what success looks like concretely and how you can prove that you’ve reached your ethical objectives. It also forces you to consider what we as designers have control over: what can I include in my design or change in my process that will lead to the right type of success? The answer to this question brings a lot of clarity and focus.

And finally, it’s good to remember that traditional businesses run on measurements, and managers love to spend much time discussing charts (ideally hockey-stick shaped)—especially if they concern profit, the one-above-all of metrics. For good or ill, to improve the system, to have a serious discussion about ethical design with managers, we’ll need to speak that business language.

Practice daily ethical design

Once you’ve defined your objectives and you have a reasonable idea of the potential metrics for your design project, only then do you have a chance to structurally practice ethical design. It “simply” becomes a matter of using your creativity and choosing from all the knowledge and toolkits already available to you.

I think this is quite exciting! It opens a whole new set of challenges and considerations for the design process. Should you go with that energy-consuming video or would a simple illustration be enough? Which typeface is the most calm and inclusive? Which new tools and methods do you use? When is the website’s end of life? How can you provide the same service while requiring less attention from users? How do you make sure that those who are affected by decisions are there when those decisions are made? How can you measure our effects?

The redefinition of success will completely change what it means to do good design.

There is, however, a final piece of the puzzle that’s missing: convincing your client, product owner, or manager to be mindful of well-being, equity, and sustainability. For this, it’s essential to engage stakeholders in a dedicated kickoff session.

Kick it off or fall back to status quo

The kickoff is the most important meeting that can be so easy to forget to include. It consists of two major phases: 1) the alignment of expectations, and 2) the definition of success.

In the first phase, the entire (design) team goes over the project brief and meets with all the relevant stakeholders. Everyone gets to know one another and express their expectations on the outcome and their contributions to achieving it. Assumptions are raised and discussed. The aim is to get on the same level of understanding and to in turn avoid preventable miscommunications and surprises later in the project.

For example, for a recent freelance project that aimed to design a digital platform that facilitates US student advisors’ documentation and communication, we conducted an online kickoff with the client, a subject-matter expert, and two other designers. We used a combination of canvases on Miro: one with questions from “Manual of Me” (to get to know each other), a Team Canvas (to express expectations), and a version of the Project Canvas to align on scope, timeline, and other practical matters.

The above is the traditional purpose of a kickoff. But just as important as expressing expectations is agreeing on what success means for the project—in terms of desirability, viability, feasibility, and ethics. What are the objectives in each dimension?

Agreement on what success means at such an early stage is crucial because you can rely on it for the remainder of the project. If, for example, the design team wants to build an inclusive app for a diverse user group, they can raise diversity as a specific success criterion during the kickoff. If the client agrees, the team can refer back to that promise throughout the project. “As we agreed in our first meeting, having a diverse user group that includes A and B is necessary to build a successful product. So we do activity X and follow research process Y.” Compare those odds to a situation in which the team didn’t agree to that beforehand and had to ask for permission halfway through the project. The client might argue that that came on top of the agreed scope—and she’d be right.

In the case of this freelance project, to define success I prepared a round canvas that I call the Wheel of Success. It consists of an inner ring, meant to capture ideas for objectives, and a set of outer rings, meant to capture ideas on how to measure those objectives. The rings are divided into five dimensions of successful design: healthy, equitable, sustainable, desirable, feasible, and viable.

We went through each dimension, writing down ideas on digital sticky notes. Then we discussed our ideas and verbally agreed on the most important ones. For example, our client agreed that sustainability and progressive enhancement are important success criteria for the platform. And the subject-matter expert emphasized the importance of including students from low-income and disadvantaged groups in the design process.

After the kickoff, we summarized our ideas and shared understanding in a project brief that captured these aspects:

• the project’s origin and purpose: why are we doing this project?
• the problem definition: what do we want to solve?
• the concrete goals and metrics for each success dimension: what do we want to achieve?
• the scope, process, and role descriptions: how will we achieve it?

With such a brief in place, you can use the agreed-upon objectives and concrete metrics as a checklist of success, and your design team will be ready to pursue the right objective—using the tools, methods, and metrics at their disposal to achieve ethical outcomes.

Conclusion

Over the past year, quite a few colleagues have asked me, “Where do I start with ethical design?” My answer has always been the same: organize a session with your stakeholders to (re)define success. Even though you might not always be 100 percent successful in agreeing on goals that cover all responsibility objectives, that beats the alternative (the status quo) every time. If you want to be an ethical, responsible designer, there’s no skipping this step.

To be even more specific: if you consider yourself a strategic designer, your challenge is to define ethical objectives, set the right metrics, and conduct those kick-off sessions. If you consider yourself a system designer, your starting point is to understand how your industry contributes to consumerism and inequality, understand how finance drives business, and brainstorm which levers are available to influence the system on the highest level. Then redefine success to create the space to exercise those levers.

And for those who consider themselves service designers or UX designers or UI designers: if you truly want to have a positive, meaningful impact, stay away from the toolkits and meetups and conferences for a while. Instead, gather your colleagues and define goals for well-being, equity, and sustainability through design. Engage your stakeholders in a workshop and challenge them to think of ways to achieve and measure those ethical goals. Take their input, make it concrete and visible, ask for their agreement, and hold them to it.

Otherwise, I’m genuinely sorry to say, you’re wasting your precious time and creative energy.

Of course, engaging your stakeholders in this way can be uncomfortable. Many of my colleagues expressed doubts such as “What will the client think of this?,” “Will they take me seriously?,” and “Can’t we just do it within the design team instead?” In fact, a product manager once asked me why ethics couldn’t just be a structured part of the design process—to just do it without spending the effort to define ethical objectives. It’s a tempting idea, right? We wouldn’t have to have difficult discussions with stakeholders about what values or which key-performance indicators to pursue. It would let us focus on what we like and do best: designing.

But as systems theory tells us, that’s not enough. For those of us who aren’t from marginalized groups and have the privilege to be able to speak up and be heard, that uncomfortable space is exactly where we need to be if we truly want to make a difference. We can’t remain within the design-for-designers bubble, enjoying our privileged working-from-home situation, disconnected from the real world out there. For those of us who have the possibility to speak up and be heard: if we solely keep talking about ethical design and it remains at the level of articles and toolkits—we’re not designing ethically. It’s just theory. We need to actively engage our colleagues and clients by challenging them to redefine success in business.

With a bit of courage, determination, and focus, we can break out of this cage that finance and business-as-usual have built around us and become facilitators of a new type of business that can see beyond financial value. We just need to agree on the right objectives at the start of each design project, find the right metrics, and realize that we already have everything that we need to get started. That’s what it means to do daily ethical design.

For their inspiration and support over the years, I would like to thank Emanuela Cozzi Schettini, José Gallegos, Annegret Bönemann, Ian Dorr, Vera Rademaker, Virginia Rispoli, Cecilia Scolaro, Rouzbeh Amini, and many others.