Category: Blog

Do you remember when having a great website was enough? Now, people are getting answers from Siri, Google search snippets, and mobile apps, not just our websites. Forward-thinking organizations have adopted an omnichannel content strategy, whose mission is to reach audiences across multiple digital channels and platforms.

But how do you set up a content management system (CMS) to reach your audience now and in the future? I learned the hard way that creating a content model—a definition of content types, attributes, and relationships that let people and systems understand content—with my more familiar design-system thinking would capsize my customer’s omnichannel content strategy. You can avoid that outcome by creating content models that are semantic and that also connect related content. 

I recently had the opportunity to lead the CMS implementation for a Fortune 500 company. The client was excited by the benefits of an omnichannel content strategy, including content reuse, multichannel marketing, and robot delivery—designing content to be intelligible to bots, Google knowledge panels, snippets, and voice user interfaces. 

A content model is a critical foundation for an omnichannel content strategy, and for our content to be understood by multiple systems, the model needed semantic types—types named according to their meaning instead of their presentation. Our goal was to let authors create content and reuse it wherever it was relevant. But as the project proceeded, I realized that supporting content reuse at the scale that my customer needed required the whole team to recognize a new pattern.

Despite our best intentions, we kept drawing from what we were more familiar with: design systems. Unlike web-focused content strategies, an omnichannel content strategy can’t rely on WYSIWYG tools for design and layout. Our tendency to approach the content model with our familiar design-system thinking constantly led us to veer away from one of the primary purposes of a content model: delivering content to audiences on multiple marketing channels.

Two essential principles for an effective content model

We needed to help our designers, developers, and stakeholders understand that we were doing something very different from their prior web projects, where it was natural for everyone to think about content as visual building blocks fitting into layouts. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. We discovered two principles that helped the team understand how a content model differs from the design systems that we were used to:

1. Content models must define semantics instead of layout.
2. And content models should connect content that belongs together.

Semantic content models

A semantic content model uses type and attribute names that reflect the meaning of the content, not how it will be displayed. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. Although these types might make it easy to lay out content, they don’t help delivery channels understand the content’s meaning, which in turn would have opened the door to the content being presented in each marketing channel. In contrast, a semantic content model uses type names like product, service, and testimonial so that each delivery channel can understand the content and use it as it sees fit. 

When you’re creating a semantic content model, a great place to start is to look over the types and properties defined by Schema.org, a community-driven resource for type definitions that are intelligible to platforms like Google search.

A semantic content model has several benefits:

• Even if your team doesn’t care about omnichannel content, a semantic content model decouples content from its presentation so that teams can evolve the website’s design without needing to refactor its content. In this way, content can withstand disruptive website redesigns. 
• A semantic content model also provides a competitive edge. By adding structured data based on Schema.org’s types and properties, a website can provide hints to help Google understand the content, display it in search snippets or knowledge panels, and use it to answer voice-interface user questions. Potential visitors could discover your content without ever setting foot in your website.
• Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. To use the same content in multiple marketing channels, delivery channels need to be able to understand it. For example, if your content model were to provide a list of questions and answers, it could easily be rendered on a frequently asked questions (FAQ) page, but it could also be used in a voice interface or by a bot that answers common questions.

For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.

Content models that connect

After struggling to describe what makes a good content model, I’ve come to realize that the best models are those that are semantic and that also connect related content components (such as a FAQ item’s question and answer pair), instead of slicing up related content across disparate content components. A good content model connects content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.

Think about writing an article or essay. An article’s meaning and usefulness depends upon its parts being kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? On our project, our familiar design-system thinking often led us to want to create content models that would slice content into disparate chunks to fit the web-centric layout. This had a similar impact to an article that were to have been separated from its headline. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

To illustrate, let’s look at how connecting related content applies in a real-world scenario. The design team for our customer presented a complex layout for a software product page that included multiple tabs and sections. Our instincts were to follow suit with the content model. Shouldn’t we make it as easy and as flexible as possible to add any number of tabs in the future?

Because our design-system instincts were so familiar, it felt like we had needed a content type called “tab section” so that multiple tab sections could be added to a page. Each tab section would display various types of content. One tab might provide the software’s overview or its specifications. Another tab might provide a list of resources. 

Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. For example, how would another system have been able to tell which “tab section” referred to a product’s specifications or its resource list—would that other system have to have resorted to counting tab sections and content blocks? This would have prevented the tabs from ever being reordered, and it would have required adding logic in every other delivery channel to interpret the design system’s layout. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

We had a breakthrough when we discovered that our customer had a specific purpose in mind for each tab: it would reveal specific information such as the software product’s overview, specifications, related resources, and pricing. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. With a little digging, it didn’t take long to realize that the concept of tabs wasn’t relevant to the content model. The meaning of the content that they were planning to display in the tabs was what mattered.

In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. This realization prompted us to define content types for the software product based on the meaningful attributes that the customer had wanted to render on the web. There were obvious semantic attributes like name and description as well as rich attributes like screenshots, software requirements, and feature lists. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel—including future ones—could understand and present this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic (with type and attribute names that reflected the meaning of the content) and that it kept content together that belonged together (instead of fragmenting it). These two concepts curtailed our temptation to shape the content model based on the design. So if you’re working on a content model to support an omnichannel content strategy—or even if you just want to make sure that Google and other interfaces understand your content—remember:

• A design system isn’t a content model. Team members may be tempted to conflate them and to make your content model mirror your design system, so you should protect the semantic value and contextual structure of the content strategy during the entire implementation process. This will let every delivery channel consume the content without needing a magic decoder ring.
• If your team is struggling to make this transition, you can still reap some of the benefits by using Schema.org–based structured data in your website. Even if additional delivery channels aren’t on the immediate horizon, the benefit to search engine optimization is a compelling reason on its own.
• Additionally, remind the team that decoupling the content model from the design will let them update the designs more easily because they won’t be held back by the cost of content migrations. They’ll be able to create new designs without the obstacle of compatibility between the design and the content, and ​they’ll be ready for the next big thing. 

By rigorously advocating for these principles, you’ll help your team treat content the way that it deserves—as the most critical asset in your user experience and the best way to connect with your audience.

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.

CSS involves creating containers. In fact, the whole website is made of containers, from the website viewport to components on a webpage. However, every now and then a new element appears that prompts us to reevaluate our style philosophy.

Square features, for instance, make it fun to play with round picture areas. Mobile display holes and electronic keyboards offer issues to best manage content that stays clear of them. Additionally, dual-screen or portable devices force us to consider how to make the most of the available room in various device configurations.

These latest changes to the website platform have made it both more difficult and fascinating to create products. They’re wonderful opportunities for us to break out of our triangular boxes.

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

Democratic Web Apps are bridging the gap between websites and apps. They combine the best of both worlds. On the one hand, they are flexible, linkable, and stable, just like websites. On the other hand, they provide more effective features, work online, and read documents just like local apps.

As a style area, PWAs are really exciting because they challenge us to think about what mixing online and device-native user interface can get. We have more than 40 years of experience telling us what software may look like, especially on desktop computers, and it’s challenging to get out of this psychological design.

At the end of the day though, PWAs on desktops are constrained to the glass they appear in: a square with a name bar at the top.

What a standard pc PWA app looks like:

Sure, as the author of a PWA, you get to choose the color of the title bar (using the Web Application Manifest theme_color home ), but that’s about it.

What if we could assume differently and regain the full glass of the app? Doing so would give us a chance to create our programs more wonderful and feel more included in the operating system.

The Window Controls Overlay offers precisely this. This innovative PWA operation makes it possible to take advantage of the full floor area of the app, including where the name bar usually appears.

About the subject bar and screen controls

Let’s get started with an explanation of what the window and name controls are.

The title bar is the place displayed at the top of an game glass, which frequently contains the phone’s name. The controls are displayed at the top of an app’s window, along with the buttons that enable it to reduce, maximize, nearby, and close it.

Window Controls Overlay removes the natural barrier of the name bar and windows controls areas. The title bar and glass control buttons can be overlayed on top of the user’s internet material, allowing it to free up the entire height of the game window.

If you are reading this article on a desktop computer, take a quick look at other apps. Chances are they’re already doing something similar to this. In fact, the web browser you are using uses the top area to display tabs.

Spotify displays album artwork to the top of the application window at the very top.

Microsoft Word uses the available title bar space to display the auto-save and search functionalities, and more.

The whole point of this feature is to allow you to make use of this space with your own content while providing a way to account for the window control buttons. And it makes it possible to offer this modified experience across a variety of platforms without having a negative impact on browsers or other devices that don’t support Window Controls Overlay. After all, PWAs are all about progressive enhancement, so this feature is a chance to enhance your app to use this extra space when it’s available.

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. Users can create designs using only CSS and a single HTML element in this straightforward CSS playground.

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

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

We can install the app as a PWA on the desktop because I added a straightforward web manifest and service worker. Here is what it looks like on macOS:

And on Windows:

Our app is looking good, but the white title bar in the first page is wasted space. It would be really nice if the design area reached the top of the app window on the second page.

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

enabling overlay for window control

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

It has currently been incorporated into Chromium as a result of a collaboration between Microsoft and Google. We can therefore use it in Chrome or Edge by going to the internal about: //flags page, and enabling the Desktop PWA Window Controls Overlay flag.

Using the overlay of window controls

To use the feature, we need to add the following display_override member to our web app’s manifest file:

{ "name": "1DIV", "description": "1DIV is a mini CSS playground", "lang": "en-US", "start_url": "/", "theme_color": "#ffffff", "background_color": "#ffffff", "display_override": [ "window-controls-overlay" ], "icons": [ ... ]}

On the surface, the feature is really simple to use. The only thing required is for this manifest change to transform the window controls into an overlay and make the title bar disappear.

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 how the app currently looks:

Our logo, search field, and NEW button are now partially covered by the window controls, but the title bar has been removed, which is what we wanted. Our layout now begins at the top of the window.

It’s similar on Windows, with the difference that the close, maximize, and minimize buttons appear on the right side, grouped together with the PWA control buttons:

Using CSS to keep clear of the window controls

New CSS environment variables have also been introduced along with the feature:

• 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. Our header, which includes the logo, search bar, and NEW button, will be placed using two of the variables in our case.

header { position: absolute; left: env(titlebar-area-x, 0); width: env(titlebar-area-width, 100%); height: var(--toolbar-height);}

The titlebar-area-x variable gives us the distance from the left of the viewport to where the title bar would appear, and titlebar-area-width is its width. (Remember, this is not equivalent to the width of the entire viewport, just the title bar portion, which as noted earlier, doesn’t include the window controls.)

By doing this, we make sure our content remains fully visible. We’re also defining fallback values (the second parameter in the env() function) for when the variables are not defined (such as on non-supporting browsers, or when the Windows Control Overlay feature is disabled).

Now our header adapts to its surroundings, and it doesn’t feel like the window control buttons have been added as an afterthought. The interface resembles a native app much more.

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 very good. Our CSS demo area does go all the way to the top, which is what we wanted, but the way the window controls appear as white rectangles on top of it is quite jarring.

We can fix this by changing the app’s theme color. There are a few ways to define it:

PWAs can define a theme color in the web app manifest file using the theme_color manifest member. The OS then uses this color in a variety of 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 method we’ll employ:

function themeWindow(bgColor) { document.querySelector("meta[name=theme-color]").setAttribute('content', bgColor);}

With this in place, we can imagine how using color and CSS transitions can produce a smooth change from the list page to the demo page, and enable the window control buttons to blend in with the rest of the app’s interface.

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.

Users can use the Window Controls Overlay feature to move the window, but this area becomes limited to where the control buttons are, and they must carefully aim between these buttons to move the window. However, the title bar offers a sizable area for users to click and drag.

Fortunately, this can be fixed using CSS with the app-region property. This property is, for now, only supported in Chromium-based browsers and needs the -webkit- vendor prefix. 

We can use the following to make any feature of the app a dragging target for the window:

-webkit-app-region: drag;

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

-webkit-app-region: no-drag; 

These choices might be beneficial to us. We can make the entire header a dragging target, but make the search field and NEW button within it non-draggable so they can still be used as normal.

However, because the editor page doesn’t display the header, users wouldn’t be able to drag the window while editing code. Let’s take a different approach, then. We’ll create another element before our header, also absolutely positioned, and dedicated to dragging the window.

...

.drag { position: absolute; top: 0; width: 100%; height: env(titlebar-area-height, 0); -webkit-app-region: drag;}

With the above code, we’re making the draggable area span the entire viewport width, and using the titlebar-area-height variable to make it as tall as what the title bar would have been. This way, our draggable area is aligned with the window control buttons as shown below.

And, now, to make sure our search field and button remain usable:

header .search,header .new { -webkit-app-region: no-drag;}

Users can click and drag where the title bar used to be using the above code. It is an area that users expect to be able to use to move windows on desktop, and we’re not breaking this expectation, which is good.

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 situation, there wouldn’t be enough room for the search field, logo, and button to fit because the user made the window very narrow. We would want to push them a little lower.

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

The API offers three intriguing features:

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

Let’s use this to be aware of the size of the title bar area and move the header down if it’s too narrow.

if (navigator.windowControlsOverlay) { navigator.windowControlsOverlay.addEventListener('geometrychange', () => { const { width } = navigator.windowControlsOverlay.getBoundingClientRect(); document.body.classList.toggle('narrow', width < 250); });}

In the example above, we set the narrow class on the body of the app if the title bar area is narrower than 250px. We could do something similar with a media query, but using the windowControlsOverlay API has two advantages for our use case:

• It’s only fired when the feature is supported and used, we don’t want to adapt the design otherwise.
• We can see the title bar area on different operating systems, which is great because Mac and Windows have different title bar sizes. 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%;}

When the window is too small, we can use the above CSS code to move our header down and move the thumbnails down in accordance with this.

Thirty pixels of exciting design opportunities

Our straightforward demo app was transformed into something that felt much more connected to desktop devices by using the Window Controls Overlay feature. Something that reaches out of the usual window constraints and provides a custom experience for its users.

In reality, this feature only gives us about 30 more pixels of room, and it presents challenges for using the window controls. And yet, this extra room and those challenges can be turned into exciting design opportunities.

More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. To make it easier for us web authors to integrate more and more fully with those devices, new features are added to the web platform. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. We can now think outside the rectangular box when building for the web.

So let’s embrace this. Let’s use the standard technologies already at our disposal, and experiment with new ideas to provide tailored experiences for all devices, all from a single codebase!

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

Here’s the strategy. To encourage stakeholders to determine high-risk assumptions and buried complexity, you must work with them to mobilize them as much as you do to obtain answers from users. Generally, you need to make them think it’s their plan.

By bringing the group up around two straightforward issues, I’ll show you how to collectively introduce alignment and cracks in the team’s shared knowledge.

1. What are the items?
2. What are the associations between those things?

A cross between screen design and analysis

These two issues correlate to the first two methods of the ORCA approach, which may be your new best friend when it comes to reducing speculation. What’s ORCA, then? Glad you asked.

ORCA stands for Things, Relationships, CTAs, and Values, and it outlines a process for creating good object-oriented user experience. My style philosophy is based on object-oriented UX. ORCA is an iterative strategy for synthesizing person study into an elegant fundamental foundation to help monitor and conversation design. My work as a UX designer has become more creative, productive, successful, fun, proper, and meaningful thanks to OOUX and ORCA.

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 occasionally refer to ORCA as a “garbage in, garbage out” procedure. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. The ORCA process’s beginning serves another purpose: it enables you to justify the need for research if you don’t have a lot of it.

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

Getting back 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 reveal what this timeless comic so skillfully demonstrates:

This is one reason why so many UX designers are frustrated in their job and why many projects fail. Every decision-maker is confident in their own mental picture, which is another reason why we frequently can’t sell research.

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

However, it is crucial how we go about doing this. However much we might want to, we can’t just tell everyone,” YOU ARE WRONG”! Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders accept responsibility for their beliefs and understanding gaps, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Let’s say your users are physicians. 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 bothers them the most? How do they use the current app”? But here’s the issue 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 conversation is more appropriate for facilitating than engaging in. Let’s listen in:

” Wait a sec, how frequently do doctors share patients?” Does a patient in this system have primary and secondary doctors”?

” Can a patient even have more than one primary doctor”?

Is it a “primary doctor” or “primary caregiver” ?Can’t that position be considered a nurse practitioner?

” No, caregivers are something else… That’s the patient’s family contacts, right”?

” So are caregivers in scope for this redesign”?

” Yeah, because if a caregiver is present at an appointment, the doctor needs to note that. Like, tag the caregiver on the note… Or on the appointment”?

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

When these kinds of questions bubble up collaboratively and come directly from the mouths of your stakeholders and decision-makers, suddenly, designing screens without knowing the answers to these questions seems incredibly risky, even silly.

If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And most likely as a result, this software product will become more confusing, complicated, and unintuitive.

The two questions

But how do we approach these kinds of contentious inquiries diplomatically, effectively, collaboratively, and reliably?

We can do this by starting with those two big questions that align to the first two steps of the ORCA process:

1. What are the items?
2. What are the associations between those things?

In practice, getting to these answers is easier said than done. I’m going to demonstrate how these two straightforward questions can serve as the starting point 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.

Noun foraging prep work

In the next section, I’ll show you how to run an Object Definition Workshop with your stakeholders ( and entire cross-functional team, hopefully ). But first, you need to do some prep work.

In essence, search for nouns that are specific to your project’s business or industry and from at least a few sources. I call this noun foraging.

Just a few excellent noun foraging sources can be found here:

• the product’s marketing site
• the product’s competitors ‘ marketing sites ( competitive analysis, anyone? )
• the labeled version of the already-existing product!
• user interview transcripts
• notes from interviews with stakeholders or vision documents from stakeholders

Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. Use those if all you have are a marketing website, some screenshots of the current legacy system, and access to customer service chat logs.

As you peruse these sources, watch for the nouns that are used over and over again, and start listing them ( preferably on blue sticky notes if you’ll be creating an object map later! …

You’ll want to focus on nouns that might represent objects in your system. If you are having trouble determining if a noun might be object-worthy, remember the acronym SIP and test for:

1. Structure
2. Instances
3. Purpose

Consider a library app, for instance. Is “book” an object?

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

What are some instances of this conceivable “book” object? Can you name a few? Check! The Alchemist, Ready Player One, Everybody Poops, OK!

Purpose: why is this object important to the users and business? Well, “book” is what our library client is providing to people and books are why people come to the library … Check, check, check!

Concentrate on capturing the nouns with SIP as you go noun foraging. Avoid capturing components like dropdowns, checkboxes, and calendar pickers—your UX system is not your design system! Components are just the packaging for objects—they are a means to an end. No one is using your dropdown to play in your digital space! They are coming for the VALUABLE THINGS and what they can do with them. We are attempting to identify those things or objects.

Let’s say we work for a startup disrupting the email experience. This is how I’d start my noun foraging.

I’d like to take a look at my own email client, which is Gmail. I’d then look at Outlook and the new HEY email. I would examine Hotmail, Yahoo, and even Basecamp and other’email replacers’. I’d read some articles, reviews, and forum threads where people are complaining about email. While doing all this, I would look for and write down the nouns.

( Before moving on, feel free to explore this hypothetical product’s potential and then scroll down to see how closely our lists correspond. Just don’t get lost in your own emails! Rejoice to me again!

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 views this in a different way )
• saved responses and templates

Scan your list of nouns and pick out words that you are completely clueless about. It might be automation or a client in our email example. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.

Aside: Here are some real nouns that I needed to clarify while working on my own projects in the past.

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

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

Facilitate an Object Definition Workshop

You could start your workshop by doing noun foraging; this can be done in concert. If you have five people in the room, pick five sources, assign one to every person, and give everyone ten minutes to find the objects within their source. When the time’s up, come together and find the overlap. Your friend here is affinity mapping!

If your team is short on time and might be reluctant to do this kind of grunt work ( which is usually the case ) do your own noun foraging beforehand, but be prepared to show your work. I enjoy showing screenshots of documents and screens with all the highlighted nouns. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.

HOT TIP: before jumping into the workshop, frame the conversation as a requirements-gathering session to help you better understand the scope and details of the system. You don’t need to tell them you‘re looking for gaps in the team’s understanding so that you can demonstrate 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.

Let the whack-a-mole question then start.

1. What is this thing?

Want to have genuine fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Then, have everyone present their cards at once, and see if you get different definitions (you will ). This is gold for exposing misalignment and starting great conversations.

As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty appears, quietly ( but clearly ) begin a parking lot with “open questions.” � �

Here’s a fantastic follow-up to solidify definitions:

2. Do our users know what these things are? What do users refer to this as?

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

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

Ask the group to decide whether to use only that term in the near future if it becomes more user-friendly. This way, the team can better align to the users ‘ language and mindset.

Okay, let’s get to the next part.

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

3. Do these two things exist the same? Or are these different? If they are different, how are they different?

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

Stakeholder 1: Yes! Absolutely.

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 expand your expanding glossary of terms. And continue to capture areas of uncertainty in your “open questions” parking lot.

If you successfully determine that two similar things are, in fact, different, here’s your next follow-up question:

4. What’s the relationship between these objects?

You: Do saved responses and templates have any connection to each other?

Stakeholder 3: Yeah, a template can be applied to a saved response.

You, always with the follow-ups: When is the template applied to a saved response? Does that occur when the user is creating the saved response? Or when they apply the saved response to an email? How does that actually function?

Listen. Capture uncertainty. When the number of “open questions” reaches a critical mass, pause and begin asking questions of groups or individuals. Some questions might be for the dev team ( hopefully at least one developer is in the room with you ). Someone who couldn’t make it to the workshop might have a question. And many questions will need to be labeled “user”.

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

5. Is this object in scope?

Your next query makes the team’s attention narrower so that it can focus on what your users are most interested in. You can simply ask,” Are saved responses in scope for our first release”?, but I’ve got a better, more devious strategy.

By now, you should have a list of clearly defined objects. Ask participants to arrange these items either in small breakout groups or independently according to their importance. Then, like you did with the definitions, have everyone reveal their sort order at once. Unsurprisingly, it’s not unusual for the VP to place something like” saved responses” at the top of the list while everyone else places it at the bottom. Try not to look too smug as you inevitably expose more misalignment.

I did this for a startup a few years ago. The three groups ‘ wildly different sorting patterns were displayed on the whiteboard.

The CEO nodded his head and said,” This is why we haven’t been able to move forward in two years,” taking a step back.

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 attempted to figure out what two things are different, but this time, we need to ask the team about every possible connection. For each object, ask how it relates to all the other objects. In what ways are the objects connected? Pull out your dependable boxes and arrows technique to see all the connections. Here, we are connecting our objects with verbs. I prefer to keep my verbs to simple statements like “has a” and “has many”

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

• Can attachments be included in a saved response?
• Can a saved response use a template? If so, can the user override the template if an email uses a saved response with a 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. attached .jpg I’ve changed my professional photo and I want to alert everyone to update it”.

The workshop participants might provide solid responses directly. Great! Capture that new shared understanding. However, as uncertainty arises, keep adding new questions to your expanding parking lot.

Light the fuse

You’ve set up the floodgates strategically so that the explosives can be seen everywhere. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.

Have the group reflect on the list of open questions before the workshop ends. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

Your final step is now. Take those questions you’ve compiled for user research and discuss the level of risk associated with NOT answering them. Ask, “if we design without an answer to this question, if we make up our own answer and we are wrong, how bad might that turn out”?

With this approach, we are making our decision-makers fight for user research because they themselves define questions as high-risk. Sorry, not sorry.

This is your moment of truth. With everyone in the room, ask for a reasonable budget of time and money to conduct 6–8 user interviews focused specifically on these questions.

HOT TIP: if you are new to UX research, please note that you’ll likely need to rephrase the questions that came up during the workshop before you present them to users. Make sure your questions are non-ending and don’t force the user to choose any default responses.

Final words: Hold the screen design!

Seriously, if you’re ever going to design screens again, make sure you first address these fundamental inquiries: what are the objects and how do they relate?

I promise you this: if you can secure a shared understanding between the business, design, and development teams before you start designing screens, you will have less heartache and save more time and money, and ( it almost feels like a bonus at this point! ) users will be more receptive to what you put out into the world.

I sincerely hope this will give you the time and money to spend talking to your users and getting a clear understanding of what you are designing before you begin creating screens. If you find success using noun foraging and the Object Definition Workshop, there’s more where that came from in the rest of the ORCA process, which will help prevent even more late-in-the-game scope tugs-of-war and strategy pivots.

Good luck, everyone! Now go sell research!

However, we’re still very far from this best.

At the time, I didn’t realize yet how to functionally incorporate morality. Yes, I did discover some tools in past projects that had worked for me, such as using checklists, assumption monitoring, and “dark fact” sessions, but I wasn’t able to use them in every task. 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 made a deeper investigation into the main causes of business that prevent us from practicing regular social style. Today, after much research and experimentation, I believe that I’ve found the code that will let us functionally combine morality. And it’s unexpectedly easy! However, we must second move out to understand what we’re up against.

Control the structure

Unfortunately, we’re confined to a capitalist system that encourages consumerism and inequality and is obsessed with the irrationality of infinite expansion. Sea levels, temperature, and our demand for energy continue to rise unquestioned, while the divide between rich and poor continues to increase. Owners expect ever-higher returns on their investments, and firms feel forced to set short-term goals that reflect this. Over the past few decades, those goals have transformed our well-meaning human-centered mentality into a potent tool that encourages 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. We’re a part of the problem, despite our best efforts and the fact that we like to claim that we provide solutions for people.

What can we do to alter this?

We may start by acting on the appropriate level of the system. A system intellectual named Donna H. Meadows after outlined ways to influence a system in order of success. When you apply these to style, you get:

You can change things like usability ratings or the number of style critiques at the least effective level. But none of that may change the direction of a business.
• 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.
• A business can improve its ability to achieve its goals by concentrating instead on administration control, employee recognition, or design-system purchases. But that doesn’t alter the goals themselves, which means that the business will also work against your ethical-design ideals.
• The change of honest methods, toolkits, articles, conferences, workshops, and other topics are what most ethical-design initiatives are currently focusing on at the next level, details flows. This is also where moral style has remained largely theoretical. We’ve been focusing on the wrong level of the system all this day.
• Take, for instance, the regulations; they consistently outwit information. There can be commonly accepted guidelines, such as how fund works, or a sprint group’s concept of done. However, illegal laws intended to maintain income, frequently revealed through comments like” the customer didn’t ask for it” or “don’t make it too big” can smother social style.
• Changing the rules without holding established energy is extremely difficult. That’s why the next stage is thus important: self-organization. Bottom-up initiatives, love projects, self-steering teams, and experiment all contribute to a company’s resilience and creativity. It’s precisely this diversity of viewpoints that’s needed to functionally address major structural issues like materialism, money injustice, and climate change.
• But goals and metrics are even more powerful than self-organization. Our businesses want to make more money, which means that everything and everyone in the business does their best to… make the company more money. And when I realized that profit is nothing more than a measurement, I understood how important a very particular, defined measurement may be toward pushing a company in a specific direction.

What is 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.

However, we all know that the three dimensions are not equally important: viability is ultimately what determines whether a product will become functional. So a more realistic representation might look like this:

The means are feasibility and desire, while viability is the objective. 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. Therefore, both feasibility and viability are important factors in the company’s efforts to accomplish what they stated. It makes intuitive sense: to achieve most anything, you need resources, people, and money. Fun fact: the Italian language is completely unaware of the differences between feasibility and viability; both are merely 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. When it comes to a product’s usability, such as user satisfaction or conversion, don’t take into account whether it is good 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 are unsuitable for striking a healthy balance with the natural world.

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. There are many variations of these models, some calling them “imputability, 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 is no single way to accomplish this because it depends greatly on your country’s values, culture, 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 equity, sustainability, and well-being.

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

An objective on a personal level teaches us that success transcends the typical area of user experience and satisfaction, taking into account factors like how much time and effort are required of users. We pursued well-being:

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

A societal goal requires us to consider our impact beyond the mere user, widening our focus to the economy, communities, and other involuntary parties. We called this objective equity:

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

Finally, the global goal of maintaining harmony with humanity’s sole home is the ultimate goal. Referring to it simply as sustainability, our definition was:

We create products and services that reward sufficiency and reusability. Our products are repurposed, given, and given priority to making sustainable choices in order to support the circular economy. We deliver functionality instead of ownership, and we limit energy use.

In essence, ethical design ( to us ) meant achieving the wellbeing of each user and an equitable value distribution within society through a design that can sustain 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

However, it is still necessary to define these goals. 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 includes some examples of metrics you can use to measure your progress toward equity, well-being, and sustainability:

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

” 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 lead to 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 we instead used ( reduced ) screen time or software energy consumption to measure success?

There’s another important message here. Even if we set an objective to create a calm interface, we might end up with a screen that makes you anxious if we were to pick the wrong metric for calmness, such as the number of interface elements. Choosing the wrong metric can completely undo good intentions.

Additionally, choosing the right metric is enormously helpful in focusing the design team. You are forced to consider what success looks like in real life and how you can demonstrate that you have met your ethical goals once you have chosen the metrics to use. 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 response to this query is very concise and focused.

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. Making the decision to” simply” use your imagination and pick one of the many resources and knowledge resources at your disposal.

I think this is quite exciting! It opens a whole new set of challenges and considerations for the design process. Would a brief illustration suffice, or should you go with that enticing video? Which typeface is the most calm and inclusive? What fresh techniques and tools do you employ? When is the website’s end of life? How can you provide the same service while requiring less attention from users? How can you ensure that those who are impacted by decisions are present when they are made? How can you measure our effects?

The definition of success will fundamentally alter what doing good design entails.

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 return to the pre-existing situation.

The kickoff is the most important meeting that can be so easy to forget to include. There are two main stages in it: 1 ) coordinating expectations; 2 ) defining success as a goal.

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. Possumptions 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 instance, we conducted an online kickoff meeting with the client, a subject-matter expert, and two other designers for a recent freelance project that aimed to create a digital platform that facilitates US student advisors ‘ documentation and communication. 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. However, agreeing on the project’s success means having respect for its desirability, viability, feasibility, and ethics is just as crucial as expressing expectations. What are the objectives in each dimension?

You need to be sure that you can trust success at this early stage because it will determine the project’s future. 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. To create a successful product, we agreed in our first meeting that a diverse user group that includes A and B is necessary. So we do activity X and follow research process Y”. Compare those odds to a situation where the team had to ask for permission halfway through the project and didn’t agree to it in advance. 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. A set of outer rings is used to measure the objectives, as well as an inner ring that is intended to capture ideas for those objectives. The rings are divided into five dimensions of successful design: healthy, equitable, sustainable, desirable, feasible, and viable.

We explored each dimension and recorded 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. Additionally, the subject-matter expert stressed the value of involving students from underprivileged and low-income 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 history and purpose: What is the purpose of 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 objectives, procedures, and role descriptions: how will we accomplish them?

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

How do I get started with ethical design, many of my coworkers have questioned me over the past year? 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. There is no skipping this step if you want to be an ethical, responsible designer.

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 think of yourself as a system designer, you need to first understand how your industry influences consumerism and inequality, how finance drives business, and how to think creatively about how to best influence the system. 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. Gather your coworkers to set design goals for sustainability, well-being, and equity. Engage your stakeholders in a workshop and challenge them to think of ways to achieve and measure those ethical goals. Take their ideas, make them clear and tangible, ask for their consent, 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 coworkers had questions to ask, such as” Will they take this 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 thought, isn’t it? 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.

That’s not enough, as systems theory suggests, though. 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 continue to live in the design-for-designers bubble and enjoy our privileged working-from-home environment without access to the real world. 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. By challenging them to redefine success in business, we must actively engage with our colleagues and clients.

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 simply need to come to terms with the right goals when starting each design project, identify the appropriate metrics, and acknowledge that we already have everything in place. 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.

In today’s data-driven environment, it’s becoming more and more possible for you to be asked to create a personal electronic expertise, whether it’s a common website, consumer portal, or indigenous application. However while there continues to be no lack of marketing buzz around personalization systems, we also have very few defined approaches for implementing personalized UX.

That’s where we begin. After completing tens of personalisation projects over the past few years, we gave ourselves a purpose: could you make a systematic personalization platform especially for UX practitioners? A human-centered personalization program that includes data, classification, content delivery, and general objectives can be compared to the Personalization Pyramid, a design-focused design. By using this strategy, you will be able to understand the core elements of a modern, UX-driven personalization system ( or at the very least know enough to get started ).

Getting Started

We’ll assume that you are already comfortable with the fundamentals of modern personalization for the purposes of this article. A nice guide can be found these: Website Personalization Planning. Although Graphic jobs in this field can take a variety of forms, they frequently start from the same place.

Common scenarios for starting a personalisation task:

• Your business or client made a purchase to support personalization with a content management system ( CMS ), marketing automation platform ( MAP ), or other related technology.
• The CMO, CDO, or CIO has identified customisation as a target
• Consumer data is unclear or disjointed.
• You are running some secluded targeting strategies or A/B tests
• On the personalisation method, parties of contention
• Mandate of customer privacy rules ( e. g. GDPR ) requires revisiting existing user targeting practices

Regardless of where you begin, a powerful personalization system will require the same key building stones. These are the “levels” on the tower, which we have identified. Whether you are a UX artist, scholar, or planner, understanding the core components may help make your contribution effective.

From top to bottom, the rates include:

North Star: What larger corporate goal is driving the personalization system?
1. Objectives: What are the specific, tangible benefits of the system?
2. Touchpoints: Where will you get personal service?
3. Contexts and Campaigns: What personalization information does the person view?
4. What constitutes a distinct, accessible market according to consumer parts?
5. Actionable information: What dependable and credible information is captured by our professional platform to generate personalization?
6. Natural Data: What wider set of data is conceivable ( now in our environment ) to allow you to optimize?

We’ll go through each of these amounts in change. An associated deck of cards was created to demonstrate specific examples from each level to make this more meaningful. We’ve found them helpful in customisation brainstorming periods, and will include cases for you here.

Starting at the Top

The tower has the following elements:

North Star

Ultimately, you want a North Star in your personalization plan, whether big or small. The North Star defines the (one ) overall mission of the personalization program. What do you hope to accomplish? North Stars cast a ghost. The larger the sun, the larger the darkness. Example of North Starts may contain:

Function: Personalized based on fundamental person inputs. Examples:” Raw” messages, basic search effects, system user settings and settings options, general flexibility, basic improvements
1. Feature: Self-contained customisation component. Examples:” Cooked” notifications, advanced optimizations ( geolocation ), basic dynamic messaging, customized modules, automations, recommenders
2. User knowledge: Personal consumer experiences across various user flows and interactions. Examples: Email campaigns, landing pages, advanced messaging ( i. e. C2C chat ) or conversational interfaces, larger user flows and content-intensive optimizations ( localization ).
3. Solution: Highly distinctive, personalized solution experiences. Example: Standalone, branded experience with personalization at their base, like the “algotorial” songs by Spotify quite as Discover Weekly.

Goals

Personalization can aid in accelerating designing with customer intentions, as in any good UX design. Goals are the tactical and measurable metrics that will prove the overall program is successful. Start with your current analytics and measurement program, as well as metrics you can benchmark against. In some cases, new goals may be appropriate. The most important thing to remember is that personalization is more of a means of achieving an objective than a desired result. Common goals include:

• Conversion
• Time spent on task
• Net promoter score ( NPS)
• Customer satisfaction

Touchpoints

Touchpoints are where the personalization happens. One of your main responsibilities as a UX designer will be in this area. The touchpoints available to you will depend on how your personalization and associated technology capabilities are instrumented, and should be rooted in improving a user’s experience at a particular point in the journey. Touchpoints can be multi-device ( mobile, in-store, website ), but they can also be more specific ( web banner, web pop-up, etc. ). Several examples are given below:

Channel-level touchpoints

• Email: Role
• Email opens at what time?
• In-store display ( JSON endpoint )
• Native app
• Search

Wireframe-level Touchpoints

• Web overlay
• Web alert bar
• Web banner
• Web content block
• Menu on the web

If you’re designing for web interfaces, for example, you will likely need to include personalized “zones” in your wireframes. Based on our next step, contexts, and campaigns, the content for these can be presented programmatically in touchpoints.

Contexts and Campaigns

Once you’ve identified some touchpoints, you can decide what kind of personalized content a user will receive. Many personalization tools will refer to these as” campaigns” ( so, for example, a campaign on a web banner for new visitors to the website ). These will be displayed to specific user segments programmatically, as defined by user data. At this stage, we find it helpful to consider two separate models: a context model and a content model. The context helps you consider the user’s level of engagement at the personalization moment, such as when they are casually browsing information or deep-dive. Think of it in terms of information retrieval behaviors. The content model can then guide you in deciding what kind of personalization to use in the context ( for instance, an” Enrich” campaign that features related articles might be a good substitute for extant content ).

Personalization Context Model:

1. Browse
2. Skim
3. Nudge
4. Feast

Content model for personalization:

1. Alert
2. Make Easier
3. Cross-Sell
4. Enrich

If you’d like to read more about each of these models, check out Colin’s Personalization Content Model and Jeff’s Personalization Context Model.

User Groups

User segments can be created prescriptively or adaptively, based on user research ( e. g. via rules and logic tied to set user behaviors or via A/B testing ). You will need to think about how to treat the logged-in visitor, the guest or returning visitor for whom you may have a stateful cookie ( or another post-cookie identifier ), or the authenticated visitor who is logged in at the very least. Here are some examples from the personalization pyramid:

• Unknown
• Guest
• Authenticated
• Default
• Referred
• Role
• Cohort
• Unique ID

Actionable information

Every organization with any digital presence has data. It’s important to inquire about how to use the data you can ethically collect on users, its inherent reliability and value, and what is the term for “data activation.” Fortunately, the tide is turning to first-party data: a recent study by Twilio estimates some 80 % of businesses are using at least some type of first-party data to personalize the customer experience.

First-party data has a number of benefits for the user experience, including being relatively simple to collect, more likely to be accurate, and less susceptible to the” creep factor” of third-party data. So a key part of your UX strategy should be to determine what the best form of data collection is on your audiences. Several examples are given below:

There is a progression of profiling when it comes to recognizing and making decisioning about different audiences and their signals. As user numbers increase in terms of time, confidence, and data volume, it varies more granularly.

While some combination of implicit / explicit data is generally a prerequisite for any implementation ( more commonly referred to as first party and third-party data ) ML efforts are typically not cost-effective directly out of the box. This is because optimization requires a strong content repository and data backbone. But these approaches should be considered as part of the larger roadmap and may indeed help accelerate the organization’s overall progress. At this point, you will typically work with key stakeholders and product owners to create a profiling model. The profiling model includes defining approach to configuring profiles, profile keys, profile cards and pattern cards. a scalable, multi-faceted approach to profiling.

Pulling it Together

The cards serve as a starting point for an inventory of sorts ( we offer blanks for you to customize your own ), a set of potential levers and motivations for the personalization activities you aspire to deliver, but they are more valuable when grouped together.

In assembling a card “hand”, one can begin to trace the entire trajectory from leadership focus down through a strategic and tactical execution. It serves as the foundation for the workshops that both co-authors have conducted to build a program backlog, which would make a good article topic.

In the meantime, what is important to note is that each colored class of card is helpful to survey in understanding the range of choices potentially at your disposal, it is threading through and making concrete decisions about for whom this decisioning will be made: where, when, and how.

Lay Down Your Cards

Near, medium, and long-term goals must be taken into account in any sustainable personalization strategy. Even with the leading CMS platforms like Sitecore and Adobe or the most exciting composable CMS DXP out there, there is simply no “easy button” wherein a personalization program can be stood up and immediately view meaningful results. Having said that, every personalization activity has a common grammar, just like every sentence has nouns and verbs. These cards attempt to map that territory.

The mobile-first design approach is excellent because it concentrates on what the customer truly needs, is well-practiced, and has become a standard design practice for years. But developing your CSS mobile-first should also be fantastic, too…right?

Well, not necessarily. Classic mobile-first CSS development is based on the principle of overwriting style declarations: you begin your CSS with default style declarations, and overwrite and/or add new styles as you add breakpoints with min-width media queries for larger viewports (for a good overview see “What is Mobile First CSS and Why Does It Rock?”). But all those exceptions create complexity and inefficiency, which in turn can lead to an increased testing effort and a code base that’s harder to maintain. Admit it—how many of us willingly want that?

Mobile-first CSS may yet be the best option for your own projects, but you need to first determine how ideal it is in light of the physical design and user interactions you’re trying to create. To help you get started, here’s how I go about tackling the elements you need to watch for, and I’ll discuss some alternative remedies if mobile-first doesn’t seem to fit your job.

merits of mobile-first technology

Some of the benefits of mobile-first CSS creation, and why it has been the de facto growth practice for so long, make a lot of sense:

Development order. A good development hierarchy is something you can definitely get from mobile-first; you simply get developing while paying attention to the mobile view.

tested and verified. It’s a tried and tested technique that’s worked for years for a cause: it solves a problem actually also.

prioritizes the portable watch. The smart see is the simplest and arguably the most significant because it covers all of the crucial consumer journeys and frequently accounts for more user visits ( depending on the project ) in terms of complexity.

Prevents desktop-centric growth. It can be tempting to first focus on the desktop perspective because desktop computers are used for growth. No one wants to spend their time retrofitting a desktop-centric website to function on mobile devices, but thinking about smart right away keeps us from getting stuck later on!

Drawbacks of mobile-first

Kind declarations can be set at lower breakpoints and therefore overwritten at higher breakpoints:

More breadth. The farther up the target order you go, the more unnecessary script you inherit from lower thresholds.

higher CSS sensitivity A group name declaration’s default style has then a higher specificity that has been returned to the browser’s default value. This can be a pain on big projects when you want to preserve the CSS candidates as simple as possible.

Requires more analysis tests. All higher thresholds must be regression tested if CSS changes at lower views ( such as adding a new design ).

The browser can’t prioritize CSS downloads. At wider breakpoints, classic mobile-first min-width media queries don’t leverage the browser’s capability to download CSS files in priority order.

Property price issue overrules its own.

There is nothing intrinsically wrong with overwriting principles, CSS was designed to do just that. However, inheriting incorrect principles can be laborious and ineffective, which is counterproductive. When you have to replace styles to restore them to their defaults, which may cause issues after, especially if you are using a combination of bespoke CSS and power classes, it can also lead to more fashion precision. We won’t be able to use a power school for a design that has been restore with a higher precision.

With this in mind, I’m developing CSS with a focus on the default values much more these days. Since there’s no specific order, and no chains of specific values to keep track of, this frees me to develop breakpoints simultaneously. I concentrate on finding common styles and isolating the specific exceptions in closed media query ranges (that is, any range with a max-width set). 

As you can view each target as a blank slate, this technique opens up some opportunities. If a product’s layout appears to be based on Flexbox at all thresholds, that is acceptable and can be coded in the definition style sheet. But if it looks like Grid would be much better for large windows and Flexbox for portable, these can both be done entirely freely when the CSS is put into finished media keyword ranges. Additionally, developing simultaneously requires you to have a thorough understanding of any given component in all breakpoints right away. This can help identify issues with the design more quickly in the development process. We don’t want to get stuck down a rabbit hole building a complex component for mobile, and then get the designs for desktop and find they are equally complex and incompatible with the HTML we created for the mobile view!

Although this strategy won’t work for everyone, I urge you to try it. There are plenty of tools available to support concurrent development, including Responsively App, Blisk, and many others.

Having said that, I don’t feel the order itself is particularly relevant. If you like to work on one device at a time, are comfortable with focusing on the mobile view, and are familiar with the requirements for other breakpoints, then you should definitely follow the classic development order. It’s crucial to find common styles and exceptions in the appropriate stylesheet, which is a manual tree-shaking procedure! Personally, I find this a little easier when working on a component across breakpoints, but that’s by no means a requirement.

In practice, closed media query ranges

We overwrite the styles in the traditional mobile-first CSS, but media query ranges can be used to prevent this. To illustrate the difference ( I’m using SCSS for brevity ), let’s assume there are three visual designs:

• smaller than 768
• from 768 to less than 1024
• 1024 and anything larger

Take a simple example where a block-level element has a default padding of “20px,” which is overwritten at tablet to be “40px” and set back to “20px” on desktop.

.my-block { padding: 20px; @media (min-width: 768px) { padding: 40px; } @media (min-width: 1024px) { padding: 20px; }}

.my-block { padding: 20px; @media (min-width: 768px) and (max-width: 1023.98px) { padding: 40px; }}

The subtle difference is that the mobile-first example sets the default padding to “20px” and then overwrites it at each breakpoint, setting it three times in total. In contrast, the second example sets the default padding to “20px” and only overrides it at the relevant breakpoint where it isn’t the default value (in this instance, tablet is the exception).

The goal is to: 

• Only set styles when needed. 
• Not set them with the expectation of overwriting them later on, again and again. 

To this end, closed media query ranges are our best friend. If we need to make a change to any given view, we make it in the CSS media query range that applies to the specific breakpoint. We’ll be much less likely to introduce unwanted alterations, and our regression testing only needs to focus on the breakpoint we have actually edited. 

Taking the above example, if we find that .my-block spacing on desktop is already accounted for by the margin at that breakpoint, and since we want to remove the padding altogether, we could do this by setting the mobile padding in a closed media query range.

.my-block {  @media (max-width: 767.98px) {    padding: 20px;  }  @media (min-width: 768px) and (max-width: 1023.98px) {    padding: 40px;  }}

The browser default padding for our block is “0,” so instead of adding a desktop media query and using unset or “0” for the padding value (which we would need with mobile-first), we can wrap the mobile padding in a closed media query (since it is now also an exception) so it won’t get picked up at wider breakpoints. At the desktop breakpoint, we won’t need to set any padding style, as we want the browser default value.

Bundling versus separating the CSS

Back in the day, keeping the number of requests to a minimum was very important because the browser's concurrent request limit (typically around six ) was high. In consequence, using image sprites and CSS bundling was the norm, with all CSS being downloaded as a single stylesheet with the highest priority.

With HTTP/2 and HTTP/3 now on the scene, the number of requests is no longer the big deal it used to be. By using a media query, we can separate the CSS into several files. The obvious benefit of this is that the browser can now request the CSS it currently requires with a higher priority than the CSS it doesn't. This is more performant and can reduce the overall time page rendering is blocked.

What version of HTTP do you use?

Go to your website and open the dev tools for your browser to find out which version of HTTP you're using. Next, select the Network tab and make sure the Protocol column is visible. If "h2" is included in the protocol list, that indicates that HTTP/2 is being used.

Note: To check the Protocol column in your browser's dev tools, right-click any column header ( such as Name ), go to the Network tab, reload your page, and then check the Protocol column.

If your website still uses HTTP/1, please check it out. WHILE!! What are you waiting for? Excellent user support exists for HTTP/2.

CSS should be split.

Separating the CSS into individual files is a worthwhile task. Linking the separate CSS files using the relevant media attribute allows the browser to identify which files are needed immediately (because they’re render-blocking) and which can be deferred. Based on this, it allocates each file an appropriate priority.

In the following example of a website visited on a mobile breakpoint, we can see the mobile and default CSS are loaded with" Highest" priority, as they are currently needed to render the page. The last three CSS files ( print, tablet, and desktop ) are still being downloaded in case they're needed later, but with" Lowest" priority.

Before rendering can begin, the browser will need to download the CSS file and parse it using bundled CSS before rendering can begin.

While, as noted, with the CSS separated into different files linked and marked up with the relevant media attribute, the browser can prioritize the files it currently needs. Using closed media query ranges allows the browser to do this at all widths, as opposed to classic mobile-first min-width queries, where the desktop browser would have to download all the CSS with Highest priority. We can’t assume that desktop users always have a fast connection. For instance, in many rural areas, internet connection speeds are still slow. 

Depending on project requirements, the media queries and the number of separate CSS files will vary from project to project, but the example below might look similar.

Depending on the project’s deployment strategy, a change to one file (mobile.css, for example) would only require the QA team to regression test on devices in that specific media query range. Compare that to the prospect of deploying the single bundled site.css file, an approach that would normally trigger a full regression test.

Moving on

The adoption of mobile-first CSS was a significant development milestone because it allowed front-end developers to concentrate on mobile web applications rather than creating websites for desktop use and attempting to retrofit them to work on other devices.

I don't think anyone wants to return to that development model again, but it's important we don't lose sight of the issue it highlighted: that things can easily get convoluted and less efficient if we prioritize one particular device—any device—over others. For this reason, it seems natural to concentrate on the CSS in its own right, keeping an eye on both the default setting and the exceptions. I've started to notice subtle simplifications in both the CSS and other developers', and that the work is also a little more organized and effective.

In general, simplifying CSS rule creation whenever we can is ultimately a cleaner approach than going around in circles of overrides. However, whatever method you use, it must fit the project. Mobile-first may turn out to be the best option for the situation at hand, but first you need to fully comprehend the trade-offs you're entering.

The personalization space is real, between the dream of getting it right and the worry of it going wrong ( like when we encounter “persofails” similar to a company’s constant plea to regular people to purchase additional bathroom seats ). It’s an particularly confusing place to be a modern professional without a map, a map, or a strategy.

Because successful personalization is so dependent on each group’s skill, technology, and market position, there are no Lonely Planet and some tour guides for those of you who want to personalize.

But you can ensure that your group has packed its carriers reasonably.

There’s a DIY method to increase your chances for victory. You’ll at least at least disarm your boss ‘ irrational exuberance. Before the group you’ll need to properly plan.

It’s known as prepersonalization.

Behind the song

Take into account the DJ have on Spotify, which was introduced last year.

We’re used to seeing the polished final outcome of a personalization function. A personal have had to be developed, budgeted, and given priority before the year-end prize, the making-of-backstory, or the behind-the-scenes success chest. Before any customisation have goes live in your product or service, it lives amid a delay of valuable ideas for expressing consumer experiences more automatically.

How do you decide where to position customisation wagers? How do you design regular interactions that didn’t journey up users or—worse—breed mistrust? We’ve discovered that several budgeted programs second required one or more workshops to join key stakeholders and domestic customers of the technology in order to justify their continuing investments. Make it count.

We’ve witnessed the same evolution up near with our clients, from big tech to budding companies. In our experience with working on small and large personalization work, a program’s best monitor record—and its capacity to weather tough questions, work steadily toward shared answers, and manage its design and engineering efforts—turns on how successfully these prepersonalization activities play out.

Effective workshops consistently distinguish successful future endeavors from unsuccessful ones, saving countless hours of time, resources, and overall well-being in the process.

A personalization practice involves a multiyear effort of testing and feature development. Your tech stack is not experiencing a switch-flip. It’s best managed as a backlog that often evolves through three steps:

1. customer experience optimization ( CXO, also known as A/B testing or experimentation )
2. always-on automations ( whether rules-based or machine-generated )
3. mature features or standalone product development ( such as Spotify’s DJ experience )?

This is why we created our progressive personalization framework and why we’re field-testing an accompanying deck of cards: we believe that there’s a base grammar, a set of “nouns and verbs” that your organization can use to design experiences that are customized, personalized, or automated. These cards won’t be necessary for you. But we strongly recommend that you create something similar, whether that might be digital or physical.

Set the timer for the kitchen.

How long does it take to cook up a prepersonalization workshop? The activities we suggest including during the assessment can ( and frequently do ) last for weeks. For the core workshop, we recommend aiming for two to three days. Here are a summary of our broad approach and information on the most crucial first-day activities.

The full arc of the wider workshop is threefold:

Kickstart: This specifies the terms of your engagement as you concentrate on both your team’s and your team’s readiness and drive.
1. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
2. Work your plan: This stage essentially entails creating a competitive environment in which team members can individually present their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

Give yourself at least a day, split into two large time blocks, to power through a concentrated version of those first two phases.

Kickstart: Apt your appetite

We call the first lesson the “landscape of connected experience“. It looks at the possibilities for personalization in your company. A connected experience, in our parlance, is any UX requiring the orchestration of multiple systems of record on the backend. This might be a marketing-automation platform combined with a content-management system. It could be a digital-asset manager combined with a customer-data platform.

Give examples of connected experience interactions that you admire, find familiar, or even dislike, as examples of consumer and business-to-business examples. This should cover a representative range of personalization patterns, including automated app-based interactions ( such as onboarding sequences or wizards ), notifications, and recommenders. These are in the cards, which we have a catalog of. Here’s a list of 142 different interactions to jog your thinking.

The table must be set up for this. What are the possible paths for the practice in your organization? Here’s a long-form primer and a strategic framework for a broader view.

Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature ( or something similar ). In our cards, we break down connected experiences into five categories: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to draw attention to the benefits of ongoing investment as well as the difference between what you deliver right now and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is crucial because it emphasizes how personalization can affect your own ways of working as well as your external customers. It’s also a reminder ( which is why we used the word argument earlier ) of the broader effort beyond these tactical interventions.

Each team member should decide where they would like to place your company’s emphasis on your product or service. Naturally, you can’t prioritize all of them. Here, the goal is to demonstrate how various departments may view their own advantages over the effort, which can be different from one department to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

The third and final Kickstart activity is about filling in the personalization gap. Is your customer journey well documented? Will compliance with data and privacy be a significant challenge? Do you have content metadata needs that you have to address? ( We’re pretty sure you do; it’s just a matter of recognizing the need’s magnitude and its solution. ) In our cards, we’ve noted a number of program risks, including common team dispositions. For instance, our Detractor card lists six intractable behaviors that prevent progress.

Effectively collaborating and managing expectations is critical to your success. Consider the potential obstacles to your upcoming progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. According to research, personalization initiatives face a number of common obstacles.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? You’re all set to go on, good.

Hit that test kitchen

Next, let’s take a look at what you’ll need to create personalization recipes. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. They give you a variety of options for how your organization can conduct its activities because of their broad and potent capabilities. This presents the question: Where do you begin when you’re configuring a connected experience?

The key here is to avoid treating the installed software ( as one of our client executives humorously put it ) like some sort of dream kitchen. These software engines are more like test kitchens where your team can begin devising, tasting, and refining the snacks and meals that will become a part of your personalization program’s regularly evolving menu.

Over the course of the workshop, the final menu of the prioritized backlog will be created. And creating “dishes” is the way that you’ll have individual team stakeholders construct personalized interactions that serve their needs or the needs of others.

The dishes will be made from recipes, which have predetermined ingredients.

Verify your ingredients

You’ll ensure that you have everything you need to create your desired interaction ( or that you can determine what needs to be added to your pantry like a good product manager ) and that you have validated with the right stakeholders present. These ingredients include the audience that you’re targeting, content and design elements, the context for the interaction, and your measure for how it’ll come together.

This is not just about identifying needs. Documenting your personalizations as a series of if-then statements lets the team:

1. compare findings to a common method for developing features, similar to how artists paint with the same color palette,
2. specify a consistent set of interactions that users find uniform or familiar,
3. and establish parity between all important performance indicators and performance metrics.

This helps you streamline your designs and your technical efforts while you deliver a shared palette of core motifs of your personalized or automated experience.

Create your recipe.

What ingredients are important to you? Consider a who-what-when-why construct:

• Who are your key audience segments or groups?
• What kind of content will you offer them, what design elements, and under what circumstances?
• And for which business and user benefits?

Five years ago, we created these cards and card categories. We regularly play-test their fit with conference audiences and clients. And there are still fresh possibilities. But they all follow an underlying who-what-when-why logic.

In the cards in the accompanying photo below, you can typically follow along with right to left in three examples of subscription-based reading apps.

1. Nurture personalization: When a guest or an unknown visitor interacts with a product title, a banner or alert bar appears that makes it easier for them to encounter a related title they may want to read, saving them time.
2. Welcome automation: An email is sent to a newly registered user to highlight the breadth of the content catalog and convert them to happy subscribers.
3. Winback automation: Before their subscription lapses or after a recent failed renewal, a user is sent an email that gives them a promotional offer to suggest that they reconsider renewing or to remind them to renew.

A good preworkshop activity might be to consider a first draft of what these cards might be for your organization, though we’ve also found that cocreating the recipes themselves can sometimes help this process. Start with a set of blank cards, and begin labeling and grouping them through the design process, eventually distilling them to a refined subset of highly useful candidate cards.

The workshop’s later stages could be characterized as shifting from focusing on a cookbook to a more nuanced customer-journey mapping. Individual” cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Better architecture is required for better kitchens.

Simplifying a customer experience is a complicated effort for those who are inside delivering it. Avoid those who make up their mind. With that being said,” Complicated problems can be hard to solve, but they are addressable with rules and recipes“.

When a team is overfitting, it’s because they aren’t designing with their best data, which is why personalization turns into a laugh line. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. For instance, your AI’s output quality is in fact impacted by your IA. Spotify’s poster-child prowess today was unfathomable before they acquired a seemingly modest metadata startup that now powers its underlying information architecture.

You can withstand the heat without a doubt.

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a deliberate and cooperative approach will produce the desired outcome. So banish the dream kitchen. Instead, head to the test kitchen to burn off the fantastical ideas that the doers in your organization have in store for time, to preserve job satisfaction and security, and to avoid unnecessary distractions. There are meals to serve and mouths to feed.

You have a better chance of lasting success and sound beginnings with this workshop framework. Wiring up your information layer isn’t an overnight affair. However, if you use the same cookbook and the same recipes, you’ll have solid ground for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

Although there are associated costs associated with purchasing this kind of technology and product design, your time well spent is on sizing up and confronting your unique situation and digital skills. Don’t squander it. The pudding is the proof, as they say.

The same holds true for those of us who are currently employed in design and development. Having worked on the web for about three years at this point, I’ve seen the typical wax and wane of concepts, strategies, and systems. Every day we as developers and designers re-enter a routine music, a brand-new concept or technology emerges to shake things up and completely alter our world.

How we got below

I built my first website in the mid-’90s. Design and development on the web back then was a free-for-all, with few established norms. For any layout aside from a single column, we used table elements, often with empty cells containing a single pixel spacer GIF to add empty space. We styled text with numerous font tags, nesting the tags every time we wanted to vary the font style. And we had only three or four typefaces to choose from: Arial, Courier, or Times New Roman. When Verdana and Georgia came out in 1996, we rejoiced because our options had nearly doubled. The only safe colors to choose from were the 216 “web safe” colors known to work across platforms. The few interactive elements (like contact forms, guest books, and counters) were mostly powered by CGI scripts (predominantly written in Perl at the time). Achieving any kind of unique look involved a pile of hacks all the way down. Interaction was often limited to specific pages in a site.

The development of online requirements

At the turn of the century, a new cycle started. Crufty code littered with table layouts and font tags waned, and a push for web standards waxed. Newer technologies like CSS got more widespread adoption by browsers makers, developers, and designers. This shift toward standards didn’t happen accidentally or overnight. It took active engagement between the W3C and browser vendors and heavy evangelism from folks like the Web Standards Project to build standards. A List Apart and books like Designing with Web Standards by Jeffrey Zeldman played key roles in teaching developers and designers why standards are important, how to implement them, and how to sell them to their organizations. And approaches like progressive enhancement introduced the idea that content should be available for all browsers—with additional enhancements available for more advanced browsers. Meanwhile, sites like the CSS Zen Garden showcased just how powerful and versatile CSS can be when combined with a solid semantic HTML structure.

Server-side languages like PHP, Java, and.NET overtook Perl as the predominant back-end processors, and the cgi-bin was tossed in the trash bin. The first era of web applications started with content-management systems (especially those used in blogs like Blogger, Grey Matter, Movable Type, and WordPress ), with these better server-side tools. In the mid-2000s, AJAX opened doors for asynchronous interaction between the front end and back end. Pages could now update their content without having to reload. A crop of JavaScript frameworks like Prototype, YUI, and jQuery arose to help developers build more reliable client-side interaction across browsers that had wildly varying levels of standards support. Techniques like image replacement enable the use of fonts by skilled designers and developers. And technologies like Flash made it possible to add animations, games, and even more interactivity.

These new methods, standards, and technologies greatly boosted the sector’s growth. Web design flourished as designers and developers explored more diverse styles and layouts. However, we still relied on numerous hacks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes ( such as rounded or angled corners ) and tiled backgrounds for the appearance of full-length columns (among other hacks ). All kinds of nested floats or absolute positioning were required for complicated layouts ( or both ). Flash and image replacement for custom fonts was a great start toward varying the typefaces from the big five, but both hacks introduced accessibility and performance problems. And JavaScript libraries made it simple for anyone to add a dash of interaction to pages, even at the expense of double, even quadrupling, the download size of basic websites.

The web as software platform

The interplay between the front end and the back end continued to grow, which led to the development of the current era of modern web applications. Between expanded server-side programming languages ( which kept growing to include Ruby, Python, Go, and others ) and newer front-end tools like React, Vue, and Angular, we could build fully capable software on the web. Along with these tools, there were additional options, such as shared package libraries, build automation, and collaborative version control. What was once primarily an environment for linked documents became a realm of infinite possibilities.

Mobile devices increased in their capabilities as well, and they gave us access to the internet while we were traveling. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This fusion of potent mobile devices and potent development tools contributed to the growth of social media and other centralized tools for people to use and interact with. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media provided connections on a global scale, with both positive and negative outcomes.

Want a much more extensive history of how we got here, with some other takes on ways that we can improve? ” Of Time and the Web” was written by Jeremy Keith. Or check out the” Web Design History Timeline” at the Web Design Museum. A fun tour through” Internet Artifacts” is also provided by Neal Agarwal.

Where we are now

It seems like we’ve been at a new significant inflection point over the past couple of years. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. From the tried-and-true classic of hosting plain HTML files to static site generators and content management systems of all kinds, there are many different ways to create websites. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. Webmentions, RSS, ActivityPub, and other IndieWeb tools can be useful in this regard, but they’re still largely underdeveloped and difficult to use for the less geeky. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

Especially with efforts like Interop, browser support for CSS, JavaScript, and other standards like web components has increased. New technologies gain support across the board in a fraction of the time that they used to. I frequently find out about a new feature and check its browser support only to discover that its coverage has already exceeded 80 %. Nowadays, the barrier to using newer techniques often isn’t browser support but simply the limits of how quickly designers and developers can learn what’s available and how to adopt it.

With a few commands and a few lines of code, we can currently prototype almost any concept. All the tools that we now have available make it easier than ever to start something new. However, as we upgrade and maintain these frameworks, we eventually pay the upfront costs that these frameworks may initially save in terms of our technical debt.

If we rely on third-party frameworks, adopting new standards can sometimes take longer since we may have to wait for those frameworks to adopt those standards. These frameworks, which previously made it easier to adopt new techniques sooner, have since evolved into obstacles. These same frameworks often come with performance costs too, forcing users to wait for scripts to load before they can read or interact with pages. And when scripts fail ( whether due to poor code, network issues, or other environmental factors ), there is frequently no other option, leaving users with blank or broken pages.

Where do we go from here?

Hacks of today help to shape standards for tomorrow. And there’s nothing inherently wrong with embracing hacks —for now—to move the present forward. Problems only arise when we refuse to acknowledge that they are hacks or when we refuse to take their place. So what can we do to create the future we want for the web?

Build for the long haul. Optimize for performance, for accessibility, and for the user. weigh the costs of those user-friendly tools. They may make your job a little easier today, but how do they affect everything else? What does each user pay? To future developers? to the adoption of standards? Sometimes the convenience may be worth it. Sometimes it’s just a hack that you’ve gotten used to. And sometimes it’s holding you back from even better options.

Start with standards. Standards continue to evolve over time, but browsers have done a remarkably good job of continuing to support older standards. Not all third-party frameworks are the same. Sites built with even the hackiest of HTML from the’ 90s still work just fine today. The same can’t always be said of websites created with frameworks even after a few years.

Design with care. Consider the effects of each choice, whether your craft is code, pixels, or processes. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that those decisions can have. Use the time saved by modern tools to consider more carefully and design with consideration rather than rush to “move fast and break things”

Always be learning. If you constantly learn, you also develop. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. Even if you were to concentrate solely on learning standards, you might end up focusing on something that won’t matter next year. ( Remember XHTML? ) However, ongoing learning opens up new neural connections in your brain, and the techniques you learn in one day may be used to inform different experiments in the future.

Play, experiment, and be weird! This website we created is the most incredible experiment. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be brave and try something new. Build a playground for ideas. Create absurd experiments in your own crazy science lab. Start your own small business. There has never been a place where we have more room to be creative, take risks, and discover our potential.

Share and amplify. Share what you think has worked for you as you go through testing, playing, and learning. Write on your own website, post on whichever social media site you prefer, or shout it from a TikTok. Write something for A List Apart! But take the time to amplify others too: find new voices, learn from them, and share what they’ve taught you.

Make a move and make it happen.

As designers and developers for the web ( and beyond ), we’re responsible for building the future every day, whether that may take the shape of personal websites, social media tools used by billions, or anything in between. Let’s incorporate our values into the products we produce, and let’s improve the world for everyone. Create that thing that only you are uniquely qualified to make. Then distribute it, improve it, re-use it, or create something new with it. Learn. Make. Share. Grow. Rinse and repeat. Everything will change whenever you believe you have the ability to use the internet.

I’d like you to consider this a “yes … and” piece to complement Joe’s post. I’m just trying to contradict what he’s saying, but I’m just trying to give some context to initiatives and opportunities where AI can make a difference for people with disability. To be clear, I want to take some time to speak about what’s possible in hope that we’ll get there one day. There are, and we’ve needed to address them, like, yesterday.

Other words

Joe’s article spends a lot of time examining how computer vision models can create other word. He raises a lot of valid points about the state of the world right now. And while computer-vision concepts continue to improve in the quality and complexity of information in their information, their benefits aren’t wonderful. He argues to be accurate that the state of image research is currently very poor, especially for some graphic types, in large part due to the absence of contextual contexts in which to look at images ( as a result of having separate “foundation” models for words analysis and image analysis ). Today’s models aren’t trained to distinguish between images that are contextually relevant ( which should probably have descriptions ) and those that are purely decorative ( which might not even need a description ) either. However, I still think there’s possible in this area.

As Joe points out, far text editing via human-in-the-loop should be a given. And if AI can intervene to provide a starting place for alt text, even if the rapid might say What is this BS? That’s not correct at all … Let me try to offer a starting point— I think that’s a win.

If we can specifically station a design to examine image usage in context, it might help us more quickly determine which images are likely to be elegant and which ones are likely to need a description. That will clarify which situations require image descriptions, and it will increase authors ‘ effectiveness in making their sites more visible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way ( even for humans ), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s say you came across a map that merely stated the chart’s name and the type of representation it was:” Pie chart comparing smartphone use to have phone usage in US households making under$ 30, 000 annually.” ( That would be a pretty bad alt text for a chart because it frequently leaves many unanswered questions about the data, but let’s just assume that was the description in place. ) If your website knew that that picture was a pie chart ( because an onboard model concluded this ), imagine a world where people could ask questions like these about the creative:

• Do more people use feature phones or smartphones?
• How many more are there?
• Is there a group of people that don’t fall into either of these buckets?
• How many people are that?

For a moment, the chance to learn more about images and data in this way could be revolutionary for people with low vision and blindness as well as for those with various forms of color blindness, cognitive disabilities, and other issues. It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

What if you could ask your browser to make a complicated chart simpler? What if you demanded that the line graph be isolated into just one line? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you asked it to switch colors in favor of patterns? That seems like a possibility given the chat-based interfaces and our current ability to manipulate images in modern AI tools.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. For instance, it might be able to convert that pie chart (or, better yet, a number of pie charts ) into more usable ( and useful ) formats, like spreadsheets. That would be incredible!

Matching algorithms

When Safiya Umoja Noble chose to put her book Algorithms of Oppression, she hit the nail on the head. Although her book focused on the ways that search engines can foster racism, I believe it to be equally accurate to say that all computer models have the potential to amplify conflict, bias, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. A large portion of this is a result of a lack of diversity in the people who design and construct them. There is still a lot of potential for algorithm development when these platforms are built with inclusive features in mind.

Take Mentra, for example. They serve as a network of people with disabilities. They employ an algorithm to match job seekers with potential employers based on more than 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it takes into account each work environment, communication strategies for each job, and other factors. Mentra made the decision to change the script when it came to the typical employment websites because it was run by neurodivergent people. They use their algorithm to propose available candidates to companies, who can then connect with job seekers that they are interested in, reducing the emotional and physical labor on the job-seeker side of things.

When more people with disabilities are involved in developing algorithms, this can lower the likelihood that these algorithms will harm their communities. That’s why diverse teams are so crucial.

Imagine that a social media company’s recommendation engine was tuned to analyze who you’re following and if it was tuned to prioritize follow recommendations for people who talked about similar things but who were different in some key ways from your existing sphere of influence. For instance, if you were to follow a group of non-disabled white male academics who talk about AI, it might be advisable to follow those who are disabled, aren’t white, or aren’t men who also talk about AI. If you followed its advice, you might gain a more in-depth and nuanced understanding of what’s happening in the AI field. These same systems should also use their understanding of biases about particular communities—including, for instance, the disability community—to make sure that they aren’t recommending any of their users follow accounts that perpetuate biases against (or, worse, spewing hate toward ) those groups.

Other ways that AI can assist people with disabilities

I’m sure I could go on and on about using AI to assist people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

Voice preservation You may be aware of the voice-prescribing options from Microsoft, Acapela, or others, or you may have seen the announcement for VALL-E or Apple’s Global Accessibility Awareness Day. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS ( Lou Gehrig’s disease ) or motor-neuron disease or other medical conditions that can lead to an inability to talk. This technology can also be used to create audio deepfakes, so we need to approach it responsibly, but the technology has truly transformative potential.
• voice recognition is. Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are currently hiring people with Parkinson’s and related conditions, and they intend to expand this list as the project develops. More people with disabilities will be able to use voice assistants, dictation software, and voice-response services, as well as to use only their voices to control computers and other devices, according to this research.
• Text transformation. The most recent generation of LLMs is capable of altering already-existing text without giving off hallucinations. This is incredibly empowering for those who have cognitive disabilities and who may benefit from text summaries, simplified versions, or even text that has been prepared for Bionic Reading.

The importance of diverse teams and data

We must acknowledge the importance of our differences. The intersections of the identities we live in have an impact on our lived experiences. These lived experiences—with all their complexities ( and joys and pain ) —are valuable inputs to the software, services, and societies that we shape. Our differences must be reflected in the data we use to develop new models, and those who provide that valuable information must be compensated for doing so. More robust models are produced by inclusive data sets, which promote more justifiable outcomes.

Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that the training data includes information about disabilities written by people with a range of disabilities.

Want a model that doesn’t speak in ableist language? You may be able to use existing data sets to build a filter that can intercept and remediate ableist language before it reaches readers. Despite this, AI models won’t be replacing human copy editors anytime soon when it comes to sensitivity reading.

Want a copilot for coding that provides recomprehensible recommendations after the jump? Train it on code that you know to be accessible.

I have no doubts about how dangerous AI will be for people today, tomorrow, and for the rest of the world. However, I also think that we can acknowledge this and make thoughtful, thoughtful, and intentional changes in our approaches to AI that will reduce harm over time as well. Today, tomorrow, and well into the future.

Many thanks to Kartik Sawhney for supporting the development of this article, Ashley Bischoff for providing me with invaluable editorial support, and of course, Joe Dolson for the prompt.