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However, how can a content management system ( CMS ) be set up to reach your audience both now and in the future? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing content versions that are conceptual and even join related content, you can avoid that result.

I just had the opportunity to lead a Fortune 500 company’s CMS application. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.

For our information to be understood by many systems, the unit needed conceptual types, which are names given based on their meaning rather than their presentation. This is crucial for an multichannel content strategy. Our aim was to allow writers to write articles and use it where necessary. But as the job proceeded, I realized that supporting material utilize at the range that my client needed required the whole group to identify a new pattern.

Despite our best efforts, we remained influenced by what we were more comfortable with: design techniques. An holistic information approach doesn’t rely on WYSIWYG tools for design and layout, unlike web-focused material strategies. 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 fundamental tenets govern a successful content model

We needed to explain to our designers, developers, and stakeholders that we were undertaking a very different task from their earlier web projects, where it was common for everyone to view content as visual building blocks that fit 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 learned two guiding principles that helped the team understand how a content model and the design processes we were familiar with were:

1. Instead of layout, content models must define semantics.
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 content’s intended purpose and not how it will be displayed. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. These types may make it simple to present content, but they do not aid in understanding the meaning of the content, which would have opened the door to the content presented in each marketing channel. In contrast, a semantic content model employs type names like product, service, and testimonial to allow for each delivery channel to interpret the content and use it as necessary.

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

Benefits of a semantic content model include:

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 irrational website redesigns.
• A semantic content model also gives you a competitive advantage. By adding structured data based on Schema. A website can provide hints to Google to understand the content, display it in search snippets or knowledge panels, and use it to respond to user voice-interface queries. Without ever visiting your website, potential visitors could easily find your content.
• Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. Delivery channels must be able to understand the same content in order to use it across multiple marketing channels. For instance, if your content model provided a list of questions and answers, it could be easily displayed on a frequently asked questions ( FAQ ) page as well as be used by a bot to answer frequently asked 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

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

Consider creating an essay or article. The meaning and usefulness of an article depend on how well its components are kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. This had a similar effect to an article that had had its headline removed. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

Let’s examine how connecting related content can be used in a practical setting to illustrate. A complex layout for a software product page that included multiple tabs and sections was presented by the client’s design team. Our instincts were to follow suit with the content model. Shouldn’t we make adding any number of tabs in the future as simple and flexible as possible?

Because our design-system instincts were so well-known, it appeared that we needed a “tab section” content type so that multiple tab sections could be added to a page. Each tab section would display various types of content. The software’s overview or specifications might be available in one tab. A list of resources might be found under another tab.

Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. How would a different system have been able to determine which “tab section” referred to a product’s specifications or resource list, for instance? Would that system have had to have used tab sections and content blocks to calculate this? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

Our customer had a breakthrough when we realized that each tab’s specific information, such as the software product’s overview, specifications, related resources, and pricing, was intended to reveal a specific purpose. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. It wasn’t long after a little digging that the idea of tabs wasn’t applicable to the content model. What was important was the meaning of the content they were planning to display in the tabs.

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

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 ideas made it easier for us to decide what to do with the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure Google and other interfaces understand your content, keep in mind:

• A design system isn’t a content model. Team members may be persuaded to combine them and have their content model resemble their design system, so you should guard the semantic and contextual integrity of the content strategy throughout the entire implementation process. Without the use of a magic decoder ring, every delivery channel will be able to consume the content.
• If your team is struggling to make this transition, you can still reap some of the benefits by using Schema. Your website uses structured data from org. The advantage of search engine optimization is a compelling argument on its own, even if additional delivery channels are not in the works.
• 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 will be prepared for the upcoming big thing, and they will be able to create new designs without compromising the compatibility between the content and the design.

You’ll help your team understand these principles by firmly defending them in their efforts to give content the attention it deserves as both your most valuable resource and your most effective way to engage with your audience.

This book will provide you with that plan of action. It covers how to incorporate safety principles into your design work in order to make tech that’s secure, how to persuade your stakeholders that this work is important, and how to respond to the critique that what we really need is more diversity. ( Spoiler: we do, but diversity alone is not the solution to fixing unethical, unsafe technology. )

The procedure for diverse safety

Your objectives when designing for protection are to:

• determine way your product can be used for misuse,
• style ways to prevent the maltreatment, and
• offer assistance for customers who are prone to regain control and power.

The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). I developed this strategy in 2018 to better understand the various methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. The Process includes five public areas of action:

• conducting exploration
• Creating tropes
• Pondering issues
• Designing answers
• Testing for health

The Process is meant to be flexible; in some situations, it didn’t make sense for groups to adopt every step. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.

And once you use it, if you have an idea for making it better or simply want to give perspective of how it helped your group, please get in touch with me. It’s a living document, and I want to use it as a practical and useful application for engineers in their day-to-day tasks.

If you’re working on a product especially for a resilient team or survivors of some form of injury, such as an application for survivors of domestic violence, sexual abuse, or drug addiction, be sure to read Section 7, which covers that position directly and should be handled a bit different. The purpose of this design is to prioritize safety when creating a more general product with a broad user base ( which, as we already know from statistics, will include some groups who need to 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

A thorough analysis of how your technology might be used for abuse as well as specialized insights into the experiences of those who have witnessed and perpetrated that kind of abuse should be included in design research. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.

broad-based 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 involves artificial intelligence, be aware of the potential for racism and other issues that have been reported in other AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. For these studies, Google Scholar is a useful resource.

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. In order to gain a better understanding of the subject and avoid retraumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

It is important to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. Alternative to paying is to donate to a cause fighting the kind of violence the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

Abusers specific research

It’s unlikely that teams aiming to design for safety will be able to interview self-proclaimed abusers or people who have broken laws around things like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Attempt to understand how abusers or bad actors use technology to harm others, how they use it against others, and how they justify or explain the abuse.

Step 2: Create archetypes

Use your research’s findings to create the archetypes of abuser and survivor once you’ve finished your research. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they’re based on your research into likely safety issues, much like when we design for accessibility: we don’t need to have found a group of blind or low-vision users in our interview pool to create a design that’s inclusive of them. Instead, we base those designs on existing research and the requirements of this group. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

The abuser archetype is a person who views a product as a tool to cause 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 describes a person 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 be aware of the abuse is occurring but not be able to stop it, such as when a stalker keeps figuring out where they are from ( Fig 5.4), or they may be aware that it is happening but not know how ( for example, when an abuser locks them out of IoT devices ). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later when you create solutions to help your survivor archetypes achieve their objectives of preventing and ending abuse.

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic details we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and the abuser’s goals.

And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For example, if you uncovered an issue with security, such as the ability for someone to hack into a home camera system and talk to children, the malicious hacker would get the abuser archetype and the child’s parents would get survivor archetype.

3. Brainstorming issues

After creating archetypes, brainstorm novel abuse cases and safety issues. You’re trying to identify entirely new safety issues that are unique to your product or service by using the term” Novel” in terms of things you’ve not found in your research. The goal with this step is to exhaust every effort of identifying harms your product could cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

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

Try conducting a Black Mirror brainstorming session if you want to start somewhere. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out how your product would be used in an episode of the show—the most wild, awful, out-of-control ways it could be used for harm. Participants in Black Mirror brainstorming typically end up having a lot of fun ( which I believe is great because having fun when designing for safety! ). I recommend time-boxing a Black Mirror brainstorm to half an hour, and then dialing it back and using the rest of the time thinking of more realistic forms of harm.

After identifying as many opportunities for abuse as you can, you may still not feel confident that you have found every potential source 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 something is missing, then? If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.

It’s impossible to say 100 % assurance that you’ve done everything right, but instead of aiming for 100 % assurance, acknowledge that you’ve taken this step and have done everything you can, and pledge to keep putting safety first 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

You should now be able to identify potential harm-causing uses for your product as well as survivor and abuser archetypes describing opposing user objectives. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This is a good addition to existing design processes where you’re making recommendations for solutions to the various issues your research has identified.

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 barriers can you place to stop the harm from occurring?
• How can you make the victim aware that abuse is happening through your product?
• How can you assist the victim in understanding what they need to do to stop the problem?
• 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 detect harm is occurring. For example, a pregnancy app might be modified to allow the user to report that they were the victim of an assault, which could trigger an offer to receive resources for local and national organizations. Although it’s not always possible to be this proactive, it’s worthwhile to spend a half hour talking about how your product could help the user receive help in a safe manner if any kind of user activity would indicate some form of harm or abuse.

That said, use caution: you don’t want to do anything that could put a user in harm’s way if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll walk through a good illustration of this.

Step 5: Test for safety

The final step is to evaluate your prototypes from the perspective of your archetypes, who wants to harm the product 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 work for a company that doesn’t conduct usability testing, you might be able to use safety testing to deftly perform both. A user who uses your design while trying to use it against someone else can also be encouraged to point out interactions or other design details that don’t make sense to them.

You’ll want to conduct safety testing on either your final prototype or the actual product if it’s already been released. It’s okay to test an existing product that wasn’t created with safety goals in mind right away; “etrofitting” it for safety is a good thing.

Remember that testing for safety involves testing from the perspective of both an abuser and a survivor, though it may not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.

You as the designer are probably too closely acquainted with the product and its design at this point, just like other usability testing techniques, and 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.

Abuse 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. Use your product in an effort to accomplish the objectives in the abuser archetype you created earlier.

For example, for a fitness app with GPS-enabled location features, we can imagine that the abuser archetype would have the goal of figuring out where his ex-girlfriend now lives. With this in mind, you’d make every effort to discover the location of a different user who has their privacy settings in place. You might try to see her running routes, view any available information on her profile, view anything available about her location ( which she has set to private ), and investigate the profiles of any other users somehow connected with her account, such as her followers.

If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Reverting to step 4 and figuring out how to stop this from occurring is your next step. You may need to repeat the process of designing solutions and testing them more than once.

Survivor testing

Survivor testing involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. The survivor archetype’s goal of not being stalked is satisfied by preventing an attempt by an abuser archetype to stalk someone, so separate testing wouldn’t be required from the survivor’s perspective.

However, there are cases where it makes sense. For instance, a survivor archetype’s goal would be to discover who or what causes the temperature to change when they aren’t altering it themselves. You could test this by looking for the thermostat’s history log and checking for usernames, actions, and times, if you couldn’t find that information, you would have more work to do in step 4.

Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Your test would involve trying to figure out how to do this: are there instructions on how to remove and change the password, and are they simple to locate? 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 noted that personas typically focus on happy people, but happy people are frequently anxious, stressed, unhappy, or even tragic. These are called” stress cases”, and testing your products for users in stress-case situations can help you identify places where your design lacks compassion. More information about how to incorporate stress cases into your design can be found in Design for Real Life, as well as in many other effective methods for compassionate design.

In the 1950s, several members of the elite running group had come to accept the idea that it was impossible to run a hour in less than four hours. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

However, on May 6, 1956, Roger Bannister caught anyone by surprise. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

The world presently knew that the four-minute hour could be accomplished thanks to this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Finally, a year later, three runners all managed to cross the four-minute hurdle in the same culture. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

We accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for human running speed, we also think there are the strictest requirements for how a website should do.

Establishing requirements for a green website

The key indicators of climate performance in most big companies are pretty well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. But, we are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods to do so.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the amount of CO₂ that a website merchandise produces. We can’t measure the pollutants coming out of the exhaust valves on our devices. The pollution coming from power plants that burn coal and oil are considerably away, out of sight, and out of mind. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. What then do we do?

If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as coal pollution gauges:

1. Transfer of data
2. Electricity’s carbon power

Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

Transfer of data

Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a reliable indicator of how much power is being consumed and how much carbon is being released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.

The page weight, or the page’s transfer size in kilobytes, can be most easily calculated for a single visit for web pages. It’s fairly easy to measure using the developer tools in any modern web browser. Frequently, any web application’s overall data transfer statistics will be included in your web hosting account ( Fig. 2.1 ).

The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes.

A large scope is necessary to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for roughly half of this data transfer, making them the single biggest contributor to carbon emissions on a typical website.

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

You might be aware of the idea behind performance budgeting as a method for directing a project team to deliver faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than vague suggestions, much like speed limits while driving, so the goal should always be to come within budget.

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

We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use the page weight to compare it to competitors or the outdated website we’re replacing. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.

We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, visitors who load the same page more frequently are likely to have a high percentage of the files cached in their browser, which means they don’t need to move all the files on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. We can learn even more about how to optimize efficiency for users who regularly visit our pages by measuring transfer size at this next level of detail, which will also enable us to establish page weight budgets for situations that extend beyond the initial visit.

Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose their data on energy consumption and carbon emissions, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, less data transfer leads to more energy efficiency, which is a crucial component of lowering web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some.

Electricity’s carbon power

Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” is used to describe how many grams of carbon are produced for every kilowatt-hour of electricity (gCO₂/k Wh ). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately ₂00–400 gCO₂/k Wh.

The majority of electricity is produced by national or state grids, where different levels of carbon intensity are combined with energy from a variety of sources. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

Although we have some control over where our projects are hosted, we do not have complete control over the energy supply of web services. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps the user-provided data, and a look at their map demonstrates how, for instance, choosing a data center in France will result in significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

Having said that, we don’t want to locate our servers too far away from our users; however, it takes energy to transmit data through the telecom’s networks, and the more energy is used, the further the data travels. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance between that location and the data center that our hosting company uses as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.

For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could look up the travel distance between London and San Francisco, which is 5,300 miles. That’s a long way! We can see how hosting it somewhere in North America, ideally on the West Coast, would significantly lessen the distance and the amount of energy required to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Reverting it to carbon emissions

If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. The method my team developed converts the data transferred over wire when loading a website into a CO₂ figure ( Fig. ₂.4), calculating the associated electricity, and then converting that data into a figure ( Fig. ₂.4). It also factors in whether or not the web hosting is powered by renewable energy.

The Energy and Emissions Worksheet that comes with this book teaches you how to take it to the next level and tailor the data more accurately to the individual aspects of your project.

With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO₂ is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds an air of abstraction, carbon budgets do focus our minds on the main issue we’re trying to reduce, which also supports the main goal of sustainable web design: reducing carbon emissions.

Browser Energy

Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are smart TVs, tablets, laptops, phones, tablets, laptops, or other front-end web technologies. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React allow us to create applications where the” thinking” process is performed either partially or completely in the browser.

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more energy is used by the user’s devices as a result of the user’s web browser’s increased computation. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally make them use older, slower devices and make their phones and laptops ‘ batteries discharge more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only harms the environment, but it places a disproportionate financial burden on the poorest members of society.

In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the developer console of the Safari browser is one of the tools we currently have ( Fig. 2.5 ).

You are aware of the moment your computer’s cooling fans start spinning so frantically that you mistakenly believe it might take off when you load a website? That’s essentially what this tool is measuring.

It uses these figures to create an energy impact rating and shows the percentage of CPU used and how long the CPU used when loading the web page last. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.

Cartons are used to style CSS. In fact, the whole website is made of containers, from the computer viewport to components on a webpage. However, every now and then a new element emerges 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. And having two or more portable devices forces us to reevaluate how to make the most of the available space in a variety of diverse device positions.

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

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

Liberal Web Apps are bridging the gap between websites and apps. They combine the best of both worlds. On the one hand, they are flexible, relatable, 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 desktops 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 consider other ways and reclaim the whole window in the app? Doing so would give us a chance to create our applications 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 glass controls

Let’s get started with an explanation of the screen and name table settings.

The title bar is the place displayed at the top of an game windows, which frequently contains the phone’s name. The buttons or buttons that are displayed at the top of an app’s window allow you to reduce, increase, or close it.

Window Controls Overlay removes the actual requirement of the name bar and windows controls areas. The title bar and windows control buttons are overlayed on top of the user’s web content, allowing for total height to be the game window.

If you are reading this article on a desktop computer, get a quick glance at another software. Odds are they’re currently doing something similar to this. In fact, the internet browser you are using uses the major area to show tabs.

Spotify’s application window’s top edge is where the album artwork appears.

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

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

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 CSS and a single HTML element in a simple CSS playground.

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

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

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

And on Windows:

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

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

Enabling Window Controls Overlay

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

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 Window Controls Overlay

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

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

On the surface, the feature is really simple to use. The only thing required is for the title bar to disappear and the window controls to become an overlay as a result of this manifest change.

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 obscured by the window controls because our layout now begins at the top of the window, which is what we wanted.

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 added to 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. We’ll position our header, which includes the logo, search bar, and NEW button, using two of the variables in our case.

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

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

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

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

Changing the window controls background color so it blends in

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

Not 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 several definitions for 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.

What will we do with this function:

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 drag and click their way to a sizable area in the title bar, but when using the Window Controls Overlay feature, they are limited to where the control buttons are, and must carefully place their fingers in between these buttons to move the window.

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

We can use the following to 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. So let’s take a different strategy. 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 now click and drag the title bar back into 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 won’t be enough room for the search field, logo, and button to fit because the user made the window very narrow. We would need to lower them a little.

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

Three intriguing things are provided by the API:

• 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.ongeometrychangeenables us to determine 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.
• The title bar area is different for 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 move the header down using the above CSS code to avoid hitting the window control buttons, and we can also lower the thumbnails accordingly.

Thirty pixels of exciting design opportunities

We were able to convert our simple demo app to something that felt much more connected to desktop devices by using the Window Controls Overlay feature. Something that reaches out of the usual window constraints and provides a custom experience for its users.

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

More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. To make it easier for us web authors to integrate more and more fully with those devices, new features are added to the web platform. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. We can now think beyond 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 report bugs to the spec’s repository if you have the chance to try the Window Controls Overlay feature and have feedback on it. It’s still early in the development of this feature, and you can help make it even better. You can also look at this demo app and the source code, the feature’s existing documentation, or the feature’s existing documentation.

Here’s the key. You must engage stakeholders to determine high-risk conclusions and invisible complexity, so that they can become just as motivated as you are to receive responses 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 group’s shared understanding in this article.

1. What are the materials?
2. What are the interactions between those things?

A cross between camera 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 approach has four incremental shells and a staggering fifteen steps. In each round we get more precision on our System, Rupees, Computer, and As.

I occasionally refer to ORCA as a “garbage in, garbage out” procedure. To ensure that the verifiable design produced in the last round truly tests properly, the process needs to be fed by great research. The beginning of the ORCA process, however, serves another purpose: it helps you sell the need for research if you don’t have a ton of research.

In other words, the ORCA process serves as a gauntlet between research and design. You can gracefully ride a 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 starts 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 is more similar to the conversation you need to facilitate. Let’s listen in:

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

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

Is it a “primary doctor” or just a “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 this redesign’s scope”?

” 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 going 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 of this, software will be more confusing, complicated, and less intuitive.

The two questions

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

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

1. What are the materials?
2. What are the interactions 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 already-existing product ( check the labels! )!
• user interview transcripts
• vision documents or notes from stakeholder interviews

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

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

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

1. Structure
2. Instances
3. Purpose

Consider, for instance, a library app. 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 out The Alchemist, Ready Player One, and Everybody Poops!

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!

Focus on capturing the nouns that have SIP as you are 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 first take a look at my own email client, which turns out to be Gmail. I’d then look at Outlook and the new HEY email. I’d check out Hotmail, Yahoo, and even Slack and 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! Remain with me!

Drumroll, please…

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

• email message
• thread
• contact
• client
• rule/automation
• email address that is not a contact?
• contact groups
• attachment
• Google doc file / other integrated file
• newsletter? ( HEY 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 a client or automation in our email example. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.

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

• Record Locator
• Home Incentive
• 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

Noun foraging can be used as a starting point for your workshop; 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 that have all the highlighted nouns. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.

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

1. What is this thing?

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

As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty strikes, ostensibly start an “open questions” parking lot. � �

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

2. Do our users know what these things are? What is the name of this thing by users?

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 if they can agree to use only that term as a starting point if a more user-friendly term does. 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. Are these the same thing? Or are these different? How are they different if they are different from one another?

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.

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

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

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? What is the process behind that?

Listen. Capture uncertainty. When the number of “open questions” reaches a critical mass, pause to begin asking questions of groups or individuals. Some questions might be for the dev team ( hopefully at least one developer is in the room with you ). One question might be specific for someone who was unable to attend the workshop. And many questions will need to be labeled “user”.

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

5. Is this object in scope?

Your next query makes the team’s attention narrow to what’s most crucial to your users. You can simply ask,” Are saved responses in scope for our first release”?, but I’ve got a better, more devious strategy.

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

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

The CEO sat back, examined it, and said,” This is why we haven’t been able to move forward in two years.”

Admittedly, it’s tragic to hear that, but as a professional, it feels pretty awesome to be the one who facilitated a watershed realization.

Once you have a good idea of in-scope, clearly defined things, this is when you move on to doing more relationship mapping.

6. Create a visual representation of the objects ‘ relationships

We’ve already done this before figuring out what two things might be different, but this time, we’ll 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 trusted boxes-and-arrows technique to visualize all the connections. Here, we are connecting our objects with verbs. I prefer to use simple statements like “has a” and “has many.”

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

• 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”.

Strong responses might come directly from the workshop participants. Great! Capture that new shared understanding. However, keep adding questions to your expanding parking lot as uncertainty arises.

Light the fuse

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

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

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

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

Your moment of truth is right now. 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-repeated 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!

The mobile-first style approach is fantastic because it concentrates on what is most important to the consumer, it’s well-practiced, and it’s a well-known style design for years. But developing your CSS mobile-first should also be wonderful, 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.

benefits of mobile-first technology

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

Development pyramid. A good development hierarchy is one thing you definitely get from mobile-first; you just concentrate on the cellular view and start developing.

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 smart see. The mobile view is the simplest and arguably the most significant because it covers all the crucial user journeys and frequently accounts for a higher proportion of user visits ( depending on the project ) ).

Stops desktop-centric growth. It can be tempting to first focus on the desktop perspective because desktop computers are used for growth. However, considering mobile from the beginning prevents us from getting stuck eventually; no one wants to spend their day getting a site that is focused on desktops to work on mobile devices!

Drawbacks of mobile-first

Model 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 password you inherit from lower thresholds.

higher CSS sensitivity Styles that have been returned to the default value in a class name charter then have a higher sensitivity. 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 modifications to CSS at a lower see ( such as adding a new style ) are required.

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.

Home value issue is overruled by the issue.

There is nothing intrinsically wrong with overwriting beliefs, 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 back 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 strategy opens up some opportunities. If a product’s layout appears to be based on Flexbox at all breakpoints, 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, having a thorough understanding of any given component in all breakpoints upfront is necessary for developing simultaneously. This can help identify issues in the design more quickly during 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 resources 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 have a good understanding of the requirements for other breakpoints, then you should definitely stick to the classic development order. The key is to find common styles and exceptions so that you can include them 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 classic mobile-first CSS, but we can prevent this by using media query ranges. 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 requests 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 break 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 your browser's dev tools 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.

Also, if your website is still using HTTP/1... WHILE!! What are you waiting for? The HTTP/2 user support is excellent.

splitting the CSS

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. In case they are needed later, the remaining CSS files ( print, tablet, and desktop ) are still being downloaded with" Lowest" priority, though they are still needed.

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

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 may vary from one project to the next, but the example below may 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 milestone in web development 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, always mindful of what is the default setting and what constitutes an exception, as a result. 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. For the reasons given, mobile-first may turn out to be the best option for the situation, but first you must fully comprehend the trade-offs you're entering.

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 honest 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 remarkably easy! However, we must first focus out to understand what we’re up against.

Control the program

Unfortunately, we are confined to a capitalist system that fosters commercialism and inequality and is obsessed with the utopian dream of infinite growth. 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 years, those goals have transformed our well-meaning human-centered attitude 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. Yet with our best motives, and despite the fact that we like to claim that we provide solutions for people, we’re a part of the issue.

What can we do to alter this?

We can begin by acting on the appropriate level of the system. System scholar Donna H. Meadows after outlined ways to increase the effectiveness of a system. 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.
• Instead of focusing on feedback loops like control power, employee reputation, or design-system investments, a company can become more effective at achieving its goals. But that doesn’t alter the goals themselves, which means that the business will also work against your ethical-design ideals.
• Most ethical-design efforts’ current focus is on the exchange of moral techniques, toolkits, articles, conferences, workshops, and other topics. 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 formal power is extremely difficult. That’s why the next stage is thus important: self-organization. Research, bottom-up initiatives, interest projects, self-steering teams, and other such self-organization techniques all contribute to the resilience and creativity of a business. 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 measures 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 income. And when I realized that profit is nothing more than a dimension, 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 go live. 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 deciding whether a product is safe for people, such as user satisfaction or conversion, durability goals are unimportant. 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 unable to restore a healthy relationship with nature.

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

This is hardly a new idea. 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.

Ensure social justice, equity, and sustainability.

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

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

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

We must consider our impact beyond the user, expanding our focus to the economy, communities, and other indirect stakeholders, as a result of having an objective on the societal level. 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 indicators of economic equality. We listen to local culture, communities, and those we affect.

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

We create products and services that reward sufficiency and reusability. Our solutions promote the circular economy by generating value from waste, reusing products, and giving priority to sustainable choices. We deliver functionality instead of ownership, and we limit energy use.

In essence, ethical design ( to us ) meant achieving well-being for 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, defining these goals is still insufficient. 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.

In this overview, you can use examples of metrics 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. If we were to choose the wrong metric for calmness, such as the number of interface elements, we might still end up with a screen that makes us anxious, even if we set an objective to create a calm interface. Choosing the wrong metric can completely undo good intentions.

Additionally, choosing the right metric is enormously helpful in focusing the design team. Once you complete the task of selecting metrics for our goals, you are forced to consider what success looks like in terms of words and how you can demonstrate that you’ve accomplished your ethical goals. 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 simple illustration suffice, or should you go with that energizing video? Which typeface is the most calm and inclusive? What brand-new equipment and techniques 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

The kickoff is the most important meeting that can be so easy to forget to include. There are two main stages to it: 1 ) the alignment of expectations and 2 ) the success definition.

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 what success means for the project in terms of desirability, viability, feasibility, and ethics is just as crucial as expressing expectations. What are the objectives in each dimension?

It is crucial to reach an understanding of what success means at this early stage because you can rely on it for the duration of the project. If, for example, the design team wants to build an inclusive app for a diverse user group, they can raise diversity as a specific success criterion during the kickoff. If the client agrees, the team can refer back to that promise throughout the project. As we agreed in our first meeting, having A and B’s diverse user group is essential to creating a successful product. 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 that beforehand. 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: Why do we work on 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?
• how will we go about defining the scope, process, and role descriptions?

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

A number of my coworkers have questioned me over the past year,” Where do I begin with ethical design?” My answer has always been the same: organize a session with your stakeholders to ( re ) define success. Even though you might not always be 100 percent successful in agreeing on goals that cover all responsibility objectives, that beats the alternative ( the status quo ) every time. There’s 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 understand how your industry influences consumerism and inequality, how finance drives business, and how to think creatively about how to use the most powerful tools to 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 and instead define design goals for well-being, equity, and sustainability. Engage your stakeholders in a workshop and challenge them to think of ways to achieve and measure those ethical goals. Give them their opinions, clarify them, and demand their consent.

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” Wouldn’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 seems like a good idea, no? 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 coworkers 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 at the start of each design project, identify the appropriate metrics, and acknowledge that we already have everything we need to get started. That’s what it means to do daily ethical design.

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

In today’s data-driven environment, it’s becoming more common for a UX specialist to be asked to create a personal digital experience, whether it be a common website, consumer portal, or native 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? The Personalization Pyramid is a designer-centric framework for establishing human-centered personalization initiatives that cover information, classification, content delivery, and overall objectives. 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 projects 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 of 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 personalization method, participants disagree.
• 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, as we’ve made them. 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 geopolitical goal is driving the personalization system?
1. Objectives: What are the specific, tangible benefits of the system?
2. Touchpoints: Where will you get customized service?
3. Contexts and Campaigns: What personalization information does the person view?
4. What makes up a distinct, useable market according to consumer segments?
5. Actionable Data: What dependable and credible information is captured by our professional platform to generate personalization?
6. 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 serves as an example of each level’s specific examples to make this more practical. 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

With your personalisation plan, whether large or small, you aim for a general north star. 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 dark. Example of North Starts may include:

Function: Use simple user inputs to optimize. 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 experience: 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 encounters with personalization at their base, like the “algotorial” songs by Spotify quite as Discover Weekly.

Goals

Personalization can aid in accelerating designing with user intentions, as in any great UX design. Goals are the military and quantifiable metrics that may prove the entire program is effective. Start with your existing analytics and assessment system, as well as indicators you can benchmark against. In some cases, fresh targets may be ideal. The most important thing to keep in mind is that personalisation is not a desired outcome. It is a means to an end. Common targets include:

• Conversion
• Time spent on work
• Net promoter score ( NPS)
• pleasure of the client

Touchpoints

Touchpoints are where the personalisation happens. This will be one of your biggest areas of responsibility as a UX custom. The connections available to you will depend on how your personalization and associated technology features are instrumented, and should be rooted in improving a person’s experience at a certain point in the trip. Touchpoints can be multi-device ( mobile, in-store, website ), as well as more specific ( web banner, web pop-up, etc. ). Voici some illustrations:

Touchpoints at the channel level

• 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, context, 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 programmatically to specific user segments, 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

We’ve written a lot more in depth about each of these models elsewhere, so be sure to 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 consider 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 at the least. Here are some examples from the personalization pyramid:

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

Actionable Data

Every organization with any digital presence has data. It’s a matter of examining what user data you can ethically collect, its inherent reliability and value, and how you can use it ( sometimes referred to as “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 on the user experience front, 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. Voici some illustrations:

There is a progression of profiling when it comes to recognizing and making decisioning about different audiences and their signals. As user data volume and time and confidence increase, it varies more granularly to more precise constructs about ever-smaller cohorts of users.

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 data backbone and content repository. 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 the foundation for an inventory of sorts ( we provide blanks for you to tailor your own ), a set of potential levers and motivations for the kind of 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

Any effective personalization plan must take into account near, middle, and long-term objectives. 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, all personalization activities follow a common grammar, similar to how every sentence contains nouns and verbs. These cards attempt to map that territory.

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 get into a routine pattern, a brand-new concept or technology emerges to shake things up and completely alter our planet.

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.

website requirements were born.

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. With these improved server-side applications, the first era of web applications started with content-management systems (especially those used in blogs like Blogger, Grey Matter, Movable Type, and WordPress ) In the mid-2000s, AJAX opened doors for asynchronous interaction between the front end and back end. Pages now no longer needed to reload their pages ‘ content. 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 ( or both ) were necessary for complicated layouts. 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 front-end and back-end symbiosis continued to improve, leading to the development of the modern web application. 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 in our pockets at the same time. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

The development of social media and other centralized tools for people to connect and use resulted from this combination of potent mobile devices and potent development tools. 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 made 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 reached yet another significant turning point in recent 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.

Browser support for CSS, JavaScript, and other web components has increased, particularly with initiatives like Interop. New technologies gain support across the board in a fraction of the time that they used to. When I first learn about a new feature, I frequently discover that its coverage is already over 80 % when I check the browser support. 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.

We can now prototype almost any idea with just a few commands and a few lines of code. 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 once 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 ), users frequently have no choice but to use 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 choose not to replace them. 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 price of those user-friendly tools. They may make your job a little easier today, but how do they affect everything else? What is the cost to the users? To future developers? To 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. The same holds true for third-party frameworks, though. 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 it is your craft, which 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, and the techniques you learn in one day may be useful for guiding future experiments.

Play, experiment, and be weird! The ultimate experiment is this web we created. 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. In your own bizarre science lab, conduct absurd experiments. 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 experiment, play, and learn. 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 share it, improve it, re-use it, or create something new. Learn. Make. Share. Grow. Rinse and repeat. Everything will change whenever you believe you’ve mastered the web.

I’d like you to consider this a “yes … and” piece to complement Joe’s post. Instead of refuting everything he’s saying, I’m pointing out some areas where AI may make real, positive impacts on people with disabilities. To be clear, I’m not saying that there aren’t true threats or pressing problems with AI that need to be addressed; there are, and we’ve needed to address them, like, yesterday; instead, I want to take a moment to talk about what’s possible so that we can get there one day.

Other text

Joe’s article spends a lot of time examining how computer vision models can create other word. He raises a lot of legitimate points regarding 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 ( should probably have descriptions ) and those that are purely decorative ( couldn’t possibly need a description ) either. However, I still think there’s possible in this area.

As Joe points out, alt text publishing via human-in-the-loop should be a given. And if AI can intervene and provide a starting point for alt text, even if the quick reads,” What is this BS?” That’s not correct at all … Let me try to offer a starting point— I think that’s a gain.

If we can specifically teach a design to consider image usage in context, it might be able to help us more swiftly distinguish between images that are likely to be attractive and those that are more descriptive. That will help 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 was simply the name of the table and the type of visualization it was: Pie table comparing smartphone use to have phone use among US households making under$ 30, 000 annually. ( That would be a pretty bad alt text for a chart because it would frequently leave many unanswered questions about the data, but let’s just assume that that was the description in place. ) If your website knew that that picture was a pie graph ( because an ship model concluded this ), imagine a world where people could ask questions like these about the creative:

• Would more people use smartphones or other types of phones?
• How many more are there?
• Is there a group of people that don’t fall into either of these containers?
• How many people are that?

For a moment, the chance to learn more about graphics and data in this way could be revolutionary for people who are blind and low vision as well as for those with various types of color blindness, cognitive impairments, and other issues. Putting aside the challenges of large language model ( LLM) hallucinations, where a model only makes up plausible-sounding “facts,” 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 could ask it to switch colors for 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 call 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’s equally true that all computer models have the potential to foster conflict, prejudice, 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. Many of these are the result of a lack of diversity in the people who create and build them. There is real potential for algorithm development when these platforms are built with inclusive features in, though.

Take Mentra, for example. They serve as a network of people with disabilities. Based on more than 75 data points, they match job seekers with potential employers using an algorithm. 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 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 the development of algorithms, this can lower the likelihood that these algorithms will harm their communities. Diverse teams are crucial because of this.

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 follow a group of white men who are not white or aren’t white and who also discuss AI, it might be wise to follow those who are also disabled or who are not white. If you followed its advice, you might be able to understand what is happening in the AI field more fully and nuancedly. 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 have been aware of the voice-prescribing options from Microsoft, Acapela, or others, or you may have seen the VALL-E paper or Apple’s announcement for 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. We need to approach this tech responsibly because it has the potential to have a truly transformative impact, which is why it can also be used to create audio deepfakes.
• Voice recognition. 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 actively recruiting people with Parkinson’s and related conditions, and they intend to expand this to other conditions 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 or simplified versions, or even text that has been prepared for Bionic Reading.

The importance of diverse teams and data

Our differences must be acknowledged as important. 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. The data we use to train new models must be based on our differences, and those who provide it to us need to 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 you include information about disabilities that has been written by people with a variety of disabilities in the training data.

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 recommendations that are accessible after the jump? Train it on code that you know to be accessible.

I have no doubt that AI has the potential to harm people today, tomorrow, and long into the future. 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.

Thanks to Kartik Sawhney for assisting me with writing this article, Ashley Bischoff for her invaluable editorial assistance, and of course Joe Dolson for the prompt.