Software services

Design for Safety, An Excerpt

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

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

The process for inclusive safety

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

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

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

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

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

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

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

Step 1: Conduct research

Design research should include a broad analysis of how your tech might be weaponized for abuse as well as specific insights into the experiences of survivors and perpetrators of that type of abuse. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.

Broad research

Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. For example, a team building a smart home device would do well to understand the multitude of ways that existing smart home devices have been used as tools of abuse. If your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. Google Scholar is a useful tool for finding these studies.

Specific research: Survivors

When possible and appropriate, include direct research (surveys and interviews) with people who are experts in the forms of harm you have uncovered. Ideally, you’ll want to interview advocates working in the space of your research first so that you have a more solid understanding of the topic and are better equipped to not retraumatize survivors. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

Especially when interviewing survivors of any kind of trauma, it is important to pay people for their knowledge and lived experiences. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

Specific research: Abusers

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

Step 2: Create archetypes

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

The abuser archetype is someone who will look at the product as a tool to perform harm (Fig 5.2). They may be trying to harm someone they don’t know through surveillance or anonymous harassment, or they may be trying to control, monitor, abuse, or torment someone they know personally.

The survivor archetype is someone who is being abused with the product. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted (Fig 5.3)?

You may want to make multiple survivor archetypes to capture a range of different experiences. They may know that the abuse is happening but not be able to stop it, like when an abuser locks them out of IoT devices; or they know it’s happening but don’t know how, such as when a stalker keeps figuring out their location (Fig 5.4). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later on when you design solutions to help your survivor archetypes achieve their goals of preventing and ending abuse.

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Instead of focusing on the demographic information we often see in personas, focus on their goals. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll brainstorm how to prevent the abuser’s goals and assist the survivor’s goals.

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

Step 3: Brainstorm problems

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

A Content Model Is Not a Design System

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

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

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

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

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

Two essential principles for an effective content model

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

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

Semantic content models

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

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

A semantic content model has several benefits:

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

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

Content models that connect

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

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

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

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

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

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

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

Conclusion

In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic (with type and attribute names that reflected the meaning of the content) and that it kept content together that belonged together (instead of fragmenting it). Th

How to Sell UX Research with Two Simple Questions

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

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

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

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

A gauntlet between research and screen design

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

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

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

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

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

Getting in the same curiosity-boat

What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.

Mark Twain

The first two steps of the ORCA process—Object Discovery and Relationship Discovery—shine a spotlight on the dark, dusty corners of your team’s misalignments and any inherent complexity that’s been swept under the rug. It begins to expose what this classic comic so beautifully illustrates:

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

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

But how we do this is important. However much we might want to, we can’t just tell everyone, “YOU ARE WRONG!” Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders take ownership of assumptions and gaps in understanding, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Say your users are doctors. And you have no idea how doctors use the system you are tasked with redesigning.

You might try to sell research by honestly saying: “We need to understand doctors better! What are their pain points? How do they use the current app?” But here’s the problem with that. Those questions are vague, and the answers to them don’t feel acutely actionable.

Instead, you want your stakeholders themselves to ask super-specific questions. This is more like the kind of conversation you need to facilitate. Let’s listen in:

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

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

“Is it a ‘primary doctor’ or just a ‘primary caregiver’… Can’t that role be a nurse practitioner?”

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

“So are caregivers in scope for this redesign?”

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

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

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

If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And this will, hands down, result in a more confusing, more complex, and less intuitive software product.

The two questions

But how do we get to these kinds of meaty questions diplomatically, efficiently, collaboratively, and reliably

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

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

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

Prep work: Noun foraging

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

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

Here are just a few great noun foraging sources:

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

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

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

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

  1. Structure
  2. Instances
  3. Purpose

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

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

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

Purpose: why is thi

Breaking Out of the Box

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

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

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

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

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

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

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

Here’s what a typical desktop PWA app looks like:

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

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

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

About the title bar and window controls

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

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

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

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

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

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

The whole point of this feature is to allow you to make use of this space with your own content while providing a way to account for the window control buttons. And it enables you to offer this modified experience on a range of platforms while not adversely affecting the experience on browsers or devices that don’t support Window Controls Overlay. After all, PWAs are all about progressive enhancement, so this feature is a chance to enhance your app to use this extra space when it’s available.

Let’s use the feature

For the rest of this article, we’ll be working on a demo app to learn more about using the feature.

The demo app is called 1DIV. It’s a simple CSS playground where users can create designs using CSS and a single HTML element.

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

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

Since I’ve added a simple web manifest and service worker, we can install the app as a PWA on desktop. Here is what it looks like on macOS:

And on Windows:

Our app is looking good, but the white title bar in the first page is wasted space. In the second page, it would be really nice if the design area went all the way to the top of the app window.

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

Enabling Window Controls Overlay

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

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

Using Window Controls Overlay

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

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

On the surface, the feature is really simple to use. This manifest change is the only thing we need to make the title bar disappear and turn the window controls into an overlay.

However, to provide a great experience for all users regardless of what device or browser they use, and to make the most of the title bar area in our design, we’ll need a bit of CSS and JavaScript code.

Here is what the app looks like now:

The title bar is gone, which is what w

Designers, (Re)define Success First

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

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

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

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

Influence the system

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

What can we do to change this?

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

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

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

Redefine success

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

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

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

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

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

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

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

Pursue well-being, equity, and sustainability

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

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

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

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

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

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

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

In short, ethical design (to us) meant achieving wellbeing for each user and an equitable value distribution within society through a design that can be sustained by our living planet. When we introduced these objectives in the company, for many collea

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