Time to Listen
Chapter 1 – What’s Wrong with Average
Average solutions aren’t just average as in “meh.” They often cause harm to the people who weren’t considered in the design. In the design field, there is an oft-repeated story about how a solution designed to support the average person actually killed people. In case you haven’t read the story, I’ll recount it here. In the late 1940s, the United States Air Force had a problem. A new generation of Air Force jets were flying dramatically faster. The original cockpit had been designed in 1926. The jet manufacturers had taken a series of measurements of 1926 pilots’ bodies at that time. They had averaged out all their measurements and designed a helmet to fit the average measured head, a seat to fit the average rear end, and cockpit distances to fit the average arm length. They designed for ten key dimensions, to fit the average (1926 male pilot’s) body. Unfortunately, by the 1940s, the cockpit design was absolutely not working.
Pilots were crashing, again and again.
The Air Force needed its military suppliers to redesign the cockpit so that the pilots would survive. So, in 1950 they put a newly graduated twenty-three-year-old, Lt. Gilbert S. Daniels, on the task. And his first idea was to check the math, which meant measuring 4,000 pilots in the Wright Air Force Base.
After the measurements were taken, Lt. Daniels sat down to look at the data. Of the thousands of pilots measured, literally zero were average in all ten dimensions. Even more interestingly, only 3.5 percent would be average-sized in three dimensions. “It can be seen that the ‘average man’ is a misleading and illusory concept as a basis for design criteria, and is particularly so when more than one dimension is being considered,” Lt. Daniels said.1 (He must have had a good mentor to be able to speak so decisively in his conclusions.)
As a result of Lt. Daniels’ work, the Air Force asked the jet manufacturers to change their design. Those engineers figured out how to make fighter jet helmets, cockpit seats, and floor pedals adjustable. The pilots were more able to handle the planes while under G forces, pilot performance soared, and many fewer people died.2 Physical product manufacturers responded, changing many things in the decades since, understanding that one size really doesn’t fit all in many circumstances. The innovation also led directly to the adjustable seats we have in modern cars, adjustable medical equipment, adjustable desks, and so on.
The Air Force cockpit story is the story of an inflection point, a moment that changed everything. Or not. There are limits to how adjustable any particular design is. Every manufacturer puts limits on how much they are willing to spend on setting up factory production. There are thousands of people who still have to make do with one extreme or the other of the adjustment. Plenty of people still add cushions to their desk chairs. We may not fully design to the average in every physical product anymore, but we certainly don’t design for everyone.
Access for People with Disabilities
After the end of the second World War, many soldiers came back to their countries with mobility-related injuries, needing canes and wheelchairs to get around. The battles, weapons, and chemicals had blasted their hearing and sight. Former soldiers with these kinds of disabilities, in fact, joined society in such vocal numbers in the late 1940s and 1950s that accessibility issues finally began reaching the public awareness.3 The world at that time was not built for wheelchair users; deaf and blind people were not supported. Most buildings—even public buildings— relied on stairs or had other architectural issues that prevented people with disabilities from accessing them without assistance.
Over time, activists with disabilities fought worldwide to create environments that could include wheelchair users. The American experience illustrates the trend. In the 1960s, American protestors took to the streets, smashing curbs to create their own accessible ramps. In the 1970s, founders of the Independent LivingMovement established a wheelchair route through the University of California campus, even “covertly laying asphalt in the middle of the night.”4 By 1973, the first American law was passed banning discrimination on the basis of disability. Sit ins and protests continued.
Meanwhile, individuals with hearing and vision impairments were making strides toward better access to technology. The hearing impaired gained greater access in the U.S. in 1972, when Julia Child’s “The French Chef” was broadcast with captions, and by 1982, ABC’s World News Tonight was broadcast with captions in real-time.5 People with visual impairments were able to access computers more easily with the development of the first Braille translator in the early 1960s6 and the first refreshable Braille display in 1975.7As a result of the tireless efforts of activists and lawmakers with disabilities, laws about providing access for people with disabilities slowly passed all over the world. Japan passed their law in 1970, and it was revised and expanded several times until it became the “Fundamental Law for Disabled Persons,” mandating social support, welfare, healthcare, community services, and work opportunities for people with disabilities.8 In 2007 to 2008 over 100 countries signed the UN treaty “Convention on the Rights of Persons with Disabilities”.9 Everywhere, Braille began appearing on public keypads and elevator controls, in airplanes, and on building signage.
This decades-long inflection point changed everything. A little bit. There are still online resources, buildings, and transit systems without accommodations for people with disabilities. Adjustment remains an ongoing struggle.
Designing for Access, Not Average
Today, there are still organizations that don’t spend much budget or attention on designing support for people with disabilities into their products. Even technologists think that machine-driven support such as automated video captions “work well enough.” They don’t invest in improving the experience, remaining oblivious to how frustrating automated captions can be for the people who have no choice but to rely on them.
Even when they do design for support, they approach everyone with a disability with the same average solution. Svetlana Kouznetsova, an independent consultant and accessibility trailblazer, has spent her career educating professionals about accessible on-screen design. She explains that all deaf people are not alike, not all blind people have the same thinking style, and you can’t treat a large group as if everyone in it has all the same needs, experiences, and desires. Yet companies do just that.
The Average Does Harm
Designing to an average user was lethal in aviation. Similarly, designing to an average user in other contexts also hurts people. Without accommodations, the built environment does tremendous harm to wheelchair users, the blind, sight impaired, deaf, and hard of hearing. Since 2016, when books, articles, and talks all over the design community began to tell the adjustable cockpit story, everyone has been repeating “We can’t design for the average.” It’s been a refrain in education, healthcare, and government circles as well. The digital and service industry, unrestricted by the same limitations of physical space and materials, can incorporate adjustability and customization so much more easily than the designers of cockpit seats or the built environment.
Why, then, does solution design still revolve around the average, especially in the technology world where there seems to be funding and inherent extensibility?
What drives the problem is the organization’s mindset. Traditionally, organizations target single solutions to the largest part of the market, not attaching importance to the fact that those people don’t all think the same. In business, government, and even the non-profit sector, organizations define the people they serve by addressing an avatar, a citizen,a job title, or a set of tasks. Organizations act as if there are only enough resources for one approach in the digital world, as if they were building physical things. So like the early air force planes, they build for an average user.
This problem still exists because organizations don’t measure it. Teams are reluctant to try to measure what seems to be “personality,” which is understandable. Universal measurement of personality or intelligence have been debunked. Teams think research at scale is the only way to get reliable knowledge, hence the proliferation of quantitative data and dashboards about the solution. We need a reliable way to truly understand people, not at scale, but as individuals with agency. What teams don’t all know is that qualitative data represents scale, even if it is not conducted at scale. Why? Because qualitative data is about patterns, and patterns extend across populations that are well-defined.
This book is the first step in being able to measure what solutions fit which people, much like what Lt. Daniels did for the military. The next step after this book is to create a mental model skyline, from patterns that emerge from listening to understand people’s cognition, align your current solutions beneath the towers in the skyline, and then evaluate the outcomes the solutions provide to a set of thinking styles. These evaluations are the measurements that combine dimensions, and like Lt. Daniels found, they reveal gaps that were covered by the illusion that “average” can represent most everyone.
Another thing driving the problem is the business perception that smaller segments of the market are “edge cases” not worth supporting. “There’s not enough profit there to justify spending to support those people,” they say. Often these segments are defined by demographics, which is why it has been such a fight to get organizations to take accessibility seriously. Or the segments are marked by philosophies that defeat a portion of the profit to be had, such as people who wish to keep their data private. In this instance, governments have made regulations to tell companies they must support that group of people. The European General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) try to enforce privacy for citizens and charge penalties for violations. Even so, many organizations don’t lift a finger until, or even when, they are caught.
“Edge cases” is a phrase that applies to a process or a procedure. It is not meant to describe people at all. An “edge case” is when a process changes to account for a particular context. For example, when there is snow or sleet at an airport, the procedure for getting a plane ready for takeoff changes. Process teams across industries do research, make lists, and plan for as many edge cases as they can.
If you look from the passengers’ perspective, it’s less about process than it is about approach. There are no edge case approaches. When taking a flight, passengers have a lot that goes through their minds. They are experiencing a lot of emotions and doing a lot of decision-making. Each person applies a variety of solutions (mental, social, manual, mechanical, and digital) that help them pursue their goal: get to a place that is distant. But they incorporate some different approaches.
In an eight-part study with 100 participant listening sessions that I led for an airline, there were 36 mental spaces people’s minds shuttled through, from “decide whether I need to take a trip” and “explore what it takes to get to that destination” to “take care of myself,” “pass the time,” and “act in a polite manner.” The studies revealed rich patterns of cognition the airline could easily innovate for. Cognition doesn’t shift fast, so the patterns have been valid for more than a decade.
The whole team deeply understood the many perspectives of passengers. I still do–I spent 996 hours with their stories over the two years that we built the mental model skyline. Dwelling with the knowledge gave us superpowers. Making that kind of time to learn, having patience not to jump to conclusions, is an act of resistance in this age. The VP made this space for us because she deeply believed in creating value for passengers. Because of the lasting nature people’s cognition, the airline could continue to launch ideas from the mental model skyline, producing a huge return on investment. However, the airline became focused only on reducing costs, and the VP left.
Another difference from the study was guiding innovation by thinking style. In the past, the airline marketing team had done segmentation of passengers along demographic lines of ticket price, destination, and loyalty program activity. People who flew for business were their most lucrative segment, followed by a couple of segments about people earning points in the loyalty program. There were a couple of segments based on ticket price, including the low end and the high end. And there was a segment of people flying to other countries. None of these predicted people’s approaches while they “get to a place that is distant.”
But the thinking styles that emerged from the eight-part study did predict people’s approaches. The four main thinking styles that emerged across all 36 mental spaces were:
- Maintain a peaceful bubble around me, to keep the chaos of air travel out (or to keep their own chaos, such as an excited toddler, from affecting others)
- Focus on doing things correctly, to make the process smooth
- Use my time wisely, accomplish some tasks/goals I set for myself
- Make a positive experience, including for other passengers and flight staff
People switch between these thinking styles from trip to trip, depending on who is with them and what’s happening.10 People who are deaf, for example, are a part of each of the thinking styles. People who are neurodiverse are a part of each of the thinking styles. The demographics are sprinkled throughout the thinking styles.
Airlines can measure themselves by how well they are supporting each thinking style, in each part of the passengers’ approach. Airlines will see the gaps where they are failing to support people’s thinking and decision-making. In this way, when you look from the passenger perspective, there is a lot of new opportunity for the airline.
This new opportunity is exciting. All digital experiences and lots of services are driven by a “back end” of software, databases, networks, and humans—a back-end that can support several different front-end experiences. Organizations are not actually in the position of having to multiply costs to build multiple back-ends. physical products—if they will design for that ability. Granted, there is thirty-year- old software architecture still in service, which breaks at the slightest touch. There are debates in the boardroom whether to pitch the old back-end into the bit-bucket and start fresh. There are cost tradeoffs, and the balance is increasingly tipped toward starting fresh. A well de- signed back-end can interface with several different user experiences for a comparatively nominal extra cost. A front-end that is aware of the organization’s thinking styles can recognize thinking-style behavior in users and guide them to a solution designed for them. The design will then lead to more people experiencing support instead of harm, and more people reaching for that experience because they feel seen., knowing that it was designed with them in mind.
No one has the time or money to make 1,000,000,000 custom-tailored user experiences for each individual. Users also do not have time and motivation to customize solutions to their own needs. But you can go from designing one average experience to two or three excellent experiences that solve for the approaches of people with different thinking styles.With a little extra work, you can support people powerfully and break the mindset of the average.
It’s that or fall back into the habit of creating harm.
The Real Harms We Do
The news is full of stories about software that is failing in ways that harm people. The harm may be mild or systemic, accidental or deliberate in practice, but it is all harm. You have likely experienced this harm yourself.
The mildest harm looks like the simple frustration of someone being forced to repeat their actions, waste time dismissing ads, or spend a moment wondering if they’ve made the right decision with every gaslighting “reminder” from an app. Another user might find that their needs are simply neglected, such as when the original iPhone health app failed to include menstrual cycle tracking, a major component of health for a large portion of the globe. This harm is real, but it gets far worse.
More serious examples of harm are making people feel unwelcome, causing them to fall victim to scammers, or allowing them to be harassed by trolls because of ineffective online protections. It has even led to people being jailed because of biased facial recognition software. The most severe harm can mean injury or death—and it can happen from something as apparently minor as momentarily taking your eyes off the road to understand details on a navigation screen. Few of these harms can be completely mended after they occur, and some cause serious lasting injury. All of them can be prevented if enough attention is paid when the experience is designed.
Harm is not distributed equally; the same solution can cause mild harm to some users and serious harm to others. In an interview for The Markup’s Hello World newsletter, Professor Brooke Erin Duffy talked about how the constantly changing nature of algorithms affects content producers in the gig economy. Duffy said, “If you use Instagram, you may recall that a few years ago they changed the algorithm … Instagram replaced its chronological feed with an algorithmically curated one. It was frustrating for [regular] users, but our livelihood are not dependent on it. For media and creative workers, their entire job is structured by the command to be visible—and the algorithm comes in and suddenly renders their content invisible.”
When the algorithm changes, content producers have to spend time developing theories about how it works so they can get back to earning what they were earning before. They are never told the explicit rules through which they can succeed. Similarly, when the behavior of other kinds of software (such as Gmail, or Word) changes, there is no person to talk to about how to adjust to or combat the change. The team designing the software is not accountable to users in this way.
There is also systemic harm baked into most software, just by the nature of how it has been made. Systemic harm is when you don’t realize that bias shaped a strategic decision, because it’s part of society. You accept a “way of doing things” as given because that is what you grew up with.
It doesn’t seem hurtful until suddenly you realize the history of where a social norm came from, and the very real stories of pain and death in that history. This is the water everyone is swimming in. Each society has this kind of history, this kind of water. You and I didn’t make the water, but if we continue to make decisions without realizing the water is there, then we are perpetuating the harm. This is the way we are culpable.
It’s hard to know the water is there. Fortunately, many voices are helping us discover its presence.
In Cathy O’Neil’s book Weapons of Math Destruction, she gives many examples of systemic bias directly coded into algorithms. Algorithms look at the data associated with a person and make a decision: richer people are seen as more credit-worthy, have more stable employment and housing, and therefore due to a multitude of factors their car insurance costs less. The result is every bit as pernicious as if the software were designed intentionally to make life harder for people who are already ignored or repressed by the system.
Facial recognition technology often fails to accurately identify people with dark skin or female features, leading directly to systemic harm. Joy Buolamwini’s definitive work and documentary11 on the subject has resulted in several cities disconnecting facial recognition from their CCTV networks—and this is a good thing.Already three people in the United States have been falsely arrested based solely on faulty software identifications. Lawsuits are pending.12
You might say, “But my product isn’t anything like these!” Even if your product is aimed at a professional process, like data warehousing, content management, hiring and supporting employees, or maintaining enterprise software, you are harming people with different philosophies, different speeds of working, who have ADD/ADHD,13 who had a bad experience that shaped their own approach, who had mentors who laid different foundations of thinking.
How do you as a researcher, designer, or product manager help avoid this cascade of harm? Spread the word that the experiences and thinking of the people with your organization is not universal.
Organizations cannot continue to shape solutions according to an average user, because there is no such perspective. There is no average thinking and decision-making style. By considering and planning to support everyone affected by your solutions, you can act to prevent harm.14I
Why We Listen
It’s not enough merely to have solutions that don’t harm. That is only the foundation, the minimum, the basic requirement. Most designers, researchers, and product designers want more. You want to be proud of the solutions you make. You want to support people in ways that match the way they think. You want to see the people using your solutions feel respected and enabled.
Yet it’s common to feel stuck, serving users exactly the way you served them seven years ago. You may feel constrained at work, hands tied. You may have limited resources and decision-making power. Your organization rolls out new features and you may have little faith that those features will make a difference. Your team adds features for personas, but the personas are actually unconscious copies of one “average user” archetype. Users leave even after the organization gives them what the data models imply they want.
How can you shift this ineffective cycle? How can you build relationships with users, deliver solutions that recognize their different approaches, and truly help them succeed?
Changing the cycle requires making space to listen, and it requires listening to more than just the answers to a preset list of solution-related questions. You must listen deeply so that your organization can support peoples’ real approaches.
Listening Sessions
This is a book about listening, but not just any listening. Here I am talking about listening deeply, listening to understand another perspective and challenge your assumptions. Specifically, this book will talk about this kind of listening in the context of a listening session.
Listening sessions put a person and that person’s goal at the center. This is by design. When an organization puts resources toward “user research,” “usability,” and “big data,” they are only covering their own perspective. They are looking at people through the lens of their products and services, and distorting people’s reality to suit the organization’s perspective.
Communicating and listening deeply with people in listening sessions, by contrast, focuses on the person’s goal. Any useful solution must give the person a valuable outcome on that goal. Deeply understanding the person’s approach to the goal purpose, therefore, allows you to see additional ways of helping people within the framework of your solutions. Most importantly, conducting listening sessions enables you to see other people accurately, without assumptions or bias. And in doing this, you will be able to see opportunities to connect the strategic direction of your solutions with the mission of supporting more people in radically better ways.
If you want to build solutions you are proud of, things that help people and do not harm them, you cannot do it without listening deeply. It is time to be intentional about confronting your assumptions, and about listening to people to get beyond those assumptions.
Feeling Understood
It is a rare moment when any of us feels truly understood. Sociologist Allison Pugh says society is not so much in a “crisis of loneliness” as in a “crisis of depersonalization.”15 She means that people are not feeling seen. The more time people spend interacting with apps (e.g. reporting an accident on an insurance claim form) instead of with other people gives them a feeling of disconnection and isolation. So, despite the need for scale and endless profit, organizations need to reintroduce the human touch. People will turn to the more humanized solutions where they feel seen and understood. People will turn away from the relentlessly sterile and extractive solutions which make them feel manipulated.
Yet, even when we connect with another person, most interactions with others happen mostly on the surface. If you make a statement like, “Everyone on this project feels overwhelmed,” it is often met with comparisons or solutions. “It’s not as bad as x,” or “Well, if you scheduled better and spent less time getting coffee …” Immediately offered solutions tend to make people feel rejected and managed.
What is it like to make someone feel understood? Avoid offering the comparisons and solutions. Give someone attention; ask questions that help you understand their perspective: “At a moment when you were really feeling overwhelmed, what went through your mind?” and “What happened internally when you realized another person on the team was feeling overwhelmed?”
These are how you open a deeper conversation and help someone un- pack what is going on internally for them. These kinds of questions help someone explain their interior cognition and go beyond opinions, preferences, explanations or perceptions.
Recognizing how much of our communication skims across the surface, speeding along too fast to build understanding, is revelatory. It is very hard to slow down enough to ask questions that reach for depth and wait for someone to explain their thinking—without interrupting or pulling them into your own framework. It takes effort, and skill. And yet it’s worth it. Paying rapt attention to another person’s words is incredibly rich for both people, and for the organization.
Deep communication is powerful. It builds relationships and connects people, even across the gulfs of distance and difference. It allows for new perspectives and builds new understanding that is impossible to get any other way. And the good news is that listening deeply is also a skill, a skill nearly everyone can improve.
In this book, I’ll teach you listening principles that will be useful in nearly every context where you interact with people. You can use them with your peers, your bosses, and your stakeholders. You can use them in your personal life, with the people close to you. Everyone wants to feel understood, in work and outside of work.
However, it’s important that you never lose sight of the real reason for learning these methods: to understand deeply the people who will use your products. These people are not averages. They are not flat personas defined only by demographics. They are people with lived experiences. Understanding them in both their differences and their similarities is how you create the next-level products you want to make.
You cannot design outside the average if you do not understand how your perspective shapes your solutions,and how other perspectives may offer other, better approaches for you to use. You cannot make great products until you can lay your assumptions aside.
Actionable Data
I recently heard from a man whose music streaming organization wanted to know why its customers were leaving. He went through all the data he had and made a decent model of what was happening. He told the executives that customers left after about two and a half years. The executives said, “Okay, but what type of people are leaving exactly?”
The man looked at them, surprised that the executives wondered what type instead of why. After further study, he came back to say, “It’s young people. The young adults are leaving.”
That demographic answer sounds nice, and it lulls colleagues into thinking they’ve isolated the issue and can easily come up with a solution. But they are probably solving the wrong problem. Instead, what if they’d set up a study to listen to people who had left? The company would have discovered valuable information about why attrition had happened. “Oh, you know, I wondered why I couldn’t log in.” “I lost that phone and couldn’t find the password, so I’m just using my flat mate’s account.” “I’m now into vinyl, so I turned it off.” Or perhaps the person faced a month when bill collectors confronted them, and in an effort to regain control of their life, canceled all the subscription accounts that had built up over the years.
All of those conversations would have led to deeper understanding of the user’s approaches, of the context they are in, of the lack of priority the solution had in their lives—real, actionable data. The company could then use the patterns that show up to help prioritize where to focus first, and to bring up new, different questions. They could see who they were harming, and who they were supporting. Choosing a priority to pursue first, they could roll out a smoother password recovery system, then roll out a more affordable service tier, and keep following the steps pointed out by the data they gathered from real people’s thinking. No more choosing the ideas of the highest-paid person in the room, spending resources to make that idea, and then launching it at the “market” to see what further issues the users discover.
This is just one of many cases where demographics didn’t illuminate the problem. Research based on deep listening would.
The Shift Starts Now
This book will teach you how to start creating better solutions by understanding the way people approach a goal. That may, eventually, lead to those people becoming your users and customers.
Note that this is the last time that I will use the words “users” and “customers” in this book. Throughout the entire rest of the book, I will use the word “people” instead.
I do this because a “user” (or any other similar noun, like “customer,” “member,” “merchant,” “passenger,” etc.) is someone with a relationship or potential relationship to your organization. It is how you refer to people when your mind is in the solution space: thinking about your existing solution, fixes to the solution, ideas you can try out, and thoughts about how to solve the problem. This wording pulls attention away from a person’s goal. People exist apart from your organization, within their own framework, and our language throughout this process must reflect that.
People exist in their own context.They are centered in their own worlds. Your product, if it appears in their world at all, is one of the tools they are using to make progress on their own goal.
Listening to people and understanding them requires putting them back at the center. It allows for you to see opportunities and insights you would never have seen any other way. This is a tool you can use to contend with the way things have always been done at your organization—to help your organization realize that it has been seeing itself as “the expert” rather than as a student of the people it serves.
In this book you will learn how to stop being the expert, how to stop being the colonial explorer intent on“discovery” and “utilization.” Instead, you’ll learn to draw on your human connectedness. You’ll embody respect and curiosity and support. By doing so, you can get beyond the broken assumptions and the “average user” fallacy, to create things that truly serve people.
Now is the time for another inflection point in history—to remove the “average user” mindset from solutions and organizations, and start to recognize the gaps and measure outcomes for a set of thinking styles. Now is the time to listen.
Endnotes
1 United States Air Force, The “Average Man”? by Gilbert S. Daniels, Technical Note WCRD 53-7, Wright-Patterson Air Force Base, Ohio: Wright Air Development Center, Air Research and Development Command, 1952, https://apps.dtic.mil/sti/pdfs/ AD0010203.pdf.
2 Todd Rose, “When U.S. Air Force Discovered the Flaw of Averages,” Toronto Star, January 16, 2016, https://www.thestar.com/news/insight/2016/01/16/when-us-air-force- discovered-the-flaw-of-averages.html.
3 “The History of the Wheelchair Ramps,” MedPlus, October 29, 2019, https://www. medplushealth.ca/blog/the-history-of-the-wheelchair-ramps/.
4 Emily Nonko, “How Wheelchair Accessibility Ramped Up,” The Atlantic, June 22, 2017, https://www.theatlantic.com/technology/archive/2017/06/ramps-disability- activism/531273/.
5 Olivia B. Waxman, “How Deaf Advocates Won the Battle for Closed Captioning,” Time, March 16, 2020, https://time.com/5797491/closed-captioning-captions-history/.
6 Joe Sullivan and David Holladay, “Early History of Braille Translators and Embossers,” Duxbury Systems, August 12, 2021, https://www.duxburysystems.com/bthist.asp.
7 “History,” HelpTech, accessed November 22, 2021, https://helptech.de/en/info/help-tech/ history.
8 The 38 Selected Japanese Laws Related to Persons with Disabilities, (Tokyo: Japanese Society for Rehabilitation of Persons with Disabilities,2004), 2-4, https://www.dinf.ne.jp/ doc/english/law/japan/selected38/index.html.
9 “Convention on the Rights of Persons with Disabilities,” opened for signature March 30, 2007, Treaty Series: Treaties and InternationalAgreements Registered or Filed and Re- corded with the Secretariat of the United Nations, vol. 2515, no. 44910 (2008): 3, https:// treaties.un.org/doc/Publication/UNTS/Volume%202515/v2515.pdf.
10 Thinking styles synthesized from a series of eight studies that Indi lead from 2011-2013.
11 Coded Bias, directed by Shalini Kantayya (2020; Brooklyn, NY: 7th Empire Media), https://www.netflix.com/title/81328723.
12 The work that Joy, Cathy, and the Algorithmic Justice League are doing to stop the use of facial recognition software is detailed in the documentary Coded Bias.
13 Conversations with actual people with attention deficit diagnoses show that different parts of the country and/or different age groups of people prefer ADD or ADHD for the general term; there does not seem to be a consensus, so we use both here.
14 There are many books that provide examples of the harm. However, I’m writing this series because there are no books I’m aware of that offer how to undo and avoid the harm in the digital world. There is the method “design thinking” and the method JTBD that purport to design better, but they don’t pay any explicit attention to harm or to how real people use products. That attention has defaulted, so far, to the designers and researchers themselves, who may or may not understand the perspective of the people they hope to support.15 Allison Pugh, The Last Human Job: The Work of Connecting in a Disconnected World, published June 4, 2024; https://www.allisonpugh.com/the-last-human-job (interview: https://youtu.be/-U6JIpPDMOU?si=-qxm3HOOclR3D-At )