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A List Apart: The Full Feed
Articles for people who make web sites.
  • Connecting the Dots

    Two plans: one for design, one for culture.

    What I’ve found is that the DNA between both dynamics must be inextricable from one another. Creating with compassion in an environment fueled by compassion means we never lose sight of what it’s all about: people. Beyond functioning in this manner because “it’s the right thing to do,” quality of work, loyalty internally (team) and externally (users), and product innovation are all benefits to reap.

    Earlier we talked through the concept of “simplicity” and its application to creation and environment. Now, let’s revisit a few other examples of healthy benchmarks from a creative culture as we’ve discussed in this book:

    • Slowing down / pausing with intent
    • Everyone has a seat at the table
    • The New Day One

    In taking a focused look at these facets, their correlation to HCD is readily apparent:

    Culture: Slowing down / pausing with intent
    Design: Discovery / observation

    The Swedish concept of fika transcends a mere “coffee break.” It’s about slowing down, the act of pausing during a typical day and making time to have a dialogue with someone (though a good cup of coffee is a vital part). I ensure this time is not only a known quantity within my team’s creative culture, but that it’s protected and actively utilized.

    Instead of getting a product manager’s Powerpoint wireframe in your inbox with a request to “make it look nice” or a client’s request to crank out a design for their approval by EOD, we must slow down to understand the people who will be interacting with our design (and the design’s potential impact on others, the environment and community in which it will be used, and so on). Rushing to get something done to tick an account manager’s client-appeasement box at the expense of the human experience is to sacrifice empathy, quality, and any prospect of innovation.

    Culture: Everyone has a seat at the table
    Design: Inclusion

    As the very definition of cultural transparency, Nick Sarillo’s pizza parlors tack their full financial statements to a wall, daily, for all employees to see. Everyone’s hourly wage is listed on a nearby whiteboard, with the means to make more money articulated in tandem (training in more areas of business = increased hourly wage). Many managers have worked their way up in this manner, and offer training to other employees who wish to advance by taking on more responsibility. This is about collaboration yielding success to both the employee and the business, the sharing of information, and access for all; key dynamics of an inclusive culture.

    Inclusion in the design process enables us, as creators, to recognize our own personal biases. By identifying the exclusion in our work, we humbly set aside our assumptions; connecting with people from diverse communities, building empathy, will expand our product’s reach (access). Via engaging humans throughout our design process, listening to them, and usability testing iteratively, objective solutions that yield innovation follow suit.

    Culture: The New Day One
    Design: Ethnography

    The New Day One concept evolves an employee’s first day from formulaic and sterile into directly personal and custom. Via the “Inspiration” portion of the day and venturing away from the office, we gain insight into a new team member as an individual that transcends what folio work can yield. What physical aspects of their selected location have impacted who they are? How did it inspire their way of creating, or approaching problems? Understanding the impact of spatial dynamics on an individual is vital toward an individualistic, yet ultimately holistic, view.

    Ethnographic research provides an environmental context to human interaction that a video-conference interview could never yield. Through direct observation, ethnography is the qualitative study of human beings in their native environment. Is the individual sitting in a high-traffic area in an office, causing frequent distraction from their work? Are they a field worker primarily utilizing a mobile device in direct sunlight, yielding paramountcolor contrast needs? By making research truly human, we gain an understanding of how those we observe see the world and how they ultimately engage with it.

    For the Greater Good

    Greater Good Studio (GGS) is a social impact-focused human- centered design firm co-founded by Sara Cantor Aye and George Aye. Their business is located within the Logan Share, a co- working space they also founded in Chicago’s Logan Square neighborhood.

    I reached out to the Studio to ask if I could stop by their space and observe a “morning in the life” view of their process: culture and design, organically, as both unfolded. Without hesitation, Sara (a former Northwestern University instructor) extended me an offer to join the team for observation. After signing a non- disclosure agreement, we agreed on a date for my visit.

    When I arrived on a Monday morning, George (formerly of IDEO) greeted me with a cup of coffee and walked me up the stairs into the naturally well-lit Logan Share space. I noticed the open seating in the co-working section was already nearly full, as he gave me a tour of the “configuration by human need and intent”-based layout and active-project areas. On long single sheets of cardboard suspended by custom-built fasteners, entire lifecycles of project- centric human-centered design artifacts were on display. Once a project is deployed, George explained, the cardboard is detached and saved for forthcoming iteration, with fresh sheets re-fastened to form the partitions of a new project space thereafter.

    The six core steps of the Studio’s HCD process manifest themselves in the following way:

    1. Framing
      Defining questions to answer and people to engage
    2. Research
      Learning from people about their needs and values
    3. Synthesis
      Finding patterns of behavior and areas of opportunity
    4. Concepting
      Creating a high volume of new ideas
    5. Prototyping
      Making tangible mock-ups and gathering feedback
    6. Piloting
      Testing solutions in real time with real people

    As a team, GGS functions via a working method called ROWE (Results Only Work Environment), a concept leveraged from Cali Ressler and Jody Thompson’s book Why Work Sucks and How to Fix It: The Results-Only Revolution. Taken from an article on the Studio’s blog, they describe the practice within GGS like this:

    “The basic principle behind ROWE is that staff doesn’t need to be supervised, when given the tools, clear expectations, and deadlines people will not only do their work, but do it better than if they were trying to fit into a mold. Within GGS, this practice is exercised by very diligent calendar management, clear deadlines, expectations on deliverables, and Cookie Rewards (little treats we give each other if we have to move something on the calendar).”

    Once a month the entire team pauses for a five-hour, non-client project block of time called “internal day.” This time is reserved for studio-centric things: team members sharing learnings from conferences they’ve attended, how to improve internal practices, past project debriefs, etc. It’s the act of pausing with intent, in full effect.

    Sara arrived a few minutes into my tour of the space, and the GGS team’s “BD charrette” was the first employee gathering (remote and in-person) of the morning. “BD” stands for “business development,” and in a cozy seating area, everyone had a seat at the table in all senses of the phrase. Sara and George ran through the status of a current request for proposal, then each team member had the opportunity to voice their opinion about whether the RFP should be pursued based on how it aligned with GGS’s (and their employees’) personal, values. Everyone was heard; every voice was respected.

    The dialogue eventually shifted to another potential new client, this time with GGS at the presentation stage. Again, everyone at the table gave their feedback on Sara and George’s presentation plan of attack and, again, every team member’s voice carried equal value and weight. The studio-wide inclusion in the business owners’ decision making was genuine, effortless, and natural.

    Forty-five minutes later, the group made a physical transition to a few nearby couches; less than a three-foot walk, as I eyed it. I inquired about the very minor spatial change for this next leg of the meeting and was told, “There’s a difference in purpose, so we transition to a different space.” Each member of the team then took their turn describing their weekend in three words:

    “Sunshine, beach, baking.”

    I got my turn as well. Changing the energy on those couches, from new business to being focused on the individual, made for a palpable climate change. In a few words everyone had a sense of what their teammates got up to over the weekend, eliciting smiles and planting the seeds for future dialogues throughout the pauses- with-intent over the rest of the day.

    Next: “validations.” In this final portion of the meeting (pre- project status), anyone who wanted to articulate their appreciation for a team member over the previous week did so. One person recognized their co-worker for their selfless collaboration, taking time from their own project work to help theirs get client-ready on time. Similar-but-unique “thanks” emerged from varied people; no one was required to speak up, but everyone did.

    After project updates I sat with Sara for a one-on-one to chat over coffee. I asked her about the synergies between their HCD process and how she interacts with her team in the office:

    “I think where it’s actually become more intentional and obvious has been with our staff who are not trained designers. Operations folks, or our community manager, etc. I’ve had to say, ‘I want you to be a designer about this’ (whatever ‘this’ is). ‘We are your users, you’re trying to get us to do our timesheets, or clean up the kitchen, etc. Observe. Talk to people. Figure out our motivations. Summarize everything you’ve learned, and then have ideas.’

    As a designer, I am constantly designing at every level. I’m designing deliverables in many cases for clients, or coaching our teams to design deliverables. I’m also designing process by which we work by writing proposals, scoping, etc. And at the highest level, I’m designing our company. I’m designing our culture based on our customs and traditions and policies (the hard and the soft) every day. My users are not hypothetical, they’re actual people.”

    When All is Not Good

    Sara went on to cite how her previous work experience shaped the leader she is today:

    “I think a lot of my design choices are based in (unhealthy dynamics) with prior employers. Where decisions were not made transparently, everything financial was completely opaque. Lots of lack of trust with other employees. It’s been so critical that I’ve had bad experiences so I can now clearly say: let’s not do that.”

    The tactics, mindsets, organizational shifts, and operational flexibility discussed in this book are predicated upon a simple truth: a company presently supports and operates as a creative culture, or it’s genuinely willing to evolve to become one. Along the way, I’ve been primarily speaking to those who are in a position to help implement change; even at a small scale. But what about when you’re not in a position to be heard, or the position to help facilitate change?

    Reality isn’t always unicorns and rainbows. Bad experiences can impact us all. For example, the fabric of a company’s creative culture can become irreparably frayed thanks to management changes, acquisition, or it can lack sustainability. Whether these circumstances reveal themselves over years or overnight, your passion and evolution should never be their casualty.

    Sometimes, creating within an environment that’s the best fit for your growth and passions means finding a new opportunity.

  • Mr. Roboto: Connecting with Technology

    People don’t always need another human being to experience a sense of connection. The deep emotional bonds many people have with their pets proves this. (So might the popularity of the Pet Rock in the 1970s but that’s just speculation.) Even Link in The Legend of Zelda had an inanimate companion: his trusty sword (see Figure 9.1).

    A screen from The Legend of Zelda where Link receives his sword from an old man saying 'It's Dangerous To Go Alone! Take This.'
    Fig 9.1 Even the company of a wooden sword is better than venturing into Hyrule alone.

    It’s also possible for people to feel that sense of connection in the context of behavior change without having direct relationships with others. By building your product in a way that mimics some of the characteristics of a person-to-person relationship, you can make it possible for your users to feel connected to it. It is possible to coax your users to fall at least a little bit in love with your products; if you don’t believe me, try to get an iPhone user to switch operating systems.

    It’s not just about really liking a product (although you definitely want users to really like your product). With the right design elements, your users might embark on a meaningful bond with your technology, where they feel engaged in an ongoing, two-way relationship with an entity that understands something important about them, yet is recognizably non-human. This is a true emotional attachment that supplies at least some of the benefits of a human-to-human relationship. This type of connection can help your users engage more deeply and for a longer period of time with your product. And that should ultimately help them get closer to their behavior change goals.

    Amp Up the Anthropomorphization

    People can forge relationships with non-humans easily because of a process called anthropomorphization. To anthropomorphize something means to impose human characteristics on it. It’s what happens when you see a face in the array of shapes on the right side in Figure 9.2, or when you carry on an extended conversation with your cat.[1]

    An assortment of the same four shapes side by side. The grouping on the right looks like a face based on the shape positions.
    Fig 9.2 The brain is built to seek and recognize human characteristics whenever a pattern suggests they might be there. That means people interpret the array of shapes on the right as face-like, but not the one on the left.

    People will find the human qualities in shapes that slightly resemble a face, but you can help speed that process along by deliberately imbuing your product with physical or personality features that resemble people. Voice assistants like Siri, Cortana, and Alexa, for example, are easily perceived as human-like by users thanks to their ability to carry on a conversation much like a (somewhat single-minded) person.

    Granted, almost nobody would mistake Alexa for a real person, but her human characteristics are pretty convincing. Some research suggests that children who grow up around these voice assistants may be less polite when asking for help, because they hear adults make demands of their devices without saying please or thank you. If you’re asking Siri for the weather report and there are little ones in earshot, consider adding the other magic words to your request.

    So, if you want people to anthropomorphize your product, give it some human characteristics. Think names, avatars, a voice, or even something like a catchphrase. These details will put your users’ natural anthropomorphization tendencies into hyperdrive.

    Everything Is Personal

    One thing humans do well is personalization. You don’t treat your parent the same way you treat your spouse the same way you treat your boss. Each interaction is different based on the identity of the person you’re interacting with and the history you have with them. Technology can offer that same kind of individualized experience as another way to mimic people, with lots of other benefits.

    Personalization is the Swiss Army Knife of the behavior change design toolkit. It can help you craft appropriate goals and milestones, deliver the right feedback at the right time, and offer users meaningful choices in context. It can also help forge an emotional connection between users and technology when it’s applied in a way that helps users feel seen and understood.

    Some apps have lovely interfaces that let users select colors or background images or button placements for a “personalized” experience. While these types of features are nice, they don’t scratch the itch of belonging that true personalization does. When personalization works, it’s because it reflects something essential about the user back to them. That doesn’t mean it has to be incredibly deep, but it does need to be somewhat more meaningful than whether the user has a pink or green background on their home screen.

    Personalized Preferences

    During onboarding or early in your users’ product experience, allow them to personalize preferences that will shape their experiences in meaningful ways (not just color schemes and dashboard configurations). For example, Fitbit asks people their preferred names, and then greets them periodically using their selection. Similarly, LoseIt asks users during setup if they enjoy using data and technology as part of their weight loss process (Figure 9.3). Users who say yes are given an opportunity to integrate trackers and other devices with the app; users who say no are funneled to a manual entry experience. The user experience changes to honor something individual about the user.

    Screenshots of the LoseIt app showing it asking whether a user enjoys looking at data and using technology then acknowledging their choice.
    Fig 9.3 LoseIt gives users an opportunity to share their technology preferences during onboarding and then uses that choice to shape their future experience.

    If you can, recall back to ancient times when Facebook introduced an algorithmic sort of posts in the newsfeed. Facebook users tend to be upset anytime there’s a dramatic change to the interface, but their frustration with this one has persisted, for one core reason: Facebook to this day reverts to its own sorting algorithm as a default, even if a user has selected to organize content by date instead. This repeated insistence on their preference over users’ makes it less likely that users will feel “seen” by Facebook.[2]

    Personalized Recommendations

    If you’ve ever shopped online, you’ve probably received personalized recommendations. Amazon is the quintessential example of a recommendation engine. Other commonly encountered personalized recommendations include Facebook’s “People You May Know” and Netflix’s “Top Picks for [Your Name Here].” These tools use algorithms that suggest new items based on data about what people have done in the past.

    Recommendation engines can follow two basic models of personalization. The first one is based on products or items. Each item is tagged with certain attributes. For example, if you were building a workout recommendation engine, you might tag the item of “bicep curls” with “arm exercise,” “upper arm,” and “uses weights.” An algorithm might then select “triceps pulldowns” as a similar item to recommend, since it matches on those attributes. This type of recommendation algorithm says, “If you liked this item, you will like this similar item.”

    The second personalization model is based on people. People who have attributes in common are identified by a similarity index. These similarity indices can include tens or hundreds of variables to precisely match people to others who are like them in key ways. Then the algorithm makes recommendations based on items that lookalike users have chosen. This recommendation algorithm says, “People like you liked these items.”

    In reality, many of the more sophisticated recommendation engines (like Amazon’s) blend the two types of algorithms in a hybrid approach. And they’re effective. McKinsey estimates that 35% of what Amazon sells and 75% of what Netflix users watch are recommended by these engines.

    Don’t Overwhelm

    Sometimes what appear to be personalized recommendations can come from a much simpler sort of algorithm that doesn’t take an individual user’s preferences into account at all. These algorithms might just surface the suggestions that are most popular among all users, which isn’t always a terrible strategy. Some things are popular for a reason. Or recommendations could be made in a set order that doesn’t depend on user characteristics at all. This appears to be the case with the Fabulous behavior change app that offers users a series of challenges like “drink water,” “eat a healthy breakfast,” and “get morning exercise,” regardless of whether these behaviors are already part of their routine or not.

    When recommendation algorithms work well, they can help people on the receiving end feel like their preferences and needs are understood. When I browse the playlists Spotify creates for me, I see several aspects of myself reflected. There’s a playlist with my favorite 90s alt-rock, one with current artists I like, and a third with some of my favorite 80s music (Figure 9.4). Amazon has a similar ability to successfully extrapolate what a person might like from their browsing and purchasing history. I was always amazed that even though I didn’t buy any of my kitchen utensils from Amazon, they somehow figured out that I have the red KitchenAid line.

    Spotify's Daily Mixes showcasing three distinct sets of musical styles based on the user's listening habits.
    Fig 9.4 Spotify picks up on the details of users’ musical selections to construct playlists that reflect multiple aspects of their tastes.

    A risk to this approach is that recommendations might become redundant as the database of items grows. Retail products are an easy example; for many items, once people have bought one, they likely don’t need another, but algorithms aren’t always smart enough to stop recommending similar purchases (see Figure 9.5). The same sort of repetition can happen with behavior change programs. There are only so many different ways to set reminders, for example, so at some point it’s a good idea to stop bombarding a user with suggestions on the topic.

    A tweet from Andy Richter saying 'I ordered a toilet seat from Amazon and now based on the ads I see they must think I have an insatiable toilet seat addiction'
    Fig 9.5 When a user only needs a finite number of something, or has already satisfied a need, it’s easy for recommendations to become redundant.

    Don’t Be Afraid to Learn

    Data-driven personalization comes with another set of risks. The more you know about users, the more they expect you to provide relevant and accurate suggestions. Even the smartest technology will get things wrong sometimes. Give your users opportunities to point out if your product is off-base, and adjust accordingly. Not only will this improve your accuracy over time, but it will also reinforce your users’ feelings of being cared for.

    Alfred was a recommendation app developed by Clever Sense to help people find new restaurants based on their own preferences, as well as input from their social networks. One of Alfred’s mechanisms for gathering data was to ask users to confirm which restaurants they liked from a list of possibilities (see Figure 9.6). Explicitly including training in the experience helped Alfred make better and better recommendations while also giving users the opportunity to chalk errors up to a need for more training.[3]

    The Alfred app takes a guess at places the user might enjoy for dinner and asks if any of them are right.
    Fig 9.6 Alfred included a learning mode where users would indicate places they already enjoyed eating. That data helped improve Alfred’s subsequent recommendations.

    Having a mechanism for users to exclude some of their data from an algorithm can also be helpful. Amazon allows users to indicate which items in their purchase history should be ignored when making recommendations—a feature that comes in handy if you buy gifts for loved ones whose tastes are very different from yours.

    On the flip side, deliberately throwing users a curve ball is a great way to learn more about their tastes and preferences. Over time, algorithms are likely to become more consistent as they get better at pattern matching. Adding the occasional mold-breaking suggestion can prevent boredom and better account for users’ quirks. Just because someone loves meditative yoga doesn’t mean they don’t also like going mountain biking once in a while, but most recommendation engines won’t learn that because they’ll be too busy recommending yoga videos and mindfulness exercises. Every now and then add something into the mix that users won’t expect. They’ll either reject it or give it a whirl; either way, your recommendation engine gets smarter.

    Personalized Coaching

    At some point, recommendations in the context of behavior change may become something more robust: an actual personalized plan of action. When recommendations grow out of the “you might also like” phase into “here’s a series of steps that should work for you,” they become a little more complicated. Once a group of personalized recommendations have some sort of cohesiveness to systematically guide a person toward a goal, it becomes coaching.

    More deeply personalized coaching leads to more effective behavior change. One study by Dr. Vic Strecher, whom you met in Chapter 3, showed that the more a smoking cessation coaching plan was personalized, the more likely people were to successfully quit smoking. A follow-up study by Dr. Strecher’s team used fMRI technology to discover that when people read personalized information, it activates areas of their brain associated with the self (see Figure 9.7). That is, people perceive personalized information as self-relevant on a neurological level.

    A front and side scan from an MRI showing activation (in yellow) in the prefrontal cortex.
    Fig 9.7 This is an fMRI image showing activation in a person’s medial prefrontal cortex (mPFC), an area of the brain associated with the self. The brain activity was recorded after showing people personalized health information.

    This is important because people are more likely to remember and act on relevant information. If you want people to do something, personalize the experience that shows them how.

    From a practical perspective, personalized coaching also helps overcome a common barrier: People do not want to spend a lot of time reading content. If your program can provide only the most relevant items while leaving the generic stuff on the cutting room floor, you’ll offer more concise content that people may actually read.

  • Color Craft & Counterpoint: A Designer’s Life with Color Vision Deficiency

    So, what is it like to be color blind and also work in the web design and development industry? I'll answer that question throughout this article, but it's something that's always factored into my thoughts, given my passion for design and now my career. I wonder if having “normal” vision would have made me a better artist growing up. Would it make me better at my job now? Would I have pursued a more design-oriented career, as opposed to one that’s more dev-focused? These are just some of the things that pop into my head.




    What it means to be color blind




    So what colors can’t you see?









    Some people even have a fourth cone cell in their retinas; "tetrachromats" have enhanced color differentiation due to extra sensitivity between red and green. The extra cone actually came standard for most mammals in the past, but ongoing studies have suggested that 12% of the world's women might still have this fourth type of cone.


    Inside look at living with CVDs



    Insults and passive-aggressive comments




    Justifying my skill set



    Life via form factor (or winging it)



    Everyday social interactions




    Getting passed over for jobs




    Inside look at how I do my job

    Relying on tools for help



    Tools and resources I use regularly:


    Accessibility and inclusion


    Color disabilities and the Web Content Accessibility Guidelines


    Color contrast




    Data visualization



    – Web Content Accessibility Guidelines 2.1 - Success Criterion 1.4.1 Use of Color




    Adding people with a CVD to your team






    Critical CVD tips for your projects



    Design color palettes for “everyone”



    Don’t assume, and be careful what you ask 





    Test with colorblind simulators AND colorblind users


    Seek out first-hand perspectives 


    Stand up for coworkers and users


    Tools and further reading

    Accounts on Twitter 

    Usability and UX

    Organizational resources

    Color perception and the brain

    Continuing to make progress




  • Building the Woke Web: Web Accessibility, Inclusion & Social Justice

    What would your life be like without the internet? Not if it didn’t exist at all, but if you were locked out of it? Would your days be different? Unrecognizable, even? Keeping your answers to that in mind, do you think access to the internet is a human right? Do we need to be able to access it to fully participate in modern society? To answer “yes” to these questions would have been unthinkable 20 years ago.

    Living without internet

    Globally, over 40% of people still do not have access to the internet. That lack of access and the issues it creates have helped motivate digital equity initiatives like Tech Goes Home and the Good Things Foundation.

    Having no access to the internet creates problems in many parts of modern life. In the UK, bank branches are closing, forcing many to do their banking online. Many utilities now require internet access to request or amend services, or get better deals. Civil services, such as registering to vote, are increasingly online. As this continues, people who have no access to broadband or who have limited access to mobile data fall behind—this often includes homeless people, elderly people, and those on low incomes who are already operating at a disadvantage.

    In the UK, only 37% of people living in social housing are online. Approximately 1 in 5 adults with a disability in the UK have not used the internet recently, and they make up half of the people who have not accessed the internet in the last three months. Globally, the UN target for affordable mobile data is 2% of monthly income for 1GB data, and yet many countries are still nowhere near reaching this goal. Not having access to the internet is expensive, locking you out of essential services and a surfeit of helpful information. Giving people full access to the splendors and knowledge of the online world should be imperative for everyone who works on it.

    Digital exclusion is when someone is unable or unwilling to access information and services online. In the UK, 10% of the adult population was digitally excluded in 2018. The number of people in the UK lacking basic digital skills is decreasing, but in 2018, 8% of adults in the UK (4.3 million people) were estimated to have zero basic digital skills, which means they are unable to do things like buy items online, verify information, or send an email. Women are more likely to have no basic digital skills. 

    Being unable to send an email, submit an application online, or use a government site is a huge barrier to civic and societal engagement. Shopping in person, rather than online, can mean you are consistently overcharged for your purchase by as much as 13%. Not knowing how to use computers can mean you earn less in the first place. Not being able to use the internet can mean that you spend more time doing tasks such as registering to vote, paying council tax in the UK, or researching your next holiday

    Being able to access the internet has social and psychological ramifications too. Loneliness is well documented as a risk factor for a number of health issues, as well as early death. Being online can help you feel less alone. Half of all people with disabilities surveyed report feeling lonely in the UK, and a quarter of them are lonely every day. People with disabilities are more likely to be a captive audience to apps and websites using their data inappropriately or engaging in other unethical practices. This may be because they rely on a particular site to interact with other people with disabilities, because they lack the tools to visit other sites, or lack other suitable websites or apps to use.

    Richer households are more likely to have full basic digital skills. The UK Office for National Statistics found that people without basic digital skills are three times as likely to be in low-income bands. In 2018, 12% of 11-to-18-year-olds had no broadband access on a tablet or computer, which 68% of them said made it difficult to do homework. Further, households in which one or more of their members have a disability make up half of those living in poverty in the UK.

    Provide non-online options for vital services


    A non-exhaustive list of other barriers

    Having access to the internet in the first place is one issue, and feeling welcome, or even safe is quite another. Even when your broadband connection is as good as can be hoped for, there are many other ways you can be discouraged or stopped from using the internet.

    Trolling and threats

    Online harassment is one of many barriers stopping people from accessing the internet. Diane Abbott, the first black woman Member of Parliament (MPs) in the UK, received almost half (45.14%) of all abusive tweets sent to female MPs in the run-up to the 2017 General Election that decided how voters would be represented in Parliament and which party would govern. Black and Asian women MPs got 35% more abusive tweets than white women MPs. The abuse directed at Dianne Abott amounted to 10 times as much as was received by any other female MP, according to an Amnesty International study.

    Mermaids is a charity that supports transgender children and their parents in the UK. Their CEO Susie Green—herself the parent of a transgender child—has been targeted with abuse and threats. The rise in abusive and threatening comments led to Mermaids’ Twitter account having to block up to 20 accounts a day.

    Trolling isn’t an easy problem to fix. Allowing users to block certain words and hide certain replies on Twitter is a start, but listening to people from marginalized backgrounds and their complaints and ideas would be another critical place to begin. 

    We need to think long and hard about what good moderation looks like and what guidelines work in online spaces to ensure those accessing them don’t have to wade through a tide of bigotry.

    Sidelining and hiding certain groups

    Information and support online are vital for at-risk LGBT people, whether to help them escape dangerous situations, access support, or find community. Yet in schools, words relating to LGBT issues are often blocked. On YouTube, videos relating to LGBT issues are demonetized, age-restricted, or even removed. This isn’t because the content is sexually explicit or not safe for work. It’s just discrimination. TikTok recently admitted it actively discriminates against certain kinds of users—namely the fat, queer, disabled, low-income, and “ugly”—in certain feeds, under the guise of paternalistic protection from bullying.

    Exclusionary design


    Liz Jackson, “Designing for Inclusivity

    Many people with disabilities rely on screen readers and screen reader compatible sites to use the internet. Screen readers can be prohibitively expensive; while there are free options, one of the most popular screen readers at the time of writing costs nearly $1200 for a professional license. Even with incredible innovation coming from within the disabled community, there’s more that everyone else can do. In their February 2020 evaluation, WebAIM found that 98.1% of the top million websites had detectable WCAG (Web Content Accessibility Guidelines) 2 errors.

    The most common WCAG 2 failures—such as missing alt text for images, having empty links, and missing form labels—would be relatively simple to fix. Because they’re shared among most websites, concentrating on fixing them would have a huge overall benefit for the internet. But as long as web accessibility standards are applied without rigor, aspects of a vast number of sites remain inaccessible even once users have a screen reader or other assistive technology.

    Hostile conditions

    Inclusion is just as pertinent as accessibility, and tackling only one side of the equation will leave some people just as locked out. Accessibility without inclusion is not real accessibility. The curb cut effect, wherein improving access for people with disabilities improves access for all, isn’t the only reason to increase web accessibility. We have a moral responsibility as tech workers to use any privilege we may have to facilitate, respond to, and support the efforts of marginalized people who are working to carve out accessible spaces for themselves.

    Hostile conditions, created or reinforced by engineering and design choices, make being on the internet harder for people who are queer, of color, or disabled. They make it more difficult to access life-saving spaces, social spaces, and civic spaces—both on and offline. Thorough accessibility and real inclusion are the solutions to these problems. To survive, marginalized people must work both against and through the abuse and accessibility issues they face on online platforms, whereas everyone else gets to use the internet as they wish. This replicates the injustices of offline in the online world.

    An incomplete list of solutions

    Center the voices and experiences of the marginalized

    There isn’t one easy solution but to start finding the solutions that are possible we need to center the voices and experiences of the marginalized. Marginalized people with insights to share aren’t hard to find when you start listening. They are your next users, your future developers, your fledgling marketing team. Excluding them reduces your options, your appeal, and your breadth of ideas.

    Hire teams that are diverse on every axis

    Hiring inclusively creates teams full of people who aren’t like you or each other. And those kinds of teams build better products, bring better ideas to the table, and better reflect the user base of the majority of products. It is important to remember that diversity isn’t just about race or hiring women; there are neurodiverse people, people with physical disabilities, people of other genders, people from various backgrounds, and many other marginalizations than could be listed here.

    Proactively promote inclusion and harness your team’s diversity

    Help disabled and otherwise marginalized people both develop and enforce policies and practices that protect them and allow them to thrive. If there are no disabled people, or otherwise marginalized or underrepresented people on your team, take a hard look at your hiring practices, your work culture, even the layout of your office. If you can’t find these problems, hire experts. Pay specialist consultants and recruiters to root out the problems. This is an investment that makes moral, logical, and business sense. The inclusive team you build will be able to spot potential issues in a way that a squad of people who pattern match to narrow ideas of what a tech worker should look and behave like never would. Create a culture where the marginalized members of your team feel supported, feel heard, and are buoyed through their work with a sense of safety in their workplace.

    Avoid legal issues preemptively

    Beyonce and Domino’s Pizza were both sued under the Americans with Disabilities Act, which contains provisions to force the companies involved to change their websites. Beyonce’s case is still in progress, but Domino’s both lost their suit and had their appeal tossed out. Both cases were about visually impaired people being unable to access their sites and complete purchases. Accessibility is often seen as a costly detour from the “real work” of building projects, but that has never and will never be true. You want users, and users of all stripes want to use your products.

    The banks HSBC, Metro Bank, and Halifax made it hard for visually impaired users to access all of their services online. When HSBC was told they had made it difficult for a user with visual impairments to access bank statements, they replied, “don’t worry, we’ll send you a video.” The Equality Act 2010 in the UK means that these users can sue. In addition to serving the far more important goal of providing people with disabilities equal access, embracing inclusive design from the outset would have saved these companies time while enhancing their trust among the public rather than putting it at risk. Fixing the content is usually much cheaper for the organization than fighting the matter in court.

    Advocate for accessibility and inclusivity in any way you can, be it big or small

    Caption your videos, Instagram content, Facebook photos, Twitter photos, conference and meetup talks, etc. Make information needed to access your product or service available in multiple formats. Speak up against problems in your workplace; if an internal hiring tool is hard for you to use, it is hard for others. If one of your websites has errors from WCAG 2’s list, advocate for taking time to fix it. If the gender options available on forms are “man,” “woman,” and “other,” speak up yourself, tell your manager, question whether you need to collect gender information at all. Don’t stay silent.

    Test your website with tools, devices, and real end users

    Run tools like axe, ChromeLens, and Lighthouse during your build processes. Do manual testing with the actual devices that are used by your end-users, and test with real users with access requirements. If you’re a team of one or a few, ensure that you run these tools from MVP to finished product—the errors that are the easiest to catch and fix will mostly be caught by automated tools, and they are a great start for learning more about accessibility. Websites such as The A11y Project compile resources, and there are other websites, Slack groups, Twitter accounts, and newsletters that are also incredibly helpful for answering any questions. The automated tools will give you the keywords to search for.

    Working towards an accessible, inclusive internet

    Web accessibility is not an optional extra. What inclusion looks like in practice will depend on your products, your users, and what you intend to achieve, but for it to be real and meaningful in any context, it cannot be an afterthought. Engineering that makes inclusion an afterthought is engineering that operates without morality and in doing so actively enacts harm. The fact that this kind of engineering is commonplace on the internet doesn’t make it OK. It just highlights that the way we have built the web is fundamentally broken. We can do better.

    “Wokeness,” at least as conceived by those divorced from the black experience and AAVE, isn’t a great concept. The way it is used in popular culture makes it sound as if being a good person is a switch you flip on and off; you’re woke or ’sleep. But wokeness is not the end state, it’s the beginning of a journey. All the tenets of intersectional feminism, web accessibility, and diversity and inclusion are inextricably tied up in making the web a better place, for all and by all. Access to the internet is essential. Staying woke, and acting on that wokeness, is what will lead us to a better internet for everyone.

  • Figure It Out

    Color is, without a doubt, the visual element most often misunderstood and misused.

    As mentioned earlier, when designing visual representations, color is often the first visual encoding that people use. It’s also quite limited to about a dozen, distinguishable colors. It’s a potent visual element, but one fraught with accessibility and perceptual problems. A general rule of thumb: Save color for things you want to draw people’s attention to. Start with grayscale representations. Add in color only later, where it might be really, really useful. That’s it. We can move along.


    We need to dispel some popular beliefs about colors, beliefs that are often held up as truth, when, in fact, this is not the case. What’s presented in this short chapter is more foundational knowledge than tips for immediate application. But also, this understanding of color is—we found in retrospect—a powerful lens for understanding the concepts shared throughout this book. We see in our exploration of color this pattern: while many of the absolutes we cling to are social constructs (varying across cultures and over time), behind these changing constructs we also find some universal human constants.

    How Many Colors Are in the Rainbow?

    Let’s begin by unpacking the statement above, suggesting that we only see about a dozen colors. Actually, the human eye can perceive many more colors, perhaps a million or so. Of this million, it’s estimated that each of us—individually—can distinguish somewhere between 130 to 300 colors.[1] But within a cultural group, we can only share about a dozen such colors. These limitations have little to do with personal visual acuity, but rather with language: a group’s ability to see and perceive a specific color is determined by language. Do we—as a society—share the same named color value associations?

    We can talk about something being “red” and feel confident in what we all see. From both a developmental perspective and an anthropological perspective, red is the first color (after white and black) that most cultures are aware of. But if I describe something as magenta, do we have a shared agreement as to what that named concept refers to? Perhaps you see hot pink where I see a vibrant, purply-reddish color? Another example of this language-color dependency: the Russian language has a specific word for the color that we (English speakers) perceive as light blue.

    To put this shared vocabulary into perspective, let’s start with something that is constant and beyond our language: the visible spectrum of light that is a rainbow.

    When Colors Are Constant

    Around the world, the meteorological phenomenon we describe as a rainbow is a constant thing. Light refracts across water droplets to create a spectrum visible to humans. What we see as colors are the wavelengths of light visible to the human eye (see Figure 8.1). On either end of this visible spectrum are ultraviolet and infrared waves, which while invisible to human eyes, we know they are visible—that is, seen—by cameras and some nonhuman creatures (cats can see certain infrared frequencies, for example). Beyond this visible spectrum, we have things like gamma rays, X-rays, and radio waves, which all make up the entire spectrum of white light from the sun.

    A diagram showing the spectrum of light
    Figure 8.1 The visible light spectrum is a small part of the broader electromagnetic spectrum. Starting from this perspective helps us recognize the subjectivity of what is “seen” and how this might vary with different creatures and devices.

    But let’s stay focused on the portion of this light spectrum that is visible to humans, the part that allows us to see. Within this spectrum, the rainbow possesses millions of color combinations, as there are no clearly defined boundaries between the colors.

    Why then, should diverse cultures over thousands of years arrive at the same set of color language definitions? Are colors an absolute thing? Not exactly.

    The Subjectivity of Color Identification

    Consider “ROYGBIV,” which is the acronym we all learned to name the colors of the rainbow. How did we conclude, at least in Western cultures, that a rainbow has seven colors? Why not five, or six, or eleven? We have Sir Isaac Newton to thank for this.

    These seven colors—red, orange, yellow, green, blue, indigo, and violet—were not the result of any serious scientific inquiry. Rather, Newton was fond of the number seven. Just as there are seven musical notes in a scale, Newton believed that colors should follow a similar pattern. He might have connected this with seven days in the week or the seven known planets (at the time) in our universe. In other words, ROYGBIV was an arbitrary choice based on mystical superstition.

    Understanding how we arrived at these seven colors sheds light on the subjective nature of color identification. This may also explain a bit about the challenge that so many people have with indigo—that odd color that sits somewhere between blue and violet—as a separate color!

    But here is where we have to be careful, as we are stepping into a decades old debate: Do the number of basic color terms and the location of color category boundaries vary across languages? Or might there be a universal pattern to the color naming systems of all cultures?

    This Wikipedia entry sums up the debate rather nicely:

    There are two formal sides to the color debate, the universalist and the relativist. The universalist side claims that the biology of all human beings is all the same, so the development of color terminology has absolute universal constraints. The relativist side claims that the variability of color terms cross-linguistically (from language to language) points to more culture-specific phenomena. Because color exhibits both biological and linguistic aspects, it has become a deeply studied domain that addresses the relationship between language and thought. [2]

    An Argument for Relative Linguistics

    We can characterize what Newton did as imposing an arbitrary number of colors upon the color spectrum. And we might conclude the same thing has happened throughout history as different people groups formed words to describe the world around them.

    Indeed, various studies of diverse cultures reveal that “although the physiological basis of color vision is essentially the same for all humans with normal trichromatic color vision, there is considerable diversity in the way that different languages segment the continuum of visible colors.”[3] In other words, the rainbow has no natural boundaries; how we slice it up into colors is a subjective thing that varies across different cultures and time. (See Figure 8.2 for an illustration of this concept.) From one research paper, we learned that “some languages have been reported to use as few as two terms to describe all visible colors (Rosch Heider, 1972). Others have been reported to use between three and eleven (Berlin & Kay, 1969), while some (e.g., Russian; Davies and Corbett, 1997) may have twelve.”[4]

    Specific examples in support of this argument:

    •  In Russian culture, there is no generic concept of blue. Rather, Russian makes an obligatory distinction between lighter blues (goluboy) and darker blues (siniy).
    • The Japanese language (before the modern period) had just one word, Ao, for both blue and green. It wouldn’t be until the year 1,000 that the word midori would be introduced to distinguish a greenish shade of blue
    • The Himba tribe from Namibia recognizes five basic colors.
    • The Berinmo of Papua New Guinea has also reached a different conclusion as to the number of colors they recognize. While they draw no distinction between blue and green, they do “draw a distinction within what English speakers would consider yellow, with the word nol on one side and wor on the other.”

    From this, we might conclude that the colors of the rainbow do seem to be arbitrary and dependent upon language. (Connect this with earlier points we made about thoughts and cognition as layers upon layers of prior associations.)

    A webcomic from XKCD, reading 'This chart shows the dominant color names over the three fully-saturated faces of the RGB cube (colors where one of the RGB values is zero)
    Figure 8.2 This comic from Randall Munroe of xkcd nicely illustrates the subjectivity of the shared color language for English speakers.[5]

    But surely, you may be thinking, color identification isn’t entirely subjective? Here’s where the research gets interesting: despite these regional differences, a fascinating and consistent pattern begins to emerge.

    An Argument for the Universal

    In the late 1960s, after studying color terms across many different languages, researchers Berlin and Kay introduced the idea that there were eleven possible basic color categories: white, black, red, green, yellow, blue, brown, purple, pink, orange, and gray. They argued a universalist theory: that color cognition is an innate, physiological process rather than a cultural one.

    While their research has been challenged on different grounds, what has since followed is some agreement that for all noted language differences, there is a fixed order in which color names arise. The ways in which color language evolves across cultures suggest maybe there is a universal pattern governing the direction of patterns in the evolution of colors. All cultures start with the ability to distinguish dark things from light things. This is followed by the recognition of red. After that, it might be the addition of yellow or green. And blue always seems to come last. Not every language follows the exact same path, but they adhere to this same general pattern.

    While the broader debate is not necessarily concluded, the general consensus seems to be that “in color, relativism appears to overlay a universalist foundation.”

    Why All the Fuss over Color?

    While this is certainly fascinating, how is this useful? We include this as a mirror to challenge assumptions. If we turn a critical eye to the commonly accepted color wheel, this was likely influenced by Newton’s original color wheel sketch. But is this the “right” way to think about colors? Primary colors combine to make secondary colors, which in turn allow us to describe tertiary colors. We learn this from an early age and accept this way of thinking about color as absolute. But this is just one frame. This is just a way of thinking about visible light. And this singular perspective has limitations, especially when used in medical, scientific, and engineering visualizations. Research papers such as “Rainbow Color Map (Still) Considered Harmful”[6] question the value of the rainbow color spectrum in data visualization applications. The point is simple: there are other ways we might think about color. We can look at alternatives such as perceptually ordered color spectrums, an isoluminant color map, or simply use representations of color that aren’t derived from a wheel. Tools such as ColorBrewer 2.0[7] or the NASA Ames Color Tool[8] are incredibly useful for choosing a palette more suitable for visualizing data.

    Since this book is concerned with how human creatures understand information, and because we so often use color to clarify, we felt it worth calling out that color and color recognition are not necessarily universal things, but are dependent on cognition, language, and biology. Understanding this allows us to challenge common assumptions about what is “true” about color and perception.

    Which leads us to…

    Color, Cultures, and Universal Associations

    Red means stop. Green means go. These concepts are universal, right? Not so fast. Across cultures, colors do not necessarily convey the same concept. And where we may have the same ability to identify a color, the associated meaning is just that—a learned association. Concluding that red means passion, vitality, or energy, because blood and fire are red things is not a universal idea. Neither is associating green with growth, just because nature involves so much green. (In some Chinese cultures, green can be associated with death.) At this point, please throw away those blog posts and posters about colors to choose for different cultures. While we’re keen to seek out human universals, color has proven to be something that does not have consistent meaning across cultures, or even within a culture group. Rather, the concepts we associate with particular colors are highly contextual and local, not just to a particular culture, but sometimes to smaller social groups. The meanings we point to—blue as a safe, corporate color, for example—are highly generalized assumptions, highly contextual, and mostly learned associations.

    The Color Purple

    Let’s take purple, as an example. For many centuries, purple dye was expensive and rare. Procuring purple dye was labor intensive and required collecting a secretion from sea snails. Historian David Jacoby remarked that “twelve thousand snails of Murex brandaris yield no more than 1.4 g of pure dye, enough to colour only the trim of a single garment.”[9] As a result of this laborious process, the high cost of producing purple clothing made this color a status symbol among kings, queens, and other rulers. If you could afford to wear purple, you were quite wealthy. The conceptual association then is one of scarcity (in this case of a particular dye), signaling something to be valued above other things. While we may still see the lingering effects of this history (the Purple Heart is among the highest honors awarded for U.S. military service), the constraint of purple as a scarce color is no longer true. As such, this color is able to take on new meanings.

    “Pink Is for Girls, Blue Is for Boys”

    To put this into perspective, let’s investigate the idea that “pink is for girls, blue is for boys.” From clothing choices to marketing toys to how we decorate bedrooms, most of us grow up believing there’s some inherent gender association built into the colors pink and blue. But, were we to travel back in time—just over 100 years—we’d find no such distinction. Or we might find the opposite association.

    According to University of Maryland historian Jo B. Paoletti, author of Pink and Blue: Telling the Girls from the Boys in America, pink and blue weren't always gender-specific colors. For centuries, young children mostly wore a functional white dress, and then in the early 20th century, things began to change. Consider this quote, pulled from the June 1918 issue of Earnshaw's Infants’ Department, a trade publication:


    A Smithsonian review of Paoletti’s book,[10] goes on to add:



    By the 1940s, this association had flipped. Manufacturers had settled on pink for girls and blue for boys (see Figure 8.3 as an example of this association). Baby Boomers were raised with wearing the two colors. The point of this narrative? Color associations are learned things and can change over time. Even something as seemingly strong as the pink/blue binary was a manufactured association. To be clear, this doesn’t mean a color association is any less powerful in the moment, at a particular point in history, but these color associations do not represent any universal truths.

    A box of 'It's a boy!' baby announcement candy cigars in blue
    A box of 'It's a girl!' baby announcement candy cigars in pink
    Figure 8.3 - The “blue is for boys and pink is for girls” concept was a manufactured one, originating in the first half of the 20th century.

    Accordingly, it’s good to be wary of generalizations such as “blue is a safe, corporate color.” In the case of corporate associations, one generation’s “safe” may—depending on the media and actions—signal stuffy, inauthentic, or distrustful to the next generation. It all depends on the learned associations embraced—for a time—by a particular culture.

    Not All Colors Are Created Equal

    We tend to treat our color palettes like interchangeable parts. Just pick a color. Or pick some colors we all find pleasing. Consider how many of us use the default color palettes built into software tools like Excel or PowerPoint. We usually choose a pleasing color palette, with the sentiment being “as long as you can distinguish one color from another, it’s okay, right?”

    Not exactly. Not all colors are created equal. In terms of visual perception, some colors jump out at you while others recede into the background (see Figure 8.4). This is because of variances in hue and saturation.

    A series of four charts, each with an increasing number of colors
    Figure 8.4 The range of colors perceived by humans is uneven.
    (Equiluminant colors from the NASA Ames Color Tool)

    A very bright color is going to draw more visual attention than a more desaturated color. This makes sense if we consider how things farther away from us tend to be hazier and desaturated. If something in the distance is noticed, it’s likely because it’s moving or contrasts with the surroundings.

    This same disparity applies to color hues. We tend to look at color charts like this one and assume that the extreme ends of red, green, and blue are on equal footing.

    Two gradients, one going from black to red, one going from black to gray
    Two gradients, one going from black to green, one going from black to gray
    Two gradients, one going from black to blue, one going from black to gray

    However, because of the wavelengths of these colors and how our eyes perceive color, we see green as brighter than red, which itself is brighter than blue.

    How Is This Knowledge Useful?

    While it’s nice to think that precise color values are interchangeable (setting aside any cultural associations), your perception doesn’t work that way. In the same way that certain frequencies on the radio come in clearer than others, certain colors do the same. You need to account for, or at least consider, the unevenness of color perception.

    In the example in Figure 8.5, you see the same eight-segment pie chart. The example on the right uses all high-saturation colors while the example on the left mixes high- and low- saturation colors.

    Two equal pie charts with differing levels of saturation in the colors
    Figure 8.5 Two pie charts showing identical information. The chart on the left uses colors of mixed saturation, meaning some colors will naturally stand out more than others, making this an uneven representation.

    Functionally, these both communicate the same thing. But consider how you perceive each. With the example on the right, use of high saturation is consistent; no color should be more prominent than another. But when you mix high and low saturation, as with the example on the left, the higher saturation colors tend to “pop” more—drawing you to these segments. While this chart is more aesthetically pleasing (as it uses half as many colors), it’s also a bit misleading—notice how your eye is drawn to the orange segment in the upper right. The lesson? Assuming the goal is objectivity and truthfulness, you’d want to avoid mixing saturations and hues that are unevenly perceived. If the goal were the opposite, to draw attention away from or toward a particular bit of data, you could manipulate perception by adjusting saturation and hue (not that this is being recommended!). This ability to direct attention by using bolder colors is something that everyone should be aware of and intentional about.

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  • How to fix audio problems on your Windows PC


    No sound in one app

    1. First, reboot your computer.

    No sound at all

    1. sound settings via speaker icon in system tray PCWorld


      To read this article in full, please click here

  • Dell XPS 15 9500 Review: Buy this laptop instead of a MacBook Pro 16

    Timing is everything in the PC business, and the Dell XPS 15 9500, an overdue refresh to the company’s high-end workhorse, arrives just in time for it to be truly considered the “MacBook Pro killer” it’s always aspired to be.

    Yes, we know “MacBook Pro killer” is overused Internet clickbait. But with Apple’s decision to throw in the towel on x86-based laptops, anyone buying a Mac today is basically volunteering to stand on the deck of the Titanic and wave as the last lifeboats pull away.

    To read this article in full, please click here

  • Townscaper impressions: Build picturesque fishing villages with no direction and no drama

    In the beginning, there was an ocean. Vast and unbroken, it stretched from one end of the horizon to the other, the blue of the sky barely distinguished from the blue of the sea.

    Then there was a pier, dredged up from the nothingness below the sea, a stone-and-sand bulwark battered by waves. The not-ocean grew, the pier becoming a harbor, then an island, and on that island grew houses—in white and red and purple and teal. Cottages and ranch homes, warehouses and monolithic apartment blocks, until ocean gave way to a town.

    This is how the story goes in my head, at least. I’ve spent much of the last two days playing (or toying with) Townscaper, and so far I’ve learned I never needed the “Sim” part of SimCity after all.

    To read this article in full, please click here

  • How to check your graphics card's GPU temperature


    The good news? Checking your PC’s graphics card temperature is dead simple, especially now that Windows finally includes a native way to keep tabs on temps. All sorts of free GPU monitoring tools are also available, and many of them can help you check your PC’s CPU temperature, too.

    To read this article in full, please click here

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