Category: Blog

Between the dream of getting it right and the fear of it going wrong—like when we encounter “persofails” in the vein of a company constantly imploring daily consumers to buy more toilet seats—the personalization gap is true. It’s an particularly confusing place to be a modern professional without a map, a map, or a strategy.

For those of you venturing into customisation, there’s no Lonely Planet and some tour guides because powerful personalization is so specific to each group’s skills, systems, and market place.

But you can ensure that your team has packed its bags sensibly.

There’s a DIY formula to increase your chances for success. At minimum, you’ll defuse your boss’s irrational exuberance. Before the party you’ll need to effectively prepare.

We call it prepersonalization.

Behind the music

Consider Spotify’s DJ feature, which debuted this past year.

We’re used to seeing the polished final result of a personalization feature. Before the year-end award, the making-of backstory, or the behind-the-scenes victory lap, a personalized feature had to be conceived, budgeted, and prioritized. Before any personalization feature goes live in your product or service, it lives amid a backlog of worthy ideas for expressing customer experiences more dynamically.

So how do you know where to place your personalization bets? How do you design consistent interactions that won’t trip up users or—worse—breed mistrust? We’ve found that for many budgeted programs to justify their ongoing investments, they first needed one or more workshops to convene key stakeholders and internal customers of the technology. Make yours count.

​ From Big Tech to fledgling startups, we’ve seen the same evolution up close with our clients. In our experiences with working on small and large personalization efforts, a program’s ultimate track record—and its ability to weather tough questions, work steadily toward shared answers, and organize its design and technology efforts—turns on how effectively these prepersonalization activities play out.

Time and again, we’ve seen effective workshops separate future success stories from unsuccessful efforts, saving countless time, resources, and collective well-being in the process.

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

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

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

Set your kitchen timer

How long does it take to cook up a prepersonalization workshop? The surrounding assessment activities that we recommend including can ( and often do ) span weeks. For the core workshop, we recommend aiming for two to three days. Here’s a summary of our broader approach along with details on the essential first-day activities.

The full arc of the wider workshop is threefold:

Kickstart: This sets the terms of engagement as you focus on the opportunity as well as the readiness and drive of your team and your leadership..
1. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
2. Work your plan: This phase is all about creating a competitive environment for team participants to individually pitch their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

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

Kickstart: Whet your appetite

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

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

This is all about setting the table. What are the possible paths for the practice in your organization? If you want a broader view, here’s a long-form primer and a strategic framework.

Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature ( or something similar ). In our cards, we divide connected experiences into five levels: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to focus the conversation on the merits of ongoing investment as well as the gap between what you deliver today and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is critical because it emphasizes how personalization can not only help your external customers but also affect your own ways of working. It’s also a reminder ( which is why we used the word argument earlier ) of the broader effort beyond these tactical interventions.

Each team member should vote on where they see your product or service putting its emphasis. Naturally, you can’t prioritize all of them. The intention here is to flesh out how different departments may view their own upsides to the effort, which can vary from one to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

The third and final kickstart activity is about naming your personalization gap. Is your customer journey well documented? Will data and privacy compliance be too big of a challenge? Do you have content metadata needs that you have to address? ( We’re pretty sure that you do: it’s just a matter of recognizing the relative size of that need and its remedy. ) In our cards, we’ve noted a number of program risks, including common team dispositions. Our Detractor card, for example, lists six stakeholder behaviors that hinder progress.

Effectively collaborating and managing expectations is critical to your success. Consider the potential barriers to your future progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. As studies have shown, personalization efforts face many common barriers.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? Good—you’re ready to continue.

Hit that test kitchen

Next, let’s look at what you’ll need to bring your personalization recipes to life. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. Their capabilities are sweeping and powerful, and they present broad options for how your organization can conduct its activities. This presents the question: Where do you begin when you’re configuring a connected experience?

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

The ultimate menu of the prioritized backlog will come together over the course of the workshop. And creating “dishes” is the way that you’ll have individual team stakeholders construct personalized interactions that serve their needs or the needs of others.

The dishes will come from recipes, and those recipes have set ingredients.

Verify your ingredients

Like a good product manager, you’ll make sure—andyou’ll validate with the right stakeholders present—that you have all the ingredients on hand to cook up your desired interaction ( or that you can work out what needs to be added to your pantry ). These ingredients include the audience that you’re targeting, content and design elements, the context for the interaction, and your measure for how it’ll come together.

This isn’t just about discovering requirements. Documenting your personalizations as a series of if-then statements lets the team:

1. compare findings toward a unified approach for developing features, not unlike when artists paint with the same palette,
2. specify a consistent set of interactions that users find uniform or familiar,
3. and develop parity across performance measurements and key performance indicators too.

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

Compose your recipe

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

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

We first developed these cards and card categories five years ago. We regularly play-test their fit with conference audiences and clients. And we still encounter new possibilities. But they all follow an underlying who-what-when-why logic.

Here are three examples for a subscription-based reading app, which you can generally follow along with right to left in the cards in the accompanying photo below.

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

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

You can think of the later stages of the workshop as moving from recipes toward a cookbook in focus—like a more nuanced customer-journey mapping. Individual” cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Better kitchens require better architecture

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

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

You can definitely stand the heat …

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a disciplined and highly collaborative approach will bring about the necessary focus and intention to succeed. So banish the dream kitchen. Instead, hit the test kitchen to save time, preserve job satisfaction and security, and safely dispense with the fanciful ideas that originate upstairs of the doers in your organization. There are meals to serve and mouths to feed.

This workshop framework gives you a fighting shot at lasting success as well as sound beginnings. Wiring up your information layer isn’t an overnight affair. But if you use the same cookbook and shared recipes, you’ll have solid footing for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

While there are associated costs toward investing in this kind of technology and product design, your ability to size up and confront your unique situation and your digital capabilities is time well spent. Don’t squander it. The proof, as they say, is in the pudding.

The same applies for those of us working in design and development these times. Having worked on the web for about three years at this point, I’ve seen the typical wax and wane of concepts, strategies, and systems. Each day that we as developers and designers get into a regular rhythm, some innovative idea or technology comes down to shake things up and copy our world.

How we got below

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

The beginning of website standards

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

Server-side languages like PHP, Java, and.NET overtook Perl as the predominant back-end processors, and the cgi-bin was tossed in the trash bin. With these better server-side tools came the first era of web applications, starting with content-management systems ( particularly in the blogging space with tools like Blogger, Grey Matter, Movable Type, and WordPress ). In the mid-2000s, AJAX opened doors for asynchronous interaction between the front end and back end. Suddenly, pages could update their content without needing to reload. A crop of JavaScript frameworks like Prototype, YUI, and jQuery arose to help developers build more reliable client-side interaction across browsers that had wildly varying levels of standards support. Techniques like image replacement let crafty designers and developers display fonts of their choosing. And technologies like Flash made it possible to add animations, games, and even more interactivity.

These new technologies, standards, and techniques reinvigorated the industry in many ways. Web design flourished as designers and developers explored more diverse styles and layouts. But we still relied on tons of hacks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes ( such as rounded or angled corners ) and tiled backgrounds for the appearance of full-length columns (among other hacks ). Complicated layouts required all manner of nested floats or absolute positioning ( or both ). Flash and image replacement for custom fonts was a great start toward varying the typefaces from the big five, but both hacks introduced accessibility and performance problems. And JavaScript libraries made it easy for anyone to add a dash of interaction to pages, although at the cost of doubling or even quadrupling the download size of simple websites.

The web as software platform

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

At the same time, mobile devices became more capable, and they gave us internet access in our pockets. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This combination of capable mobile devices and powerful development tools contributed to the waxing of social media and other centralized tools for people to connect and consume. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media offered connections on a global scale, with both the good and bad that that entails.

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

Where we are now

In the last couple of years, it’s felt like we’ve begun to reach another major inflection point. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. There are many different ways to make a website, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all flavors. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. Webmentions, RSS, ActivityPub, and other tools of the IndieWeb can help with this, but they’re still relatively underimplemented and hard to use for the less nerdy. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

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

Today, with a few commands and a couple of lines of code, we can prototype almost any idea. All the tools that we now have available make it easier than ever to start something new. But the upfront cost that these frameworks may save in initial delivery eventually comes due as upgrading and maintaining them becomes a part of our technical debt.

If we rely on third-party frameworks, adopting new standards can sometimes take longer since we may have to wait for those frameworks to adopt those standards. These frameworks—which used to let us adopt new techniques sooner—have now become hindrances instead. These same frameworks often come with performance costs too, forcing users to wait for scripts to load before they can read or interact with pages. And when scripts fail ( whether through poor code, network issues, or other environmental factors ), there’s often no alternative, leaving users with blank or broken pages.

Where do we go from here?

Today’s hacks help to shape tomorrow’s standards. And there’s nothing inherently wrong with embracing hacks —for now—to move the present forward. Problems only arise when we’re unwilling to admit that they’re hacks or we hesitate to replace them. So what can we do to create the future we want for the web?

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

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

Design with care. Whether your craft is code, pixels, or processes, consider the impacts of each decision. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that those decisions can have. Rather than rushing headlong to “move fast and break things”, use the time saved by modern tools to consider more carefully and design with deliberation.

Always be learning. If you’re always learning, you’re also growing. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. You might end up focusing on something that won’t matter next year, even if you were to focus solely on learning standards. ( Remember XHTML? ) But constant learning opens up new connections in your brain, and the hacks that you learn one day may help to inform different experiments another day.

Play, experiment, and be weird! This web that we’ve built is the ultimate experiment. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be courageous and try new things. Build a playground for ideas. Make goofy experiments in your own mad science lab. Start your own small business. There has never been a more empowering place to be creative, take risks, and explore what we’re capable of.

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

Go forth and make

As designers and developers for the web ( and beyond ), we’re responsible for building the future every day, whether that may take the shape of personal websites, social media tools used by billions, or anything in between. Let’s imbue our values into the things that we create, and let’s make the web a better place for everyone. Create that thing that only you are uniquely qualified to make. Then share it, make it better, make it again, or make something new. Learn. Make. Share. Grow. Rinse and repeat. Every time you think that you’ve mastered the web, everything will change.

I’d like you to consider this a “yes … and” piece to complement Joe’s post. I’m not trying to reject any of what he’s saying but instead provide some awareness to projects and possibilities where AI can generate substantial differences for people with disabilities. To be clear, I’m not saying that there aren’t true threats or pressing problems with AI that need to be addressed—there are, and we’ve needed to address them, like, yesterday—but I want to take a little time to talk about what’s possible in hope that we’ll get there one day.

Other text

Joe’s part spends a lot of time talking about computer-vision types generating other words. He highlights a ton of true issues with the current state of things. And while computer-vision concepts continue to improve in the quality and complexity of information in their information, their benefits aren’t wonderful. As he rightly points out, the current state of image analysis is pretty poor—especially for certain image types—in large part because current AI systems examine images in isolation rather than within the contexts that they’re in ( which is a consequence of having separate “foundation” models for text analysis and image analysis ). Today’s models aren’t trained to distinguish between images that are contextually relevant ( that should probably have descriptions ) and those that are purely decorative ( which might not need a description ) either. Still, I still think there’s potential in this space.

As Joe mentions, human-in-the-loop authoring of alt text should absolutely be a thing. And if AI can pop in to offer a starting point for alt text—even if that starting point might be a prompt saying What is this BS? That’s not right at all … Let me try to offer a starting point— I think that’s a win.

Taking things a step further, if we can specifically train a model to analyze image usage in context, it could help us more quickly identify which images are likely to be decorative and which ones likely require a description. That will help reinforce which contexts call for image descriptions and it’ll improve authors ‘ efficiency toward making their pages more accessible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way ( even for humans ), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s suppose that you came across a chart whose description was simply the title of the chart and the kind of visualization it was, such as: Pie chart comparing smartphone usage to feature phone usage among US households making under$ 30, 000 a year. ( That would be a pretty awful alt text for a chart since that would tend to leave many questions about the data unanswered, but then again, let’s suppose that that was the description that was in place. ) If your browser knew that that image was a pie chart ( because an onboard model concluded this ), imagine a world where users could ask questions like these about the graphic:

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

Setting aside the realities of large language model ( LLM) hallucinations—where a model just makes up plausible-sounding “facts” —for a moment, the opportunity to learn more about images and data in this way could be revolutionary for blind and low-vision folks as well as for people with various forms of color blindness, cognitive disabilities, and so on. It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

Taking things a step further: What if you could ask your browser to simplify a complex chart? What if you could ask it to isolate a single line on a line graph? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you could ask it to swap colors for patterns? Given these tools ‘ chat-based interfaces and our existing ability to manipulate images in today’s AI tools, that seems like a possibility.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. For example, perhaps it could turn that pie chart ( or better yet, a series of pie charts ) into more accessible ( and useful ) formats, like spreadsheets. That would be amazing!

Matching algorithms

Safiya Umoja Noble absolutely hit the nail on the head when she titled her book Algorithms of Oppression. While her book was focused on the ways that search engines reinforce racism, I think that it’s equally true that all computer models have the potential to amplify conflict, bias, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. A lot of this stems from a lack of diversity among the people who shape and build them. When these platforms are built with inclusively baked in, however, there’s real potential for algorithm development to help people with disabilities.

Take Mentra, for example. They are an employment network for neurodivergent people. They use an algorithm to match job seekers with potential employers based on over 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it considers each work environment, communication factors related to each job, and the like. As a company run by neurodivergent folks, Mentra made the decision to flip the script when it came to typical employment sites. They use their algorithm to propose available candidates to companies, who can then connect with job seekers that they are interested in, reducing the emotional and physical labor on the job-seeker side of things.

When more people with disabilities are involved in the creation of algorithms, that can reduce the chances that these algorithms will inflict harm on their communities. That’s why diverse teams are so important.

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

Other ways that AI can helps people with disabilities

If I weren’t trying to put this together between other tasks, I’m sure that I could go on and on, providing all kinds of examples of how AI could be used to help people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

Voice preservation. You may have seen the VALL-E paper or Apple’s Global Accessibility Awareness Day announcement or you may be familiar with the voice-preservation offerings from Microsoft, Acapela, or others. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS ( Lou Gehrig’s disease ) or motor-neuron disease or other medical conditions that can lead to an inability to talk. This is, of course, the same tech that can also be used to create audio deepfakes, so it’s something that we need to approach responsibly, but the tech has truly transformative potential.
• Voice recognition. Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are actively recruiting people with Parkinson’s and related conditions, and they have plans to expand this to other conditions as the project progresses. This research will result in more inclusive data sets that will let more people with disabilities use voice assistants, dictation software, and voice-response services as well as control their computers and other devices more easily, using only their voice.
• Text transformation. The current generation of LLMs is quite capable of adjusting existing text content without injecting hallucinations. This is hugely empowering for people with cognitive disabilities who may benefit from text summaries or simplified versions of text or even text that’s prepped for Bionic Reading.

The importance of diverse teams and data

We need to recognize that our differences matter. Our lived experiences are influenced by the intersections of the identities that we exist in. These lived experiences—with all their complexities ( and joys and pain ) —are valuable inputs to the software, services, and societies that we shape. Our differences need to be represented in the data that we use to train new models, and the folks who contribute that valuable information need to be compensated for sharing it with us. Inclusive data sets yield more robust models that foster more equitable outcomes.

Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that you have content about disabilities that’s authored by people with a range of disabilities, and make sure that that’s well represented in the training data.

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

Want a coding copilot that gives you accessible recommendations from the jump? Train it on code that you know to be accessible.

I have no doubt that AI can and will harm people … today, tomorrow, and well into the future. But I also believe that we can acknowledge that and, with an eye towards accessibility ( and, more broadly, inclusion ), make thoughtful, considerate, and intentional changes in our approaches to AI that will reduce harm over time as well. Today, tomorrow, and well into the future.

Many thanks to Kartik Sawhney for helping me with the development of this piece, Ashley Bischoff for her invaluable editorial assistance, and, of course, Joe Dolson for the prompt.

I am a innovative. What I do is alchemy. It is a secret. I do not so many do it, since let it be done through me.

I am a artistic. Not all imaginative people like this brand. No all see themselves this method. Some creative individuals see research in what they do. That is their reality, and I regard it. Sometimes I even envy them, a minor. But my approach is different—my becoming is unique.

Apologizing and qualifying in advance is a diversion. That’s what my mind does to destroy me. I set it aside for today. I may come back later to forgive and count. After I’ve said what I came to say. Which is challenging enough.

Except when it is simple and flows like a river of liquor.

Sometimes it does come that approach. Maybe what I need to make comes in an instant. I have learned not to say it at that time, because if you admit that sometimes the plan only comes and it is the best idea and you know it is the best idea, they think you don’t work hard enough.

Maybe I work and work and work until the plan comes. Often it comes suddenly and I don’t tell people for three weeks. Maybe I’m so excited by the idea that came immediately that I blurt it out, can’t help myself. Like a child who found a medal in his Cracker Jacks. Often I get away with this. Maybe other people agree: yes, that is the best idea. Most times they don’t and I regret having given way to joy.

Passion is best saved for the conference where it will make a difference. Certainly the casual get-together that accompanies that gathering by two different meetings. Anyone knows why we have all these discussions. We keep saying we’re doing away with them, but then only finding different ways to include them. Sometimes they are also excellent. But other days they are a distraction from the actual labor. The percentages between when conferences are important, and when they are a sad distraction, vary, depending on what you do and where you do it. And who you are and how you do it. Suddenly I digress. I am a artistic. That is the style.

Often many hours of hard and persistent work produce something that is rarely serviceable. Maybe I have to accept that and move on to the next task.

Don’t question about method. I am a artistic.

I am a innovative. I don’t handle my desires. And I don’t handle my best tips.

I can nail aside, surround myself with information or photos, and maybe that works. I can go for a walk, and maybe that works. I may be making breakfast and there’s a Eureka having nothing to do with sizzling oil and flowing pots. Usually I know what to do the instant I wake up. And then, nearly as often, as I become aware and part of the world once, the idea that may have saved me turns to vanishing sand in a senseless storm of nothingness. For imagination, I believe, comes from that other planet. The one we enter in aspirations, and possibly, before conception and after death. But that’s for writers to know, and I am not a writer. I am a artistic. And it’s for theologians to large forces about in their artistic world that they insist is true. But that is another diversion. And a miserable one. Even on a much more important issue than whether I am a inventive or not. But nevertheless a diversion from what I came here to say.

Often the process is mitigation. And horror. You know the cliché about the tortured actor? It’s true, even when the artist ( and let’s put that noun in quotes ) is trying to write a soft drink jingle, a callback in a tired sitcom, a budget request.

Some people who hate being called artistic may become closeted artists, but that’s between them and their angels. No offence meant. Your wisdom is correct, too. But mine is for me.

Creatives understand artists.

Creatives identify creatives like faggots recognize queers, like true rappers recognize true performers, like cons know cons. Creatives feel enormous regard for creatives. We love, respect, emulate, and nearly deify the excellent ones. To revere any man is, of course, a dreadful mistake. We have been warned. We know much. We know people are simply people. They dispute, they are depressed, they regret their most critical decisions, they are weak and thirsty, they can be cruel, they can be just as terrible as we can, if, like us, they are clay. But. But. But they make this wonderful thing. They beginning something that did not exist before them, and could not occur without them. They are the mother of suggestions. And I suppose, since it’s only lying it, I have to put that they are the mother of technology. Ba ho backside! Okay, that’s done. Continue.

Creatives disparage our personal small successes, because we compare them to those of the wonderful people. Wonderful graphics! Also, I‘m no Miyazaki. Now THAT is brilliance. That is brilliance directly from the mind of God. This half-starved small item that I made? It more or less fell off the back of the pumpkin trailer. And the carrots weren’t even clean.

Creatives knows that, at best, they are Salieri. Yet the creatives who are He feel that.

I am a artistic. I haven’t worked in advertising in 30 years, but in my hallucinations, it’s my former artistic managers who judge me. And they are appropriate to do so. I am very lazy, overly simplistic, and when it actually counts, my mind goes blank. There is no supplement for artistic function.

I am a innovative. Every date I make is an experience that makes Indiana Jones look like a retiree snoring in a balcony seat. The longer I remain a artistic, the faster I am when I do my job and the longer I brood and move in circles and gaze blankly before I do that job.

I am also 10 times faster than people who are not artistic, or people who have just been imaginative a short while, or people who have just been properly imaginative a short while. It’s just that, before I work 10 times as fast as they do, I spend twice as long as they do putting the work out. I am that confident in my ability to do a wonderful work when I put my mind to it. I am that attached to the excitement scramble of delay. I am also that scared of the climb.

I am not an actor.

I am a artistic. No an actor. Though I dreamed, as a child, of eventually being that. Some of us disparage our products and like ourselves because we are not Michelangelos and Warhols. That is narcissism—but at least we aren’t in elections.

I am a innovative. Though I believe in reason and science, I decide by intelligence and urge. And sit with what follows—the calamities as well as the successes.

I am a innovative. Every term I’ve said these may offend another artists, who see things differently. Ask two artists a problem, get three ideas. Our dispute, our love about it, and our responsibility to our own reality are, at least to me, the facts that we are artists, no matter how we may think about it.

I am a artistic. I lament my lack of taste in the places about which I know quite small, which is to say almost all areas of human knowledge. And I trust my preference above all other items in the regions closest to my soul, or perhaps, more precisely, to my passions. Without my passions, I would probably have to spend my time looking career in the eye, and virtually none of us can do that for longer. No seriously. No truly. Because many in existence, if you really look at it, is terrible.

I am a artistic. I believe, as a family believes, that when I am gone, some little good part of me will take on in the head of at least one other people.

Working saves me from worrying about job.

I am a artistic. I live in despair of my little present immediately going ahead.

I am a artistic. I am very active making the next thing to spend too much time seriously considering that almost nothing I make does come anywhere near the glory I awkwardly aspire to.

I am a innovative. I believe in the greatest mystery of operation. I believe in it so much, I am actually foolish enough to submit an essay I dictated into a small machine and didn’t take time to evaluate or update. I won’t do this often, I promise. But I did it just now, because, as afraid as I might be of your seeing through my pitiful gestures toward the beautiful, I was even more afraid of forgetting what I came to say.

There. I think I’ve said it.

How to Be Human in the Age of AI: Promotion Strategies for 2025 written by John Jantsch read more at Duct Tape Marketing

Table of Contents Begin with Strategy—Not Shiny ThingsEmotional Intelligence Also WinsStorytelling Is Your PowerhouseUnderstand Your Voice—and Stick to ItGet SpecificUse AI to Improve Your Team—Not Change ThemYou Don’t Have to King It All Now Come face it—marketing in 2025 feels like a whirlwind. Artificial devices are outside. They’re writing copy, designing graphics, analyzing data, ]… ]

How to Be Human in the Age of AI: Promotion Strategies for 2025 written by John Jantsch read more at Duct Tape Marketing

” How will the end of the world come upon us”? There are certain brands in every business that generate an additional level of excitement and expectation for their respective assignments. They’ve earned the audience’s faith, which if implemented correctly, you keep these storytellers important for an entire career. Shinichirō Watanabe has a remarkable movie that ]…]

The article Lazarus Review: Shinichiro Watanabe Tunes His Greatest Hits appeared initially on Den of Geek.

House of the Dragon year 2 had a bit of a crescendo problem. As has been heavily covered at Den of Geek and by the Militant Geek Industrial Complex of the internet at large, the second year of HBO&#8217, s first Game of Thrones prelude just kind of ends.

House of the Dragon season 2 episode 8 &#8220, The Queen Who Ever Was&#8221, puts in some noble effort to set up no fewer than three key incoming fights and then does n&#8217, t get round to depicting them. While the show has its reasons for cutting things off quickly, year 2&#8217, s letdown does put a lot of pressure on time 3 to take the terrible action. Fortunately, HBO revealed now that not only is House of the Dragon year 3 publicly in production, but it &#8217, s likewise cast two important tasks that point to some military conflict to come.

Here are the relevant details on the two new characters and the actors who play them.

Tommy Flanagan as Ser Roderick Dustin

Ser Roderick Dustin is the Lord of Barrowton and the head of House Dustin, which is sworn to House Stark of Winterfell. If you recall, Lord Cregan Stark ( Tom Taylor ) swore The North&#8217, s allegiance to Queen Rhaenyra ( Emma D&#8217, Arcy ) and her Black faction at the beginning of season 2. As such, Ser Roderick is one of many Northmen marching south towards the Neck to assist the dragon queen.

Another thing you might recall from season 2 is that Lord Cregan can&#8217, t necessarily afford to send his youngest, best, and brightest to battle at the moment &#8211, you know, with winter coming and all. Still, Lord Cregan promises that even the elder Northerners will be fierce fighters for Queen Rhaenyra. Ser Roderick is great evidence of that.

Known as &#8220, Roddy the Ruin, &#8221, Ser Roderick Dustin is an absolute beast on the battlefield despite his advanced age. He is the general who Lord Cregan has entrusted with leading an army of 2, 000 &#8220, Winter Wolves &#8221, to support Rhaenyra&#8217, s claim. Ser Roderick will eventually lead the charge into a battle known as the &#8220, Butcher&#8217, s Ball&#8221, &#8211, a particularly blood event ( even by Westerosi standards ).

Playing Ser Roderick is Tommy Flanagan, a Scottish actor best known for his role as Chibs in Sons of Anarchy and for his genre work in projects like Guardians of the Galaxy Vol. 2, Gotham, and Westworld. He also just happens to have distinctive facial scarring that will give Ser Roderick an extra dimension of badassery.

Dan Fogler as Ser Torrhen Manderly

Ser Torrhen Manderly is a member of House Manderly, which just happens to be one of my personal favorite families from the Game of Thrones mythos. A long time ago in the Age of Heroes, House Manderly was cast out of its homestead in the Reach by King Gwayne III Gardener. They traveled the continent of Westeros, searching for a new home and ultimately being granted lands in The North by House Stark. The Manderlys &#8217, gratitude for this offering has lasted for thousands of years making them one of House Stark&#8217, s absolute ride-or-dies. Manderly men also tend to be both very brave and very rotund, hammering home the story &#8217, s themes that heroism can come in any form.

Ser Torrhen is currently riding down with Ser Roderick and the Winter Wolves. He will have a major role to play in incoming battles and their subsequent diplomacy and negotiations. Playing Ser Torrhen is Dan Fogler. One of the few American actors to join the Game of Thrones universe, Fogler is best known for his roles in the Fantastic Beasts films, The Walking Dead, and for playing Francis Ford Coppola in Paramount+&#8217, s The Offer.

House of the Dragon season 3 does not yet have a release date but has been confirmed to contain eight episodes.

The post House of the Dragon Season 3 Castings Point to a Bloody Battle appeared first on Den of Geek.

House of the Dragon winter 2 had a bit of a crescendo problem. As has been heavily covered at Den of Geek and by the Militant Geek Industrial Complex of the internet at large, the second year of HBO’s second Game of Thrones prequel just kind of ends. House of the Dragon season 2 episode]… ]

The article House of the Dragon Season 3 Castings Point to a Bloody Battle appeared initially on Den of Geek.

House of the Dragon year 2 had a bit of a crescendo problem. As has been heavily covered at Den of Geek and by the Militant Geek Industrial Complex of the internet at large, the second year of HBO&#8217, s first Game of Thrones prelude just kind of ends.

House of the Dragon season 2 episode 8 &#8220, The Queen Who Ever Was&#8221, puts in some noble effort to set up no fewer than three key incoming fights and then does n&#8217, t get round to depicting them. While the show has its reasons for cutting things off quickly, year 2&#8217, s letdown does put a lot of pressure on time 3 to take the terrible action. Fortunately, HBO revealed now that not only is House of the Dragon year 3 publicly in production, but it &#8217, s likewise cast two important tasks that point to some military conflict to come.

Here are the relevant details on the two new characters and the actors who play them.

Tommy Flanagan as Ser Roderick Dustin

Ser Roderick Dustin is the Lord of Barrowton and the head of House Dustin, which is sworn to House Stark of Winterfell. If you recall, Lord Cregan Stark ( Tom Taylor ) swore The North&#8217, s allegiance to Queen Rhaenyra ( Emma D&#8217, Arcy ) and her Black faction at the beginning of season 2. As such, Ser Roderick is one of many Northmen marching south towards the Neck to assist the dragon queen.

Another thing you might recall from season 2 is that Lord Cregan can&#8217, t necessarily afford to send his youngest, best, and brightest to battle at the moment &#8211, you know, with winter coming and all. Still, Lord Cregan promises that even the elder Northerners will be fierce fighters for Queen Rhaenyra. Ser Roderick is great evidence of that.

Known as &#8220, Roddy the Ruin, &#8221, Ser Roderick Dustin is an absolute beast on the battlefield despite his advanced age. He is the general who Lord Cregan has entrusted with leading an army of 2, 000 &#8220, Winter Wolves &#8221, to support Rhaenyra&#8217, s claim. Ser Roderick will eventually lead the charge into a battle known as the &#8220, Butcher&#8217, s Ball&#8221, &#8211, a particularly blood event ( even by Westerosi standards ).

Playing Ser Roderick is Tommy Flanagan, a Scottish actor best known for his role as Chibs in Sons of Anarchy and for his genre work in projects like Guardians of the Galaxy Vol. 2, Gotham, and Westworld. He also just happens to have distinctive facial scarring that will give Ser Roderick an extra dimension of badassery.

Dan Fogler as Ser Torrhen Manderly

Ser Torrhen Manderly is a member of House Manderly, which just happens to be one of my personal favorite families from the Game of Thrones mythos. A long time ago in the Age of Heroes, House Manderly was cast out of its homestead in the Reach by King Gwayne III Gardener. They traveled the continent of Westeros, searching for a new home and ultimately being granted lands in The North by House Stark. The Manderlys &#8217, gratitude for this offering has lasted for thousands of years making them one of House Stark&#8217, s absolute ride-or-dies. Manderly men also tend to be both very brave and very rotund, hammering home the story &#8217, s themes that heroism can come in any form.

Ser Torrhen is currently riding down with Ser Roderick and the Winter Wolves. He will have a major role to play in incoming battles and their subsequent diplomacy and negotiations. Playing Ser Torrhen is Dan Fogler. One of the few American actors to join the Game of Thrones universe, Fogler is best known for his roles in the Fantastic Beasts films, The Walking Dead, and for playing Francis Ford Coppola in Paramount+&#8217, s The Offer.

House of the Dragon season 3 does not yet have a release date but has been confirmed to contain eight episodes.

The article House of the Dragon Season 3 Castings Point to a Bloody Battle appeared initially on Den of Geek.

Jonathan Hickman has been playing in the Marvel Universe for 15 years today and almost no one can place a greater say to the universe’s beauty in that time than him. Not only did he destroy the Marvel Multiverse ( in the greatest superhero crossover of all time, Secret Wars ), but he shaped the now-dead original ]…]

The article Hickman’s Imperial: Marvel’s Space Epic A Decade In The Making appeared second on Den of Geek.

House of the Dragon winter 2 had a bit of a crescendo problem. As has been heavily covered at Den of Geek and by the Militant Geek Industrial Complex of the internet at large, the second year of HBO&#8217, s first Game of Thrones prelude just kind of ends.

House of the Dragon season 2 episode 8 &#8220, The Queen Who Ever Was&#8221, puts in some noble effort to set up no fewer than three key incoming fights and then does n&#8217, t get round to depicting them. While the show has its reasons for cutting things off quickly, year 2&#8217, s letdown does put a lot of pressure on time 3 to take the terrible action. Fortunately, HBO revealed now that not only is House of the Dragon year 3 publicly in production, but it &#8217, s likewise cast two important tasks that point to some military conflict to come.

Here are the relevant details on the two new characters and the actors who play them.

Tommy Flanagan as Ser Roderick Dustin

Ser Roderick Dustin is the Lord of Barrowton and the head of House Dustin, which is sworn to House Stark of Winterfell. If you recall, Lord Cregan Stark ( Tom Taylor ) swore The North&#8217, s allegiance to Queen Rhaenyra ( Emma D&#8217, Arcy ) and her Black faction at the beginning of season 2. As such, Ser Roderick is one of many Northmen marching south towards the Neck to assist the dragon queen.

Another thing you might recall from season 2 is that Lord Cregan can&#8217, t necessarily afford to send his youngest, best, and brightest to battle at the moment &#8211, you know, with winter coming and all. Still, Lord Cregan promises that even the elder Northerners will be fierce fighters for Queen Rhaenyra. Ser Roderick is great evidence of that.

Known as &#8220, Roddy the Ruin, &#8221, Ser Roderick Dustin is an absolute beast on the battlefield despite his advanced age. He is the general who Lord Cregan has entrusted with leading an army of 2, 000 &#8220, Winter Wolves &#8221, to support Rhaenyra&#8217, s claim. Ser Roderick will eventually lead the charge into a battle known as the &#8220, Butcher&#8217, s Ball&#8221, &#8211, a particularly blood event ( even by Westerosi standards ).

Playing Ser Roderick is Tommy Flanagan, a Scottish actor best known for his role as Chibs in Sons of Anarchy and for his genre work in projects like Guardians of the Galaxy Vol. 2, Gotham, and Westworld. He also just happens to have distinctive facial scarring that will give Ser Roderick an extra dimension of badassery.

Dan Fogler as Ser Torrhen Manderly

Ser Torrhen Manderly is a member of House Manderly, which just happens to be one of my personal favorite families from the Game of Thrones mythos. A long time ago in the Age of Heroes, House Manderly was cast out of its homestead in the Reach by King Gwayne III Gardener. They traveled the continent of Westeros, searching for a new home and ultimately being granted lands in The North by House Stark. The Manderlys &#8217, gratitude for this offering has lasted for thousands of years making them one of House Stark&#8217, s absolute ride-or-dies. Manderly men also tend to be both very brave and very rotund, hammering home the story &#8217, s themes that heroism can come in any form.

Ser Torrhen is currently riding down with Ser Roderick and the Winter Wolves. He will have a major role to play in incoming battles and their subsequent diplomacy and negotiations. Playing Ser Torrhen is Dan Fogler. One of the few American actors to join the Game of Thrones universe, Fogler is best known for his roles in the Fantastic Beasts films, The Walking Dead, and for playing Francis Ford Coppola in Paramount+&#8217, s The Offer.

House of the Dragon season 3 does not yet have a release date but has been confirmed to contain eight episodes.

The post House of the Dragon Season 3 Castings Point to a Bloody Battle appeared first on Den of Geek.

We agree: the computer-generated eyes could be a great fit for personas—but not for the purpose you might think. Ironically, the website highlights the core issue of this very common design method: the person ( a ) does not exist. Personas are deliberately created, just like in the pictures. Knowledge is taken out of natural environment and recombined into an isolated preview that’s detached from reality.

However, oddly enough, people are personalities to serve as a source of inspiration for architecture in the real world.

Personas: A action up

Most manufacturers have created, used, or come across personalities at least once in their profession. The Interaction Design Foundation defines profile as “fictional characters, which you create based upon your research in order to represent the various consumer types that might use your company, product, page, or brand” in their article” Personas- A Simple Introduction.” In their most complete expression, personas typically consist of a name, profile picture, quotes, demographics, goals, needs, behavior in relation to a certain service/product, emotions, and motivations ( for example, see Creative Companion’s Persona Core Poster ). According to design firm Designit, the goal of personas is to “make the research relateable, ]and ] easy to communicate, digest, reference, and apply to product and service development.”

The decontextualization of personalities

Personas are common because they make “dry” research information more realistic, more people. However, this approach places a cap on the study’s ability to analyze the data in a way that excludes the subjects from their particular contexts. As a result, personalities don’t describe important factors that make you know their decision-making method or allow you to connect to users ‘ thoughts and behavior, they lack stories. You are aware of the persona’s actions, but you lack the knowledge to know why. You end up with depictions of people that are really less people.

This “decontextualization” we see in identities happens in four way, which we’ll discuss below.

People are assumed to be stable, according to individuals.

Although many companies still try to box in their employees and customers with outdated personality tests ( referring to you, Myers-Briggs ), here’s a painfully obvious truth: people are not a fixed set of features. Depending on how you feel, how you act, think, and think, you go about doing things. You appear distinct to different people, you may act pleasant to some, tough to others. And you change your mind all the time about choices you’ve taken.

Current psychologists concur that while individuals typically act in accordance with specific patterns, how people act and make decisions is ultimately influenced by a combination of history and culture. The context—the atmosphere, the effect of other people, your feelings, the whole story that led up to a situation—determines the kind of person you are in each particular time.

Personas do not account for this variability in their attempt to improve reality; instead, they present a consumer as a set of features. Like character tests, personas seize people away from real life. Even worse, individuals are reduced to a brand and categorized as” that kind of guy” with no means to practice their inherent flexibility. This behavior lowers variety, reinforces stereotypes, and doesn’t reveal reality.

Personas rely on people, not the environment

In the real world, you’re creating content for a situation, not an entity. Each individual lives in a community, a group, an habitat, where there are environmental, social, and cultural factors you need to consider. A pattern is not meant for a single customer. Instead, you create a pattern for one or more specific situations where a certain product might be used by a large number of people. Personas, yet, show the customer alone rather than explain how the consumer relates to the environment.

Would you choose the exact course of action repeatedly? Maybe you’re a dedicated vegan but also decide to buy some meats when your family are coming across. As they depend on various situations and characteristics, your decisions—and behavior, thoughts, and comments —are no absolute but extremely contextual. Because it doesn’t explain the grounds of your decisions, the persona that “represents” you doesn’t take into account this interdependence. It doesn’t provide a explanation of why you act the way you do. People practice the well-known attribution error, which states that they too often attribute others ‘ behavior to their personalities and not to the circumstances.

As mentioned by the Interaction Design Foundation, identities are often placed in a situation that’s a” specific environment with a problem they want to or have to solve “—does that mean environment actually is considered? Unfortunately, what often happens is that you take a fictional character and based on that fiction determine how this character might deal with a certain situation. How could you possibly understand how someone you want to represent behave in new circumstances if you hadn’t even fully investigated and understood the current context of the people you want to represent?

Personas are meaningless averages

A persona is depicted as a specific person in Shlomo Goltz’s introduction to Smashing Magazine, according to Shlomo Goltz’s introduction article. It is instead made up of observations from numerous people. A well-known critique to this aspect of personas is that the average person does not exist, as per the famous example of the USA Air Force designing planes based on the average of 140 of their pilots ‘ physical dimensions and not a single pilot actually fitting within that average seat.

The same limitation applies to mental aspects of people. Have you ever heard a famous person say something was taken out of context? They used my words, but I didn’t mean it like that”. The celebrity’s statement was literally reported, but the reporter failed to explain the context and how the non-verbal expressions were used. As a result, the intended meaning was lost. You do the same when you create personas: you collect somebody’s statement ( or goal, or need, or emotion ), of which the meaning can only be understood if you provide its own specific context, yet report it as an isolated finding.

However, personas go one step further, combining a decontextualized finding with another decontextualized finding from another. The resulting set of findings often does not make sense: it’s unclear, or even contrasting, because it lacks the underlying reasons on why and how that finding has arisen. It lacks any significance. And the persona doesn’t give you the full background of the person ( s ) to uncover this meaning: you would need to dive into the raw data for each single persona item to find it. What, then, is the usefulness of the persona?

People’s relatability can be deceiving.

To a certain extent, designers realize that a persona is a lifeless average. To combat this, designers create and add “relatable” details to personas to make them appear to be real people. Nothing captures the absurdity of this better than a sentence by the Interaction Design Foundation:” Add a few fictional personal details to make the persona a realistic character”. In other words, you add non-realism in an attempt to create more realism. Wouldn’t it be much more responsible to emphasize that John is only an abstraction while deliberately obscuring the fact that” John Doe” is an abstract representation of research findings? If something is artificial, let’s present it as such.

After accepting that people’s personalities are fixed, dismissed the importance of their environment, and hidden meaning by joining isolated, non-generalizable findings, designers create new context to create ( their own ) meaning. In doing so, as with everything they create, they introduce a host of biases. As phrased by Designit, as designers we can” contextualize]the persona ] based on our reality and experience. We make connections that are well-known to us. This practice reinforces stereotypes, doesn’t reflect real-world diversity, and gets further away from people’s actual reality with every detail added.

To conduct effective design research, we must report the “as-is” reality and make it relatable for our audience so that everyone can use their own empathy and formula for their own interpretation and emotional response.

Dynamic Selves: The alternative to personas

If we shouldn’t use personas, what should we do instead?

Designit suggested utilizing mindsets rather than personas. Each Mindset is a” spectrum of attitudes and emotional responses that different people have within the same context or life experience”. It challenges designers to avoid getting fixated on just one person’s way of being. Unfortunately, while being a step in the right direction, this proposal doesn’t take into account that people are part of an environment that determines their personality, their behavior, and, yes, their mindset. Therefore, Mindsets are also not absolute but change in regard to the situation. What determines a certain Mindset, is the question still unanswered.

Another alternative comes from Margaret P., author of the article” Kill Your Personas“, who has argued for replacing personas with persona spectrums that consist of a range of user abilities. For instance, a visual impairment could be permanent ( blindness ), temporary ( recovery from eye surgery ), or situational (screen glare ). Persona spectrums are highly useful for more inclusive and context-based design, as they’re based on the understanding that the context is the pattern, not the personality. Their limitation, however, is that they have a very functional take on users that misses the relatability of a real person taken from within a spectrum.

We want to change the traditional design process to be context-based by creating an alternative to personas. Contexts are generalizable and have patterns that we can identify, just like we tried to do previously with people. So how do we learn these patterns? How do we ensure truly context-based design?

Understand real individuals in multiple contexts

Nothing can be more relatable and inspiring than reality. Therefore, we have to understand real individuals in their multi-faceted contexts, and use this understanding to fuel our design. This approach is known as Dynamic Selves.

Let’s take a look at what the approach looks like, based on an example of how one of us applied it in a recent project that researched habits of Italians around energy consumption. We drafted a design research plan aimed at investigating people’s attitudes toward energy consumption and sustainable behavior, with a focus on smart thermostats.

1. Choose the right sample

We frequently get slammed for saying,” Where are you going to find a single person that encapsulates all the information from one of these advanced personas ]” when we debate personas. The answer is simple: you don’t have to. You don’t need to have information about many people for your insights to be deep and meaningful.

In qualitative research, accuracy comes from accurate sampling rather than quantity. You select the people that best represent the “population” you’re designing for. You can infer how the rest of the population thinks and acts if this sample is chosen wisely and you have a deep understanding of the sampled people. There’s no need to study seven Susans and five Yuriys, one of each will do.

Similarly, you don’t need to understand Susan in fifteen different contexts. Once you’ve seen her in a few different settings, you’ve come to understand how Susan responds to various circumstances. Not Susan as an atomic being but Susan in relation to the surrounding environment: how she might act, feel, and think in different situations.

It becomes clear why each person should be portrayed as an individual because each already represents an abstraction of a larger group of people in similar circumstances because each person is representative of a portion of the total population you’re researching. You don’t want abstractions of abstractions! These selected people need to be understood and shown in their full expression, remaining in their microcosmos—and if you want to identify patterns you can focus on identifying patterns in contexts.

However, the question persists: how do you choose a sample representative? First of all, you have to consider what’s the target audience of the product or service you are designing: it might be useful to look at the company’s goals and strategy, the current customer base, and/or a possible future target audience.

We were creating an application for those who own a smart thermostat in our example project. In the future, everyone could have a smart thermostat in their house. Right now, though, only early adopters own one. We had to understand the causes behind these early adopters ‘ development in order to create a sizable sample. We therefore recruited by asking people why they had a smart thermostat and how they got it. There were those who had chosen to purchase it, those who had been influenced by others, and those who had discovered it in their homes. So we selected representatives of these three situations, from different age groups and geographical locations, with an equal balance of tech savvy and non-tech savvy participants.

2. Conduct your research

After having chosen and recruited your sample, conduct your research using ethnographic methodologies. This will give you more examples and anecdotes to enrich your qualitative data. In our example project, given COVID-19 restrictions, we converted an in-house ethnographic research effort into remote family interviews, conducted from home and accompanied by diary studies.

To gain an in-depth understanding of attitudes and decision-making trade-offs, the research focus was not limited to the interviewee alone but deliberately included the whole family. Each interviewee would provide a story that would then become much more interesting and precise with the additions made by their spouses, husbands, kids, or occasionally even pets. We also focused on the relationships with other meaningful people ( such as colleagues or distant family ) and all the behaviors that resulted from those relationships. This extensive field of study gave us the ability to create a vivid mental image of dynamic situations involving multiple actors.

It’s essential that the scope of the research remains broad enough to be able to include all possible actors. Therefore, it normally works best to define broad research areas with macro questions. Follow-up questions will be written down in a way that is best suited for an interview, and they should be conducted in a semi-structured manner. This open-minded “plan to be surprised” will yield the most insightful findings. One of our participants responded,” My wife has not installed the thermostat’s app; she uses WhatsApp instead,” when we asked how his family controlled the house temperature. If she wants to turn on the heater and she is not home, she will text me. I am her thermostat”.

3. Analysis: Create the Dynamic Selves

You begin to represent each individual with several Dynamic Selves, each” Self” representing one of the circumstances you have examined throughout the research analysis. The core of each Dynamic Self is a quote, which comes supported by a photo and a few relevant demographics that illustrate the wider context. The research findings themselves will show which demographics are relevant to show. The important demographics were family type, number and type of houses owned, economic status, and technological maturity in our case because our research focused on families and their way of life to understand their needs for thermal regulation. ( We also included the individual’s name and age, but they’re optional—we included them to ease the stakeholders ‘ transition from personas and be able to connect multiple actions and contexts to the same person ).

Interviews and notes must be recorded verbatim as much as possible in order to capture precise quotes. This is essential to the truthfulness of the several Selves of each participant. In the case of real-life ethnographic research, photos of the context and anonymized actors are essential to build realistic Selves. These photos should be taken directly from field research, but any image that is evocative and representative will do, as long as it’s accurate and depicts meaningful actions that you associate with your participants. For example, one of our interviewees told us about his mountain home where he used to spend every weekend with his family. We depicted him hiking with his young daughter as a result.

At the end of the research analysis, we displayed all of the Selves ‘” cards” on a single canvas, categorized by activities. Each card displayed a situation, represented by a quote and a unique photo. Each participant had a different deck full of self-assessments.

4. Identify creative uses

Once you have collected all main quotes from the interview transcripts and diaries, and laid them all down as Self cards, you will see patterns emerge. These patterns will highlight the opportunity areas for new product creation, new functionalities, and new services—for new design.

A particularly intriguing finding was made in our example project regarding the concept of humidity. We realized that people don’t know what humidity is and why it is important to monitor it for health: an environment that’s too dry or too wet can cause respiratory problems or worsen existing ones. This made clear that our client had a significant opportunity to train users about the concept and work as a health advisor.

Benefits of Dynamic Selves

When you use the Dynamic Selves approach in your research, you start to notice unique social relations, peculiar situations real people face and the actions that follow, and that people are surrounded by changing environments. One of the participants in our thermostat project, Davide, is described as a boyfriend, dog lover, and tech nut.

Davide is an individual we might have once reduced to a persona called “tech enthusiast”. However, there are also those who are wealthy or poor, who are tech enthusiasts and have families or are single. Their motivations and priorities when deciding to purchase a new thermostat can be opposite according to these different frames.

Once you have understood Davide in multiple situations, and for each situation have understood in sufficient depth the underlying reasons for his behavior, you’re able to generalize how he would act in another situation. You can use your understanding of him to predict what he would think and act in the situations ( or scenarios ) you create.

The Dynamic Selves approach aims to dismiss the conflicted dual purpose of personas—to summarize and empathize at the same time—by separating your research summary from the people you’re seeking to empathize with. This is crucial because scale affects how we feel empathy for people; the bigger the group, the smaller it is to feel empathy for others. We feel the strongest empathy for individuals we can personally relate to.

If you take a real person as inspiration for your design, you no longer need to create an artificial character. No more creating new plot devices to “realize” the character, no more implausible bias. It’s simply how this person is in real life. We all know that these characters don’t really exist, so in our experience personas quickly turn into nothing more than a name in our priority guides and prototype screens.

Another powerful benefit of the Dynamic Selves approach is that it raises the stakes of your work: if you mess up your design, someone real, a person you and the team know and have met, is going to feel the consequences. It might stop you from taking shortcuts and will remind you to conduct daily checks on your designs.

Finally, real people in their specific contexts provide a better foundation for anecdotal storytelling and are thus more effective at persuasion. Documentation of real research is essential in achieving this result. It reinforces your design arguments with more urgency and weight:” When I met Alessandra, the conditions of her workplace struck me. Noise, bad ergonomics, lack of light, you name it. If we go for this functionality, I’m afraid we’re going to add complexity to her life”.

Conclusion

Designit stated in their article on Mindsets that “design thinking tools offer a shortcut to deal with reality’s complexities, but this process of simplification can occasionally flatten out people’s lives into a few general characteristics.” Unfortunately, personas have been culprits in a crime of oversimplification. They fail to account for the complex nature of our users ‘ decision-making processes and don’t take into account the fact that people are immersed in environments.

Design needs simplification but not generalization. You have to look at the research elements that stand out: the sentences that captured your attention, the images that struck you, the sounds that linger. Avoid using those and use them to describe the person in all of their contexts. Both insights and people come with a context, they cannot be cut from that context because it would remove meaning.

It’s high time for design to break away from fiction and use reality as our guide and inspiration, in all of its messy, surprising, and unquantifiable beauty.

” Any post” you might have? is perhaps one of the worst ways to ask for opinions. It’s obscure and unfocused, and it doesn’t give us a sense of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

When we realize that receiving input can be seen as a form of pattern study, it might seem counterintuitive to begin the process with a question. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

Design criticism is never a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

And suddenly, as with any great research, we need to examine what we got up, get to the base of its perspectives, and take action. Problem, generation, and analysis. This look at each of those.

The query

Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your mind” at the conclusion of a presentation are likely to garner a lot of different ideas, or worse, to make everyone follow the lead of the first speaker. And next… we get frustrated because vague issues like those can change a high-level moves review into folks rather commenting on the borders of buttons. Which topic may be a wholesome one, so it might be difficult to get the team to switch to the subject you wanted to concentrate on.

But how do we get into this scenario? It’s a combination of various aspects. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the question open and assume that everyone else will agree. Another is that in nonprofessional conversations, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, so we don’t work to make them better.

The work of asking good questions guidelines and focuses the criticism. It’s even a form of acceptance because it specifies what kind of comments you’d like to receive and how you’re open to them. It puts people in the right emotional position, especially in situations when they weren’t expecting to provide feedback.

There isn’t a second best method to request comments. It simply needs to be certain, and sensitivity can take several shapes. The one of stage than level is a design for design criticism that I’ve found to be particularly helpful in my coaching.

” Stage” refers to each of the actions of the process—in our event, the design process. The kind of feedback changes as the person research moves forward to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed opinions into updated designs as the task has evolved. The layers of user experience could serve as a starting point for future inquiries. What do you want to know: Project objectives? user requirements? Functionality? Content? Interaction design? a system of information architecture UI design? navigation planning Visual design? Branding?

Here’re a few example questions that are precise and to the point that refer to different layers:

• Functionality: Is it desirable to automate account creation?
• Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
• Information architecture: On this page, we have two competing pieces of information. Is the structure effective in communicating them both?
• User interface design: What do you think about the top-of-the-page error counter, which makes sure you can see the next error even when the error is outside the viewport?
• Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Do you have any suggestions for how to handle this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is determined by how far you would like to go with the presentation. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially helpful from one iteration to the next when it’s crucial to highlight the areas that have changed.

There are other things that we can consider when we want to achieve more specific—and more effective—questions.

A quick fix is to get rid of the generic qualifiers from questions like “good”, “well,” “nice,” “bad,” “okay,” and” cool.” For example, asking,” When the block opens and the buttons appear, is this interaction good”? is possible to appear specific, but the “good” qualifier can be found in an even better question,” When the block opens and the buttons appear, is it clear what the next action is?”

Sometimes we actually do want broad feedback. That’s uncommon, but it can occur. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps just say,” At first glance, what do you think”? so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

Sometimes the project is particularly broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding falling into rabbit holes like those that could lead to further refinement but aren’t what’s important right now.

Asking specific questions can completely change the quality of the feedback that you receive. People who have less refined critique abilities will now be able to provide more useful feedback, and even experienced designers will appreciate the clarity and effectiveness gained from concentrating solely on what is required. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Many design tools have inline commenting, but many of those methods typically display changes as a single fluid stream in the same file. These methods cause conversations to vanish once they’re resolved, update shared UI components automatically, and require designs to always display the most recent version unless these would-be useful features were manually turned off. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That’s probably not the most effective way to go about designing critiques, but even if I don’t want to be too prescriptive, it might work for some teams.

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. This can be used on any platform that can accommodate this structure. By the way, when I refer to a “write-up or presentation“, I’m including video recordings or other media too: as long as it’s asynchronous, it works.

There are many benefits to using iteration posts:

• It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
• Decisions are always available, and conversations are also made accessible for future review.
• It creates a record of how the design changed over time.
• It might also make it simpler to collect and act on feedback depending on the tool.

These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. And from there, there can develop additional feedback techniques ( such as live critique, pair designing, or inline comments ).

I don’t think there’s a standard format for iteration posts. However, there are a few high-level components that make sense as a baseline:

1. The goal
2. The layout
3. The list of changes
4. The querys

Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. Therefore, I would repeat this in every iteration post, literally copy and pasting it. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. The most recent iteration post will provide all I need to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts is actually very effective at ensuring that everyone is on the same page.

The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. It’s any design object, to put it briefly. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture.

It might also be helpful to have clear names on the artifacts so that it is easier to refer to them. Write the post in a way that helps people understand the work. It’s not much different from creating a strong live presentation.

For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

Finally, as mentioned earlier, a list of the questions must be included in order to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not every iteration is the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then, later, the iterations begin coming to a decision and improving it until the design process is complete and the feature is ready.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be just a concept to start a conversation, or it might be a cumulative list of all the features that have been added gradually over the course of each iteration until the full picture is achieved.

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

• Unique—It’s a clear unique marker. Everyone knows where to go to review things, and it’s simple to say” This was discussed in i4″ with each project.
• Unassuming—It works like versions ( such as v1, v2, and v3 ) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Attempts must be exploratory, incomplete, or partial.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to indicate when a design is finished enough to be worked on, even if there are some bits that still need work and, in turn, need more iterations:” with i8 we reached RC” or “i12 is an RC” to illustrate this.

The review

What typically occurs during a design critique is an open discussion, with a back and forth between parties that can be very productive. This approach is particularly effective during live, synchronous feedback. However, using a different approach when we work asynchronously is more effective: adopting a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

This shift has some significant advantages, making asynchronous feedback particularly effective, especially around these friction points:

1. It removes the pressure to reply to everyone.
2. It lessens the annoyance caused by swoop-by comments.
3. It lessens our personal stake.

The first friction is being forced to respond to every comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s simple, and there isn’t much to worry about. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the respondent is a stakeholder or a person who is directly involved in the project and whom we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. When we treat a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives: In asynchronous spaces, responding to all comments can be effective.

One is to let the next iteration speak for itself. That is the response when the design changes and we publish a follow-up iteration. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another option is to respond politely to acknowledge each comment, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. In the upcoming iteration, I’ll include these. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
• One more thing is to quickly summarize the comments before proceeding. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

The swoop-by comment, which is the kind of feedback that comes from a member of a team or non-project who might not be aware of the context, restrictions, decisions, or requirements, or of the discussions from earlier iterations, is the second friction point. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep coming back and forth.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, a brief response with a link to the previous discussion for additional information is typically sufficient if responding to a previously litigated point might be helpful. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting can still be useful for two reasons: first, they might point out something that isn’t clear, and second, they might have the power to fit in with a user’s perspective when they are seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

The personal stake we might have in the design could be the third friction point, which might cause us to feel defensive if the review turned into a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego ( because yes, even if we don’t want to admit it, it’s there ). In the end, presenting everything in aggregated form helps us to prioritize our work more.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come up with a conclusion that you can support, but sometimes “no” is the best choice.

As the designer leading the project, you’re in charge of that decision. In the end, everyone has their area of specialization, and the designer is the one with the most background and knowledge to make the right choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

Thanks to Mike Shelton and Brie Anne Demkiw for their initial review of this article.