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  • Opportunities for AI in Accessibility

    Opportunities for AI in Accessibility

    In reading Joe Dolson’s recent piece on the intersection of AI and accessibility, I absolutely appreciated the skepticism that he has for AI in general as well as for the ways that many have been using it. In fact, I’m very skeptical of AI myself, despite my role at Microsoft as an accessibility innovation strategist who helps run the AI for Accessibility grant program. As with any tool, AI can be used in very constructive, inclusive, and accessible ways; and it can also be used in destructive, exclusive, and harmful ones. And there are a ton of uses somewhere in the mediocre middle as well.

    I’d like you to consider this a “yes… and” piece to complement Joe’s post. I’m not trying to refute any of what he’s saying but rather provide some visibility to projects and opportunities where AI can make meaningful differences for people with disabilities. To be clear, I’m not saying that there aren’t real risks or pressing issues 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 hopes that we’ll get there one day.

    Alternative text

    Joe’s piece spends a lot of time talking about computer-vision models generating alternative text. He highlights a ton of valid issues with the current state of things. And while computer-vision models continue to improve in the quality and richness of detail in their descriptions, their results aren’t great. 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 creative.

    I am a creative.

    I am a creative. What I do is alchemy. It is a mystery. I do not so much do it, as let it be done through me.

    I am a creative. Not all creative people like this label. Not all see themselves this way. Some creative people see science in what they do. That is their truth, and I respect it. Maybe I even envy them, a little. But my process is different—my being is different.

    Apologizing and qualifying in advance is a distraction. That’s what my brain does to sabotage me. I set it aside for now. I can come back later to apologize and qualify. After I’ve said what I came to say. Which is hard enough. 

    Except when it is easy and flows like a river of wine.

    Sometimes it does come that way. Sometimes what I need to create comes in an instant. I have learned not to say it at that moment, because if you admit that sometimes the idea just comes and it is the best idea and you know it is the best idea, they think you don’t work hard enough.

    Sometimes I work and work and work until the idea comes. Sometimes it comes instantly and I don’t tell anyone for three days. Sometimes I’m so excited by the idea that came instantly that I blurt it out, can’t help myself. Like a boy who found a prize in his Cracker Jacks. Sometimes I get away with this. Sometimes other people agree: yes, that is the best idea. Most times they don’t and I regret having  given way to enthusiasm. 

    Enthusiasm is best saved for the meeting where it will make a difference. Not the casual get-together that precedes that meeting by two other meetings. Nobody knows why we have all these meetings. We keep saying we’re doing away with them, but then just finding other ways to have them. Sometimes they are even good. But other times they are a distraction from the actual work. The proportion between when meetings are useful, and when they are a pitiful distraction, varies, depending on what you do and where you do it. And who you are and how you do it. Again I digress. I am a creative. That is the theme.

    Sometimes many hours of hard and patient work produce something that is barely serviceable. Sometimes I have to accept that and move on to the next project.

    Don’t ask about process. I am a creative.

    I am a creative. I don’t control my dreams. And I don’t control my best ideas.

    I can hammer away, surround myself with facts or images, and sometimes that works. I can go for a walk, and sometimes that works. I can be making dinner and there’s a Eureka having nothing to do with sizzling oil and bubbling pots. Often I know what to do the instant I wake up. And then, almost as often, as I become conscious and part of the world again, the idea that would have saved me turns to vanishing dust in a mindless wind of oblivion. For creativity, I believe, comes from that other world. The one we enter in dreams, and perhaps, before birth and after death. But that’s for poets to wonder, and I am not a poet. I am a creative. And it’s for theologians to mass armies about in their creative world that they insist is real. But that is another digression. And a depressing one. Maybe on a much more important topic than whether I am a creative or not. But still a digression from what I came here to say.

    Sometimes the process is avoidance. And agony. You know the cliché about the tortured artist? 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 creative may be closeted creatives, but that’s between them and their gods. No offense meant. Your truth is true, too. But mine is for me. 

    Creatives recognize creatives.

    Creatives recognize creatives like queers recognize queers, like real rappers recognize real rappers, like cons know cons. Creatives feel massive respect for creatives. We love, honor, emulate, and practically deify the great ones. To deify any human is, of course, a tragic mistake. We have been warned. We know better. We know people are just people. They squabble, they are lonely, they regret their most important decisions, they are poor and hungry, they can be cruel, they can be just as stupid as we can, because, like us, they are clay. But. But. But they make this amazing thing. They birth something that did not exist before them, and could not exist without them. They are the mothers of ideas. And I suppose, since it’s just lying there, I have to add that they are the mothers of invention. Ba dum bum! OK, that’s done. Continue.

    Creatives belittle our own small achievements, because we compare them to those of the great ones. Beautiful animation! Well, I’m no Miyazaki. Now THAT is greatness. That is greatness straight from the mind of God. This half-starved little thing that I made? It more or less fell off the back of the turnip truck. And the turnips weren’t even fresh.

    Creatives knows that, at best, they are Salieri. Even the creatives who are Mozart believe that. 

    I am a creative. I haven’t worked in advertising in 30 years, but in my nightmares, it’s my former creative directors who judge me. And they are right to do so. I am too lazy, too facile, and when it really counts, my mind goes blank. There is no pill for creative dysfunction.

    I am a creative. Every deadline I make is an adventure that makes Indiana Jones look like a pensioner snoring in a deck chair. The longer I remain a creative, the faster I am when I do my work and the longer I brood and walk in circles and stare blankly before I do that work. 

    I am still 10 times faster than people who are not creative, or people who have only been creative a short while, or people who have only been professionally creative 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 off. I am that confident in my ability to do a great job when I put my mind to it. I am that addicted to the adrenaline rush of postponement. I am still that afraid of the jump.

    I am not an artist.

    I am a creative. Not an artist. Though I dreamed, as a lad, of someday being that. Some of us belittle our gifts and dislike ourselves because we are not Michelangelos and Warhols. That is narcissism—but at least we aren’t in politics.

    I am a creative. Though I believe in reason and science, I decide by intuition and impulse. And live with what follows—the catastrophes as well as the triumphs. 

    I am a creative. Every word I’ve said here will annoy other creatives, who see things differently. Ask two creatives a question, get three opinions. Our disagreement, our passion about it, and our commitment to our own truth are, at least to me, the proofs that we are creatives, no matter how we may feel about it.

    I am a creative. I lament my lack of taste in the areas about which I know very little, which is to say almost all areas of human knowledge. And I trust my taste above all other things in the areas closest to my heart, or perhaps, more accurately, to my obsessions. Without my obsessions, I would probably have to spend my time looking life in the eye, and almost none of us can do that for long. Not honestly. Not really. Because much in life, if you really look at it, is unbearable.

    I am a creative. I believe, as a parent believes, that when I am gone, some small good part of me will carry on in the mind of at least one other person.

    Working saves me from worrying about work.

    I am a creative. I live in dread of my small gift suddenly going away.

    I am a creative. I am too busy making the next thing to spend too much time deeply considering that almost nothing I make will come anywhere near the greatness I comically aspire to.

    I am a creative. I believe in the ultimate mystery of process. I believe in it so much, I am even fool enough to publish an essay I dictated into a tiny machine and didn’t take time to review or revise. 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. 

  • Design for Amiability: Lessons from Vienna

    Design for Amiability: Lessons from Vienna

    Today’s web is not always an amiable place. Sites greet you with a popover that demands assent to their cookie policy, and leave you with Taboola ads promising “One Weird Trick!” to cure your ailments. Social media sites are tuned for engagement, and few things are more engaging than a fight. Today it seems that people want to quarrel; I have seen flame wars among birders.  

    These tensions are often at odds with a site’s goals. If we are providing support and advice to customers, we don’t want those customers to wrangle with each other. If we offer news about the latest research, we want readers to feel at ease; if we promote upcoming marches, we want our core supporters to feel comfortable and we want curious newcomers to feel welcome. 

    In a study for a conference on the History of the Web, I looked to the origins of Computer Science in Vienna (1928-1934)  for a case study of the importance of amiability in a research community and the disastrous consequences of its loss. That story has interesting implications for web environments that promote amiable interaction among disparate, difficult (and sometimes disagreeable) people.

    The Vienna Circle

    Though people had been thinking about calculating engines and thinking machines from antiquity, Computing really got going in Depression-era Vienna.  The people who worked out the theory had no interest in building machines; they wanted to puzzle out the limits of reason in the absence of divine authority. If we could not rely on God or Aristotle to tell us how to think, could we instead build arguments that were self-contained and demonstrably correct? Can we be sure that mathematics is consistent? Are there things that are true but that cannot be expressed in language? 

    The core ideas were worked out in the weekly meetings (Thursdays at 6) of a group remembered as the Vienna Circle. They got together in the office of Professor Moritz Schlick at the University of Vienna to discuss problems in philosophy, math, and language. The intersection of physics and philosophy had long been a specialty of this Vienna department, and this work had placed them among the world leaders.  Schlick’s colleague Hans Hahn was a central participant, and by 1928 Hahn brought along his graduate students Karl Menger and Kurt Gödel. Other frequent participants included philosopher Rudolf Carnap, psychologist Karl Popper, economist Ludwig von Mises (brought by his brother Frederick, a physicist),  graphic designer Otto Neurath (inventor of infographics), and architect Josef Frank (brought by his physicist brother, Phillip).  Out-of-town visitors often joined, including the young Johnny von Neumann, Alfred Tarski, and the irascible Ludwig Wittgenstein. 

    When Schlick’s office grew too dim, participants adjourned to a nearby café for additional discussion with an even larger circle of participants.  This convivial circle was far from unique.  An intersecting circle–Neurath, von Mises, Oskar Morgenstern–established the Austrian School of free-market economics. There were theatrical circles (Peter Lorre, Hedy Lamarr, Max Reinhardt), and literary circles. The café was where things happened.

    The interdisciplinarity of the group posed real challenges of temperament and understanding. Personalities were often a challenge. Gödel was convinced people were trying to poison him. Architect Josef Frank depended on contracts for public housing, which Mises opposed as wasteful. Wittgenstein’s temper had lost him his job as a secondary school teacher, and for some of these years he maintained a detailed list of whom he was willing to meet. Neurath was eager to detect muddled thinking and would interrupt a speaker with a shouted “Metaphysics!” The continuing amity of these meetings was facilitated by the personality of their leader, Moritz Schlick, who would be remembered as notably adept in keeping disagreements from becoming quarrels.

    In the Café

    The Viennese café of this era was long remembered as a particularly good place to argue with your friends, to read, and to write. Built to serve an imperial capital, the cafés found themselves with too much space and too few customers now that the Empire was gone. There was no need to turn tables: a café could only survive by coaxing customers to linger. Perhaps they would order another coffee, or one of their friends might drop by. One could play chess, or billiards, or read newspapers from abroad. Coffee was invariably served with a glass of purified spring water, still a novelty in an era in which most water was still unsafe to drink. That water glass would be refilled indefinitely. 

    In the basement of one café, the poet Jura Soyfer staged “The End Of The World,” a musical comedy in which Professor Peep has discovered a comet heading for earth.

    Prof. Peep: The comet is going to destroy everybody!

    Hitler:  Destroying everybody is my business.

    Of course, coffee can be prepared in many ways, and the Viennese café developed a broad vocabulary to represent precisely how one preferred to drink it: melange, Einspänner, Brauner, Schwarzer, Kapuziner. This extensive customization, with correspondingly esoteric conventions of service, established the café as a comfortable and personal third space, a neutral ground in which anyone who could afford a coffee would be welcome. Viennese of this era were fastidious in their use of personal titles, of which an abundance were in common use. Café waiters greeted regular customers with titles too, but were careful to address their patrons with titles a notch or two greater than they deserved. A graduate student would be Doktor, an unpaid postdoc Professor.  This assurance mattered all the more because so many members of the Circle (and so many other Viennese) came from elsewhere: Carnap from Wuppertal, Gödel from Brno, von Neumann from Budapest. No one was going to make fun of your clothes, mannerisms, or accent. Your friends wouldn’t be bothered by the pram in the hall. Everyone shared a Germanic Austrian literary and philosophical culture, not least those whose ancestors had been Eastern European Jews who knew that culture well, having read all about it in books.

    The amiability of the café circle was enhanced by its openness. Because the circle sometimes extended to architects and actors, people could feel less constrained to admit shortfalls in their understanding. It was soon discovered that marble tabletops made a useful surface for pencil sketches, serving all as an improvised and accessible blackboard.

    Comedies like “The End Of The World” and fictional newspaper sketches or feuilletons of writers like Joseph Roth and Stefan Zweig served as a second defense against disagreeable or churlish behavior. The knowledge that, if one got carried away, a parody of one’s remarks might shortly appear in Neue Freie Presse surely helped Professor Schlick keep matters in hand.

    The End Of Red Vienna

    Though Austria’s government drifted to the right after the War, Vienna’s city council had been Socialist, dedicated to public housing based on user-centered design, and embracing  ambitious programs of public outreach and adult education. In 1934 the Socialists lost a local election, and this era soon came to its end as the new administration focused on the imagined threat of the International Jewish Conspiracy. Most members of the Circle fled within months: von Neumann to Princeton, Neurath to Holland and Oxford, Popper to New Zealand, Carnap to Chicago. Prof. Schlick was murdered on the steps of the University by a student outraged by his former association with Jews.  Jura Soyfer, who wrote “The End Of The World,” died in Buchenwald.

    In 1939, von Neumann finally convinced Gödel to accept a job in Princeton. Gödel was required to pay large fines to emigrate. The officer in charge of these fees would look back on this as the best posting of his career; his name was Eichmann.

    Design for Amiability

    An impressive literature recounts those discussions and the environment that facilitated the development of computing. How can we design for amiability?  This is not just a matter of choosing rounded typefaces and a cheerful pastel palette. I believe we may identify eight distinct issues that exert design forces in usefully amiable directions.

    Seriousness: The Vienna Circle was wrestling with a notoriously difficult book—Wittgenstein’s Tractus Logico-Philosophicus—and a catalog of outstanding open questions in mathematics. They were concerned with consequential problems, not merely scoring points for debating. Constant reminders that the questions you are considering matter—not only that they are consequential or that those opposing you are scoundrels—help promote amity.

    Empiricism: The characteristic approach of the Vienna Circle demanded that knowledge be grounded either in direct observation or in rigorous reasoning. Disagreement, when it arose, could be settled by observation or by proof. If neither seemed ready to hand, the matter could not be settled. On these terms, one can seldom if ever demolish an opposing argument, and trolling is pointless.

    Abstraction: Disputes grow worse when losing the argument entails lost face or lost jobs. The Vienna Circle’s focus on theory—the limits of mathematics, the capability of language—promoted amity. Without seriousness, abstraction could have been merely academic, but the limits of reason and the consistency of mathematics were clearly serious.

    Formality: The punctilious demeanor of waiters and the elaborated rituals of coffee service helped to establish orderly attitudes amongst the argumentative participants. This stands in contrast to the contemptuous sneer that now dominates social media.  

    Schlamperei: Members of the Vienna Circle maintained a global correspondence, and they knew their work was at the frontier of research. Still, this was Vienna, at the margins of Europe: old-fashioned, frumpy, and dingy. Many participants came from even more obscure backwaters. Most or all harbored the suspicion that they were really schleppers, and a tinge of the ridiculous helped to moderate tempers. The director of “The End Of The World” had to pass the hat for money to purchase a moon for the set, and thought it was funny enough to write up for publication.

    Openness: All sorts of people were involved in discussion, anyone might join in. Each week would bring different participants. Fluid borders reduce tension, and provide opportunities to broaden the range of discussion and the terms of engagement. Low entrance friction was characteristic of the café: anyone could come, and if you came twice you were virtually a regular. Permeable boundaries and café culture made it easier for moderating influences to draw in raconteurs and storytellers to defuse awkward moments, and Vienna’s cafés had no shortage of humorists. Openness counteracts the suspicion that promoters of amiability are exerting censorship.

    Parody: The environs of the Circle—the university office and the café—were unmistakably public. There were writers about, some of them renowned humorists. The prospect that one’s bad taste or bad behavior might be ridiculed in print kept discussion within bounds. The sanction of public humiliation, however, was itself made mild by the veneer of fiction; even if you got a little carried away and a character based on you made a splash in some newspaper fiction, it wasn’t the end of the world.

    Engagement: The subject matter was important to the participants, but it was esoteric: it did not matter very much to their mothers or their siblings. A small stumble or a minor humiliation could be shrugged off in ways that major media confrontations cannot.

    I believe it is notable that this environment was designed to promote amiability through several different voices.  The café waiter flattered each newcomer and served everyone, and also kept out local pickpockets and drunks who would be mere disruptions. Schlick and other regulars kept discussion moving and on track. The fiction writers and raconteurs—perhaps the most peripheral of the participants—kept people in a good mood and reminded them that bad behavior could make anyone ridiculous.  Crucially, each of these voices were human: you could reason with them. Algorithmic or AI moderators, however clever, are seldom perceived as reasonable. The café circles had no central authority or Moderator against whom everyone’s resentments might be focused. Even after the disaster of 1934, what people remembered were those cheerful arguments.

  • Design Dialects: Breaking the Rules, Not the System

    Design Dialects: Breaking the Rules, Not the System

    “Language is not merely a set of unrelated sounds, clauses, rules, and meanings; it is a totally coherent system bound to context and behavior.” — Kenneth L. Pike

    The web has accents. So should our design systems.

    Design Systems as Living Languages

    Design systems aren’t component libraries—they’re living languages. Tokens are phonemes, components are words, patterns are phrases, layouts are sentences. The conversations we build with users become the stories our products tell.

    But here’s what we’ve forgotten: the more fluently a language is spoken, the more accents it can support without losing meaning. English in Scotland differs from English in Sydney, yet both are unmistakably English. The language adapts to context while preserving core meaning. This couldn’t be more obvious to me, a Brazilian Portuguese speaker, who learned English with an American accent, and lives in Sydney.

    Our design systems must work the same way. Rigid adherence to visual rules creates brittle systems that break under contextual pressure. Fluent systems bend without breaking.

    Consistency becomes a prison

    The promise of design systems was simple: consistent components would accelerate development and unify experiences. But as systems matured and products grew more complex, that promise has become a prison. Teams file “exception” requests by the hundreds. Products launch with workarounds instead of system components. Designers spend more time defending consistency than solving user problems.

    Our design systems must learn to speak dialects.

    A design dialect is a systematic adaptation of a design system that maintains core principles while developing new patterns for specific contexts. Unlike one-off customizations or brand themes, dialects preserve the system’s essential grammar while expanding its vocabulary to serve different users, environments, or constraints.

    When Perfect Consistency Fails

    At Booking.com, I learned this lesson the hard way. We A/B-tested everything—color, copy, button shapes, even logo colors. As a professional with a graphic design education and experience building brand style guides, I found this shocking. While everyone fell in love with Airbnb’s pristine design system, Booking grew into a giant without ever considering visual consistency.  

    The chaos taught me something profound: consistency isn’t ROI; solved problems are.

    At Shopify. Polaris () was our crown jewel—a mature design language perfect for merchants on laptops. As a product team, we were expected to adopt Polaris as-is. Then my fulfillment team hit an “Oh, Ship!” moment, as we faced the challenge of building an app for warehouse pickers using our interface on shared, battered Android scanners in dim aisles, wearing thick gloves, scanning dozens of items per minute, many with limited levels of English understanding.

    Task completion with standard Polaris: 0%.

    Every component that worked beautifully for merchants failed completely for pickers. White backgrounds created glare. 44px tap targets were invisible to gloved fingers. Sentence-case labels took too long to parse. Multi-step flows confused non-native speakers.

    We faced a choice: abandon Polaris entirely, or teach it to speak warehouse.

    The Birth of a Dialect

    We chose evolution over revolution. Working within Polaris’s core principles—clarity, efficiency, consistency—we developed what we now call a design dialect:

    ConstraintFluent MoveRationale
    Glare & low lightDark surfaces + light textReduce glare on low-DPI screens
    Gloves & haste90px tap targets (~2cm)Accommodate thick gloves
    MultilingualSingle-task screens, plain languageReduce cognitive load

    Result: Task completion jumped from 0% to 100%. Onboarding time dropped from three weeks to one shift.

    This wasn’t customization or theming—this was a dialect: a systematic adaptation that maintained Polaris’s core grammar while developing new vocabulary for a specific context. Polaris hadn’t failed; it had learned to speak warehouse.

    The Flexibility Framework

    At Atlassian, working on the Jira platform—itself a system within the larger Atlassian system—I pushed for formalizing this insight. With dozens of products sharing a design language across different codebases, we needed systematic flexibility so we built directly into our ways of working. The old model—exception requests and special approvals—was failing at scale.

    We developed the Flexibility Framework to help designers define how flexible they wanted their components to be:

    TierActionOwnership
    ConsistentAdopt unchangedPlatform locks design + code
    OpinionatedAdapt within boundsPlatform provides smart defaults, products customize
    FlexibleExtend freelyPlatform defines behavior, products own presentation

    During a navigation redesign, we tiered every element. Logo and global search stayed Consistent. Breadcrumbs and contextual actions became Flexible. Product teams could immediately see where innovation was welcome and where consistency mattered.

    The Decision Ladder

    Flexibility needs boundaries. We created a simple ladder for evaluating when rules should bend:

    Good: Ship with existing system components. Fast, consistent, proven.

    Better: Stretch a component slightly. Document the change. Contribute improvements back to the system for all to use.

    Best: Prototype the ideal experience first. If user testing validates the benefit, update the system to support it.

    The key question: “Which option lets users succeed fastest?”

    Rules are tools, not relics.

    Unity Beats Uniformity

    Gmail, Drive, and Maps are unmistakably Google—yet each speaks with its own accent. They achieve unity through shared principles, not cloned components. One extra week of debate over button color costs roughly $30K in engineer time.

    Unity is a brand outcome; fluency is a user outcome. When the two clash, side with the user.

    Governance Without Gates

    How do you maintain coherence while enabling dialects? Treat your system like a living vocabulary:

    Document every deviation – e.g., dialects/warehouse.md with before/after screenshots and rationale.

    Promote shared patterns – when three teams adopt a dialect independently, review it for core inclusion.

    Deprecate with context – retire old idioms via flags and migration notes, never a big-bang purge.

    A living dictionary scales better than a frozen rulebook.

    Start Small: Your First Dialect

    Ready to introduce dialects? Start with one broken experience:

    This week: Find one user flow where perfect consistency blocks task completion. Could be mobile users struggling with desktop-sized components, or accessibility needs your standard patterns don’t address.

    Document the context: What makes standard patterns fail here? Environmental constraints? User capabilities? Task urgency?

    Design one systematic change: Focus on behavior over aesthetics. If gloves are the problem, bigger targets aren’t “”breaking the system””—they’re serving the user. Earn the variations and make them intentional.

    Test and measure: Does the change improve task completion? Time to productivity? User satisfaction?

    Show the savings: If that dialect frees even half a sprint, fluency has paid for itself.

    Beyond the Component Library

    We’re not managing design systems anymore—we’re cultivating design languages. Languages that grow with their speakers. Languages that develop accents without losing meaning. Languages that serve human needs over aesthetic ideals.

    The warehouse workers who went from 0% to 100% task completion didn’t care that our buttons broke the style guide. They cared that the buttons finally worked.

    Your users feel the same way. Give your system permission to speak their language.

  • An Holistic Framework for Shared Design Leadership

    An Holistic Framework for Shared Design Leadership

    Picture this: You’re in a meeting room at your tech company, and two people are having what looks like the same conversation about the same design problem. One is talking about whether the team has the right skills to tackle it. The other is diving deep into whether the solution actually solves the user’s problem. Same room, same problem, completely different lenses.

    This is the beautiful, sometimes messy reality of having both a Design Manager and a Lead Designer on the same team. And if you’re wondering how to make this work without creating confusion, overlap, or the dreaded “too many cooks” scenario, you’re asking the right question.

    The traditional answer has been to draw clean lines on an org chart. The Design Manager handles people, the Lead Designer handles craft. Problem solved, right? Except clean org charts are fantasy. In reality, both roles care deeply about team health, design quality, and shipping great work. 

    The magic happens when you embrace the overlap instead of fighting it—when you start thinking of your design org as a design organism.

    The Anatomy of a Healthy Design Team

    Here’s what I’ve learned from years of being on both sides of this equation: think of your design team as a living organism. The Design Manager tends to the mind (the psychological safety, the career growth, the team dynamics). The Lead Designer tends to the body (the craft skills, the design standards, the hands-on work that ships to users).

    But just like mind and body aren’t completely separate systems, so, too, do these roles overlap in important ways. You can’t have a healthy person without both working in harmony. The trick is knowing where those overlaps are and how to navigate them gracefully.

    When we look at how healthy teams actually function, three critical systems emerge. Each requires both roles to work together, but with one taking primary responsibility for keeping that system strong.

    The Nervous System: People & Psychology

    Primary caretaker: Design Manager
    Supporting role: Lead Designer

    The nervous system is all about signals, feedback, and psychological safety. When this system is healthy, information flows freely, people feel safe to take risks, and the team can adapt quickly to new challenges.

    The Design Manager is the primary caretaker here. They’re monitoring the team’s psychological pulse, ensuring feedback loops are healthy, and creating the conditions for people to grow. They’re hosting career conversations, managing workload, and making sure no one burns out.

    But the Lead Designer plays a crucial supporting role. They’re providing sensory input about craft development needs, spotting when someone’s design skills are stagnating, and helping identify growth opportunities that the Design Manager might miss.

    Design Manager tends to:

    • Career conversations and growth planning
    • Team psychological safety and dynamics
    • Workload management and resource allocation
    • Performance reviews and feedback systems
    • Creating learning opportunities

    Lead Designer supports by:

    • Providing craft-specific feedback on team member development
    • Identifying design skill gaps and growth opportunities
    • Offering design mentorship and guidance
    • Signaling when team members are ready for more complex challenges

    The Muscular System: Craft & Execution

    Primary caretaker: Lead Designer
    Supporting role: Design Manager

    The muscular system is about strength, coordination, and skill development. When this system is healthy, the team can execute complex design work with precision, maintain consistent quality, and adapt their craft to new challenges.

    The Lead Designer is the primary caretaker here. They’re setting design standards, providing craft coaching, and ensuring that shipping work meets the quality bar. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

    But the Design Manager plays a crucial supporting role. They’re ensuring the team has the resources and support to do their best craft work, like proper nutrition and recovery time for an athlete.

    Lead Designer tends to:

    • Definition of design standards and system usage
    • Feedback on what design work meets the standard
    • Experience direction for the product
    • Design decisions and product-wide alignment
    • Innovation and craft advancement

    Design Manager supports by:

    • Ensuring design standards are understood and adopted across the team
    • Confirming experience direction is being followed
    • Supporting practices and systems that scale without bottlenecking
    • Facilitating design alignment across teams
    • Providing resources and removing obstacles to great craft work

    The Circulatory System: Strategy & Flow

    Shared caretakers: Both Design Manager and Lead Designer

    The circulatory system is about how information, decisions, and energy flow through the team. When this system is healthy, strategic direction is clear, priorities are aligned, and the team can respond quickly to new opportunities or challenges.

    This is where true partnership happens. Both roles are responsible for keeping the circulation strong, but they’re bringing different perspectives to the table.

    Lead Designer contributes:

    • User needs are met by the product
    • Overall product quality and experience
    • Strategic design initiatives
    • Research-based user needs for each initiative

    Design Manager contributes:

    • Communication to team and stakeholders
    • Stakeholder management and alignment
    • Cross-functional team accountability
    • Strategic business initiatives

    Both collaborate on:

    • Co-creation of strategy with leadership
    • Team goals and prioritization approach
    • Organizational structure decisions
    • Success measures and frameworks

    Keeping the Organism Healthy

    The key to making this partnership sing is understanding that all three systems need to work together. A team with great craft skills but poor psychological safety will burn out. A team with great culture but weak craft execution will ship mediocre work. A team with both but poor strategic circulation will work hard on the wrong things.

    Be Explicit About Which System You’re Tending

    When you’re in a meeting about a design problem, it helps to acknowledge which system you’re primarily focused on. “I’m thinking about this from a team capacity perspective” (nervous system) or “I’m looking at this through the lens of user needs” (muscular system) gives everyone context for your input.

    This isn’t about staying in your lane. It’s about being transparent as to which lens you’re using, so the other person knows how to best add their perspective.

    Create Healthy Feedback Loops

    The most successful partnerships I’ve seen establish clear feedback loops between the systems:

    Nervous system signals to muscular system: “The team is struggling with confidence in their design skills” → Lead Designer provides more craft coaching and clearer standards.

    Muscular system signals to nervous system: “The team’s craft skills are advancing faster than their project complexity” → Design Manager finds more challenging growth opportunities.

    Both systems signal to circulatory system: “We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities.”

    Handle Handoffs Gracefully

    The most critical moments in this partnership are when something moves from one system to another. This might be when a design standard (muscular system) needs to be rolled out across the team (nervous system), or when a strategic initiative (circulatory system) needs specific craft execution (muscular system).

    Make these transitions explicit. “I’ve defined the new component standards. Can you help me think through how to get the team up to speed?” or “We’ve agreed on this strategic direction. I’m going to focus on the specific user experience approach from here.”

    Stay Curious, Not Territorial

    The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both people to care about the whole organism, even when they’re not the primary caretaker.

    This means asking questions rather than making assumptions. “What do you think about the team’s craft development in this area?” or “How do you see this impacting team morale and workload?” keeps both perspectives active in every decision.

    When the Organism Gets Sick

    Even with clear roles, this partnership can go sideways. Here are the most common failure modes I’ve seen:

    System Isolation

    The Design Manager focuses only on the nervous system and ignores craft development. The Lead Designer focuses only on the muscular system and ignores team dynamics. Both people retreat to their comfort zones and stop collaborating.

    The symptoms: Team members get mixed messages, work quality suffers, morale drops.

    The treatment: Reconnect around shared outcomes. What are you both trying to achieve? Usually it’s great design work that ships on time from a healthy team. Figure out how both systems serve that goal.

    Poor Circulation

    Strategic direction is unclear, priorities keep shifting, and neither role is taking responsibility for keeping information flowing.

    The symptoms: Team members are confused about priorities, work gets duplicated or dropped, deadlines are missed.

    The treatment: Explicitly assign responsibility for circulation. Who’s communicating what to whom? How often? What’s the feedback loop?

    Autoimmune Response

    One person feels threatened by the other’s expertise. The Design Manager thinks the Lead Designer is undermining their authority. The Lead Designer thinks the Design Manager doesn’t understand craft.

    The symptoms: Defensive behavior, territorial disputes, team members caught in the middle.

    The treatment: Remember that you’re both caretakers of the same organism. When one system fails, the whole team suffers. When both systems are healthy, the team thrives.

    The Payoff

    Yes, this model requires more communication. Yes, it requires both people to be secure enough to share responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

    When both roles are healthy and working well together, you get the best of both worlds: deep craft expertise and strong people leadership. When one person is out sick, on vacation, or overwhelmed, the other can help maintain the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

    Most importantly, the framework scales. As your team grows, you can apply the same system thinking to new challenges. Need to launch a design system? Lead Designer tends to the muscular system (standards and implementation), Design Manager tends to the nervous system (team adoption and change management), and both tend to circulation (communication and stakeholder alignment).

    The Bottom Line

    The relationship between a Design Manager and Lead Designer isn’t about dividing territories. It’s about multiplying impact. When both roles understand they’re tending to different aspects of the same healthy organism, magic happens.

    The mind and body work together. The team gets both the strategic thinking and the craft excellence they need. And most importantly, the work that ships to users benefits from both perspectives.

    So the next time you’re in that meeting room, wondering why two people are talking about the same problem from different angles, remember: you’re watching shared leadership in action. And if it’s working well, both the mind and body of your design team are getting stronger.

  • From Beta to Bedrock: Build Products that Stick.

    From Beta to Bedrock: Build Products that Stick.

    As a product builder over too many years to mention, I’ve lost count of the number of times I’ve seen promising ideas go from zero to hero in a few weeks, only to fizzle out within months.

    Financial products, which is the field I work in, are no exception. With people’s real hard-earned money on the line, user expectations running high, and a crowded market, it’s tempting to throw as many features at the wall as possible and hope something sticks. But this approach is a recipe for disaster. Here’s why:

    The pitfalls of feature-first development

    When you start building a financial product from the ground up, or are migrating existing customer journeys from paper or telephony channels onto online banking or mobile apps, it’s easy to get caught up in the excitement of creating new features. You might think, “If I can just add one more thing that solves this particular user problem, they’ll love me!” But what happens when you inevitably hit a roadblock because the narcs (your security team!) don’t like it? When a hard-fought feature isn’t as popular as you thought, or it breaks due to unforeseen complexity?

    This is where the concept of Minimum Viable Product (MVP) comes in. Jason Fried’s book Getting Real and his podcast Rework often touch on this idea, even if he doesn’t always call it that. An MVP is a product that provides just enough value to your users to keep them engaged, but not so much that it becomes overwhelming or difficult to maintain. It sounds like an easy concept but it requires a razor sharp eye, a ruthless edge and having the courage to stick by your opinion because it is easy to be seduced by “the Columbo Effect”… when there’s always “just one more thing…” that someone wants to add.

    The problem with most finance apps, however, is that they often become a reflection of the internal politics of the business rather than an experience solely designed around the customer. This means that the focus is on delivering as many features and functionalities as possible to satisfy the needs and desires of competing internal departments, rather than providing a clear value proposition that is focused on what the people out there in the real world want. As a result, these products can very easily bloat to become a mixed bag of confusing, unrelated and ultimately unlovable customer experiences—a feature salad, you might say.

    The importance of bedrock

    So what’s a better approach? How can we build products that are stable, user-friendly, and—most importantly—stick?

    That’s where the concept of “bedrock” comes in. Bedrock is the core element of your product that truly matters to users. It’s the fundamental building block that provides value and stays relevant over time.

    In the world of retail banking, which is where I work, the bedrock has got to be in and around the regular servicing journeys. People open their current account once in a blue moon but they look at it every day. They sign up for a credit card every year or two, but they check their balance and pay their bill at least once a month.

    Identifying the core tasks that people want to do and then relentlessly striving to make them easy to do, dependable, and trustworthy is where the gravy’s at.

    But how do you get to bedrock? By focusing on the “MVP” approach, prioritizing simplicity, and iterating towards a clear value proposition. This means cutting out unnecessary features and focusing on delivering real value to your users.

    It also means having some guts, because your colleagues might not always instantly share your vision to start with. And controversially, sometimes it can even mean making it clear to customers that you’re not going to come to their house and make their dinner. The occasional “opinionated user interface design” (i.e. clunky workaround for edge cases) might sometimes be what you need to use to test a concept or buy you space to work on something more important.

    Practical strategies for building financial products that stick

    So what are the key strategies I’ve learned from my own experience and research?

    1. Start with a clear “why”: What problem are you trying to solve? For whom? Make sure your mission is crystal clear before building anything. Make sure it aligns with your company’s objectives, too.
    2. Focus on a single, core feature and obsess on getting that right before moving on to something else: Resist the temptation to add too many features at once. Instead, choose one that delivers real value and iterate from there.
    3. Prioritize simplicity over complexity: Less is often more when it comes to financial products. Cut out unnecessary bells and whistles and keep the focus on what matters most.
    4. Embrace continuous iteration: Bedrock isn’t a fixed destination—it’s a dynamic process. Continuously gather user feedback, refine your product, and iterate towards that bedrock state.
    5. Stop, look and listen: Don’t just test your product as part of your delivery process—test it repeatedly in the field. Use it yourself. Run A/B tests. Gather user feedback. Talk to people who use it, and refine accordingly.

    The bedrock paradox

    There’s an interesting paradox at play here: building towards bedrock means sacrificing some short-term growth potential in favour of long-term stability. But the payoff is worth it—products built with a focus on bedrock will outlast and outperform their competitors, and deliver sustained value to users over time.

    So, how do you start your journey towards bedrock? Take it one step at a time. Start by identifying those core elements that truly matter to your users. Focus on building and refining a single, powerful feature that delivers real value. And above all, test obsessively—for, in the words of Abraham Lincoln, Alan Kay, or Peter Drucker (whomever you believe!!), “The best way to predict the future is to create it.”

  • How Small Businesses Can Grow Their Own Talent

    How Small Businesses Can Grow Their Own Talent

    How Small Businesses Can Grow Their Own Talent written by John Jantsch read more at Duct Tape Marketing

    Listen To The Full Episode:   Episode Overview In this episode of the Duct Tape Marketing Podcast, John Jantsch interviews workplace futurist Alexandra Levit about her new book, Make Schoolwork: Solving the American Youth Employment Crisis Through Work-Based Learning. They explore how work-based learning, including apprenticeships, internships, and immersive real-world experiences, can bridge the growing […]

    How Small Businesses Can Grow Their Own Talent written by John Jantsch read more at Duct Tape Marketing

    Listen To The Full Episode:

     

    Alexandra LevitEpisode Overview

    In this episode of the Duct Tape Marketing Podcast, John Jantsch interviews workplace futurist Alexandra Levit about her new book,
    Make Schoolwork: Solving the American Youth Employment Crisis Through Work-Based Learning.

    They explore how work-based learning, including apprenticeships, internships, and immersive real-world experiences, can bridge the growing gap between employers struggling to find skilled workers and young people facing underemployment after graduation.

    As AI reshapes entry-level knowledge work and skilled trades face labor shortages, Alexandra makes the case that businesses of all sizes can build their own talent pipeline while strengthening their brand, culture, and community impact.

    This episode is a practical guide for small and mid-sized business owners who are tired of chasing ready-made talent and want a smarter, more sustainable workforce strategy.

    About Alexandra Levit

    Alexandra Levit is a workplace futurist, author, and CEO of Inspiration at Work. She has written extensively about the future of work, talent intelligence, and workforce trends.

    In Make Schoolwork, co-authored with GPS Education Partners, she outlines a scalable framework for work-based learning that connects students, employers, educators, and communities to address the American youth employment crisis.

    Learn more at: makeschoolwork.org

    What Is Work-Based Learning?

    Work-based learning is education that takes place in a real-world work environment. It typically includes:

    • Apprenticeships
    • Internships
    • One-to-one mentoring
    • Immersive, skills-based workplace experiences

    High-quality work-based learning is:

    • Authentic to the student’s interests
    • Immersive and hands-on
    • Structured with clear learning objectives
    • Designed to build both technical and interpersonal skills

    Students gain practical abilities, such as operating equipment, integrating AI technologies, or mastering skilled trades, while also developing judgment, communication, and problem-solving capabilities.

    The Youth Employment Crisis Explained

    Alexandra describes a growing mismatch between open positions in the workforce, employers struggling to find qualified candidates, and young people who are unemployed or underemployed, even after earning four-year degrees.

    Key contributing factors include:

    • A cultural push toward universal four-year college enrollment
    • Oversupply of graduates for traditional knowledge worker roles
    • Declining entry-level hiring due to AI automation
    • Persistent stigma around skilled trades

    Meanwhile, industries like plumbing, carpentry, manufacturing, and technical trades offer strong starting pay, family-sustaining wages, career stability, and lower automation risk.

    Work-based learning creates a direct pathway between students and real workforce demand.

    Why This Matters in the Age of AI

    AI is automating many entry-level knowledge jobs first. At the same time, roles that require complex physical movement, human-to-human interaction, skilled craftsmanship, and judgment and adaptability are far harder to replace.

    Alexandra emphasizes that students who begin learning AI tools and robotics early can grow alongside the technology, developing practical integration skills that many experienced workers are still trying to catch up with.

    Work-based learning does not compete with AI. It integrates AI into real workflows from day one.

    The Employer Advantage: Building a Talent Pipeline

    A Reliable Talent Pipeline

    Instead of competing for scarce, ready-made talent, businesses can bring students in early, train them in company-specific processes, and develop loyalty and cultural fit.

    Stronger Employer Branding

    Participating businesses are seen as investing in their community, supporting local youth, and creating meaningful career pathways.

    Improved Employee Engagement

    Employees often thrive in mentorship roles. Acting as mentors increases engagement, develops leadership skills, and strengthens internal culture.

    Long-Term Retention

    Contrary to popular belief, young workers can be loyal when given clear growth opportunities, meaningful work, and competitive wages.
    Many students who start at 16 or 17 through structured programs go on to build full careers with the same employer.

    How Small Businesses Can Start

    You do not need a complex corporate program to begin.

    Step 1: Define the Outcome

    Ask:

    • What skills do we need long-term?
    • What would success look like 2 to 3 years from now?

    Step 2: Partner With a School or Program

    Establish relationships with:

    • Local high schools
    • Community colleges
    • Universities
    • Work-based learning intermediaries (like GPS Education Partners)

    Step 3: Avoid Random Acts of Work-Based Learning

    Tours and one-off talks are helpful, but not enough. Create a structured plan with clear skill objectives, defined responsibilities, and a measurable timeline, such as a 10-week paid micro-internship.

    Step 4: Leverage Existing Certifications

    Use third-party certification programs to standardize skill acquisition, measure progress, and provide recognized credentials.

    Addressing Concerns: Supervision, Liability, and Compliance

    Common employer concerns include:

    • Labor laws, especially for minors
    • Transportation and scheduling
    • Academic credit coordination
    • Insurance and liability

    Alexandra recommends working with experienced intermediaries, especially those familiar with local regulations, to avoid reinventing the wheel and ensure compliance.

    Measuring Success

    Key metrics for evaluating work-based learning initiatives include:

    • Skill acquisition and certifications earned
    • Retention rates post-program
    • Conversion to full-time employment
    • Employee engagement among mentors
    • Workforce readiness improvements

    Skill development is the most powerful and measurable indicator of success.

    Key Takeaways

    • The youth employment crisis is a mismatch problem, not a talent shortage.
    • Four-year degrees are not the only path to meaningful, high-paying work.
    • AI is reshaping entry-level jobs, increasing the need for adaptable, skills-based workers.
    • Work-based learning builds loyalty, culture, and long-term workforce stability.
    • Small businesses can start small, but must define outcomes clearly.
    • Mentorship benefits existing employees as much as students.

    Great Moments From the Episode

    • 00:54 What work-based learning really means
    • 02:25 The root cause of the youth employment crisis
    • 04:19 The stigma around skilled trades
    • 06:31 The human advantage over automation
    • 08:45 Real-world success stories from GPS Education Partners
    • 11:41 Why work-based learning builds loyalty
    • 15:12 The underrated power of mentorship
    • 19:55 Measuring skill acquisition as a success metric
    • 22:21 Why AI integration must start early

    Pulled Quotes

    We don’t want random acts of work-based learning.

    If you’re small and don’t have brand name recognition, this is how you build your own talent pipeline.

    It’s as important to know what you don’t want to do as what you do.

    Resources

     

    John Jantsch (00:01.566)

    If you’re tired of hiring ready-made talent that doesn’t actually exist, today’s episode will show you how to build your own pipeline through something called work-based learning that strengthens your business and your brand at the same time. Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Alexandra Levitt. She is a workplace futurist, author and CEO of Inspiration at Work. She’s written extensively about

    how work is changing. And today we’re going to talk about her new book, Make Schoolwork Solving the American Youth Employment Crisis Through Work-Based Learning. So, Alexandra, welcome back to the show.

    Alexandra Levit (00:42.862)

    Thanks so much for having me, John. It’s good to see and hear you.

    John Jantsch (00:45.634)

    Likewise, likewise. So let’s break down a couple of things in the title. What is work-based learning?

    Alexandra Levit (00:54.702)

    Work-based learning is the most simple explanation for it is that it is work, is learning that takes place in a real world work environment. And that typically includes things like apprenticeships, internships, one-to-one mentoring. And we refer to high quality work-based learning as being a fully immersive experience that’s authentic to the individual in terms of the things that they are passionate about.

    John Jantsch (01:04.0)

    Yeah, yeah.

    Alexandra Levit (01:23.902)

    and that provides a tangible opportunity to spend a good degree of time learning skills that will make you career ready. So these can be anything from learning judgment and interpersonal relations to problem solving. But also it, lot of times gives students a very concrete group of skills about how to work a set of equipment. For example, it depends on where you’re doing work-based learning. But if it’s in a manufacturing setting, for example, you could very well be

    John Jantsch (01:47.479)

    Yes.

    Alexandra Levit (01:53.044)

    literally on the front lines of learning how to integrate AI-based technologies into existing robotics or existing equipment. And that’s a very valuable skill set in today’s workforce.

    John Jantsch (02:04.61)

    I would suggest far more valuable than, I don’t know, AP calculus.

    Alexandra Levit (02:09.87)

    For sure.

    John Jantsch (02:12.308)

    I suppose it depends. All right. So, so the other part of the title I wanted to break out, how would you describe, I mean, you use the word youth employment crisis. How would you describe what you’re trying to convey there?

    Alexandra Levit (02:25.518)

    Well, I think the important thing to recognize from my perspective, at least when I look at my own trajectory, is that there has been this mismatch or this gap for quite some time between the positions that are available in the workforce and the length of time that it takes employers to find the right talent and the number of young people who are unemployed or underemployed. And you would think if there’s just a way to match

    John Jantsch (02:55.17)

    Mm-hmm.

    Alexandra Levit (02:55.186)

    the students who are looking for work with the organizations that are needing to fill positions that that would be a good way to go. Unfortunately, the way our current educational system is structured, it doesn’t exactly operate that way in that over the last couple of decades, we really pushed, especially here in the US, toward every student should go to a four year college.

    John Jantsch (03:20.13)

    Yeah.

    Alexandra Levit (03:20.652)

    the be all end all, it doesn’t matter what you’re really interested in, whether you have the aptitude for post-secondary education, whether you have the desire, that’s the outcome that both students and their parents expect that they’re going to do. And so as a result, we have more people graduating college than we ever have had before, which is good that we are providing opportunities for education and especially education that was unaffordable to some prior to the last couple of decades.

    because we have so many college students graduating, the jobs that are available on the knowledge worker front are not as prolific. And this is especially relevant in the last year or so where entry-level hiring has taken a massive dip due to the integration of AI-based technologies into the workforce. Some of those jobs have been the first to be automated. So what we really still see is there’s a tremendous skills gap in jobs that

    John Jantsch (03:58.273)

    Mm-hmm.

    John Jantsch (04:10.849)

    Yeah.

    Alexandra Levit (04:19.34)

    don’t necessarily require a four-year college degree, but there’s a glut of students on the other side who’ve gotten all this education and don’t know what to do with it. So work-based learning is what we feel is the solution to that employment crisis that’s happening.

    John Jantsch (04:33.962)

    Well, and you take it from the headlines. mean, Amazon lays off, I don’t know what the number was, 20,000 people or something like that. We have, in my agency, we have a lot of home service businesses that we do work for and finding skilled labor right now for jobs like plumbing and carpentry and things. There’s a real need for that and consequently, they’re paying a lot for those positions now. And so I see, do you see a real shift where

    Alexandra Levit (04:58.467)

    Yes.

    John Jantsch (05:03.391)

    AI is probably a ways away from being able to do plumbing and carpentry.

    Alexandra Levit (05:08.162)

    That’s exactly how I see it. And I see that these, there is this strange stigma that I don’t really know where it came from, but ever since I’ve been in this line of work, it’s that, you want to have a career that requires a four year college degree. You don’t want to go into manufacturing or plumbing or carpentry because that’s not a desirable career path. Well, if you look at what is a desirable career path, it’s something that allows you to earn a family sustaining wage.

    John Jantsch (05:09.622)

    Yeah.

    Alexandra Levit (05:36.567)

    and something that you enjoy doing. So to me, that’s a pretty broad definition and it depends on who you are, what you might find rewarding and meaningful. And as you mentioned, these jobs pay astronomically well, way better out of the gate than a lot of knowledge worker jobs or what we used to call knowledge worker jobs. And so I think that that’s, but there’s this strange stigma. I do see a little bit of a shift though. And I think part of that is

    everyone is starting to wake up to the impact of AI and realize we need to go back to what humans can do in our unique way. And that’s things, I remember there was one study that showed that the robotics couldn’t do simple things like clean a house because there were too many complex motions that they would have to program and it was just physically incapable of doing it. And there’s a lot of things like that. And a lot of times too, these,

    John Jantsch (06:20.458)

    Mm-hmm.

    Alexandra Levit (06:31.95)

    trade occupations, they are really human to human and they’re very interpersonal in nature. And so sometimes you don’t, maybe you don’t want an AI plumber coming to your house. Maybe you have your same plumber that you’ve worked with for 10, 15 years and now you’re getting to know his or her son or daughter because they’re taking over the family business. I mean, this is how we worked for most of human history. And I think we’re starting to see that there was some value in that.

    John Jantsch (06:57.92)

    Yeah, just look at their Google reviews of these kinds of businesses. They hardly ever mentioned the company. It’s Rusty, you know, who fixed my boiler. Right. So I think you’re absolutely right. You had, I don’t want to spend too much time on this, but you co-authored this with GPS Education Partners. Was there a research component that they participated in?

    Alexandra Levit (07:04.77)

    Yeah. Yeah.

    Alexandra Levit (07:20.622)

    It’s a great question. And the answer is that I was looking for the solution to this problem for many, many years. The fact that we again have so many open positions and so many young people that aren’t filling them. And I didn’t really know what the solution was. I did a book a couple of years ago on talent intelligence, hoping that AI could help us with seeing the potential and adjacent skills of people. And that is one solution. But when GPS education partners came to me and they talked about their solution,

    which is to convene a group of parties, it depends on what your unique situation is, but it could be a school district with a set of employers, with policymakers, with nonprofits who have an interest in the community. You get everyone together and you say, is the problem we’re trying to solve here? Are we trying to get our local students into our local employers? And a lot of times that is the objective. But how can we all work together to come up with a common…

    not only a goal, but also a plan of attack for mapping that directly, your local students to the jobs that are available in your community. And they have successfully done this over 25 years in many places in the US, but in particular in the Midwest here in Wisconsin, Illinois, Minnesota, and they have had astronomical success. And one of the things that I love about their story is that you hear these

    John Jantsch (08:31.266)

    Hmm.

    Alexandra Levit (08:45.838)

    crazy things like a kid would go into an employer at 16 years old, start working. And then the kid, I was able to talk to 10 years later, you know, he’s 28 years old or 20, 26 years old. And he’s now like a master welder at this organization. He built an entire career off one work-based learning experience. And so that’s when I was like, we got to get the word out. We’ve got to figure out how to scale this because this is to me kind of a no brainer solution to a very, very significant problem that we are having.

    John Jantsch (08:51.01)

    Thanks.

    John Jantsch (09:15.276)

    So in the school, know, a lot of schools have had like intern programs that are part of a department and I’m thinking of colleges, but I’m sure high schools do this too. you know, the department has like some employers that they work with and there’s internships and things. I mean, is this more on the school to actually make a curriculum that they can, you know, so like I can get three hours of credit or something for going and doing this work-based learning and the employer gets

    You know, something that they’ve designed. mean, is that, is that the start of how it works?

    Alexandra Levit (09:49.217)

    Yes, and the curriculum is a lot of times co-created between the school and the employer with GPS Education Group, GPS Education Partners acting as an intermediary that understands the different objectives of the different parties. And in an ideal world, these practical experiences where a kid goes into a learning center and is doing a couple hours of schoolwork that pertains

    John Jantsch (09:57.452)

    Mm-hmm.

    Alexandra Levit (10:18.328)

    pretty closely to the work-based learning experience and then is going out on a shop floor, for example, and doing the very practical. So they might be getting certified in certain manufacturing areas. So while they’re getting the very, I don’t know, I guess you would say, hardcore on the ground experience, they’re also getting some of that background educational knowledge that is essential to continue to pursue that career.

    John Jantsch (10:29.878)

    Mm-hmm.

    Alexandra Levit (10:46.924)

    And that’s what I love about it is that it’s education for a purpose. It’s not just, well, we’re going to go do this for your degree. We don’t know if we’re actually going to use it for anything, but we’re going to do it. And this way, I feel like with work-based learning, you have a really educated determination about whether further education makes sense for something that you have learned you either want to do or don’t want to do. We love to say with work-based learning that that’s as important to know what you don’t want to do as what you do.

    John Jantsch (11:06.144)

    Mm-hmm.

    John Jantsch (11:17.058)

    So I 100 % get the value for the students and for the schools really frankly. Let’s talk about the employer for a minute. Is the employer, is the real goal of the employer is to actually entice this person to come and see how awesome we are and they’re gonna eventually wanna work for us or is it to get cheap labor or what, how should an employer look at the value for them?

    Alexandra Levit (11:21.23)

    Mm-hmm. Yeah. Yep.

    Alexandra Levit (11:41.741)

    I think employers can look at it simply as a pipeline of talent. And the way that I’ve heard a lot of employers discuss this, it almost is like a CSR initiative, corporate social responsibility, where they want to be perceived as adding value to the community in general so that the community can prosper, employer can prosper, and the whole system works. And that is one objective. But I would also suggest that it’s much simpler than that even, which is that where

    John Jantsch (12:06.754)

    Thank

    Alexandra Levit (12:11.234)

    Particularly, I know you have a lot of small businesses as your listeners. It’s like if you’re small business without brand name recognition, it’s really hard to get talent. It’s hard to get talent anyway, but it’s especially hard if you don’t have that name recognition and having a way to reliably get students in the door, train them on what they need to do, teach them how to be good workers. And then I think if you do a good job with this,

    they do stay with you. I mean, we see that over and over again, and people say young people aren’t loyal. I don’t think that’s true. I think it depends on the environment. And if they are provided an environment where they feel like they’ve gotten an amazing experience and they want to continue and they know they can earn a family sustaining wage if they keep going, and it makes sense, I think they are likely to stay with that employer. So to me, yes, it’s a socially responsible thing to do.

    But also, I think it literally gets people in the door. even if though not every single kid who goes into work-based learning is going to become a full-time employee. ideally, you have a few every year. And I think that that would be a really important benefit for organizations that are having trouble getting people.

    John Jantsch (13:23.468)

    So how would I, if I’m a business and I don’t know, I’m a 20 person firm, I’m not, you know, I’m not a lawyer. mean, social responsibility is nice, but it’s also, it’s also down, probably somewhat down the list of all the other stuff I have to manage, right? So how do I start small? How do I look at, you know, obviously I need to, I probably need to find a school maybe that’s got this program already, right? But how do, so how do I start small?

    Alexandra Levit (13:29.166)

    Okay.

    Alexandra Levit (13:36.908)

    Yep.

    Alexandra Levit (13:49.239)

    I recommend it because I actually did this myself. So I have an even smaller business than you. But what I did is I got some Northwestern students because I’m in Chicago and I had my own little work-based learning program for these Northwestern students. Some of them are still working with me today in different capacities. And so I think that’s really it. It’s establishing a relationship with a school that has the type of student that you think would be effective working in your organization. And then

    You got to come up with a plan with the school to understand like, they going to be getting credit? What kind of credit are they going to be getting? are the other components of this besides they’re coming to your location to work? When they are coming to your location to work, what does that look like? What is the experience going to entail? Because one of my favorite things I heard Stephanie Locke, one of my co-authors say is,

    We don’t want to encourage random acts of work-based learning where, you know, we do like a tour of our facility for a bunch of students or somebody comes and talks. It’s like those things are nice. They’re important for exploration, but ideally there would be a really concrete plan about what that student is going to learn, what they’re going to do, and how the different parties are going to benefit, as you said, because employers are putting themselves out there trying to do something that they haven’t done before. And therefore,

    John Jantsch (14:45.238)

    Yeah, yeah, yeah. Right. Yeah.

    Alexandra Levit (15:12.224)

    It does require some degree of effort and some degree of willingness to change and do things a little bit differently. And the other thing that I’d point out that is a real benefit, I think for any size business is that employees love to be in the mentorship position. It really goes a long way toward their own engagement when they are able to take a student under their wing and teach them things.

    John Jantsch (15:30.368)

    Mm-hmm.

    Yeah, that’s true.

    Alexandra Levit (15:39.148)

    And I think that’s kind of an underrated benefit. We people think, or leaders think, employees don’t have time for this. They don’t want to bother. And it’s actually the opposite, I found. When it’s done correctly, this is really rewarding for employees and allows them growth opportunities as well.

    John Jantsch (15:53.858)

    And I suspect, and again, I’m just thinking myself, you know, I suspect the way to do this is to actually, I mean, it’s like a lot of things start with what’s the outcome you want, then back it into like, okay, we’re to make this a 10 week paid micro internship or something. I mean, just really define it. Even have like down to the level of having checklists of what we want that person, you know, to accomplish and what we hope the outcome can be from that. Because I think if

    Alexandra Levit (16:04.27)

    Yep.

    John Jantsch (16:20.63)

    I think a lot of mistakes, a lot of times, and this goes with hiring in general, a lot of times people, I need a VA or I need an executive assistant or I need, you know, whatever. And then they really don’t define the position and they don’t define the outcome. so then it just becomes babysitting.

    Alexandra Levit (16:37.59)

    Yes, absolutely. And actually, that’s the value that GPS Education Partners brought to me and my desire to solve this problem. They’ve got a really well thought out six part process that takes you literally through what you do first, second, third, fourth, and fifth. And it allows you to be creative in the sense if you want to do a smaller program or you want to pilot something, like you can still use that framework. It’s just a matter of how

    John Jantsch (16:42.956)

    Yes.

    John Jantsch (16:49.654)

    Right.

    Alexandra Levit (17:04.472)

    complex it needs to be at the beginning. And the answer is it probably doesn’t need to be super complex at the beginning. And it does, but it does give that blueprint. And of course, if you need help and make schoolwork has a lot of detail in it about how to do these different steps, but you can always call them or a group like them for help in setting something like this up. I don’t, it’s not super expensive to do. It’s just a matter of feeling passionately about it, that this is a viable solution for your business.

    John Jantsch (17:34.516)

    And, and, and I, I’m again, I’m thinking like business owners, time supervision liability. mean, are there things, concerns, you know, beyond just like getting the work done, but other, concerns of bringing a work-based learning might be a teenager, you know, that, you’re bringing into an environment that you’ve not had teenagers in. you know, are there other considerations like, you know, supervision and liability?

    Alexandra Levit (18:00.694)

    Yeah, I mean, there are. And that’s one of the reasons if I was doing it myself, I would definitely be consulting with a group that’s done this before, because there’s all sorts of things. And there’s even the fact that if they’re getting a high school degree while trying to do this, well, how are they going to be transported? How is credit going to work? There are just a lot of things like that, where once you dig into the weeds, you’re like, well, actually, there’s a lot of factors and things to consider.

    John Jantsch (18:08.054)

    Yeah.

    John Jantsch (18:19.734)

    Right.

    Alexandra Levit (18:30.21)

    That’s not to say that these are deal breakers, but they are things where I personally, if I was gonna do this, would be consulting someone who’s done it before, especially in my geography, because we do find that those labor laws differ by state. So you want somebody who’s done this kind of thing in your state and who understands like these are the boxes we have to check for different, we wanna be in compliance of all of the things we need to get, just like with any employee, you wanna be in compliance.

    John Jantsch (18:33.442)

    Mm-hmm.

    John Jantsch (18:44.042)

    Mm-hmm.

    John Jantsch (18:54.743)

    Yeah.

    John Jantsch (18:58.146)

    Yeah. So, so another, whether it’s GPS or somebody else, mean, another kind of, um, check mark for, um, going with somebody that’s figured all that part of it out. Right. So, so you’re not at a surface.

    Alexandra Levit (19:10.478)

    Yes, yes, exactly. It’s going to be, I think the part that you mentioned, which is answering the why and what do we want the outcome to be. I mean, that part is the thing the employer has to think really, really carefully on and no one can do that except for the employer themselves and their leadership. But some of this other stuff, I think, why not? Why try to reinvent the wheel? Why not work with someone who’s already done it a bunch?

    John Jantsch (19:34.594)

    So, and a lot of business owners think this way as well. How do I measure the success of this if I’m going to do this? What are some kind of common metrics you mentioned? Obviously the social impact is one that I think people want. It’s a little harder to measure, but what are some of the things that people might measure?

    Alexandra Levit (19:55.746)

    My there’s a whole bunch of things that people can measure and we do talk a lot about this in the book, but I would say my favorite measurement is skill acquisition and it’s understanding. All right, you come in and work for me. What what literal skills are you going to come out with and how do we measure whether you’ve acquired them or not? So having certification programs that are tied to this, for example, there’s a lot of certification programs that already exist in different industries that were established by.

    John Jantsch (20:21.59)

    Mm.

    Alexandra Levit (20:23.119)

    third party organizations or nonprofits that you can piggyback on. And you make that a priority for them to acquire certain skills. And by the way, we are in the middle right now of this massive workforce wide upskilling in the area of AI. AI is being integrated into literally everything. So having that as part of your work-based learning initiative, well, not only are you going to be helping students, but again, you’re gonna be helping all the employees.

    John Jantsch (20:40.055)

    Mm-hmm.

    Alexandra Levit (20:52.367)

    who need to learn this stuff as well. And what I love is that if you have a 16, 17 year old student on the front lines of learning these technologies, they can grow up with the technology. And as the technology evolves and changes, the student is keeping up with it. And that’s something that we, those of us who’ve been in the workforce a while, we’re just trying to play catch up here. And we’ve done things a different way for a very long time. And I love the idea of starting students

    John Jantsch (20:52.544)

    Mm-hmm. Yeah.

    John Jantsch (21:06.7)

    Yeah.

    Alexandra Levit (21:21.355)

    in robotics, like what can the robots do right now? What can they do next year? How is this going to evolve? And what are the very practical things we need to do to make sure that we are deploying AI ethically, responsibly, and efficiently? Well, this is stuff we all need to learn.

    John Jantsch (21:37.844)

    Well, and you know, one of the things I think is interesting and, know, when social media came along, all of our clients would like, just go get a teenager. Like they use all this stuff all the time. They know what to do. They didn’t know how to apply it. They didn’t know actually that they didn’t know actually the practical use of it in, the environment, that, that they were being put in. And I think that that’s a, an element that, you, a business owner or a business person can certainly bring to.

    Alexandra Levit (21:50.979)

    Yeah, that’s not true.

    John Jantsch (22:07.638)

    Yeah, okay, they understand all these and they have no fear of playing with all these tools, but how they actually put them in context of a good use in a business situation, I think is something that is an invaluable skill they’re never gonna learn in school.

    Alexandra Levit (22:21.657)

    you’re exactly right. And that gets to the heart of what the problem is workforce wide, which is that nobody knows how to integrate these things into their existing business processes and workflows. And so we’re finding that AI is a lot of hype right now without a lot of ROI precisely for that reason. So if we can teach students that at a very young age and get them used to, okay, every time a new technology comes down the pike.

    I had to figure out what’s the best use of that. How do we deploy that in a sensible way? That’s going to be incredible because these things are only going to keep evolving. We are not going to stop and it’s only going to get faster.

    John Jantsch (22:57.462)

    No. Yeah, absolutely. Well, Alexander, I appreciate you taking a few moments to stop by. Where would you invite people to connect with you and find out more about Make School Work? And I think you also have a makeschoolwork.org organization.

    Alexandra Levit (23:12.823)

    Yes, our website, MakeSchoolWork.org has obviously the book, but it’s going to continue to have resources for how you can assess your own readiness to start work-based learning, just some additional things to think about. This is not an easy thing to do, but it’s also, when it goes well, it’s extremely rewarding. And I think we’re going to see more and more of this as we just come to terms with the fact that…

    John Jantsch (23:32.076)

    and

    Alexandra Levit (23:38.179)

    The current education system here in the US is not really doing its job to prepare all students for the world of work. We’ve got kind of a narrow approach that I think deserves to be widened and further considered.

    John Jantsch (23:49.568)

    Yeah, awesome. Well, again, thanks for stopping by the show and hopefully we’ll run into you one of these days out there on the road.

    Alexandra Levit (23:56.374)

    You’re welcome. Thanks for having me, John. It’s good to see you again.

    John Jantsch (23:59.222)

    Likewise.

    powered by

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    Classic Rockers in Photos Only They Could Be a Part Of

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    Where the classic Universal Mummy was a romantic whose love transcended the bounds of death, and where Fraser’s Rick O’Connell battled a supervillain version of the mummy, Cronin is drawing inspiration from his most recent film, Evil Dead Rise. The trailer is filled with not just the types of audacious split diopter shots that Sam Raimi would love, but also with icky bits like gooey bandages, bloody teeth, and limbs that creak as they twist into unnatural configurations.

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    One might feel that Cronin is jumping on a bandwagon for his kid-centric take on the mummy, if the concept didn’t seem like something that fits the premise. As outrageous as the imagery gets, the trailer promises to ground the horror in emotional fears of the parents. That very real anxiety gives Cronin and other filmmakers room to go a little harder with the horror.

    And if Evil Dead Rise is any indication, Cronin certainly will go hard with The Mummy, reanimating the tired old monster and making him something all too terrifying.

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    Where the classic Universal Mummy was a romantic whose love transcended the bounds of death, and where Fraser’s Rick O’Connell battled a supervillain version of the mummy, Cronin is drawing inspiration from his most recent film, Evil Dead Rise. The trailer is filled with not just the types of audacious split diopter shots that Sam Raimi would love, but also with icky bits like gooey bandages, bloody teeth, and limbs that creak as they twist into unnatural configurations.

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    }).render(“0270c398a82f44f49c23c16122516796”);
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    Most of all, the trailer for Lee Cronin’s The Mummy features kids being dead and/or scary. Creepy kids and child endangerment aren’t exactly new to cinemas: after all, Frankenstein’s Monster tossed a little girl into a lake in 1931 and eight-year-old Rhoda Penmark terrified her mother in The Bad Seed in 1956.

    But lately, moviegoers have taken a renewed interest in seeing kids come to terrible ends on screen, and sometimes return to do new terrible things. The It franchise and its TV spinoff Welcome to Derry, the Terrifier series with its exploding child bits and creepy Art the Clown girl, the tykes with mutilated faces in Talk to Me and Bring Her Back, and the midnight runners of Weapons have ignored all taboos to enjoy critical acclaim and/or big box office returns.

    One might feel that Cronin is jumping on a bandwagon for his kid-centric take on the mummy, if the concept didn’t seem like something that fits the premise. As outrageous as the imagery gets, the trailer promises to ground the horror in emotional fears of the parents. That very real anxiety gives Cronin and other filmmakers room to go a little harder with the horror.

    And if Evil Dead Rise is any indication, Cronin certainly will go hard with The Mummy, reanimating the tired old monster and making him something all too terrifying.

    Lee Cronin’s The Mummy arrives in theaters on April 17, 2026.

    The post Lee Cronin’s The Mummy Makes Ancient Egypt Spooky Kid Scary appeared first on Den of Geek.