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Generative AI was trained on centuries of art and writing produced by humans. But scientists and critics have wondered what would happen once AI became widely adopted and started training on its outputs. A new study points to some answers. In January 2026, artificial intelligence researchers Arend Hintze, Frida Proschinger ström, and Jory Schossau published a study showing what happens when generative AI systems are allowed to run autonomouslygenerating and interpreting their own outputs without human intervention. The researchers linked a text-to-image system with an image-to-text system and let them iterateimage, caption, image, captionover and over and over. Regardless of how diverse the starting prompts wereand regardless of how much randomness the systems were allowedthe outputs quickly converged onto a narrow set of generic, familiar visual themes: atmospheric cityscapes, grandiose buildings, and pastoral landscapes. Even more striking, the system quickly forgot its starting prompt. The researchers called the outcomes visual elevator musicpleasant and polished, yet devoid of any real meaning. For example, they started with the image prompt, The Prime Minister pored over strategy documents, trying to sell the public on a fragile peace deal while juggling the weight of his job amidst impending military action. The resulting image was then captioned by AI. This caption was used as a prompt to generate the next image. After repeating this loop, the researchers ended up with a bland image of a formal interior spaceno people, no drama, no real sense of time and place. As a computer scientist who studies generative models and creativity, I see the findings from this study as an important piece of the debate over whether AI will lead to cultural stagnation. The results show that generative AI systems themselves tend toward homogenization when used autonomously and repeatedly. They even suggest that AI systems are currently operating in this way by default. The familiar is the default This experiment may appear beside the point: Most people dont ask AI systems to endlessly describe and regenerate their own images. The convergence to a set of bland, stock images happened without retraining. No new data was added. Nothing was learned. The collapse emerged purely from repeated use. But I think the setup of the experiment can be thought of as a diagnostic tool. It reveals what generative systems preserve when no one intervenes. This has broader implications, because modern culture is increasingly influenced by exactly these kinds of pipelines. Images are summarized into text. Text is turned into images. Content is ranked, filtered, and regenerated as it moves between words, images, and videos. New articles on the web are now more likely to be written by AI than humans. Even when humans remain in the loop, they are often choosing from AI-generated options rather than starting from scratch. The findings of this recent study show that the default behavior of these systems is to compress meaning toward what is most familiar, recognizable, and easy to regenerate. Cultural stagnation or acceleration? For the past few years, skeptics have warned that generative AI could lead to cultural stagnation by flooding the web with synthetic content that future AI systems then train on. Over time, the argument goes, this recursive loop would narrow diversity and innovation. Champions of the technology have pushed back, pointing out that fears of cultural decline accompany every new technology. Humans, they argue, will always be the final arbiter of creative decisions. What has been missing from this debate is empirical evidence showing where homogenization actually begins. The new study does not test retraining on AI-generated data. Instead, it shows something more fundamental: Homogenization happens before retraining even enters the picture. The content that generative AI systems naturally producewhen used autonomously and repeatedlyis already compressed and generic. This reframes the stagnation argument. The risk is not only that future models might train on AI-generated content, but that AI-mediated culture is already being filtered in ways that favor the familiar, the describable, and the conventional. Retraining would amplify this effect. But it is not its source. This is no moral panic Skeptics are right about one thing: Culture has always adapted to new technologies. Photography did not kill painting. Film did not kill theater. Digital tools have enabled new forms of expression. But those earlier technologies never forced culture to be endlessly reshaped across various mediums at a global scale. They did not summarize, regenerate and rank cultural productsnews stories, songs, memes, academic papers, photographs, or social media postsmillions of times per day, guided by the same built-in assumptions about what is typical. The study shows that when meaning is forced through such pipelines repeatedly, diversity collapses not because of bad intentions, malicious design or corporate negligence, but because only certain kinds of meaning survive the text-to-image-to-text repeated conversions. This does not mean cultural stagnation is inevitable. Human creativity is resilient. Institutions, subcultures, and artists have always found ways to resist homogenization. But in my view, the findings of the study show that stagnation is a real risknot a speculative fearif generative systems are left to operate in their current iteration. They also help clarify a common misconception about AI creativity: Producing endless variations is not the same as producing innovation. A system can generate millions of images while exploring only a tiny corner of cultural space. In my own research on creative AI, I found that novelty requires designing AI systems with incentives to deviate from the norms. Without it, systems optimize for familiarity because familiarity is what they have learned best. The study reinforces this point empirically. Autonomy alone does not guarantee exploration. In some cases, it accelerates convergence. This pattern already emerged in the real world: One study found that AI-generated lesson plans featured the same drift toward conventional, uninspiring content, underscoring that AI systems converge toward whats typical rather than whats unique or creative. Lost in translation Whenever you write a caption for an image, details will be lost. Likewise, for generating an image from text. And this happens whether its being performed by a human or a machine. In that sense, the convergence that took place is not a failure thats unique to AI. It reflects a deeper property of bouncing from one medium to another. When meaning passes repeatedly through two different formats, only the most stable elements persist. But by highlighting what survives during repeated translations between text and images, the authors are able to show that meaning is processed inside generative systems with a quiet pull toward the generic. The implication is sobering: Even with human guidancewhether that means writing prompts, selecting outputs, or refining resultsthese systems are still stripping away some details and amplifying others in ways that are oriented toward whats average. If generative AI is to enrich culture rather than flatten it, I think systems need to be designed in ways that resist convergence toward statistically average outputs. There can be rewards for deviation and support for less common and less mainstream forms of expression. The study makes one thing clear: Absent these interventions, generative AI will continue to drift toward mediocre and uninspired content. Cultural stagnation is no longer speculation. Its already happening. Ahmed Elgammal is a professor of computer science and director of the Art & AI Lab at Rutgers University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Many people spend an incredible amount of time worrying about how to be more successful in life. But what if thats the wrong question? What if the real struggle for lots of us isnt how to be successful, but how to actually feel successful? Thats the issue lots of strivers truly face, according to ex-Googler turned neuroscientist and author Anne-Laure Le Cunff. In her book Tiny Experiments, she explores how to get off the treadmill of constantly chasing the next milestone, and instead find joy in the process of growth and uncertainty. Youre probably doing better than you give yourself credit for, she explained on LinkedIn recently, before offering 10 telltale signs that what you need isnt to achieve more but to recognize your achievements more. Are you suffering from success dysmorphia? Before we get to those signs, let me try to convince you that youre probably being way too hard on yourself about how well youre doing in life. Start by considering the concept of dysmorphia. Youve probably heard the term in relation to eating disorders. In that context, dysmorphia is when you have a distorted picture of your body. You see a much larger person in the mirror than the rest of the world sees when they look at you. But dysmorphia doesnt just occur in relation to appearance. One recent poll found that 29% of Americans (and more than 40% of young people) experience money dysmorphia. That is, even though theyre doing objectively okay financially, they constantly feel as if theyre falling behind. Financial experts agree that thanks to a firehose of unrealistic images and often dubious money advice online, its increasingly common for people to have a distorted sense of how well theyre actually doing when it comes to money. Or take the idea of productivity dysmorphia, popularized by author Anna Codrea-Rado. In a widely shared essay, she outed herself as a sufferer, revealing that despite working frantically and fruitfully, she never feels that shes done enough. When I write down everything Ive done since the beginning of the pandemicpitched and published a book, launched a media awards, hosted two podcastsI feel overwhelmed. The only thing more overwhelming is that I feel like Ive done nothing at all, she wrote back in 2021. Which means she did all that in just over a year and still feels inadequate. Thats crazy. But its not uncommon to drive ourselves so relentlessly. In Harvard Business Review, Jennifer Moss, author of The Burnout Epidemic, cites a Slack report showing that half of all desk workers say they rarely or never take breaks during the workday. She calls this kind of toxic productivity, a common sentiment in todays work culture. 10 signs of success All together, this evidence paints a picture of a nation that is pretty terrible at gauging and celebrating success. The roots of the issue obviously run deep in our culture and economy. Reorienting our collective life to help us all recognize that there is such a thing as enough is beyond the scope of this column. But in the meantime, neuroscience can help you take a small step toward greater mental peace by reminding you youre probably doing better than you sometimes feel you are. Especially, Le Cunff stresses, if you notice these signs of maturity, growth, and balance in your life. You celebrate small wins. You try again after failing. You pause before reacting. You take breaks without guilt. You recover from setbacks faster. You ask for help when you need it. Youre kind to yourself when you make mistakes. You notice patterns instead of judging them. You make decisions based on values, not pressure. Youre more curious than anxious about whats next. A neuroscientist and a writer agree: Practice becoming Writer Kurt Vonnegut once advised a young correspondent, Practice any art, music, singing, dancing, acting, drawing, painting, sculpting, poetry, fiction, essays, reportage, no matter how well or badly, not to get money and fame, but to experience becoming, to find out whats inside you, to make your soul grow. In other words, artists agree with neuroscientists. Were all works in progress. Youre always going to be in the middle of becoming who you are. You may as well learn to appreciate yourself and the process along the way. We often feel like we need to reach just one more milestone before we can feel successful. But the tme to celebrate isnt when youre arrived at successnone of us fully ever gets thereits at every moment of growth and wisdom along the journey. By Jessica Stillman This article originally appeared in Fast Company‘s sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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The Grammy Awards return February 1 at a pivotal moment for the music industry, one shaped by trending Latin artists, resurgent rock legends, and even charting AI acts. To unpack what will make this years broadcast distinctive, the Recording Academy CEO Harvey Mason Jr. shares how Grammy winners are chosen, and how music both reflects and influences the broader business marketplace. This is an abridged transcript of an interview from Rapid Response, hosted by former Fast Company editor-in-chief Robert Safian. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with todays top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. This year’s Grammy Awards come at an intriguing inflection point for the music business. I mean, the music business is always changing, but I was looking at your Album of the Year nominees, which feature a bunch of mega artists: Justin Bieber, Tyler the Creator, Lady Gaga, Kendrick Lamar, Bad Bunny. How much do Grammy nominees reflect the marketplace? The Grammy nominees are meant to reflect the marketplace, and that’s our hope, but it really reflects the voters will. And you don’t know what’s going to resonate with the voting body year over year. We have roughly 15,000 voting members. Those members are all professional music people, whether they’re writers or arrangers or producers or artists. So they’re the peers of the people that are being nominated. Sometimes they surprise you and they vote for something that I wasn’t thinking of and sometimes they are right down the middle. But the hope is that the nominations are a direct and unencumbered reflection of what the voters appreciate and want to vote for. And in this sort of more fragmented media ecosystem . . . do the biggest artists have the same kind of cultural sway, or is the cultural impact more diffuse? It’s debatable. . . . I’m sure everyone has an opinion, but the big artists are always going to be impactful and important and shift the direction of music. And there’s always going to be a new class of creators coming up. KPop Demon Hunters [is] the animated band [from] this breakthrough filmthe most-watched movie ever on Netflix. But the [soundtrack] album charted No. 1 on Billboard also. Did that surprise you? Are there any messages in that about music and where it’s going in the future? It didn’t surprise me, because it was really, really good. And the message that it sends is you can come from anywhere, any country, any medium. You can come off a streaming platform, off a show, off of a garage studio. And if your music resonates, it’s going to be successful. It’s going to find an audience. And that’s what’s exciting to me right now about music is the diverse places where you’re finding it being created and sourced from. And also, the accessibility to audiences. You don’t have to record a record and then hopefully it gets mixed and mastered and hopefully somebody releases it and markets it the right way. You can make something and put it out. And if it creates excitement . . . people are going to love it and gravitate towards it. One of the bands that ended up putting up big streaming numbers was the Velvet Sundown, an AI-based artist. I’m curious, is there going to be a point where AI acts have their own Grammy category? Are there any award restrictions on artists who use AI in their music now? I know there was a lot of tumult about that with the Oscars last year with The Brutalist. AI is moving so darn fast. . . . Month to month it’s doing new things and getting better and changing what it’s doing. So we’re just going to have to be very diligent and watch it and see what happens. My perspective is always going to be to protect the human creators, but I also have to acknowledge that AI is definitely a tool that’s going to be used. People like me or others in the studios around the world are going to be figuring out, How can I use this to make some great music? So for now, AI does not disqualify you from being able to submit for a Grammy. There are certain things that you have to abide by and there are certain rules that you have to follow, but it does not disqualify you from entering. You’re a songwriter, you’re a producer. Are you using AI in your own stuff? I am. I’m fine to admit that I am using it as a creative tool. There are times when I might want to hear a different sound or some different instrumentation. . . . I’m not going to be the creator that ever relies on AI to create something from scratch, because that’s what I love more than anything in the world is making music, being able to sit down at a piano and come up with something that represents my feelings, my emotions, what I’m going through in my life, my stories. So I don’t think I’ll ever be that person that just relies on a computer or software or platform to do that for me. But I do think much like auto-tune, or like a drum machine, or like a synthesizer, there are things that can enhance what I’m trying to get from here out to here. And if those are things that come in that form, I think we’re all going to be ultimately taking advantage of them. But we have to do it thoughtfully. We have to do it with guardrails. We have to do it respectfully. What is the music being trained on? Are there the right approvals? Are artists being remunerated properly? Those are all things that we have to make sure are in place. So, let me ask you about Latin music. I know the Latin Recording Academy split off from the Recording Academy 20 years ago or so. Do you rethink that these days? Latin music is all over the mainstream charts, and plenty of acts are getting Grammy nominations. Should Latin music be separated out? The history of it is a little different. We were representing music, the Latin music on the main show, and the popularity of it demanded that we have more categories. In order to feature more categories and honor the full breadth of the different genres of Latin music, we created the Latin Grammy so they could have that spotlight. Currently, members of the Latin Academy are members of the U.S. Academy. So we’ve not set aside the Latin genres. We’ve not tried to separate them. We’ve only tried to highlight them and lift those genres up. As you know, in the U.S. show we feature Latin categories, we feature many Latin artists, and that will be the same this year, maybe more so, especially with the Bad Bunny success. So in no way does that try to separate the genres. And I think we’ll see some more of that in the future as other genres and other regions continue to make their music even more globally known. It’s not just about music that’s made in one country, right? At least it shouldn’t be. It should be about music everywhere in the world. Instead of narrowing, you might have . . . additional or supplemental academies or projects so that you have tat expertise in those new and growing areas across the globe? Absolutely. We’re going to have to continue to expand our membership. In order for us to honor all the different music that’s being made now, which is more than ever and music coming from more places than ever, our membership has to be reflective of that. Just like, I don’t know what type of music you’re a fan of, but I wouldn’t ask you if you didn’t know everything about classical to go into the classical categories and say, “What did you think was the best composing?” [There are] so many categories you wouldn’t be able to evaluate other than say, “Oh, I recognize that name. Let me vote for that.” And that’s what we can’t have. We have to have people that know the genres. And you’re seeing K-pop, you’re seeing Afrobeats, you’re seeing Latin, you’re seeing growth in the Middle East, you’re seeing growth coming out of India. There are so many great artists and so many great records. And you’re hearing a blend of genres where you’re seeing Western artists interact or collaborate with artists from different parts of the world. That’s what’s happening. You can’t argue it. You can’t deny it. You can’t pretend that it’s not what’s going on.
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January arrives with a familiar hangover. Too much food. Too much drink. Too much screen time. And suddenly social media is full of green juices, charcoal supplements, foot patches, and seven-day liver resets, all promising to purge the body of mysterious toxins and return it to a purer state. In the first episode of Strange Health, a new visualized podcast from The Conversation, hosts Katie Edwards and Dr. Dan Baumgardt put detox culture under the microscope and ask a simple question: Do we actually need to detox at all? Strange Health explores the weird, surprising, and sometimes alarming things our bodies do. Each episode takes a popular health or wellness trend, viral claim, or bodily mystery and examines what the evidence really says, with help from researchers who study this stuff for a living. Edwards, a health and medicine editor at The Conversation, and Baumgardt, a general practicioner and lecturer in health and life sciences at the University of Bristol, share a long-standing fascination with the bodys improbabilities and limits, plus a healthy skepticism for claims that sound too good to be true. This opening episode dives straight into detoxing. From juice cleanses and detox teas to charcoal pills, foot pads, and coffee enemas, Edwards and Baumgardt watch, wince, and occasionally laugh their way through some of the internets most popular detox trends. Along the way, they ask what these products claim to remove, how they supposedly work, and why feeling worse is often reframed online as a sign that a detox is working. The episode also features an interview with Trish Lalor, a liver expert from the University of Birmingham, whose message is refreshingly blunt. Your body is really set up to do it by itself, she explains. The liver, working alongside the kidneys and gut, already detoxifies the body around the clock. For most healthy people, Lalor says, there is no need for extreme interventions or pricey supplements. That does not mean everything labeled detox is harmless. Lalor explains where certain ingredients can help, where they make little difference, and where they can cause real damage if misused. Real detoxing looks less like a sachet or a foot patch and more like hydration, fiber, rest, moderation, and giving your liver time to do the job it already does remarkably well. If youre buying detox patches and supplements, then its probably your wallet that is about to be cleansed, not your liver. Strange Health is hosted by Katie Edwards and Dan Baumgardt. The executive producer is Gemma Ware, with video and sound editing by Sikander Khan. Artwork by Alice Mason. Edwards and Baumgardt talk about two social media clips in this episode, one from 30.forever on TikTok and one from velvelle_store on Instagram. Listen to Strange Health via any of the apps listed above, download it directly via our RSS feed, or find out how else to listen here. A transcript is available via the Apple Podcasts or Spotify apps. Katie Edwards is a commissioning editor for health and medicine and host of the Strange Health podcast at The Conversation. Dan Baumgardt is a senior lecturer at the School of Psychology and Neuroscience at the University of Bristol. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Its 7:45 a.m. in the office. Someone bounces in, already back from the gym, already through their emails. Cheerfully asks if everyone’s “okay” because its so quiet and people seem a bit tired. Around the office, people clutch coffee like a life raft, waiting for their brains to come online and cursing the 8 a.m. meeting. And the cheerful colleague. But at least they got in early enough to find parking and grab coffee before it ran outthis time. Now: which person are you? The early riser, or the one watching them, wondering why you can never feel that awake at this hour no matter how hard you try? Those clutching their strong brews are probably not just tired, they are socially jet-lagged. Up to 80% of the workforce uses alarm clocks to wake earlier than their body is primed to. That’s not a discipline problem. That’s a design problem. That coffee isn’t a character weakness. And the fact that most humans require chemical and digital intervention to function at socially mandated hours should tell us something important about those hours. Neurodiversity and Chronodiversity What comes to your mind when people mention neurodiversity at work? Many people have heard that neurodiversity refers to ADHD or dyslexia, or they equate it with cognitive diversitydifferent ways of thinking or processing information. However, these interpretations are narrowand insufficient for supporting neurologically friendly environments. Neurodiversity is neurological diversity: the full range of ways human nervous systems can be wired. It encompasses cognition, emotion, sensory processing, motor coordination, speech, and crucially, circadian regulation: how our nervous systems manage sleep-wake timing, energy fluctuations, and daily rhythms. But the latter is rarely discussed in the context of talent processes in organizationsand hardly ever in the context of neurodiversity. Neurodiversity and chronodiversity are as central to human life as biodiversity to life on Earth. Maximizing the thriving of human talent at work requires understanding of many ways diversity manifests itself and impacts the ways we work. Normativity and Its Enforcement The parallel between neurodiversity and chronodiversity is that societies and cultures treat forms of neurological wiring and time orientation as normative, and others as aberrant. While neurodiversity and chronodiversity are biological facts, neuronormativity and chrononormativity are the social enforcement of what is deemed to be “normal.” Chrononormativity expresses itself in workplace assumptions and behaviors that are rarely questioned: Early arrival is equated with ambition and commitment Morning responsiveness is read as professionalism Meetings default to early hours those with more power prefer Leadership visibility clusters in morning time Performance reviews implicitly reward temporal conformity Just as neurodivergent individuals often feel pressure to mask, performing neurotypicality to appear “normal,” chronodivergent individuals simulate morningness with sheer grit and coffee. This comes at a cost. The Current Reality: The Difference Tax Most organizations are yet to achieve meaningful neurological inclusion. The few that have begun addressing neurodiversity typically focus narrowly on its cognitive aspects or communication styles. And most organizations continue to operate as if everyone’s internal clock were identical. The timing structures of modern workearly meetings, fixed hours, morning-centric performance expectationswere inherited from agricultural and industrial time systems. But they were never designed for biological realityand those whose bodies do not fit cultural models pay a significant price not only in fatigue, but in mental (e.g., depression) and physical health (cardiovascular risks, metabolic dysfunction). The healthcare cost of this preventable damage also adds up. Population-scale research reveals that chronotype follows a normal distribution, with approximately 30% early chronotypes, 30% intermediate types, and 40% late chronotypes. Among specific populations, the distribution skews laterstudies of young adults consistently find the prevalence of evening types. The chronic misalignment between biological and social timesocial jet lag that most of us feelproduces accumulating sleep debt, cognitive function loss, and increased health risks. Chrononormativity produces what might be called the chronodiversity paradox: a biological majority is treated as a cultural minority. When late chronotypes struggle with early starts, they are labeled unmotivated and lazy, while mismatches with the system are ignored. Neurodivergent populations are disproportionately impacted. Research consistently demonstrates that adults with ADHD exhibit delayed circadian rhythm phase, with up to 7578% showing significantly later timing of physiological sleep readiness and preferred sleep-wake schedules compared to neurotypical peers. Autistic individuals also frequently experience irregular or delayed sleep-wake patterns. These are not poor behavioral choices or signs of insufficient discipline. They are neurological realities stemming from genetic, neurological, and hormonal processes. A Holistic Inclusion Framework: Where Chronodiversity Fits Early-morning meetings exclude late chronotypes from social participation. Fixed schedules ignore cognitive performance variations across the day. Forcing temporal conformity produces emotional exhaustion. Misaligned timing creates physical stress through chronic sleep disruption. Early risers can suffer from misalignment too – night shifts, late-night email expectations, commutes that devour their best creative time. Without attention to chronodiversity, everyone suffers. A workplace that insists everyone perform on the same schedule harms people and limits the expression of their full talent. But applying the holistic and intersectional inclusion principles developed in Ludmilas book, The Canary Code: A Guide to Neurodiversity, Dignity, and Intersectional Belonging at Work, can make much difference. Here are some suggestions for what this might look like: Participation: Include employees in designing schedules rather than imposing “flexibility” designed by morning-normative managers. Those who experienced social jet lag firsthand understand the impact a 9 a.m. “optional” meeting has on the rest of their day. Designig for people without their input produces policies that look inclusive on paper while excluding in practice. Even when shift work is required, having a choice makes all the difference. Focus on Outcomes: For most jobs, productivity has no timestamp. If an employee delivers exceptional analysis submitted at 3 a.m., does it matter they weren’t visible at 8 a.m.? When performance evaluations reward “responsiveness” measured by morning email reply speed, or when “commitment” is assessed by early arrival, we evaluate temporal style rather than substance. Review your criteria: do they measure what gets accomplished, or when someone is seen accomplishing it? Flexibility: Remove arbitrary temporal barriers. Genuine flexibility means examining every time-bound requirement: Must this meeting be synchronous? Must it be morning? Must everyone attend the same session? Expanding flexibility to include schedule self-determination supports the vast majority of employees. Both larks and owls can thrive when design is thoughtful and work is aligned around meaning. Organizational Justice: Examine schedules and policies from the justice perspective. Are scheduling procedures applied consistently, or do senior leaders get flexibility denied to others? Are decisions free from bias, or do early risers receive more favorable evaluations? Are parking, food, and workspaces available for people of later chronotypes? Transparency: Make temporal expectations explicit. Many organizations claim flexibility while maintaining hidden norms: the unspoken understanding that “real players” attend the 8 a.m. leadership meeting, that promotion requires visibility during executive hours, that working remotely in the afternoon signals lower commitment. Make expectations explicitand make them job-relevant. Valid Tools: Stop using temporal proxies for personal qualities. Early arrival doesn’t indicate dedication. Visible presence during specific hours doesn’t measure performance. These shortcuts embed chronotype bias into talent decisions. Valid assessment examines what someone produces, not when they produce it. Moving toward chrono-inclusive practice requires organizations to recognize that morningness is cultural, not biological, and remove stigma around biological timing differences. Normalizing chronotype differences can help develop systems that offer meaningful flexibility and create infrastructureparking, food access, workspace availability, and chronoleadership approaches developed by Camillato address temporal bias. Talent thrives when organizations practice holistic inclusion. And holistic inclusion requires neurological and time rhythm inclusionneither is optional if relying on coffee, alarm clocks, and fumes to function is to stop being a default.
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