Youve tried it all before. Waking up at 5:30 a.m. Journaling first thing in the morning. The exercises youre supposed to do before work. But do your morning habits stick? Are you still practicing them?
We all want to win the morning, to be productive and intentional. The trouble with morning routines is that they dont work as they should if you dont fix your evening habits. People are obsessed with morning routines. But they forget that winning in the morning starts the night before.
Every single choice you make after dinner is either setting you up for a great morning or sabotaging tomorrow before it begins. That late-night binge doesnt just keep you up. Its changing your entire sleep-wake cycle. That work email you answered at 10 p.m. stays on your mind and makes you think about all the many responses youre expecting.
Doing work or dealing with issues right before bed keeps your brain thinking, figuring out options. And the worst part is that you pick it all up again when you wake up. Youre not just losing sleep. Youre training your brain to wake up in stress mode.
The quality of your evening routine determines the success of your morning habits. Every time you miss out on a better evening ritual, your morning routine will suffer. Your willpower will be lower.
The decision fatigue trap most people overlook
By the end of your day, youve already made thousands of decisions: what to wear, what to eat, which emails to answer, which tasks to tackle first. Each decision demands mental energy. The more decisions you make in the morning, the less energy you have left for your tasks.
The bigger problem? If you wait until morning to decide what youre going to do first, youre not starting your day right. Make your morning decisions at night instead.
In just 10 to 15 minutes the night before, eliminate the decisions that stop you from taking action on your ideal morning routine. Write down a list of things you want to get right in the morning. Youll sleep better and feel more prepared when you wake up. By creating a good plan the night before, you set yourself up to be productive.
Ive been using this pre-decision method to make my writing habit stick for years. And its working for me. I decide what to write the night before. I even write down the introduction. And then I pick up where I left off.
You could start by prioritizing three tasks for the morning. By reducing the number of decisions you have to make, you free up time to actually make your morning habit, whatever you intend it to be, stick.
I think of an evening routine as a systema series of small dominoes you set up for the results you want. Start with your sleep. Everything flows from this.
Your brain begins winding down for sleep a few hours before bedtime as part of your natural sleep-wake cycle. Work with this, not against it. That means two hours before bed, start dimming lights. Put away work. No more emails. Your body needs time to transition into a good morning.
You could even take it further30 minutes before bed is your clarity window. Journal if you want. Read a good book. The goal is to empty your brain so youre not lying awake thinking about all the things you need to remember.
Now try to go to bed at the same time each night. An inconsistent sleep routine prevents your body from releasing hormones at the right time, which can throw off your sleep cycle. Give your brain the right evening routine to shut down. When you prepare the night before, youre not relying on willpower in the morning. Youre just following the plan you already made.
Self-control is highest in the morning and steadily deteriorates over the course of the day. Use your evening brain, which is tired but still functional, to set up your morning brain for success.
Establishing a Routine Takes Time
Youre not going to nail this immediately. Youre going to forget something in the evening. Youll most likely stay up late watching just one more episode. If you break the chain, dont stress yourself about it. The goal is to make your defaults a little bit betterto remove some of the friction between you and the person you want to be in the morning.
Start small. Pick one thing youre going to decide the night before. Just one. Maybe its writing down three things you need to do in the morning. Do that for a week. Then add another thing. Aim to add one or two changes at a time, slowly building a routine. What you want is sustainable change.
Morning people are not more disciplined than you. They just figured out that mornings are won the night before. Do the boring work the night before. And go to bed on time. Tonight, before you go to bed, do three things. Decide what time youre waking up tomorrow. Be specific. Write down what youre doing first when you wake up.
Prep whatever you need to make that happen. Make it visible. Thats the system and the setup to give your morning a chance to be successful. Everything else can come later.
Your morning routine is failing because youre trying to build a routine without systems, and making decisions when you should be doing things. Fix the night habits, and the mornings will be better.
In 2015, in Gallups State of the American Manager report, then CEO and Chairman Jim Clifton made an assertion that startled many and quietly confirmed what others already suspected:
Most CEOs I know honestly dont care about employees or take an interest in human resources. Sure, they know who their stars are and love thembut it ends there. Since CEOs dont care, they put little to no pressure on their HR departments to get their cultures right . . .
Given the unique vantage point Clifton had into American business at the time, he offered a rather harsh and honest assessment. And, more than a decade later, the obvious question worth asking isnt whether Clifton was right then. Its whether top leaders are still operating as if he is right today.
If you ask the average American worker whether they feel their employer genuinely cares about them and their well-being, the majority will say no. Recent research shows that fewer than one-in-four strongly agreea level roughly similar to pre-pandemic lowsand perceptions of care have steadily declined even as leaders insist they prioritize their employee experience.
In my new book, The Power of Employee Well-Being, and in articles Ive recently written for Fast Company, Ive argued that companiesand their leadersmust make a transformational pivot by prioritizing employee well-being as a core driver of performance.
Sadly, Ive received many messages from readers suggesting Im fighting a lost causethat despite mountains of evidence, the leaders they work have no inclination to change. More often than not, they treat employee well-being as a complete and utter distraction from the real work of hitting goals and meeting targets.
Ive heard this lament so many times that I had to ask myself why my message hasnt gotten through. And my conclusion is that deep down, many leaders continue to fear that any support they give to their people will come at direct expense of productivity. Consciously or unconsciously, theyre convinced supporting well-being is a fools game.
Rarely stated outright, this belief system influences leaders decisions every dayhow workloads are structured, how feedback is delivered, and how much time and energy are devoted to supporting employees in ways that make a difference. The problem is theres a mountain of evidence that refutes this very fear. We now have irrefutable proof that well-being is one of the primary conditions that makes achieving goals possible.
Evidence Leaders Cant Ignore
Well-Being Drives Key Performance Metrics:Drawing on 339 studies covering 1.8 million employees, a meta-analysis from the University of Oxfords Wellbeing Research Centre found a consistent and direct relationship between employee well-being and key business metricsones most leaders are directly on the line for: productivity, customer loyalty, employee retention, and profitability.
Well-Being Predicts Performance:
As separate reinforcement, a study in Population Health Management found that high employee well-being is a predictor of future productivity, lower absenteeism, reduced disability leave and lower turnovereven when controlling for other variables. Said another way, well-being doesnt merely coexist with strong performance, it precedes it.
Investment Boosts Profitability:
New research from the Chartered Institute of Personnel and Development (CIPD) shows that organizations which meaningfully invest in employee well-being are four times more profitable than those that dontand are viewed far more positively by employees and job candidates.
Well-Being Fuels Stock Growth
Irrational Capital analyzed S&P 500 companies over 11 years and found firms in the top 20% for employee well-being outperformed the bottom 20% in stock performance by nearly six percentage points annually. Companies that intentionally offered competitively better pay and benefits alone outperformed by just two points.
Why Resistant Leaders Are Wrong
Leading a team of people, and being accountable for its results, can feel formidable at timesand its a common response for managers to believe that pushing harder and demanding longer hours is a justified action. But humans are not machines who can work endlessly without meaningful separation from work and adequate rest. When workdays feel endless, and people feel a lack of empathy and support, their capacity to focus, solve complex problems, and collaborate effectively nose-dives. Creativity stalls, mistakes increase, and high-level goals become harder to achieve. In short, neglecting well-being directly undermines the very outcomes leaders need to achieve.
The High Cost of the Status Quo
Despite many leaders vows to prioritize their employees well-being, the current reality in our workplaces is stark. Recent surveys show burnout has reached epidemic levels, nearly 60% of American workers report feeling stressed very oftenor always on the job. And burnout is the leading reason employees quit. Consequently, mental health struggles are widespread with one in five workers reporting symptoms of depression directly linked to their workplace conditions.
And the stakes arent just emotionalignoring well-being hits the bottom line. Replacing a burned-out employee can cost 1.5 to 2 times their annual salary, while disengaged or over-stressed workers lower productivity, slow innovation, and increase errors. In short, neglecting employee well-being isnt just bad for peopleits bad for business.
Leaders Wont Fix This Overnight, But Must Take The First Steps
As the journey of a thousand miles begins with a single step, leaders must be realistic that they cannot solve all these conditions overnight. What they should do first is initiate support for their teams well-being by addressing the specific things people crave most:
Emotional and Psychological Safety: Across multiple workforce studies, roughly 60% of employees say they want a culture where they can speak up without fear of negative consequences.
Belonging: Around 55% report that feeling part of a cohesive, collaborative team that valuesthem personally is their top need.
Meaningful Work: About 50% prioritize having work they know connects to a larger purpose or makes a tangible impact.
Growth and autonomy: Neary half of employees48%seek support for skill development and more control over how they accomplish tasks.
More than a decade later, Jim Cliftons jarring observation still resonates: many leaders have never cared because theyve never thought they had to. But, ignoring employee well-being today puts leaders in direct peril. Well-beingsomething 84% of all U.S. workers now say is their number-one priority in life isn’t a reward for hitting goals; it’s a condition for attaining them.
Organizations (and leaders) that invest in it see higher performance, retention, innovation, profitability, and market value. Those that don’t will fall behind, no matter how competitive their pay or perks.
The leaders who succeed in the next decade won’t choose between results and care. Theyll see this as a false dichotomy and embrace the new reality that thriving people sustainably produce uncommon results.
If this resonates, share it with a leader who needs to hear it.
Lead with care, and your organization will follow. Ignore it, and performance suffers. Its really an easy choice.
The hottest AI tool on the market today isnt a powerful frontier model from the likes of OpenAI or Anthropic.
Rather, its a kludgey, wildly complex, open-source platform thats already provoked a trademark dispute, multiple corporate bansand fawning praise from developers around the world.
Its OpenClaw, and its specifically designed to build AI agents.
I set it up, built an agent of my own, and promptly trained it to do my job for me. Heres what happened.
Beware the Claw
For more than a year now, Big AI companies have promised us an agentic AI future. AI wouldnt simply answer our queries or help us shop for a toaster, companies like OpenAI and Anthropic assured usit would actually do useful things.
Turns out, the AI giants are generally too squeamish and cost-sensitive to actually release such a tool. Because AI agents can take actions on behalf of a user, they can easily cause harm or make mistakes at scale.
As well see, theyre also blindingly expensive.
Both those things scare Big AI firms with reputations and valuations to protect. Therefore, theyve largely given users neutered versions of agentic AI.
Todays agents come with strict guardrails and perform very specific, bounded functions (like writing code or performing research). Theyre engineered to be unlikely to escape their cages or run up the compute bill.
OpenClaw is different. The system is open source and model agnostic. That means it can leverage the best LLMs from OpenAI, Anthropic, Grok, or any other company. Developers install OpenClaw on their local server or computer, giving it broad permissions.
This combination of unfettered access to hardware and tie-ins to the worlds most powerful LLMs is a potent one.
It allows OpenClaw to do things that other agents cant, spending minutes or hours acting on its users behalf, crawling the web, signing into external platforms, and even controlling cameras and local hardware.
The developers behind OpenClaw originally named it Clawdbot, a clear shot at Anthropics Claude system. Anthropic didnt take kindly to that provocation, and threatened a trademark lawsuit.
OpenClaws creators briefly named their tool MoltBot, before pivoting to the current, lobster-themed moniker.
And thats not the only trouble OpenClaw has gotten into during its brief tenure on the planet. Because the bot has such broad access to users hardware and data, multiple security experts have warned that its a potential data security disaster.
Meta and multiple other Big Tech companies have already banned their own developers from using the bot, ostensibly on privacy and security grounds.
Those bans just made me want to try OpenClaw even more. So I went to my hosting provider, found a reasonably safe way to install the bot, and set about training its agentic AI to make me obsolete.
A Steep Curve
To begin experimenting with OpenClaw, I used a Virtual Private Server from Hostinger to create a new OpenClaw instance. Basically, this keeps the bot contained within its own dedicated pretend computer, where it can do minimal damage.
I immediately discovered that OpenClaws learning curve, especially for nonprogrammers, is extremely steep. I know my way around a Linux terminal, but it still took me several hoursand lots of back and forth with ChatGPT as my guideto get OpenClaw successfully set up and ready to use.
Once it was active, I paired it with my OpenAI credentials, set it up to use OpenAIs flagship models, and set about building an agent.
My goal was simple: I wanted an agent that I could unleash on the open internet, and that would do my job as a Fast Company contributing writer for me.
Specifically, I wanted my agent to research everything happening in the world of AI, find a compelling news story, hunt down all the relevant details, write up a snappy and blindingly clever (but factual) piece in my writing style, add inline citations, craft a strong headline, and deliver the whole thing back to me.
Unlike traditional chatbots, OpenClaw allows users to configure the system deeply. To build my agent, I gave OpenClaw specific instructions about my research process, as well as multiple samples of my prior Fast Company stories. That allowed the system to learn the nuances of my writing style and determine exactly what I wanted.
After several hours of maddeningly complex configuration work, I had my OpenClaw doppelgänger ready to go. I named it AI News Desk. Then, I set it to work.
Replace Me!
Although configuring OpenClaw isto put it in technical termsa pain in the ass, using my AI News Desk agent is extremely easy. All I need to do is fire up a Linux terminal connected to my OpenClaw instance and tell my agent to work its magic.
The first thing that struck me was how long OpenClaw spends doing its work.
OpenAI users pay the company a flat monthly fee. That gives the company an incentive to do as little work as possible in responding to user queriesthe more work and thinking ChatGPT does on a given query, the more OpenAI has to spend on computing power, and the less profit it makes from the users fixed monthly fee.
OpenClaw, in contrast, doesnt care about costs or profit. Its content to blithely burn through tokens to do the best possible job fielding your request.
When I asked my agent to research and write an article for me, it often took as long as 20 minutes to produce a response, blowing though $2 to $3 worth of OpenAI API credits in the process. Thats not a lot of money in the grand scheme of things, but its way more than even a Blitz-scaling OpenAI or Anthropic would devote to a single query.
With all that work and thinking, though, OpenClaws responses were quite good.
In one test, the system successfully found a relevant piece of juicy AI news (Anthropics decision togive free users access to its powerful new Sonnet 4.6 model), researched more than 50 sources, chose a solid headline (Anthropic just moved its best everyday Claude into the cheap seats), and wrote a piece thats factually accurate and quite polished.
Functionally, the Sonnet tier just cannibalized a lot of work that used to force teams onto Opus, OpenClaw opined in the article.
I could see writing that. Human sacrifice metaphors in a business story? Thats my jam!
OpenClaw writing an article
OpenClaw even captured my propensity for including data and stats in my articles. Internal evals show developers prefer Sonnet 4.6 over 4.5 about 70% of the time and even choose it over last falls Opus 4.5 in nearly six out of ten trials, the bot wrote, citing a blog post from Anthropic.
Overall, OpenClaw did a surprisingly good job following journalistic best practices.
It has a strong sense of whats newsworthy, cites a mixture of sources (including company announcements and external analysis pieces), and keeps things compelling without embellishing facts or hallucinating. Sometimes it drones on about technical things. But then, so do I!
In short, its a decent journalistif not, Id like to think, a real replacement for yours truly.
Agents for the Win?
To be clear, I would never use OpenClaw to actually write a Fast Company article for me. But based on my experiments, the system is a compelling and powerful tool.
I spent most of my time on the basics. But with more time spent tweaking and improving its instructions and training data, I could likely improve its output even more.
I could also give the bot more capabilities beyond just writing. Because OpenClaw allows deep integrations with other tools, I could train the bot to put its articles into a Google Doc, fact-check them, and even send them directly to my Fast Company editor.
Other developers have trained the system to create videos for them, control their smart home devices, build entire iPhone apps, and clear their inboxes by responding to hundreds of emails on their behalf.
Beyond the specifics of my experiment, using OpenClaw showed me the real potential of agentic AIas well as its drawbacks.
OpenClaw bills itself as The AI that actually does things. Thats true, and refreshing. Its also expensive. In a day of using OpenClaw, I can easily spend $10 to $15. Companies like OpenAI are already burning through hundreds of billions just fielding basic ChatGPT queries. Theres no way theyd let everyday users access such a pricey technology.
That means until frontier AI models get far cheaper, agentic AI will be the purview of big enterprises that can build their own bespoke agents, and the crazy few who are devoted (and deep-pocketed) enough to implement tools like OpenClaw for themselves.
In short, based on price alone, you can ignore promises of powerful AI agents for the masses. Model prices will come down, though. And when they do, even consumer-friendly tools will be able to pull the same magic as OpenClaw.
The agentic future will arrive. But not until its profitable.
“AI;DR” is new internet speak for AI-generated slop posts have just dropped. It is a riff on the initialism TL;DR (too long; didnt read), which is often wielded as a criticism of a piece of writing simply too long or confusing to be worth the time it takes to read.
The AI slopification of LinkedIn, X, and other social media platforms has been much discussed. A 2024 study found that more than 50% of long-form LinkedIn posts are likely AI-assisteda surprise to exactly no one who has spent more than a few minutes scrolling the feed. That number has likely only increased in recent years, as AI becomes more embedded in our daily processes. Were now entering the era of “AI unless proven otherwise.”
Often the intent behind these AI-slop posts is metrics and engagement at the expense of quality writing. LinkedIn’s algorithm slurps it up, so everyone keeps churning out more of it.
Now, internet users are refusing to give the slop machines what they want, calling out clearly AI-generated posts with the declaration ai;dr (artificial intelligence; didnt read). Because why bother reading something someone else couldn’t be bothered to write?
This is not the first anti-AI term to enter the lexicon. Google Trends data showed a spike in searches for clanker (a Star Wars-inspired insult used to mock robots and AI systems) in mid-2025. On an X thread, suggestions for what to call users of Xs AI chatbot Grok included Grokkers, Groklins, and Grocksuckers. Meanwhile, on TikTok, someone came up with sloppers to describe people who are becoming increasingly overreliant on ChatGPT.
The actual word of the year for 2025, as crowned by Merriam-Webster, was slopsumming up the general mood.
AI;DR was coined on Threads by developer David Minnigerode in response to AI safety researcher Mrinank Sharmas resignation letter from Anthropic. Sorry, that is definitely tl;dr. But also kinda ai;dr. Some of those sentencesyeesh, Minnigerode wrote.
The new term was taken up with enthusiasm in the replies. You just coined something bro, one of those now that I see it I cant believe it took this long to come up with, which is the best kind of discovery, one Threads user responded. We all need to adopt that right quick, another user on Bluesky said.
The call to arms is at a time when anti-AI sentiment is growing. Concerns about AI among U.S. adults have escalated since 2021, according to the Pew Research Center. More than half (51%) say they are more concerned than excited about the technologys rise.
From the SaaSpocalypse to Hollywoods freak-out over Seedance-generated blockbusters, AI is moving in fast on a range of industries, leaving a trail of “workslop” in its wake.
Next time you come across a clearly AI-generated chunk of text, instead of, Grok, what is this about?, hit them with an “AI;DR”it’s a small victory in clawing back our shared humanity.
Most workplace frustration doesnt come from a lack of effort or commitment. It comes from expectations that werent metnot because people failed to try, but because those expectations were never clearly stated or truly understood.
In our organizational research over the past 30 years, weve seen this pattern repeatedly: when expectations are unclear, trust in leadership and collaboration begins to drop. When this happens, the frustration that follows is real. But the deeper cost is often invisibletrust begins to erode.
This dynamic is increasingly common. Roles evolve, priorities shift, and teams are asked to move faster with less certainty. People continue to work in good faith, investing energy and time into what they believe is needed. They solve problems based on experience and what has worked before. When theyre later told the outcome fell short, the issue is more than disappointment. Its disorientation. People begin to question their judgment and whether they can reliably meet expectations going forward. Over time, that uncertainty weakens collaboration and trustthe sense that people are truly working with one another toward a shared outcome.
Consider a common scenario. A leader asks a team member to move this forward quickly. The work gets done on time, but when its delivered, the leader is disappointed. What they needed wasnt just speed, but alignment with a broader strategyor more collaboration with another team before finalizing decisions.
The expectation wasnt ignored; it was incomplete. The leader never named the strategy, nor the need. In the absence of clarity, effort went in one direction while expectations lived in another.
Over time, moments like this teach people to hesitate, over-check, or disengage because trust in their understanding has been shaken. Heres how to break that cycle.
Set expectations explicitly
This means being clear not just about tasks or deadlines, but about what success looks like, along with what constraints or tradeoffs are in play. It also means being realisticconsidering current priorities and what support may be required to do the work well.
Rather than assuming clarity, make it visible. Instead of saying, Can you move this forward? try something more specific: Id like to review my expectations with you for clarity. What Im trying to accomplish is [outcome], and what matters most here is [speed, quality, alignment, or collaboration]. I need this delivered by [timeframe], and I want to make sure thats realistic given everything else youre managing.
Setting expectations this way signals partnership, not control. It shows consideration for others and consistency in how expectations are applied. It also opens the door to an essential question: What do you need from me? Asking that upfront helps leaders provide the right support and ensure people are set up to succeed.
Confirm understanding before work begins
Shared history and good intentions can create the illusion of alignment. Leaders may believe expectations are obvious, that others understand what matters most, or that capable people will speak up if something is unclear. In effect, clarity is assumedand theres often an unspoken expectation that people will initiate their own understanding.
In reality, many people hesitate to ask clarifying questions, especially in environments shaped by urgency or rapid change. They dont want to slow things down, appear uninformed, or challenge direction. Trust is strengthened when leaders treat clarity as something to be created together, not something to be inferred.
Rather than assuming alignment, invite it. That might mean asking someone to reflect back what they heard or encouraging them to surface concerns. For example, instead of asking, Any questions?which often shuts conversation downtry something more specific: Before you get started, Id like to make sure were aligned. What are you hearing matters most here? or What concerns or constraints do you see?
And if youre the person receiving the instruction, this is a moment to step into ownership. Asking a clarifying question doesnt signal uncertainty: it signals engagement. Questions like, Can I confirm my understanding of what success looks like? or What would be most helpful from you as I work on this? both clarify expectations and demonstrate initiative. Managers notice this. It builds confidence on both sides and reduces the risk of misalignment later.
Renegotiate expectations when reality changes
Because it always does. Expectations can grow larger than anticipated, take longer than expected, or become more complex as work unfolds. New priorities emerge. Constraints surface. Resources shift. When these changes go unaddressed, people continue operating on outdated assumptions, drifting further out of alignment.
Renegotiation isnt a failure of planning; its a leadership and partnership responsibility.
If youre receiving an expectation and recognize that something has changed, bring it up immediately. Share what youre seeing, explain whats different, and be explicit about the support that would help you succeed. That might sound like:As Ive been working on this, Im realizing the scope is larger than expected because [reason]. Im concerned I wont be able to meet the original expectation as defined. Id like to talk about what supportor what adjustment to scope or timingwould help me complete this successfully.
Asking for support isnt a sign of weakness; its a sign of ownership.
If youre the one who set the expectation, make support visible. Ask questions like: Are you running into any challenges? Is there anything I need to be aware of thats creating a barrier to progress? or What support would help you get back on track? These questions normalize course correction and reinforce that success is shared.
Renegotiation replaces disappointment with dialogue. It keeps people aligned to what matters now, not what mattered when the expectation was first set. And it reinforces a critical truth: trust isnt built by pushing through in silence, but by adapting together when reality changes.
Managing expectations is one of the most overlooked ways trust is built at work. When managers make expectations visible, confirm understanding, and adapt together as needs change, they create more than alignmentthey create confidence. People know whats expected, why it matters, and where to ask for support when reality shifts. In a world defined by constant change, that kind of partnership isnt a luxury. Its a management responsibility.
When social psychologist Jonathan Haidt published The Anxious Generation in March 2024, his core proposalthat children should be kept off social media until at least age 16, with tech companies bearing the burden of enforcementwas treated by many as aspirational, even quixotic. The tech industry dismissed it. Libertarian critics called it paternalistic overreach. Skeptics questioned the evidence base.
That was then.
In barely two years, Haidt’s “radical” idea has become something close to a global consensusa textbook example of what political scientists call the “Overton Windowone that’s shifted at extraordinary speed.
The Overton Window describes the range of ideas that are considered politically acceptable at any given time, ranging from unthinkable to popular and eventually to policy. Ideas outside the windowno matter how sensibleget dismissed as too extreme, too impractical, or too politically risky to touch. But when conditions change, the window can move, sometimes gradually and sometimes with startling speed, pulling yesterday’s fringe idea into today’s mainstream. That is exactly what has happened with children and social media. Politicians everywhere are now racing to get on the right side of a window that has moved decisively.
The Floodgates Have Opened
Consider what has happened just since late 2025. Australia led the charge, enacting an outright ban on social media for children under 16 that took effect in December 2025, with monetary penalties falling squarely on the platformsnot on parents or kids. France has passed a bill banning social media for children under 15. Denmark secured cross-party support for a similar ban, expected to become law by mid-2026. Spain, Germany, Malaysia, Slovenia, Italy, and Greece are all moving in the same direction.
In the United States, where bipartisan agreement on anything feels miraculous, the Kids Off Social Media Act has attracted co-sponsors from both partiesSen. Brian Schatz (D-HI) alongside Sen. Ted Cruz (R-TX), and Chris Murphy (D-CT) alongside Katie Britt (R-AL). Virginia enacted a law effective January 2026 limiting under-16 social media use to one hour per day unless parents opt in. Over 45 states have pending legislation.
And in the U.K., a January 2026 government consultation is explicitly considering a social media ban for children, after the House of Lords defeated the government to insert an under-16 ban into the Children’s Wellbeing and Schools Bill.
This is no longer a debate about whether to act. It’s a debate about the details.
Why the Window Moved So Fast
Several forces converged to make this shift possible.
First, mounting evidence. Haidt marshaled data showing that since the early 2010sprecisely when smartphones and social media became ubiquitous among teensrates of anxiety, depression, self-harm, and suicide among young people have surged across the developed world. The patterns are strikingly consistent across countries and cultures. As Haidt puts it: We “over-protected children in the real world and under-protected them online.”
Second, personal stories that broke through the noise. Australia’s ban originated partly from a mother’s letter to Prime Minister Anthony Albanese about her 12-year-old daughter’s suicide following social media bullying. At the U.N. General Assembly in September 2025, a mother’s speech about her daughter’s “death by bullying, enabled by social media” won support from world leaders across continents. Data persuades policymakers; stories move publics.
Third, the collective action problem became too painful to ignore. Haidt nailed this insight: Individual parents feel powerless against platforms engineered by billions of dollars of design expertise to maximize engagement. No single family can opt out without socially isolating their child. This is precisely why governments need to shift the responsibility to the platforms. When enforcement becomes the tech companies’ problemnot the parents’ problemthe collective action trap breaks.
Fourth, early results from related interventions are encouraging. Arkansas’ phone-free-school pilot program showed a 51% drop in drug-related offenses and a 57% decline in verbal and physical aggression among students within the first year. Results like these give politicians the cover they need to act boldly.
The Strategic Lesson
For those of us who study how change happens, this is a master class. An idea that seemed politically impossible in early 2024 has become politically inevitable by early 2026. That’s the speed at which Overton Windows can move when lived experience, accumulating evidence, moral urgency, and a clear articulation of the problem all align.
Note, too, where the burden of proof has shifted. Two years ago, advocates for restricting children’s social media access had to justify intervention. Today, it is the tech companies and their defenders who must explain why children should continue to have unrestricted access to platforms designed to be addictive. That reversalthe shift in who must justify whatis the surest signal that an Overton Window has decisively moved. It is further set against the backdrop of the first set of legal challenges to the platforms business models, arguing that their designers have deliberately designed their products to be harmful to maximize their profits.
What Comes Next
Haidt, a professor of ethical leadership at New York University, didn’t create this movement alonemillions of anxious parents, grieving families, and alarmed educators did. But he gave it a framework, a language, and a set of actionable proposals. And now, politicians everywhee are scrambling to catch up with what parents already knew in their bones: that we handed our children’s attention, self-worth, and mental health to companies that optimize for engagement, not well-beingand that better guardrails, uniformly enforced, are essential.
For decades, weve been told that the smartest organizations are data-driven. The phrase carries moral weight. To be guided by data is to be serious, rational, modern. If youre not, youre seen as ideological or sentimental. In the workplace, quantification has become synonymous with credibility and competence.
And yet, the more data we accumulate, the less certain we seem to be that we are making better decisions. Theres a paradox. Organizations are drowning in dashboards, KPIs, performance metrics, behavioral traces, biometric indicators, predictive scores, engagement rates, and AI-generated forecasts. We have more data than we know what to do with. We pretend that the mere presence of data guarantees clarity. It does not.
Thats data hubristhe arrogant belief that because something can be measured, it can be mastered.
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The Illusion of Objectivity
In executive meetings, a slide filled with graphs and percentages signals authority. Numbers appear to silence dissent and create the impression of neutrality. But behind every dataset lies a series of human decisions: what to measure, how to measure it, what to ignore, and how to interpret it. Metrics are never neutral; they are constructed within particular frameworks, assumptions, and interests.
Too often, data is used not to inform decisions but to justify them after the fact. It lends post-hoc legitimacy to strategies already chosen, wrapping subjective choices in the language of objectivity. Take creative industries, for example, where algorithms supposedly predict success. Netflix built part of its reputation on data sophistication, claiming to understand viewers better than traditional studios ever could.
Yet insiders have described how metrics shift, interpretations vary, and executives selectively highlight numbers that support their preferred projects. The result can be content engineered to be watchable but forgettableoptimized for fragmented attention rather than lasting cultural impact.
Also, the problem is that data reflects the past. It captures what has already worked, not what might resonate tomorrow. It struggles to grasp the emerging mood of a societythe intangible zeitgeist that makes a story, product, or idea feel timely. Focusing on backward-looking indicators institutionalizes mediocrity.
When Data Confirms What We Already Know
The same pattern appears in corporate HR, where the rise of people analytics promised revolutionary insight into engagement and performance. Sensors track badge swipes, algorithms map collaboration networks, and predictive models estimate attrition risk. After enormous investment, companies often discover that good managers matter, that employees dislike micromanagement, and that people leave when they feel undervalued.
These findings are hardly revolutionary. Some of the most celebrated data-driven insights simply confirm what experienced people already suspected. There is a widening gap between the sophistication of measurement tools and the banality of many of the conclusions they generate. In open, messy environments, organizations often produce vast quantities of noise and mistake it for knowledge.
Healthcare offers another revealing example. Radiology once seemed perfectly suited for AI transformation: millions of standardized images and clear diagnostic categories. Early systems performed impressively on routine cases. However, real-world practice quickly exposed limitations. Radiology reports are filled with cautious phrasescannot rule out, clinical correlation recommendedthe product of decades of medico-legal prudence. Algorithms struggle with this ambiguity and may flag excessive urgencies because they cannot distinguish legal caution from genuine clinical risk.
More fundamentally, medicine is defined by exceptions. AI may handle 90% of common cases effectively, but it is the rare and atypical cases that truly test expertise. A seasoned radiologist can reason through an unprecedented situation; an algorithm remains confined to its training data. Abundant historical data does not eliminate the variability of reality.
The Blind Spots of Overconfidence
One of the most dangerous effects of data hubris is overconfidence. When decisions are backed by numbers, leaders may lose caution. Digital traces capture clicks and transactions but not informal conversations. Not everything meaningful leaves a digital record, and dashboards rarely display their own blind spots.
We face what we don’t know we don’t know. In his work on uncertainty, Vaughn Tan distinguishes between riskwhere probabilities are calculableand deeper forms of not-knowing where probabilities themselves are unknown. Treating all uncertainty as if it were calculable risk is a category error.
Mathematics cannot resolve questions about emerging values and unprecedented events. The COVID-19 crisis illustrated this confusion vividly. Some leaders relied heavily on models built from previous diseases, assuming that all unknowns were simply risk variables awaiting calculation. In reality, many were genuine uncertainties that required experimentation, humility, and adaptive learning.
From Data Mastery to Uncertainty Literacy
Data hubris can also extend into one’s personal life through the quantified self movement. Wearables measure sleep cycles, heart rate variability, step counts, and glucose levels, promising unprecedented self-knowledge. But more information does not always mean better well-being. In medicine, excessive testing increases the risk of false positives, detecting anomalies that may never cause harm but may trigger anxiety and invasive follow-ups. Constant self-tracking can fuel obsession. Instead of asking whether we feel rested or hungry, we defer to numerical indicators, thus ignoring more intuitive signals (feeling hungry, rested . . .).
None of this means we should reject data. Of course not. Data is invaluable. But it must sit within a broader understanding of how knowledge is actually producedthrough field observations, expert judgment, and lived experience. Data demands interpretation. It requires humility nd open conversations. What is missing here? What assumptions shaped these metrics? Who decided what to measureand why?
In genuinely uncertain environments, small, reversible experiments often outperform grand predictive models. Instead of pretending to know, organizations can probe, learn, and adapt. Intuitionfar from being irrationalrepresents compressed experience accumulated over time. Above all, leaders must remain humble in the face of unknown unknowns. The most sophisticated analytics cannot absolve decision-makers of responsibility.
As sensors multiply and AI systems proliferate, the temptation to equate measurement with mastery will only intensify. Beware of data hubris. Knowing that we do not fully know is the foundation of sound judgment in a world that remains irreducibly complex.
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A culture of fear makes it easy to cloud our judgment
For thousands of years, walking and horseback riding were the fundamental modes of transport, and settlement patterns were a direct reflection of transport options. Compact, low-rise villages and cities made sense based on how far people could reasonably travel on foot or by horse. This was true all the way up until the late 1800s.
Then came an invention that let people travel incredible distances in seconds, entirely reshaping cities with dense population clusters. The technology was a sturdy box designed to transport multiple people at once, but often carried just one. I’m talking, of course, about the elevator.
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Elevators transformed city planning in remarkable ways, long before automobiles sprawled life horizontally. Before elevators, buildings stayed squat because stairs limited height. Walking up two or three flights isn’t terrible. Carrying a briefcase up 10 flights of steep, dark stairs to the office is, pardon the pun, another story. It didnt take long for skylines to change following the invention of the elevator.
Each early elevator had its own operator who mastered the timing and touch of hand-crank controls. These operators wore their Sunday best as a psychological reminder: “We will safely get you to your destination.” Brilliant minds innovated on the elevator, adding safety technology like automatic brakes, but it was the human touch that eased public nerves. It’s hard now to imagine feeling completely helpless in an elevator, but such was life in the early 20th century. Zero chance ordinary people like you and me were going to attempt to operate an elevator without rigorous training first.
Full automation
That changed dramatically with the September 1945 New York City elevator operators’ strike. Around 15,000 operators, doormen, porters, and maintenance workers walked off, halting service in over 2,000 buildings. About 1.5 million people avoided elevators, opting for stairs or staying home rather than risk operating the cars themselves. But self-service features like electric power, emergency phones, and push buttons were already spreading, so the strike helped open the doors to full automation.
Self-driving elevators! You can practically hear the traveling public gasp. Walk into a box, let the doors close and lock you in, and trust that this thing would take you quicklybut not too quicklythe proper distance.
Otis gets credit for installing the first fully automated elevator in 1950 in Dallas. But the transition took time, both for technology to improve and for a skeptical population to trust it. Operators were still employed in some cities 30 years later. Today, you can casually scan your hotel room key in a lobby that summons a box to whisk you to your precise destination without even pressing buttons inside.
A public health crisis
You and I will never have the time, energy, or need to read the thousands of opinion pieces about the dangers of autonomous technology as it relates to cars. And as robotaxis accelerate deployments in 2026, there will be no shortage of fear-based stories.
There’s no scenario, with or without technology, that results in a danger-free life. The challenge for us is to identify and analyze trade-offs without being clouded by ideology or thwarted by lazy straw man arguments.
I’m not a technology expert, so I don’t get too deep on what a particular shiny new object can or can’t do. I am a traffic safety expert, though, and I can tell you motor vehicle deaths remain a public health crisis.
Every day, more than 100 people are killed in traffic crashes, and thousands more experience life-altering injuries. That’s the track record of human drivers for decades. Software can save lives by preventing people from driving too fast, running red lights, passing school buses, tailgating in bad weather, or committing other dangerous antisocial acts. If only 50 people are killed each day because of autonomous technology, isnt that worth celebrating? What if the technology could bring traffic fatalities down to nearly zero?
It’s natural to be scared by emerging tech. Early elevator riders felt helpless stepping into a closing box with no operator to guide them. But people adapted because the status quo (stairs limiting how we could build and live) was worse, and incremental safety features built confidence over time.
There are absolutely valid concerns about autonomous vehicles, like software hacking, or failure to recognize a one-way street. But remember that humans are not the safest operators, that our current state of mobility is a public health crisis killing tens of thousands every year. Autonomous vehicles programmed to operate safely are part of the quest to design for human flourishing.
If we’ve entrusted machines to carry us sky-high without hesitation, we can approach transportation systems the same way: cautiously optimistic, evidence-driven, and open to progress that saves lives.
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This coverage is made possible through a partnership between Grist and BPR, a public radio station serving western North Carolina.
The Tennessee Valley Authoritys (TVA’s) quarterly meeting in Hopkinsville, Kentucky, opened with a triumphant video homage to its work during Winter Storm Fern. Energy had come through, yet again, to defeat extreme cold. The montage credited this to the utilitys coal workhorses, then noted that nuclear provided uninterrupted power and hydro responded instantly. The list ended there, despite years of promises that the agency would bolster renewables and battery storage. The message was clear: Solar had been unceremoniously dropped from the mix, and coal, which the agency had been phasing out, was back.
What the video hinted at, the board made official. Its seven members unanimously dropped renewable energy as a priority, ended diversity programs, and granted two of the agencys four remaining coal plants a reprieve. The decision followed the seating of four members selected by President Trump, breaking months of paralysis that followed the termination of three Biden appointees.
The changes, made during the February 11 board meeting, signal more than a routine policy reset for the nations largest public power provider. They will slow the TVAs shift away from fossil fuels just as electricity demand is spiking, raising questions about future costs, pollution, and the role of federally-owned utilities in the countrys energy transition.
For years, TVA planners had mapped out a future without coal. That is now on hold. The Kingston Fossil Plant in Roane County, Tennessee, was scheduled for retirement in 2027, with all nine of its units slated for demolition and replacement with an energy complex of gas generation and battery storage. All of them will remain online alongside the gas plant, but renewables are no longer part of the picture. The board also shelved plans to scuttle the Cumberland Fossil Plant in Stewart County, Tennessee, in 2028.
These moves come despite the agencys 2025 Integrated Resource Plan, which called for retiring the two facilities because of Kingstons high cost and challenged condition and Cumberlands lack of flexibility. The Kingston coal plant was also the site of a devastating 2010 coal ash disaster, the largest industrial spill in U.S. history.
The board defended its decision by citing energy affordability for the Tennessee Valley.
As power demand grows, TVA is looking at every option to bolster our generating fleet to continue providing affordable, reliable electricity to our 10 million customers, create jobs, and help communities thrive, agency spokesperson Scott Brooks said in a statement.
Left unsaid was the fact that a coal-fired power generation unit at the Cumberland Fossil Plant failed during last months storm.
Much of TVAs load growth comes from the rise of artificial intelligence, said CEO Don Moul, and data centers account for 18% of its industrial load. During the same meeting, the board allowed the company xAI, owned by Elon Musk, to double the amount of power it draws from the grid.
For former board member Michelle Moore, one of the Biden-era appointees President Trump fired in March, the shift aligns squarely with the administrations priorities. It also signals, she said, that the utility is no longer fulfilling its mission to provide affordable power, economic development, and environmental stewardship across the seven-state Tennessee Valley. The politics in Washington may change, she said. But the TVAs mission does not.
That independence has at times put the Tennessee Valley Authority at odds with presidents of both parties. The utility resisted Trump administration pressure to keep coal plants open, continuing to retire facilities based on economic reasons. But it also fell short of President Bidens decarbonization goals.
Moore worries ordinary ratepayers are no longer an active part of TVAs decision-making. Typically, a shift as monumental as turning away from renewable energy would have been subject to a lengthy review with input from communities throughout the region, something that simply will not occur now. This is one more indicator that the public power model is being eroded and is at risk, Moore said.
Last month, the TVA said it would streamline how it reviews the ecological impacts of its projects, allowing some to move ahead with far less, if any, scrutiny. The move follows a broader rollback of the National Environmental Policy Act under President Trump that grants greater discretion over such considerations to entities like the TVA. For nearly 60 years, the law required an assessment of the environmental impacts of federal projects. Over the past several years, the TVA board has faced pressure to make decisions based on stringent environmental regulations, said board member Wade White.
The TVAs willingness to join the Trump administrations push to revive the coal industry has rankled locals and environmentalists. In the first year of his second term, President Trump lifted Environmental Protection Agency restrictions on the industry, used emergency executive orders to keep aging coal plants open, expanded mining, and ordered the Pentagon to buy electricity from power plants that use coal. The president has since received an award from industry executives dubbing him the Undisputed Champion of Clean, Beautiful Coal.
From a public health standpoint, its a nightmare. Coal is one of the worst things you can imagine for the environment, said Avner Vengosh, a professor of environmental quality at Duke University who leads a coal and coal ash research group. Mining destroys ecosystems and poisons groundwater, polluting rivers and streams with sulfuric acid. Burning the fossil fuel releases fine particulate matter, impacting the health of nearby residents. A 2023 study in the journal Science found that coal plants caused nearly half a millon excess deaths between 1999 and 2020, and a Sierra Club report notes that TVA coal-fired plants were the nations deadliest.
People are upset, they feel like were going backwards, said Amy Kelly, a Sierra Club campaign manager. The fact that these plants are from the ’50s and ’60s, and were just going to prop them up with Band-Aid solutions to appease the current administration is going to cost people.
Even some coal plant operators agree. A Colorado utility is suing to close a facility, calling a federal emergency order to keep it online unconstitutional. For those who live near the two plants the TVA just saved, the decision is, in Joe Schillers words, a betrayal. Schiller, a retired college professor, has lived near the Cumberland plant for 30 years. It contradicts everything theyve told us about the plants in the past, he said. Even so, he added, its a beautiful area. Moments before, his wife had called him outside to admire the sandhill cranes flying by.
Its not like you look around every day and say, Yep, that Cumberland plant is slowly killing me, Schiller said with a laugh. Although it probably is.
Reading or sending emails may seem like an innocuous task, but sometimes, this simple act can trigger a dramatic bodily response. Like forgetting to literally breathe.
Many of us have heard of sleep apnea: the condition where breathing gets interrupted during sleep. Dora Kamau, Lead Mindfulness and Meditation Teacher at mental health app Headspace, told Fast Company. Email apnea is a similar ideajust happening in the middle of your workday,
When we’re intensely focused on a task, the brain will “switch off” certain unconscious functions to redirect its processing power to the task at hand. In that state, a lot of people unknowingly alter their breathing, taking short sips of breath, or sometimes holding it altogether.
The term for this phenomenon was first coined by Linda Stone in the late 2000s in an article published by HuffPost. After noticing her own breathing became shallow when sat at her computer checking her emails, she decided to invite 200 participants to take part in a study at her home.
She found that 80% of the participants also breathed more shallowly when stationed in front of a screen. Those who didnt had received some kind of formal training in breathing as either athletes, dancers or musicians.
When we open an inbox, scroll through a feed, or get pulled into something on a screen, our nervous system shifts into low-grade alert mode, explains Kamau. In these moments, the body is doing what has been designed to do: to protect us. Its a human, biological response to perceived uncertainty, threat or danger, which in the modern world, an overflowing inbox can feel like.
If you dont think you do this, the tricky thing about email apnea is that its easy to miss, because it happens in the background of something else youre doing, says Kamau.
Do you reach the end of a work session feeling inexplicably tired, even if you havent done anything physically demanding? Do you suffer from tension headaches or a tight feeling across the shoulders and chest? Do you find yourself taking a big, involuntary sigh or deep breathing without really knowing why?
These are all signs of email apnea. That sigh is your body self-correcting, trying to restore balance after a period of shallow or held breath, says Kamau.
When we hold our breath or breathe shallowly for extended periods, carbon dioxide builds up in the bloodstream, signaling to the body to stay on high alert. Even after you’ve closed the email, that stress response keeps running, holding on to that tension long after your laptop is shut.
It also negatively impacts cognitive function, Kamau explains. When we’re not breathing fully, we’re not getting optimal oxygen to the brain, which means decision-making, creativity, and focus all take a hit. Ironically, the very things we need most at work.
Next time youre racing to hit inbox zero, take a beat and notice your breath. Slow diaphragmatic breathing, expanding the lungs fully and breathing into the stomach, signals to the body it can relax. It reduces the heart rate, lowers blood pressure and can even help us make better decisions.
Its also important to designate mini-breaks to keep email apnea at bay. At Headspace, we just created and launched a Pomodoro timer specifically designed with this in mind, says Kamau.
Making micro-adjustments to the way you sit can help, too. Hunching over a screen compresses the lungs and makes full breathing physically harder, she says.
Simply sitting up slightly, rolling the shoulders back, and dropping them away from the ears creates more space for the breath to move in our bodies.
