Unclosed Loops: Why We Remember the Rude Stuff

What is Baumol’s cost disease?Why do healthcare and education costs rise faster than inflation?Will AI make services like healthcare and education cheaper?The Phoenix Symphony sold more tickets, cut its office costs, and still laid off 66 musicians. I use that story and a 1960s idea from economist William Baumol to explain why tuition, childcare and doctor’s visits keep climbing while almost everything else gets cheaper. Then I test it against Sam Altman’s promise that AI will make everything cheaper. You’ll come away knowing which costs AI can bring down, and which part of your life it will make more expensive.Baumol’s cost disease is an economic idea from William Baumol explaining why work that depends on people’s time, such as teaching, nursing and live performance, gets more expensive over time. Technology makes factory and software workers more productive, which raises wages across the whole economy. Industries where a person’s time is the product have to match those wages without getting any more productive, so their prices rise faster than inflation. AI can lower the cost of work where a person was only the means of getting it done, such as tax prep or reading an X-ray, while the work where the person is the product gets relatively more expensive.#futureofwork #inflation #BaumolsCostDisease #AIEconomics #ClassicalMusic #OrchestraLIfe #ArtsAdministration

A ticket sold by one airline and flown by another can fail at check-in in a way neither airline can see in full, leaving the customer to carry information between them. Adele Wang argues that problems falling between companies persist even as each company adopts AI, because no single company owns the gap and the cost of failure is spread across customers instead of showing up on anyone's budget.The day before a trip to Croatia, my check-in failed somewhere between KLM and Delta. Each airline sent me to the other, and for an hour at the Atlanta airport I was the only one who could see the whole problem. The technology to catch failures like this already exists. Here's why nobody puts it to work, and who ends up doing the job instead.Essays: Wired for Meaning on SubstackLinkedIn: Adele Wang#AllThingsHuman #AI #CustomerExperience

A man in West Africa was tied up and taken at gunpoint over a payroll schedule. Nobody in the story was a bad person.Head office wanted to save money, so payroll moved from every two weeks to once a month. It made sense on a spreadsheet. Nobody asked the 600 guards how they lived, or knew that most of them were feeding whole villages on a two-week rhythm. Ten days later children were not eating. A bodyguard did the fastest thing he could think of to get someone's attention.Leanne Terrace was there. She has spent the thirty years since working out why groups of well-meaning people keep doing this to each other, and what stops it.This one is about companies. It is also about your HOA, your PTA, your church committee, and every group of humans that ever went quiet after somebody overruled them.Leanne's book, Built to Think, comes out September 17.Built to Think: https://builttothink.aiWired for Meaning: https://adelewang.substack.com

Adele published a quiet episode about walking her dog. Within a day, dozens of emails arrived pitching podcast guests, and nearly every one quoted the exact same abstract phrase back to her. None of the senders had listened. This is what happens when the effort that used to prove attention gets automated away, and why nobody in the production machinery has a clue that it failed the end recipient. The irony is that most of the pitches were generated by AI to promote guests hoping to be booked to talk about the importance of authenticity and being human in the age of AI.AI podcast booking tools scrape transcripts of newly published episodes, extract a quotable phrase, and generate personalized-looking guest pitches at scale, often without anyone listening to the episode. When the effort that once proved genuine attention is automated away, the host can no longer distinguish real interest from generated flattery. The failure is invisible to the sender because no feedback loop exists to report that the pitch fell flat.#AI #ArtificialIntelligence #Podcast #Automation #FutureOfWork #Technology #WorkSlop #AISlop #Podcasting #ColdOutreach #AIEthics #HumanConnection #DigitalCultureQ&AWhy am I getting so many AI-generated podcast guest pitches promoting authenticity?How can you tell a podcast pitch was written by AI?What does automated outreach do to genuine signals of attention?

You can know a person for years and never learn their name. You know their dog, though. You know Max is reactive, that Sophie just had surgery, that the golden at the corner loses his mind the second he spots you. The human stays a little bit of a mystery, and somehow that works fine.This is a solo episode about the friendships that live entirely on the sidewalk. How a dog gives two strangers permission to stop and talk. Why the dog's name sticks while the owner's slides right off. And why these light, low-stakes connections do real work in a neighborhood, the kind of work that used to belong to front porches and corner shops.I used to think relationships like this were shallow. I've changed my mind. There is a particular comfort in being recognized by someone who isn't asking for your whole life in return. We want to be known. We don't always want to be examined. A good dog walk hands you the first without the second.If you have ever hidden the fact that you forgot someone's name for the eighth time, this one is for you.Listen, then tell me: how many dogs on your street do you know by name, and how many owners?Watch the video version on YouTube: All Things Human with Adele Wang Essays: Wired for Meaning on Substack Connect with Adele on LinkedIn

Psychologists call it contamination theory. When something pure comes into contact with something threatening — even at trace levels — we consider the whole thing spoiled. Researchers are now finding the same response in how audiences value creative work that involves AI.In this episode, I walk through a recent University of Chicago study where participants bid real money for art prints at different levels of AI involvement: 100% human, 1% AI-assisted, 30% AI-generated. The result was striking. The penalty for 1% AI involvement was nearly identical to the penalty for 30%. The contamination response isn't proportional. It doesn't respond to information. And across multiple studies spanning 2023 to 2026, better AI technology didn't change it.We also get into what this means practically for creators. Audiences consistently pay a premium for work that carries evidence of irreplaceable human time and effort. Those same audiences now expect a level of polish that AI tools produce. Both things are true at once, and there's no clean way through it.What are we actually protecting when we resist AI in creative work? Quality? The studies suggest probably not, since the work can be identical. Something harder to name — proof that a specific person chose to spend finite time on something they didn't have to.This episode doesn't resolve the tension. It tries to name what's underneath it.Topics: AI and creativity, AI disclosure, content authenticity, creator economy, contamination theory, human creativity, AI ethics, content strategy, AI-generated art, podcast about AI, staying human in the age of AI.#AIandCreativity #ContentStrategy #CreatorEconomy #HumanCreativity #AIDisclosure #ContentCreators #AIEthics #DigitalCreativity #Authenticity #FutureOfContent

"I Was Breaking the Internet. Then My Brain Broke First."Why is everyone generating so much content than ever before?Today, millions of creators are using AI to produce content faster than humans can consume it, leading to "Content Shock."Episode Description: I Was Breaking the Internet. Then My Brain Broke First.We are currently living through the loudest, fastest, and most saturated era in human history. Every second, millions of determined creators, powered by AI, are frantically churning out infinite content, all competing for a shrinking slice of your attention. They are shouting louder, optimizing faster, and yes, "breaking the internet."But while content might be infinite, human capacity is not. In this episode, we explore the quiet catastrophe occurring on the other side of the algorithm: a profound, physical failure of the audience to keep consuming.I’ve been on both sides. I know the seductive, frantic energy of chasing that "break the internet" moment. I know how it feels when your output is unstoppable. But I also know what happens next. My brain broke first.This isn’t a forecast about a future "apathy"; it’s a post-mortem on the "Maxed Out" audience of 2026. Join me for a contemplative, deeply personal, and ultimately empowering look at "Content Shock."We will discuss:The "Loudness War": Why creators are shouting into a void that is already full.The Physical Limit: Why a single human brain simply cannot process infinite churn.The Great Retreat: Inside the silent, powerful, and necessary audience flight from the noise.Finding Sanity: Practical strategies for rebuilding your own attention filters and reclaiming your mental sovereignty.The frantic race to out-produce the machines is a race to the bottom. In an age of infinite automated clutter, the winners of the next decade won't be the ones who produced the most; they’ll be the ones who dared to stay human.Ready to stop breaking the internet and start rebuilding yourself? Join me. Reclaim your focus.

About this Episode: This is a Raw Memo edition of All Things Human. In the spirit of staying authentic and keeping the conversation moving, I’m skipping the studio polish and the theme music to bring you a thought exactly as it happened.In this memo:The "Type 3" Distraction: Why some public behaviors feel like a "system failure" rather than a simple annoyance.Unclosed Loops: The psychological reason why we remember a rude encounter from 15 years ago.Shared Scripts: How the lack of explicit rules in public spaces is changing the way we interact with one another.The Goal of All Things Human: To explore the quiet rules of how we are with each other—even when those rules get broken.#HumanExperience #PublicEtiquette #RawPodcast #SocialPsychology #HumanBehavior #AllThingsHuman

Have you ever had an automated system deny your loan, flag your social media post, or change your work schedule without explanation?In this episode, we dive into the "talk of the town" in tech circles: AI Governance. What is AI Governance?. While it sounds like a dry topic for lawyers, it’s actually a deeply human issue that impacts our daily lives and livelihoods.We explore the growing "accountability gap" where decisions are made instantly and at scale, yet no single human feels responsible for the outcome. From the workplace to customer support, we break down why the current lack of clear ownership is eroding trust—even when the technology is working exactly as designed.Key topics covered in this episode:The Black Box Effect: Why "the system flagged it" is becoming the ultimate shield against accountability.Human Speed vs. AI Scale: How the transition from manual audits to instant, automated decisions has broken our traditional feedback loops.Ethics vs. Accountability: Why having an "ethics team" isn't the same as having someone empowered to stop or reverse a system.The Future of Trust: What leaders must do to bridge the gap between human responsibility and machine efficiency.Join us as we pull back the curtain on AI governance and discuss why the most important question in tech today isn't "What can AI do?" but "Who is responsible when it does it?".#AI #ArtificialIntelligence #TechTrends #AIGovernance #EthicalAI #DigitalTrust #FutureOfWork

Many conversations about AI-driven job losses frame entrepreneurship as “freedom.” But what if you don’t want to start a business? In this episode, I talk honestly about why not everyone is wired to be a solopreneur—and why that matters as AI reshapes work.This episode is for people who have been laid off or displaced and are quietly overwhelmed by the pressure to “figure it out” on their own. There's the idea that they can do that, armed with a bunch of AI tools. Even though it may be theoretically possible, I don't think this is an accurate portrayal of the situation people find themselves in. I share my own accidental path into solopreneurship, the support that made it possible, and why my experience doesn’t generalize to everyone.I don’t offer a neat solution. Instead, I sit with the discomfort of a system that celebrates independence while ignoring uneven risk, caregiving realities, and psychological cost. There has to be more than one path forward. I cover some possibilties in my Substack substack.com/@adelewangQ: What happens when AI layoffs push people into entrepreneurship? What if people don't want to be business owners?A: Not everyone benefits from becoming a solopreneur. While some thrive with autonomy, others experience increased stress, financial insecurity, and emotional overload—especially when they didn’t choose this path.I explore this topic more deeply on Substack, where I write longer essays on work, AI, and meaning. Visit me at substack.com/@adelewang