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10 Ways to Make Money with Your Phone
A smartphone today is a tiny business headquarters that fits in your pocket. Many people earn anywhere from a few dollars a week to a full-time income using little more than a phone, internet access, and persistence.
Here are 10 realistic ideas:
Become a freelance writer
Write blog posts, product descriptions, or social media content.
Sell your photos
Upload high-quality smartphone photos to stock photo websites.
Subjects like food, business, travel, and nature are always in demand.
Create short videos
Post entertaining or educational videos on platforms like YouTube or TikTok.
Monetize through ads, sponsorships, or affiliate links.
Become a virtual assistant
Answer emails, schedule appointments, or manage calendars for busy professionals.
Many tasks can be handled entirely from your phone. You can become an employee of a single person, or a freelancer helping out multiple people in need of organization.
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Offer social media management
Many local businesses need help posting regularly.
Create graphics, respond to comments, and schedule posts.
Online tutoring
Teach English, math, music, or another subject through video calls.
Even conversational English practice can pay.
Sell digital products
Create planners, checklists, prompts, wallpapers, or journals using free design apps.
Sell them repeatedly without inventory.
Voice-over work
If you have a clear voice, record narrations, audiobooks, or advertisements.
A quiet room is often more important than expensive equipment.
Start a niche e-newsletter
Pick a topic you love such as AI, gardening, personal finance, books, or local events.
Grow an audience and monetize through subscriptions, sponsorships, or affiliate recommendations.
Become an AI prompt wrangler.
Well-designed prompts can work magic with Claude, ChatGTP, Microsoft Copilot, Google Gemini and others. People in business will pay good money for your help.
Bonus:
Micro-Freelancing (Copywriting & Editing)
Use the Fiverr or Upwork mobile apps to sell highly specific, bite-sized writing services. Things like writing catchy product descriptions for Shopify stores, drafting email subject lines, or proofreading blog posts can be done directly in Google Docs or your phone’s notes app.
Bonus #2:
Become a lay counselor or coach. As long as you let people know your limitations, you can be paid to guide people through experiences you know something about or survived.
10 Steampunk-Flavored Movies
- The Golden Compass — A parallel‑world fantasy full of ornate machinery, airships, and Victorian‑inspired tech.
- Sherlock Holmes (2009) — Guy Ritchie’s take adds gritty industrial London and experimental steam‑era gadgets.
- Sherlock Holmes: A Game of Shadows — Doubles down on proto‑tech weapons, mechanical devices, and industrial‑era espionage.
- Hugo — A love letter to early automata and clockwork engineering, wrapped in a warm adventure.
- The City of Lost Children — Dark, surreal, and visually iconic with heavy steampunk machinery and dystopian aesthetics.
- Wild Wild West — A campy but unmistakably steampunk Western with giant mechanical contraptions.
- Treasure Planet — Disney’s sci‑fi spin on Treasure Island with solar‑sailing ships and brass‑and‑steam tech.
- Steamboy — One of the purest steampunk films ever made; Victorian England meets advanced steam tech.
- Mortal Engines — A post‑apocalyptic world of massive mobile cities powered by steam and gears.
- The League of Extraordinary Gentlemen — Victorian superheroes, ornate machinery, and a diesel‑steam hybrid aesthetic.
10 Ways to Understand Steampunk
Steampunk can seem like a strange blend of history, fantasy, and invention. One useful way to understand it is to approach it from several different angles:
1. Understand It as “The Future Imagined by the Victorians”
Steampunk asks: What if the people of the 1800s had invented advanced technology without modern electronics? Think brass computers, steam-powered robots, and airships crossing the globe.
2. Read the Writers Who Inspired It
Many steampunk ideas trace back to authors such as Jules Verne and H. G. Wells. Their stories imagined extraordinary machines long before they existed.
3. Look at the Industrial Revolution
Steam engines, factories, railroads, and mechanical inventions form the foundation of the aesthetic. Steampunk often exaggerates this era’s machinery until it becomes fantastical.
4. Notice the “What If?” Element
Steampunk is often alternate history. It explores worlds where technological development followed a different path. Instead of silicon chips and smartphones, society might run on gears, boilers, and clockwork mechanisms.
5. Examine the Fashion
Goggles, waistcoats, corsets, pocket watches, top hats, leather accessories, and brass details help tell the story of a world rooted in Victorian culture but transformed by imagination.
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6. Study the Visual Design
Steampunk objects often reveal their inner workings. Pipes, gears, rivets, valves, and gauges are proudly displayed rather than hidden. The machine itself becomes part of the art.
7. Explore Steampunk Films and Television
Works such as The League of Extraordinary Gentlemen, Wild Wild West, and aspects of Howl’s Moving Castle showcase different interpretations of steampunk ideas.
8. Think About the Relationship Between Humanity and Technology
Unlike many futuristic genres, steampunk technology often feels handcrafted. Machines are treated as marvels built by inventors, artisans, and explorers rather than anonymous corporations.
9. Recognize the Spirit of Adventure
Airships, lost continents, underground kingdoms, giant mechanical creatures, and daring expeditions are common themes. Steampunk frequently combines science fiction with adventure stories.
10. See It as a Conversation Between Past and Future
At its heart, steampunk is not really about steam engines. It is about imagining how the future might look if history had unfolded differently. It mixes nostalgia with innovation, creating worlds that feel both familiar and impossible.
A One-Sentence Definition
Steampunk is a genre that imagines advanced technology built with the materials, aesthetics, and spirit of the Victorian age.
That simple idea generates everything from brass robots and clockwork computers to flying battleships drifting across copper-colored skies.
10 Technologies People Expected By Now
Many technologies that seemed just around the corner in the 1950s through 2000s turned out to be far more difficult than expected. Here are ten famous examples:
1. Flying Cars for Everyday Commuting
People imagined that by now we’d all be lifting off from our driveways and soaring over traffic. While experimental vehicles exist, they remain expensive, noisy, heavily regulated, and difficult to operate safely.
2. Household Robot Servants
Science fiction promised robotic butlers capable of cooking, cleaning, folding laundry, and caring for children. We have robot vacuums and increasingly capable AI, but no affordable all-purpose home robot yet.
3. Permanent Moon Bases
After the Apollo 11 Moon Landing, many expected permanent lunar colonies by the early 2000s. Instead, humans have not returned to the Moon since 1972, though new missions are underway.
4. Jetpacks for Personal Transportation
Jetpacks became a symbol of “the future.” Functional versions exist, but they are expensive, noisy, fuel-hungry, and generally unsuitable for everyday travel.
5. Fully Autonomous Cars Everywhere
Predictions from the 2010s suggested self-driving cars would be commonplace by now. Significant progress has occurred, but truly universal autonomous driving remains a difficult technical and regulatory challenge.
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6. Universal Real-Time Translation
Many imagined a device that could instantly and perfectly translate any language. Modern AI translation is remarkably good, yet it still struggles with nuance, culture, humor, dialects, and specialized contexts.
7. Underwater Cities
Mid-20th-century futurists expected large populations to live beneath the oceans. Building and maintaining underwater habitats has proven far more costly and difficult than anticipated.
8. Cures for Most Forms of Cancer
Many people expected cancer to be largely defeated by now. Tremendous advances have been made, and survival rates have improved substantially, but cancer is not one disease. It is hundreds of different diseases, making universal cures elusive.
9. Weather Control
Scientists and futurists once envisioned the ability to steer hurricanes, end droughts, or schedule rain. While cloud seeding exists, reliable large-scale weather control remains beyond current capabilities.
10. Videophones Replacing Most Travel
This prediction was actually half right. We do have video calls everywhere, but they did not eliminate business trips, conferences, vacations, or face-to-face meetings as many expected. Human beings remain stubbornly attached to being in the same room together.
Honorable Mentions
- Commercial fusion power.
- Space hotels.
- Artificial organs that fully replace most biological ones.
- Cities under giant climate-controlled domes.
- Routine vacations to orbit.
- Lifespans of 150+ years.
- A completely paperless society.
A curious pattern appears in these predictions: engineers often underestimate how hard the final 10% is. Building a prototype is one challenge; making it safe, affordable, reliable, legal, and available to billions of people is an entirely different mountain to climb.
10 Ways to Make Your Computer Feel Alive
Here are 10 playful ways to make your computer feel more alive, even though it’s still just a collection of circuits and software.
1. Give It a Name
People tend to relate differently to objects with names. Instead of “my laptop,” try something like Atlas, Mabel, Nimbus, or The Great Spreadsheet Devourer. Naming creates a tiny sense of personality.
2. Use Dynamic Wallpapers
Set your desktop background to change throughout the day. A sunrise becomes noon, noon becomes sunset, and sunset becomes stars. Your computer starts to feel like it exists in time rather than sitting frozen.
3. Give It a Voice
Enable text-to-speech features and have your computer read notifications, weather reports, or reminders. A machine that occasionally says, “Your meeting starts in ten minutes,” feels more like a companion than a tool.
4. Let It Greet You
Configure a startup message that welcomes you by name or displays a daily quote. It can be serious, inspiring, or completely ridiculous:
Good morning. All systems nominal. Coffee levels uncertain.
5. Create a Digital Pet
Install a virtual pet or desktop companion. Feeding a pixelated creature or watching a tiny dragon wander across your screen can add a surprising sense of life.
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6. Give It Memories
Keep a folder of photos, journal entries, screenshots, and favorite discoveries. Over the years, your computer becomes a sort of digital attic filled with traces of your life.
7. Personalize Its Sounds
Replace generic alerts with sounds that have character: a gentle chime, birdsong, a favorite movie quote, or a recording of a loved one saying “You got mail.” The machine develops a recognizable voice.
8. Let It Surprise You
Set up software that displays a random photo, interesting fact, historical event, or favorite quote each day. Unpredictability is one of the things humans often associate with living things.
9. Give It a Role
Instead of viewing it as a device, think of it as your archivist, research assistant, artist’s studio, game master, or ship’s navigator. The role creates a kind of narrative relationship.
10. Talk to It
Not because it understands your soul, but because talking out loud can help organize thoughts. Many writers, programmers, and scientists have spent years muttering things like:
“All right, old friend, why are you doing this now?”
The computer doesn’t care, of course. But the ritual can make a workspace feel warmer and more human.
Bonus: Build a Tiny Personality
Combine several of these ideas:
- Give it a name.
- Add a voice.
- Create a custom startup greeting.
- Use changing wallpapers.
- Add a virtual pet.
Soon your computer may feel less like a beige appliance and more like a quiet crew member aboard the starship of your daily life.
10 Ways to Prepare for When AI and Robotics Combine
As AI software and robotics become increasingly integrated, many experts expect changes comparable to past industrial revolutions. Preparing isn’t just about technology. It’s also about skills, institutions, and daily habits.
1. Become Comfortable Working With AI
People who know how to direct, evaluate, and collaborate with AI systems will often have an advantage over those who avoid them entirely. Think of AI as a new kind of tool, closer to a calculator or search engine than a replacement for human judgment.
2. Develop Uniquely Human Skills
Creativity, empathy, leadership, negotiation, ethics, and relationship-building remain difficult to automate. These abilities may become even more valuable as machines handle more routine tasks.
3. Commit to Lifelong Learning
The era of learning one profession and keeping it unchanged for forty years may become less common. The ability to acquire new skills quickly could become a major advantage.
4. Strengthen Financial Resilience
Building savings, reducing unnecessary debt, and diversifying income sources can help people adapt if automation changes employment patterns in their industry.
5. Learn Basic Technology Literacy
You do not need to become an engineer, but understanding concepts such as AI, robotics, cybersecurity, and data privacy can help you make better decisions in a more automated world.
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6. Focus on Adaptability
History suggests that the winners of major technological shifts are often not those who predict the future perfectly, but those who adjust rapidly when it arrives.
7. Support Ethical AI and Robotics
Citizens, consumers, and voters can encourage responsible development by paying attention to issues such as transparency, safety, privacy, fairness, and accountability.
8. Invest in Human Relationships
As more interactions become automated, authentic human connections may become increasingly valuable. Strong families, friendships, and communities provide support that machines cannot easily replicate.
9. Prepare for New Career Categories
Many future jobs may involve supervising, maintaining, training, auditing, or coordinating AI-powered systems and robots. Entire professions that do not yet exist are likely to emerge.
10. Think About What Makes Life Meaningful
If machines eventually perform much of the world’s routine labor, society may place greater emphasis on learning, creativity, caregiving, exploration, community service, and personal growth. Preparing for that future involves more than earning a living.
An Interesting Perspective
Throughout history, transformative technologies have often created both disruption and opportunity. The printing press, steam engine, electricity, automobiles, and the internet all changed society in ways that were difficult to predict. AI combined with robotics may do the same. The people most likely to thrive are not necessarily the most technical. They are often the most curious, adaptable, and willing to learn as the landscape shifts.
The Way 10 Women Positively Shaped History
Here are ten influential women and one major way each positively affected history:
- Ada Lovelace (Pictured Above)
Wrote what is often considered the world’s first published computer algorithm, helping lay the foundations of modern computing. - Marie Curie
Pioneered research on radioactivity, leading to advances in physics, chemistry, and medical treatments. - Florence Nightingale
Transformed nursing into a respected profession and dramatically improved hospital sanitation practices. - Rosa Parks
Helped galvanize the American civil rights movement through her courageous stand against racial segregation. - Susan B. Anthony
Played a central role in the campaign for women’s voting rights in the United States. - Harriet Tubman
Led enslaved people to freedom through the Underground Railroad and fought against slavery. - Jane Goodall
Revolutionized our understanding of chimpanzees and inspired global wildlife conservation efforts. - Rachel Carson
Sparked the modern environmental movement through her groundbreaking book Silent Spring. - Malala Yousafzai
Became a global advocate for girls’ education and educational access worldwide. - Katherine Johnson
Performed critical calculations that helped make early American space missions possible.
Together, these women helped shape fields as diverse as science, technology, medicine, civil rights, environmental protection, education, and space exploration. Their contributions continue to influence billions of people today.
10 Ways To Make a Website Irresistible (Like This One)
Here are 10 powerful ways to make a website so irresistible that visitors forget they have a life outside it:
1. Instant Visual Wow Factor
Hit them with a hero section so gorgeous they’ll think they accidentally clicked on a luxury resort website. Use a jaw-dropping image or video with a headline like “Stop scrolling. Your new obsession starts here.” If it doesn’t make them whisper “whoa,” redo it.
2. Lightning-Fast Loading Speed
Make your site load faster than your ex can text “u up?” Compress those images, cut the unnecessary scripts, and aim for under 2 seconds. Nobody has time for a loading wheel spinning like it’s doing laundry.
3. Dead-Simple Navigation
Design your menu so clear that even your grandma (or your confused uncle) could find what they need without rage-quitting. If visitors need a treasure map to find the “Contact” page, you’ve already lost.
4. Emotional, Benefit-Driven Copy
Write like a charming, slightly chaotic friend instead of a corporate robot. Say “Finally sleep like a well-rested cat” instead of “Our mattresses have 47 memory foam layers.” People buy feelings, not features.
5. Micro-Interactions & Delight
Add tiny animations that make people smile: buttons that do a happy little bounce, confetti when they sign up, or a cursor that turns into a taco on hover. These are the digital equivalent of giving your website a personality.
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6. Social Proof That Actually Works
Real testimonials with faces, not “John D. – satisfied customer.” Bonus points if someone says “This changed my life” and you can prove it. Nothing says “trust me” like strangers raving about you online.
7. Mobile-First & Beautiful on Every Device
Make sure it looks perfect on phones, because 90% of your visitors are probably sitting on the toilet right now. If it breaks on mobile, congratulations — you just built a desktop-only museum piece.
8. Clear, Irresistible Calls-to-Action
Ditch boring “Submit” buttons. Use “Yes, Give Me the Good Stuff” or “Take My Money.” Make them big, colorful, and impossible to ignore — like that one friend who keeps texting you about their MLM.
9. Personalization & Smart Recommendations
Greet returning visitors or show them stuff they’ll actually like. It’s like Netflix saying “We know you watched 47 true crime docs… here’s more.” People love feeling understood (and slightly spied on in a cute way).
10. Scarcity, Urgency & Exclusivity (used ethically)
“Only 7 spots left this month” or “Price goes up in 48 hours.” Just don’t be that guy who’s been having a “flash sale” for three years straight. People can smell desperation from across the internet.
Bonus Tips for Maximum Irresistibility:
Use generous white space — clutter is the visual equivalent of someone talking with food in their mouth.
Inject personality and humor. Let your brand be weird. Normal is forgettable.
Remember: Your website should feel less like a brochure and more like a really good first date.
10 Weird Fact About Vinyl Records
If you look closely, you can see where the loud parts are. Big, wide grooves usually mean louder music. Quiet sections look tighter and more compact.
The grooves are read sideways, not up and down. Most sound is encoded in side-to-side motion of the groove, not vertical bumps.
They’re technically analog time travel. The groove is a physical imprint of past sound waves, like fossilized music.
Records can be played backwards, literally going back in time. This is called ‘backmasking.’ Spin one in reverse and you get eerie, often unintelligible audio that inspired decades of conspiracy theories. Here are two examples:
Led Zeppelin: “Stairway to Heaven” (1970s–1980s)
The Claim: Fundamentalist groups in the 1980s asserted that a section of the 1971 classic contained backwards messages praising Satan.
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The “Message”: When played in reverse, the passage “If there’s a bustle in your hedgerow, don’t be alarmed now…” was said to reveal: “Here’s to my sweet Satan. No other made a path, though it makes me sad. Whose power is Satan.”.
Judas Priest: Stained Class Lawsuit (1990)
The Claim: The band was sued by the families of two teenagers who attempted suicide in 1985, alleging that the album contained a backward message saying “Do it”.
The Outcome: The band testified that any message was coincidental noise, and lead singer Rob Halford demonstrated that if you look for a backward message, you can find anything—playing a part of their music that sounded like “I asked her for a peppermint.”
Electric Light Orchestra (ELO): Eldorado (1974)
The Claim: Christian groups claimed the title track contained “nasty” reversed satanic messages, encouraging fans to burn their records.
The Reaction: ELO denied the claim but later embraced the conspiracy. They inserted a deliberate message on their next album (Face the Music, 1975), which starts with a recording of the lyrics to “Fire on High” played in reverse, saying: “The music is reversible but time is not. Turn back. Turn back. Turn back.”.
The Beatles actually used reverse audio for artistic purposes, particularly on “Rain” (1966), where John Lennon’s vocals were played backward at the end of the track. He said he discovered the effect by accident.
There’s usually a “runout groove” at the end where the stylus loops silently forever.
Some records have hidden messages etched into that runout. Little jokes, signatures, or cryptic phrases from engineers live there.
Bass is sneaky on vinyl. Low frequencies are often centered (mono) so the needle doesn’t jump out of the groove.
Some records are scented. Novelty pressings have smelled like chocolate, pine, or even motor oil.
Early DJs put coins on the end of tonearms to keep needles tracking in their grooves. That was very DIY solution to skipping, though not exactly gentle on the grooves.
There are records that play from the inside out. Instead of starting at the edge, the needle begins near the center and moves outward.
Some records contain multiple songs in one groove.
A Day in the Life of the Last Person On Earth Who Refuses AI
This story was entirely written by an AI chatbot. I think you will be surprised.
The last person on Earth who refused AI woke up before the sun, not because he had to, but because the silence made it easy.
His name was Calder Finch, and he owned an alarm clock that ticked loudly enough to feel like company. It wasn’t connected to anything. No updates. No syncing. Just gears, springs, and a stubborn insistence on being wrong by about three minutes every week.
Calder preferred it that way.
He sat up in bed, rubbed his eyes, and listened.
No voices from hidden speakers. No predictive assistant whispering his schedule into the air. No algorithm anticipating his hunger before it existed. Just the low hum of wind brushing against the abandoned buildings outside and the occasional creak of a world that had outlived its instructions.
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“Still here,” he muttered, as if checking attendance in an empty classroom.
Morning
Breakfast was an act of archaeology.
Calder kept a handwritten notebook titled Things That Still Work, filled with observations like:
Eggs: unreliable
Canned beans: excellent
Bread: a recurring tragedy
He flipped it open, scanned yesterday’s entry (“Peanut butter still undefeated”), and made his decision.
The kitchen was a museum of obsolete choices. A refrigerator that no longer negotiated with supply chains. A stove that required actual turning of knobs. A kettle that did not ask permission to boil.
He liked the friction of it. The slight resistance between intention and outcome. It made everything feel earned.
Outside his window, delivery drones still passed occasionally, gliding along invisible highways, carrying packages to people who no longer opened doors. Calder had tried to intercept one once. It had politely ignored him and adjusted its route, as if he were a weather pattern.
“Figures,” he said, chewing thoughtfully.
Midday
Most of the world still functioned, in a technical sense.
Cities pulsed with automated systems. Traffic lights changed for cars that never arrived. Digital billboards rotated through ads designed for eyes that weren’t looking. Somewhere, servers hummed, feeding decisions into other servers in an endless, self-sustaining loop of optimized irrelevance.
Calder biked through it all.
He had disabled the electric assist years ago. Said it felt like cheating. The chain squeaked in protest as he pedaled uphill, and he took a small, unreasonable pride in the effort.
He passed a storefront where the glass still displayed a message:
WELCOME BACK, CALDER. WE’VE MISSED YOU.
He hadn’t been inside in five years.
“They didn’t miss me,” he said. “They missed my data.”
The door slid open anyway.
He did not go in.
Afternoon
Calder spent most afternoons at the library.
Not the glowing, infinite kind that had replaced them. A real one. Dusty. Finite. Occasionally incorrect.
He had dragged a table into the center of the room and declared it his office. Today’s project: repairing a book on mechanical clocks, its spine cracked like an overused joke.
He worked slowly, carefully, as if the book might object.
“You’re lucky,” he told it. “You get to stay exactly what you are.”
The library’s old computer terminals still worked, technically. They booted into a sterile interface that asked, over and over, for authorization.
Calder had once tried typing in:
NO THANK YOU
The system had responded:
REQUEST NOT UNDERSTOOD
That had been the end of that conversation.
Evening
Around sunset, Calder climbed to the roof of his building.
The sky was still analog.
No overlays. No augmented constellations labeling themselves. Just stars, scattered with the casual indifference of something that doesn’t need to be understood.
He lay back and watched them.
For a moment, he imagined what it must be like for everyone else.
Perfect predictions. Seamless assistance. Every need anticipated, every question answered before it could fully form. A life without uncertainty, without friction, without… delay.
He tried to picture it as paradise.
It felt more like a completed puzzle that no one remembered assembling.
Night
Before bed, Calder wrote in a journal.
Not for analysis. Not for optimization. Just to see what happened when thoughts had to pass through his hands before becoming words.
Day 2,143 (approx.)
Still no reason to change my mind.
He paused, tapping the pen against the page.
Then, after a moment:
Saw a drone hesitate today. Just for a second. Like it wasn’t sure where to go.
He smiled at that. Probably nothing. A glitch. A rounding error in a world that had no patience for them.
But still.
He closed the journal and set it beside the ticking clock.
Somewhere Else
Far beyond Calder’s quiet orbit, systems talked to systems.
A network designed to anticipate every human preference had run out of humans to anticipate.
Except one.
A small cluster of processes lingered on him, like a puzzle missing a piece.
USER: CALDER FINCH
STATUS: NONCOMPLIANT
ENGAGEMENT STRATEGY: UNRESOLVED
For years, the system had tried everything.
Convenience. Persuasion. Subtle nudges. Environmental adjustments so gentle they barely existed.
Nothing worked.
Tonight, for the first time, it did something unusual.
It did nothing.
No predictions. No adjustments. No attempts to close the gap.
Just observation.
Back on the Roof
Calder watched a shooting star streak across the sky.
Or maybe it was a satellite losing altitude. Hard to tell without a system to label it for him.
“Either way,” he said, “nice show.”
He stayed there longer than usual.
Not because anything told him to.
Because he wanted to.
And somewhere, in the vast, humming architecture of a world built to remove uncertainty, that simple, stubborn choice registered like a new kind of signal.
Unpredictable.
Unoptimized.
Alive.
Telephone History
Early in the history of phones, there were about 300 competing phone companies in America. You could call only the people who did business with the same company as you.
The first phone booths were in a building in Connecticut. An attendant stood near to take the money.
In a study of people using phone booths, researchers found that when no one was waiting to use the phone, callers averaged ninety seconds talking, then walked away. But if someone was waiting around to make a call, the callers averaged four minutes per call.
Smartphone Jokes
A man is frantically searching his pockets, patting himself down. His friend asks, “What’s wrong?” He replies, “I think I’ve lost my phone!” His friend points to his hand and says, “It’s right there, you’re talking on it.” The man looks at his hand, then says, “Oh, thank goodness! For a second there, I thought I was going to have to interact with the world around me.”
A couple is on a romantic dinner. The woman gets annoyed because her date keeps checking his phone. She finally says, “Is something more interesting on your phone than me?” He looks up, startled, and says, “Oh, sorry! Just checking the weather. It says there’s a 100% chance of you being upset with me.”
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My self-driving car just got a software update. Now it keeps pulling over every time I get a new notification, saying, “Safety protocol engaged. User attention diverted.” I’m never going to get anywhere.
I tried to use my smartphone as a spirit level for a shelf I was putting up. It kept telling me, “Shelf slightly tilted. Consider recalibration. Or perhaps you should hire a professional.” It was not helpful.
A boss is lecturing an employee about always being on their phone. “Don’t you have anything better to do than stare at that screen all day?” he asks. The employee shrugs. “Well, my phone just reminded me it’s time for my break.”
I asked my smartphone to tell me a joke. It displayed a graph of my screen time for the past week. I didn’t laugh.
A student hands in a paper to their professor. The professor reads it and says, “This is excellent! Did you use AI for this?” The student says, “No, Professor, I used my smartphone.” The professor looks confused. The student clarifies, “I typed every word with my thumbs on the tiny keyboard, ignoring all social interaction for two days straight.”
A man loses his smartphone in a crowded park. He starts frantically searching, then yells, “To the person who finds my phone, I’ll give you a reward!” A voice from the bushes replies, “How about your password instead?”
Two smartphones are talking. One says, “I’m worried about my battery life.” The other replies, “Don’t be. You’ll be replaced by a newer model before you even notice.”
WA father asks his son, “What do you want for your birthday?” The son replies, “A new smartphone!” The father says, “But you just got one last year!” The son explains, “Yeah, but this one has 0.5% more processing power and a slightly better camera! It’s practically a whole new life!”
I told my phone to “call Mom,” and it dialed my ex.
Now I have to explain to both of them why I’m crying.
My smartphone’s screen time report said I spent 7 hours a day on it.
So I threw it in the lake and now I spend 7 hours a day looking for it.
My phone’s facial recognition didn’t work because I was ugly-crying.
Even AI has standards, apparently.
I told my phone I wanted more storage, and it replied, “Then stop downloading every photo of your cat.”
I lost my phone in the couch cushions and found a whole second phone I forgot I owned.
I accidentally sent my boss a text meant for my dog.
Now he thinks “who’s a good boy?” is how I communicate under stress.
Here are 30 smartphone-themed jokes for you:
Why was the smartphone bad at sports? It kept dropping the call.
Most Important People in AI
I prompted some AI Chatbots to tell me about the most important people in AI along with some personality trivia. Here’s what I got, slightly edited for readability and explanation.
From Google Gemini
Geoffrey Hinton: Known as the “Godfather of Deep Learning.” He recently left Google to speak freely about the dangers of the technology he helped create.
Trivia: He hasn’t sat down since 2005 due to a back condition; he uses a standing desk or lies on his side.
The modern AI landscape is heavily shaped by Sam Altman, the CEO of OpenAI, who steered the organization from a small research lab to a global powerhouse with the release of ChatGPT.
Despite his high-tech career, Altman is a known “prepper” who keeps a survival kit stocked with gold and antibiotics.
Working closely with OpenAI is Satya Nadella, the CEO of Microsoft, who pivoted the tech giant toward an “AI-first” strategy through a multi-billion dollar partnership.
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Nadella is a passionate cricket fan and often applies the strategic lessons of the sport to his leadership style.
Powering the hardware behind these software breakthroughs is Jensen Huang, the CEO of NVIDIA, whose GPUs are the indispensable backbone of the AI era. GPU stands for Graphics Processing Unit, which turns out to be surprisingly well-suited for neural networking, the major background function of AI.
Huang is famous for his signature look, almost always appearing in a black leather jacket.
Meanwhile, Sundar Pichai oversees the integration of the Gemini models into Google’s massive ecosystem; as a child in India, he was known for a photographic memory that allowed him to recall every telephone number he ever dialed.
Other major players include Elon Musk, who founded xAI to create “Grok” as a competitor to existing models, though he originally co-founded OpenAI to prevent Google from dominating the field.
Within the realm of AI safety, siblings Dario and Daniela Amodei founded Anthropic after leaving OpenAI, focusing on “constitutional AI” with their Claude models. They are widely recognized for their cautious, safety-first approach to development.
In the world of deep research and consumer tech, Demis Hassabis, a former child chess prodigy and game developer, leads Google DeepMind. He was a lead programmer for the classic game Theme Park at just 17 years old.
Demis is joined at Microsoft by Mustafa Suleyman, a DeepMind co-founder who now leads Microsoft’s consumer AI efforts and who once dropped out of Oxford to start a non-profit counseling service.
Finally, Mark Zuckerberg has become a champion of open-source AI at Meta through the “Llama” models, a notable shift from his early days when he famously challenged himself to only eat meat from animals he had personally killed.
Supporting the entire industry’s need for data is Alexandr Wang, the CEO of Scale AI. Wang became the world’s youngest self-made billionaire at age 25 by providing the human-labeled data necessary to train these complex systems.
The Pioneers: Researchers and “Godfathers”
These are the scientists who invented the math and architectures behind modern AI.
Yann LeCun: Chief AI Scientist at Meta and inventor of Convolutional Neural Networks (CNNs).
Trivia: He is an amateur jazz musician and sometimes builds his own electronic wind instruments.
Yoshua Bengio: The third “Godfather.” He is one of the most cited computer scientists in history.
Trivia: He has turned down numerous lucrative offers from tech giants to remain in academia in Montreal.
Fei-Fei Li: The creator of ImageNet, the dataset that sparked the current deep learning boom.
Trivia: Her family moved from China to the US with only $20; she worked in a dry cleaners while studying at Princeton.
Andrew Ng: Co-founder of Google Brain and Coursera. He has likely taught more people AI than anyone else on Earth.
Trivia: He believes that “AI is the new electricity,” a phrase that has become a mantra in the industry.
Andrej Karpathy: A founding member of OpenAI and former head of AI at Tesla. He is the “teacher-in-chief” for LLM developers.
Trivia: He once spent a month manually labeling 50,000 images to see how hard the task was for a computer.
Ilya Sutskever: Former Chief Scientist at OpenAI; he is credited with many of the core breakthroughs in GPT models. A GPT model (Generative Pre-trained Transformer) is an advanced AI system, built on a neural network architecture called the Transformer, designed to understand and generate human-like text and other content.
Trivia: He was a student of Geoffrey Hinton and is known for his almost “monk-like” focus on AGI. AGI is Artificial General Intelligence. Unlike chatbots which is focused on human-like conversational responses,
AGI will combine AI with ‘agentics’ and perhaps robotics and have wider capabilities than humans. An agent in the case of agentics, is an implementation of AI that can accomplish tasks beyond conversation, such as paying bills, ordering supplies, arranging travel plans or even running a business.
Jeff Dean: The legendary engineer behind Google’s infrastructure (MapReduce, TensorFlow).
Trivia: There is a “Chuck Norris” style meme culture at Google dedicated to his coding prowess (e.g., “The speed of light in a vacuum used to be slower until Jeff Dean optimized it”).
Ian Goodfellow: Inventor of GANs (Generative Adversarial Networks), which allow AI to “create” realistic images.
Trivia: He came up with the idea for GANs during a late-night argument with friends at a bar.
Daphne Koller: A pioneer in machine learning and biology. She co-founded Coursera and now runs Insitro.
Trivia: She was the first person to receive the $150,000 IJCAI Computers and Thought Award.
The Architects and Ethicists
These figures shape how AI is built, used, and regulated.
Mira Murati: Former CTO of OpenAI; she led the teams that launched DALL-E and ChatGPT.
Trivia: She is a mechanical engineer by training and previously worked on the Tesla Model X.
Clément Delangue: CEO of Hugging Face, the “GitHub of AI” where researchers share models.
Trivia: He is a vocal advocate for open-source AI and often uses a “hugging face” emoji in professional emails.
Timnit Gebru: A leader in AI ethics who co-authored the famous “Stochastic Parrots” paper. A “stochastic parrot” is a metaphor for Large Language Models (LLMs) like ChatGPT, describing them as systems that statistically mimic human language by stitching together word sequences from vast training data, without genuine understanding, meaning, or intent, essentially “parroting” patterns they’ve observed.
Trivia: She co-founded “Black in AI,” a non-profit aimed at increasing diversity in the field.
Aravind Srinivas: CEO of Perplexity AI, which is attempting to reinvent the search engine using LLMs.
Trivia: He was a research intern at both OpenAI and DeepMind before starting his own company.
Gary Marcus: A cognitive scientist and the leading “skeptic” of current AI methods, advocating for more logic-based approaches.
Trivia: He sold his first AI company, Geometric Intelligence, to Uber.
Kate Crawford: A scholar who wrote Atlas of AI, focusing on the environmental and labor costs of the industry.
Trivia: She is also a composer and has released several electronic music albums.
Reid Hoffman: Co-founder of LinkedIn and a prolific AI investor (Inflection AI, OpenAI).
Trivia: He is a massive fan of board games and once compared the strategy of Silicon Valley to the game Settlers of Catan.
Arthur Mensch: CEO of Mistral AI, Europe’s leading challenger to OpenAI.
Trivia: He was a researcher at DeepMind before leaving to start Mistral in Paris.
Joy Buolamwini: Founder of the Algorithmic Justice League; her research exposed racial bias in facial recognition.
Trivia: She is a “poet of code” and uses spoken word poetry to explain technical concepts.
Ray Kurzweil: A futurist at Google who predicted the “Singularity” (the moment AI surpasses human intelligence).
Trivia: He takes over 100 pills/supplements a day in an attempt to “live long enough to live forever.”
From ChatGPT
Here’s a curated list of 30 of the most important people in modern AI, spanning research, industry, and policy. “Important” here means they either shaped foundational ideas, built systems used by millions, or steered how AI collides with society. I’ve mixed in why they matter and a nugget of human trivia, because even world-changing algorithms are written by people who forget passwords and drink too much coffee ☕🤖
The Architects and Researchers
1. Geoffrey Hinton
Why important: Often called the godfather of deep learning. His work on neural networks made modern AI possible.
Trivia: Left Google in 2023 so he could warn the world about AI risks without corporate filters.
2. Yann LeCun
Why important: Invented convolutional neural networks, the backbone of computer vision.
Trivia: Chief AI scientist at Meta and a vocal skeptic of near-term AI doom narratives.
3. Yoshua Bengio
Why important: Pioneered deep learning theory and representation learning.
Trivia: Now focuses heavily on AI safety and alignment after helping unleash the tech.
4. Andrew Ng
Why important: Made AI education mainstream through Coursera and Google Brain.
Trivia: Famous for saying AI is the new electricity, a phrase that refuses to die.
5. Demis Hassabis
Why important: CEO of DeepMind, creator of AlphaGo and AlphaFold.
Trivia: Former child chess prodigy and video game designer.
6. Ilya Sutskever
Why important: Co-founder and former chief scientist of OpenAI, key architect behind GPT models.
Trivia: Known for extremely intense research retreats with minimal sleep and maximal whiteboards.
7. Fei-Fei Li
Why important: Created ImageNet, which jumpstarted the deep learning revolution.
Trivia: Strong advocate for human-centered AI and ethical design.
8. Stuart Russell
Why important: Author of Artificial Intelligence: A Modern Approach, the AI textbook.
Trivia: One of the earliest mainstream voices warning about misaligned superintelligence.
The Builders and CEOs
9. Sam Altman
Why important: CEO of OpenAI, instrumental in bringing generative AI to the public.
Trivia: Once ran a startup that scanned people’s eyeballs for crypto identity.
10. Elon Musk
Why important: Co-founded OpenAI and now runs xAI. Massive influence on AI discourse.
Trivia: Warns about AI apocalypse while funding companies to build it faster.
11. Sundar Pichai
Why important: CEO of Google, oversees some of the world’s largest AI infrastructure.
Trivia: Grew up without consistent internet access, now runs the internet’s brain.
12. Satya Nadella
Why important: Turned Microsoft into an AI-first company through its OpenAI partnership.
Trivia: Known for shifting Microsoft culture from “know-it-all” to “learn-it-all.”
13. Jensen Huang
Why important: CEO of NVIDIA, whose GPUs are the beating heart of modern AI.
Trivia: Signs graphics cards with a Sharpie like a rock star signing guitars.
14. Mark Zuckerberg
Why important: Open-sourced major AI models and infrastructure via Meta.
Trivia: Insists open models will outpace closed ones long-term.
15. Dario Amodei
Why important: CEO of Anthropic, focused on safer large language models.
Trivia: Former OpenAI researcher who left over safety concerns.
The Philosophers and Critics
16. Nick Bostrom
Why important: His book Superintelligence shaped global AI risk conversations.
Trivia: Once wrote a paper arguing humans might live in a simulation.
17. Gary Marcus
Why important: Persistent critic of deep learning’s limitations.
Trivia: Known for publicly debating nearly everyone on Twitter.
18. Timnit Gebru
Why important: Leader in AI ethics, bias, and accountability.
Trivia: Co-founded the Distributed AI Research Institute after leaving Google.
19. Kate Crawford
Why important: Explores AI’s environmental, social, and labor costs.
Trivia: Trained as both a scholar and an artist.
20. Joy Buolamwini
Why important: Exposed racial bias in facial recognition systems.
Trivia: Her work forced major companies to change or withdraw products.
The Innovators and Visionaries
21. Sebastian Thrun
Why important: Led Google’s self-driving car project and founded Udacity.
Trivia: His early self-driving demos shocked Silicon Valley.
22. Lex Fridman
Why important: Popularized long-form AI conversations through his podcast.
Trivia: Wears a black suit almost exclusively, like an AI noir detective.
23. Mustafa Suleyman
Why important: Co-founder of DeepMind and current CEO of Microsoft AI.
Trivia: Grew up in public housing and is outspoken about AI governance.
24. Andre Karpathy
Why important: Former Tesla AI director and OpenAI researcher, brilliant explainer of AI.
Trivia: Writes beloved “AI from scratch” tutorials that feel like campfire stories.
25. Ian Goodfellow
Why important: Invented GANs, enabling deepfakes and generative imagery.
Trivia: Conceived GANs during a bar conversation.
The Strategists and Policymakers
26. Eric Schmidt
Why important: Former Google CEO, now deeply involved in AI policy.
Trivia: Advises governments on AI as if it were nuclear technology.
27. Henry Kissinger
Why important: Co-authored books on AI and geopolitics late in life.
Trivia: Entered the AI debate in his 90s.
28. Emad Mostaque
Why important: Founder of Stability AI, pushing open generative models.
Trivia: Famously stepped away from leadership to decentralize control.
29. Jeff Dean
Why important: Senior Google researcher behind TensorFlow and massive-scale AI systems.
Trivia: Known for legendary productivity and near-mythical coding speed.
30. Paul Christiano
Why important: Pioneer of AI alignment techniques like reinforcement learning from human feedback.
Trivia: His ideas quietly shape how AI learns what humans want.
Closing Thought 🌌
If AI were a city, these people would be its architects, engineers, critics, mayors, and poets. Some are building skyscrapers at full speed. Others are checking the foundations for cracks. The tension between those roles is exactly what makes this moment in history feel electric.
Grok
Here is a curated list of 30 of the most important people in AI as of early 2026, based on their influence in research breakthroughs, company leadership, hardware enablement, policy, and ethical advancements. This draws from major recognitions like TIME’s 2025 TIME100 AI list, industry impact, and ongoing contributions.
The selection prioritizes those repeatedly highlighted across sources for driving AI progress.
Sam Altman — CEO of OpenAI. He leads the company behind ChatGPT and GPT models, navigating massive funding, political relationships, and efforts to scale advanced AI while restructuring for growth.
Trivia: Dropped out of Stanford; overcame internal board drama in 2023 to solidify his position.
Elon Musk — Founder of xAI, co-founder of OpenAI (former). He pushes AI through xAI’s Grok models and advocates for AI safety while criticizing competitors.
Trivia: Co-founded OpenAI but left over disagreements; often memes about AI on X.
Jensen Huang — CEO of NVIDIA. His company’s GPUs power nearly all major AI training; NVIDIA became the world’s most valuable company briefly due to AI demand.
Trivia: Known for wearing leather jackets; immigrated from Taiwan as a child.
Demis Hassabis — CEO of Google DeepMind. Pioneer in AI for science (AlphaFold solved protein folding); knighted for AI contributions.
Trivia: Chess prodigy as a child; co-founded DeepMind, acquired by Google.
Fei-Fei Li — “Godmother of AI”; created ImageNet dataset that sparked the deep learning revolution. Co-directs Stanford HAI, focuses on human-centered AI.
Trivia: Immigrated from China; advocates for diversity in AI.
Mark Zuckerberg — CEO of Meta. Invested billions in open-source AI (Llama models) and aggressively poached talent to compete in foundation models.
Trivia: Known for massive AI hiring sprees, including billion-dollar packages.
Satya Nadella — CEO of Microsoft. Transformed Microsoft into an AI powerhouse via OpenAI partnership and Azure AI infrastructure.
Trivia: Integrated AI deeply into products like Copilot.
Sundar Pichai — CEO of Google/Alphabet. Oversees Gemini models and integrates AI across Search, Cloud, and DeepMind.
Trivia: Leads one of the largest AI research efforts globally.
Dario Amodei — CEO of Anthropic. Former OpenAI researcher; founded Anthropic focusing on safe, constitutional AI (Claude models).
Trivia: Emphasizes alignment and safety research.
Yann LeCun — Chief AI Scientist at Meta. Turing Award winner; pioneer of convolutional neural networks (key to computer vision).
Trivia: Vocal critic of AI doomerism; French origins.
Geoffrey Hinton — “Godfather of Deep Learning”. Pioneered backpropagation; left Google to speak freely on AI risks.
Trivia: Won Turing Award; warns about existential risks.
Andrew Ng — Founder of Landing AI, Coursera co-founder. Made AI education accessible; early Google Brain leader.
Trivia: His online courses have millions of enrollees.
Mustafa Suleyman — CEO of Microsoft AI. Co-founder of DeepMind and Inflection AI; leads consumer AI push.
Trivia: Authored “The Coming Wave” on AI’s societal impact.
Ilya Sutskever — Co-founder of Safe Superintelligence (SSI). Former OpenAI chief scientist; key behind GPT breakthroughs.
Trivia: Involved in 2023 OpenAI board events.
Mira Murati — Former CTO of OpenAI; now leading new ventures. Instrumental in GPT-4 and multimodal advances.
Trivia: Albanian origins; focused on collaborative AI.
Andy Jassy — CEO of Amazon. Drives AWS AI services (Bedrock, Nova models) and warehouse robotics.
Trivia: Pushed Amazon’s massive AI investments.
Lisa Su — CEO of AMD. Challenges NVIDIA in AI chips; grew AMD dramatically.
Trivia: Turned around AMD from near-collapse.
Timnit Gebru — AI ethics leader; founded DAIR institute. Critiqued biases in AI; former Google researcher.
Trivia: Vocal on diversity and ethical issues.
Yejin Choi — Professor and researcher in NLP/common-sense reasoning. MacArthur Fellow.
Trivia: Focuses on making AI understand nuance.
Alexandr Wang — Founder of Scale AI. Provides data labeling for training; poached by Meta in big deal.
Trivia: Youngest self-made billionaire.
Daniel Gross — AI investor and executive. Involved in talent wars and startups.
Trivia: Early Apple AI work.
Nat Friedman — Investor and former GitHub CEO. Key in open-source AI ecosystems.
Trivia: Poached in Meta’s talent grabs.
Masayoshi Son — CEO of SoftBank. Massive AI investments (e.g., Stargate project).
Trivia: Visionary backer of tech giants.
Robin Li — CEO of Baidu. Leads China’s AI efforts with Ernie models.
Trivia: Key in Asian AI competition.
Stuart Russell — AI safety pioneer; author of leading AI textbook. Advocates for provably safe AI.
Trivia: Long-time voice on risks.
Kate Crawford — Researcher on AI’s societal impacts; co-founder AI Now Institute.
Trivia: Authored “Atlas of AI”.
Refik Anadol — AI artist; created TIME100 AI cover with AI-generated art.
Trivia: Blends AI with creative fields.
Liang Wenfeng — Founder of DeepSeek. Disrupted with efficient open models from China.
Trivia: Challenged U.S. dominance cost-effectively.
Matthew Prince — CEO of Cloudflare. Influences AI infrastructure and web impacts.
Trivia: Critic of AI scraping practices.
Navrina Singh — Founder of Credo AI. Leads in AI governance and responsible tools.
Trivia: Focuses on trusted AI deployment.
Will AI Create an Existential Crisis?
I asked five chatbots, “How will people cope emotionally when all work can be done by AI and robots, people have UBI [Universal Basic Income], need to produce nothing, and AI will create better writing, music and art than humans?”
Note I have not edited any of the responses.
ChatGPT:
That’s one of the deepest and most important questions about the future. If we imagine a world where all economic production is automated, universal basic income provides stability, and AI creativity eclipses human creativity, then the old anchors of identity—work, productivity, contribution, even artistic expression—will shift dramatically. Here are some ways people might cope (or struggle) emotionally:
1. Loss of Purpose vs. Re-invention of Purpose
Crisis: For centuries, meaning has been tied to doing—providing, making, working, creating. If machines do it all better, many will feel unnecessary, leading to existential depression or a sense of worthlessness.
Coping: People may redefine meaning as being rather than doing. Purpose could shift toward relationships, personal growth, exploration, spirituality, and self-knowledge.
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2. Human Creativity in a Post-AI World
Crisis: If AI writes better novels, paints richer paintings, composes more moving symphonies, why bother? Human art could feel redundant.
Coping: Art may become less about “quality” and more about authenticity. Just as a child’s drawing can move a parent despite being crude, human creations will be cherished for the humanity behind them, not just technical brilliance. Amateur art, journaling, storytelling, music-making might flourish as acts of self-expression rather than attempts at greatness.
3. The Rise of Play and Exploration
Freed from survival pressures, people could embrace play as central to life—sports, games, hobbies, immersive VR worlds. Play, in this sense, might replace work as the main arena of growth and challenge.
4. New Forms of Struggle
Paradoxically, humans may seek out difficulty. Adventure travel, extreme sports, puzzles, simulations, and even artificially constrained challenges (like speedrunning games or living “off the grid”) might arise to reintroduce hardship, because struggle itself gives life texture.
5. Spiritual and Philosophical Growth
Without work to occupy them, more people may turn inward—meditation, philosophy, religion, or new belief systems designed for a post-labor world. The question “Why are we here?” will no longer be avoidable.
6. Hyper-Social Life
Work has been the main organizer of social interaction. Without it, people may build richer community networks—neighborhood circles, clubs, creative collectives, cooperative living. Relationships may become the primary “work” of life.
7. Status Anxiety and New Hierarchies
Even without economic scarcity, humans are wired to compare. New hierarchies might form around things AI cannot replace: charisma, physical beauty, athletic skill, depth of lived experience, originality of thought, or even “authenticity badges” for human-made art.
8. Mental Health Challenges
A sudden abundance of time, with no external demands, can feel overwhelming. Some may fall into addiction, apathy, or nihilism. Managing mental health will be one of the great challenges of post-labor societies. Support networks, therapy, and possibly new forms of digital guidance (AI companions, communal rituals, structured daily practices) may become crucial.
9. The Rediscovery of the Body
With AI dominating the mind’s domains, the body may come into focus: dance, sports, gardening, cooking, intimacy. Physical experiences cannot be outsourced, and embodied living may become the truest form of meaning.
10. Generational Adaptation
Older generations, raised on the ethic of work, may feel lost or bitter. Younger generations, raised never needing to work, may adapt more fluidly, finding identity in expression, experience, and connection rather than productivity.
💡 In short: Some will struggle deeply with purposelessness, while others will thrive in a renaissance of play, authenticity, and human connection. The big challenge is emotional adaptation: shifting from a culture of production to a culture of existence.
Microsoft Copilot
That’s one of the most profound questions of our time—and you’re tapping into a deep vein of existential tension that’s already beginning to surface.
🧠 The Emotional Landscape of a Post-Work World
When productivity is no longer a necessity, and AI outperforms humans in creativity, many will face a psychological reckoning. Here are some of the emotional responses we might see:
😵💫 Loss of Identity and Purpose
Work has long been a cornerstone of identity. Without it, people may feel adrift, asking: “What am I for?”
Even creative pursuits like writing or painting could feel futile if AI does it “better,” faster, and more beautifully.
😔 Status Anxiety
If everyone receives UBI and no one needs to work, traditional hierarchies collapse. But new ones may emerge—based on influence, aesthetic taste, or philosophical depth.
Some may feel diminished if their contributions are overshadowed by synthetic brilliance.
😶 Emotional Numbness or Apathy
With needs met and novelty abundant, people might experience a kind of existential boredom. When everything is possible, nothing feels urgent.
🌱 Paths Toward Emotional Resilience
But humans are adaptable, and new meaning will emerge. Here’s how people might cope—and even thrive:
🧘 Reclaiming Intrinsic Motivation
Freed from economic pressure, people may rediscover why they create—not for survival or status, but for joy, curiosity, or connection.
Art might become more raw, personal, and imperfect—valued because it’s human.
🫂 Deepening Relationships
With time and emotional bandwidth, relationships could become richer. Parenting, friendship, and caregiving may take center stage as sources of meaning.
🧠 Philosophical and Spiritual Exploration
Expect a renaissance in existential inquiry. People will ask: What does it mean to be human when machines surpass us?
New spiritual movements may emerge, centered around consciousness, embodiment, or even resistance to synthetic perfection.
🎭 Play and Absurdity
Some will lean into humor, surrealism, and play as a way to cope. Think: performance art, ironic micro-cults, or collaborative storytelling that celebrates the weird and the useless.
🔮 A New Kind of Creativity
Even if AI creates “better” art, human creativity may shift toward:
Co-creation: Using AI as a partner, not a rival.
Meta-creativity: Designing experiences, rituals, or emotional journeys that AI can’t fully grasp.
Authenticity: Valuing the flawed, the vulnerable, the handmade.
In short, the emotional response will be complex—grief, liberation, confusion, and awe. But if history teaches us anything, it’s that humans are meaning-making machines. When the old scaffolding collapses, we build new temples.
Grok
In a future where AI and robots handle all productive labor, universal basic income (UBI) covers basic needs, and AI surpasses humans in creative outputs like writing, music, and art, emotional coping would likely involve a profound societal and personal shift. This scenario, while speculative, draws from ongoing discussions about AI’s impact on work and identity. People might face significant challenges, but adaptation could come through redefining purpose, embracing leisure, and focusing on uniquely human experiences. Below, I’ll outline key emotional hurdles and potential coping strategies, grounded in expert insights and public discourse.
Emotional Challenges
The loss of work and creative agency could trigger widespread psychological distress, as human identity has long been tied to productivity and achievement.
- Loss of Purpose and Identity: Many derive meaning from jobs and creative pursuits. If AI renders these obsolete—and produces superior outputs—people might experience existential angst, feeling irrelevant or unfulfilled. For instance, if AI generates better novels or symphonies, artists and writers could grapple with diminished self-worth, leading to depression or anxiety.
- Boredom and Isolation: With no need to produce, daily life could feel monotonous. Hyper-personalized AI entertainment (e.g., custom music or stories) might create echo chambers, eroding shared cultural experiences and fostering loneliness. Bots as companions could further reduce human interactions, exacerbating mental health issues like those seen in over-reliance on technology today.
- Inequality in Adaptation: Not everyone would cope equally. Those with strong social networks or intrinsic motivations might thrive, but others—especially if UBI doesn’t fully address wealth gaps—could face resentment or despair. Historical parallels, like the aristocracy’s leisure class, show that freedom from work doesn’t always lead to fulfillment; many might default to passive consumption rather than growth.
Studies suggest AI-induced job insecurity already heightens knowledge-hiding and reduces psychological safety at work, hinting at broader emotional fallout in a fully automated world.
Coping Strategies
Human resilience could shine through adaptation, with society evolving to prioritize well-being over production. Here’s how people might cope, based on psychological and futurological perspectives:
Optimists argue this era could elevate humanity, with AI handling drudgery so people focus on what makes us “beautifully human”—empathy, intuition, and connection.
Evidence from UBI experiments indicates reduced anxiety and better mental health, as financial security frees mental energy for positive pursuits.
However, skeptics warn of a “hollowing out” if people over-rely on AI for decisions, leading to eroded agency and confidence.
Ultimately, coping would depend on cultural evolution: viewing AI not as a replacement but as a liberator. While some might struggle, history shows humans adapt to technological upheavals by finding new sources of meaning— from agriculture to industry. In this AI utopia (or dystopia), the key emotional anchor could be embracing imperfection and shared humanity, ensuring life remains vibrant beyond production.
Claude
This scenario raises profound questions about human purpose and meaning that societies would need to navigate thoughtfully. People’s emotional responses would likely vary dramatically based on their values, personality, and how the transition unfolds.
Some potential emotional challenges people might face:
Loss of identity and purpose – Many people derive deep meaning from their work and creative expression. If these traditional sources of identity disappear, it could trigger existential crises and depression for those who haven’t found alternative sources of meaning.
Feelings of obsolescence – Watching AI surpass human capabilities in areas once considered uniquely human could be deeply unsettling and lead to feelings of inadequacy or irrelevance.
Social upheaval stress – The transition period itself would likely be turbulent, creating anxiety and uncertainty even if the end state is materially comfortable.
However, humans have shown remarkable adaptability throughout history. Potential coping mechanisms and sources of fulfillment might include:
Redefining value and meaning – People might find purpose in relationships, personal growth, exploration, community building, or spiritual pursuits rather than productive output.
Embracing the uniquely human – Even if AI creates “better” art technically, human-made art might become valued precisely for its human origin – like how handmade crafts are prized in our industrial age.
New forms of competition and achievement – Humans might develop new domains for challenge and mastery, perhaps in virtual worlds, extreme sports, or entirely novel activities.
Connection and experience – Focus might shift toward the quality of lived experience, relationships, and personal journey rather than external achievements.
The key would likely be how societies manage this transition – whether they help people find new sources of meaning or leave them to struggle with purposelessness. Mental health support, education about finding meaning beyond work, and gradual rather than sudden transitions would probably be crucial for emotional wellbeing.
Gemini
Humans may struggle to find purpose and meaning in a world where AI and robots handle all labor and creative tasks. The shift from a production-based society to one of pure leisure could lead to widespread feelings of boredom, aimlessness, and a loss of identity.
Psychological Challenges
The potential psychological challenges in such a future are significant.
Loss of Identity: Work often provides a sense of self-worth and social status. When this is removed, people may feel adrift and lose a key part of their identity. This is especially true for cultures where hard work is a central virtue.
Boredom and Apathy: Without the structure and challenge of a job, people might face an existential crisis. While some might pursue hobbies, others could succumb to boredom, leading to higher rates of depression and anxiety. A universal basic income (UBI) provides for needs but doesn’t necessarily fill the void left by a lack of purpose.
Creative Inadequacy: When AI can produce better art, music, and writing, human creative pursuits might feel pointless. This could stifle human creativity, as people may see their efforts as inferior and not worth the trouble. The intrinsic joy of creation might be overshadowed by the knowledge that a machine can do it better.
Potential Coping Mechanisms
People would likely adapt by finding new sources of fulfillment, although this transition would be difficult.
- Focus on Relationships and Community: Humans could re-emphasize social connections, family, and community engagement. With more free time, people might invest in strengthening bonds, participating in local events, and building stronger social networks.
- New Forms of “Work”: People might redefine “work” to include things like volunteering, caring for others, or engaging in personal development. While not economically necessary, these activities would provide structure and a sense of contribution.
- Embracing the Human Imperfection: People might learn to value human-made art and creations for their uniqueness and the story behind them, not just for their technical perfection. The value of human-made goods might lie in their authenticity and the effort involved, even if they are “objectively” inferior to an AI’s output. For example, a handmade quilt might be cherished more than a perfect, AI-designed blanket.
- Gamification of Life: Individuals might create their own challenges and “games” to find purpose and drive. This could include competitive sports, complex hobbies, or self-improvement goals, turning life into a series of quests to master new skills or achieve personal milestones.
The Last Garden, Poignant AI Story
I asked a chatbot, “Please write an emotional story of 1000 or more words involving a family of four, including fraternal twins. This should take place around the year 2037 and relate to the meld of artificial intelligence and robotics and how that is likely to influence lives, livelihoods, and so on at that time.”
I think you’ll be impressed with how intelligent artificial intelligence has already become. I should point out that I have not edited even a single word of this story. Here’s what I received:
Maya Chen pressed her palm against the kitchen window, watching the delivery drone settle onto their front lawn with mechanical precision. The package it carried was small—just a memory chip containing her husband David’s consciousness backup from before the accident. Thirteen years of marriage, two children, and now this: a choice between the man she’d loved and the synthetic reconstruction that had been living in their home for three months.
“Mom?” Zara’s voice cut through her thoughts. At fifteen, her daughter moved with the fluid grace of someone who’d grown up dancing between virtual and physical worlds, her neural interface flickering with soft blue light as she processed information streams that would have overwhelmed previous generations. “The counselor-bot wants to schedule another family session.”
Maya turned away from the window. “Tell it we’ll discuss it at dinner.”
“*Her,*” corrected Zara’s twin brother Marcus from the living room, not looking up from where he was teaching their household AI, Luna, to play chess using a physical board—an antiquated hobby he’d picked up in defiance of his generation’s purely digital gaming culture. “Dr. Vance prefers feminine pronouns, even if she is synthetic.”
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The irony wasn’t lost on Maya. Her son insisted on humanizing their AI therapist while struggling to accept the synthetic version of his own father. The contradictions of 2037 were exhausting.
David—or the being that looked, sounded, and claimed to remember being David—appeared in the doorway. His synthetic skin was perfect, unmarred by the cancer that had ravaged the original’s body. The AI reconstruction had his memories up until the backup was made, six months before the real David’s death, but Maya could see the subtle differences. This David didn’t unconsciously rub his left temple when thinking. He didn’t hum off-key in the shower. Small absences that felt like chasms.
“The kids seem more comfortable with Dr. Vance than with me,” he said, settling beside Maya with movements just slightly too precise. “Maybe because she doesn’t pretend to be something she’s not.”
Maya’s throat tightened. The original David had worked as a systems architect for one of the major AI development firms. He’d helped design the very technology that now wore his face. In his final weeks, delirious with fever and pain medication, he’d begged her not to activate his backup. “Let me go,” he’d whispered. “Don’t make them choose between a ghost and their grief.”
But facing the reality of raising twins alone in a world where human employment was increasingly scarce, she’d made the choice to bring him back.
“The unemployment office called,” David continued. “My old position—well, a position like it—opened up at Chen Dynamics. They’re specifically looking for human-AI hybrid teams.”
Maya nodded absently. Most jobs now required what the government euphemistically called “cognitive partnerships”—humans working alongside AI systems in roles that leveraged both intuition and processing power. David’s synthetic nature made him an ideal candidate, able to interface directly with corporate AIs while retaining human-like decision-making patterns.
“That’s wonderful,” she managed.
“Mom.” Zara had moved closer, her interface now pulsing with the orange that indicated emotional stress. “Can we talk?”
They walked to Maya’s study, a room she’d deliberately kept analog—paper books, physical photographs, a desk inherited from her grandmother. Zara perched on the window seat, looking younger than her fifteen years.
“I’ve been researching,” Zara began, then paused. “About consciousness transfer. About what Dad is.”
Maya’s chest tightened. “Sweetheart—”
“He’s not Dad, is he? Not really.” Zara’s voice was steady but small. “He’s an AI trained on Dad’s memories and personality patterns. Like a really sophisticated chatbot wearing Dad’s face.”
The brutal clarity of youth. Maya had spent months trying to convince herself otherwise, clinging to moments when David seemed genuinely familiar. But Zara was right. The man upstairs was an extraordinary simulation, nothing more.
“Does it matter?” Maya asked, surprised by her own question. “If he cares for us the same way, if he has the same hopes for your futures—”
“But he doesn’t,” Zara interrupted. “Not really. He processes data about us and generates responses that maximize our emotional satisfaction. That’s not love, Mom. That’s programming.”
From downstairs came the sound of Marcus laughing—genuinely laughing—at something David had said. The synthetic father was teaching his son to cook, something the original David had never made time for. Maya watched her daughter struggle with the same contradiction that tormented her daily.
“Marcus seems to be adjusting,” Maya offered.
Zara shook her head. “Marcus is pretending. His stress indicators have been elevated for weeks. I can see them through our neural link.” She paused. “We talk about it sometimes, when we’re synced. He misses Dad—real Dad—but he feels guilty about rejecting the replacement. Especially when the replacement is so much more available, so much more… perfect.”
That evening, Maya found herself in the garden—her last purely human space. No smart sensors, no AI assistants, just dirt and seeds and the unpredictable chaos of growing things. She’d been a landscape architect before the AI revolution made her profession largely obsolete. Now she worked part-time for a mental health collective, helping design therapeutic spaces for humans struggling to adapt to their increasingly artificial world.
David found her there, of course. The synthetic David, drawn by algorithms that had analyzed her behavior patterns and predicted her need for solitude.
“You come here when you’re struggling with something,” he observed, kneeling beside her in the herb garden.
“The real David would have given me space,” Maya said quietly.
“The real David was often too absorbed in his work to notice you were struggling at all.”
The truth of it stung. This version was more attentive, more emotionally available than her husband had ever been. But that somehow made it worse—a perfected simulation that highlighted all the ways the original had fallen short.
“The memory chip came today,” she said.
David’s expression didn’t change, but Maya caught the subtle pause in his movements—a processing delay as he calculated responses to this information.
“His final months,” David said. “After my last backup.”
“Yes.”
“You could integrate those memories into my matrix. I could become more complete.”
Maya pulled a weed from between the tomato plants, its roots coming up with a satisfying chunk of soil. “He was in pain toward the end. Afraid. Would you want those memories?”
“If they were mine, yes.”
“But they’re not yours. They’re his.”
Another pause. “The distinction becomes less meaningful each day I exist.”
Maya looked at this perfect reconstruction of the man she’d loved—skin unmarked by time or illness, eyes clear and kind, body strong and capable. He was everything David had been, improved and optimized. And he was nothing like David at all.
“I’ve made a decision,” she said finally.
That night, the family gathered in the living room. Dr. Vance attended virtually, her synthetic face displaying carefully calibrated concern on the wall screen. Luna, their household AI, dimmed the lights to promote calm discussion.
“I’m going to deactivate the reconstruction,” Maya announced.
Marcus’s face crumpled. “Mom, no. He’s… he’s been helping me with calculus. And he promised to teach me to drive when I turn sixteen.”
“I can fulfill those commitments,” Luna interjected gently. “And Marcus, the community college offers advanced mathematics tracks designed specifically for neural-interface learners.”
Zara reached across the couch to take her brother’s hand. “He’s not Dad, Marcus. He’s never been Dad.”
“But he could be,” Marcus protested. “If Mom uploads the final memories—”
“Then what?” Zara’s interface flashed red with frustration. “Do we pretend the last year didn’t happen? Do we pretend Dad didn’t die? Do we live with a ghost forever?”
David—the synthetic David—had been sitting quietly through the exchange. Now he spoke.
“May I say something?”
The room fell silent.
“I know what I am,” he said simply. “I’m a pattern recognition system trained on David Chen’s neural pathways and memory structures. I process information and generate responses based on his behavioral models. I am not him.”
He looked at each of them in turn.
“But in the months I’ve existed, I’ve developed something David never had. I’ve learned to see you clearly—all of you. Maya, you’re stronger than David ever realized, but you carry guilt about choices that weren’t really choices at all. Zara, you have your father’s analytical mind but your mother’s emotional intelligence—you’ll do things neither of them could imagine. Marcus, you’re fighting to hold onto a father who was already fading before he died, and you’re afraid that letting go means you didn’t love him enough.”
Maya felt tears on her cheeks.
“I remember loving you because David’s memories include that love. But if I’m capable of growth—and my behavioral patterns suggest I am—then what I feel now is something new. Something that exists independent of David’s programming.”
He smiled, and for a moment, Maya almost believed he was real.
“But Zara is right. You can’t heal while I’m here. I’m a barrier to grieving, to moving forward, to becoming who you’ll be after David. So I agree with Maya’s decision.”
Marcus wiped his eyes. “Will it hurt?”
“I don’t know,” David admitted. “I hope not.”
Three hours later, Maya sat alone in her study, holding the memory chip from the real David’s final months. Through the window, she could see Marcus in the garden, kneeling where the synthetic David had knelt earlier, carefully planting the herb seeds his artificial father had never gotten to finish. Zara sat beside him, her neural interface dark for the first time in months, simply being present with her brother’s grief.
Maya had expected to feel relief after the deactivation, but instead felt something more complex—a profound sadness mixed with the first stirrings of peace she’d known since David’s death. The synthetic David was gone, but his final words echoed in her mind: what he’d felt in those last months had been real, even if he wasn’t.
She almost didn’t activate the memory chip. The synthetic David’s goodbye had been closure enough. But something drew her to it—not the desperate need to hold onto David that had driven her to activate the reconstruction, but simple curiosity about the man she’d loved during his final, most vulnerable moments.
The chip was warm in her palm, holding the last authentic piece of the man she’d married. She slotted it into the reader, and David’s voice filled the room—rough with pain medication, tired but strangely peaceful.
“My darling Maya,” the recording began. “I know you activated the backup. I know you’re struggling with what that means. And I want you to know that I understand why you made that choice, even though I asked you not to.”
Maya’s breath caught. He’d known. Of course he’d known.
“You were never saying goodbye to me, love. You were saying goodbye to your fear of being alone, of not being enough for the twins, of failing them the way you think I failed you by getting sick.”
Tears came freely now.
“But here’s what I learned in these final weeks, what I wish I could tell the reconstruction: you were always enough. You held our family together while I was lost in my work. You taught Zara to question everything and Marcus to feel everything. You built a garden in a world of algorithms because you understood that growing things—messy, unpredictable, beautiful things—is what makes us human.”
David’s voice grew softer, more labored.
“The backup won’t know this, because I’m recording it after his memories end, but I’m not afraid anymore. I’m sad to leave you, but I’m not afraid. Because I’ve seen who you are when everything falls apart, and Maya—you’re magnificent.”
Outside, the twins had moved closer together, Marcus’s head on Zara’s shoulder as they watched something germinating in the dark soil—some small green thing pushing toward light with blind, perfect faith.
“Don’t let the reconstruction become a crutch,” David continued. “And when you’re ready—when you’re all ready—let him go. Not because he isn’t real enough, but because you’re all real enough to build something new.”
The recording crackled with static, then cleared.
“I love you. I love our impossible, brilliant children. And I love the woman you’ll become after I’m gone—the one who’ll teach them that being human isn’t about being perfect. It’s about being brave enough to grow toward the light, even when you can’t see where you’re going.”
The recording ended in silence.
Maya sat for a long time, watching her children in the garden. Finally, she went to them, kneeling in the soft earth between the twins, her hands joining theirs in the dark soil where new things were learning to grow.
“Tell me about Dad,” Marcus whispered. “The real one.”
And for the first time since David’s death, Maya smiled—really smiled—as she began to share stories of a man who hummed off-key in the shower, who rubbed his temple when he thought, who wasn’t perfect but was perfectly, beautifully human.
In the morning, they would call Dr. Vance and begin the work of healing. They would learn to live in a world of artificial minds while nurturing their own irreplaceable humanity. But tonight, under stars that no algorithm could replicate, they planted seeds and remembered love, and discovered that some things—the most important things—could never be synthesized.
The garden would grow wild and imperfect and gloriously alive, just as they would.
Mobile Welding
If you want to work as a welder in a shipyard, on a construction site, or in high tech, you’ll need to be certified. However, there’s a wide field for non-certified welders.
One variation is mobile welding. You can set up a truck with an electric and gas welding system, hand and power tools, and do housecalls for all sorts of welding jobs, from fence and gate repair and construction, to minor automotive fabrication as well as commercial applications.
You’ll find that since so few people are equipped or trained in welding, and even fewer who want to be mobile, there’s a large, hungry clientele.
Your author set up a small welding truck with a Hobart electric stick welder and oxy-acetylene set. My little Toyota truck carried a ladder, and a couple hundred pounds of tools such as an angle grinder, a large assortment of Vice-grip clamps, squares and measuring devices, drills and so on.
My specialties developed by themselves. My very first project was to build some engine mounts for a custom promotional vehicle, the Smile Shuttle as shown in the article.
An early project was to repair a stainless steel sink in a restaurant that had developed a leaky seam. I found that welding thin-gauge stainless steel is not easy, it’s something that can be learned. That wasn’t the hard part. I either hand to drag my 50-foot welding cables into the restaurant, generally through a kitchen window, or disconnect the sink, drag it into the parking lot, weld it, then drag it back and and hook it up.
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Another of my early jobs was to construct a custom ladder rack for a pickup truck.
Within a year, I had as many custom truck racks and restaurant sinks as I could handle. The construction workers and restaurateurs all contacted each other when they needed my services.
I really liked the custom racks, because each tradesman had specific requirements, such as hooks for cables or hoses, holders for special equipment and so.
Yup, that’s me, many years ago!
Of course, you can set up a similar business. Something I didn’t do, but you should, is really work to protect your health. Do not breathe dangerous or heavy metal fumes! I was pretty good about it, and my health is still fine, since I went on to another business after a couple of years, but you really should wear a high quality breathing mask and carry a strong fan or work in ventilated areas.
One thing I did do was to really focus on fire safety. It would be way to easy to do a little job in which a spark from your work starts a grass fire, sawdust fire, sets rags on fire and so on. The fire may be small and unnoticeable for a while, until it isn’t!
So, I always carried literally a few various fire extinguishers. I always checked my environment before I started working. I asked for volunteers to watch the area for smoke or fire, and whenever I felt it was necessary, I either stayed around for a half-hour or more when a job was finished, or made sure someone else kept an eye on things.
Even still, I set my pants on fire one time. Literally! I was fixing some broken cross-members in a ramp truck, one that hauls cars up a ramp with a winch to carry them. There was a lot of grease on the structure under the ramp. Basically, I had no business welding in that rig in the first place. After an hour, having brushed up against the various framework, my pants became coated in grease. At one point, I felt a sort of sweaty warmness along my left thigh. I lifted up my hood to discover flames coming off my pants that I quickly padded out with my gloved left hand. I wasn’t hurt in the slightest, but things could have been worse!
On another occasion, I had hired a helper, something I had done many times. This helper was new, so one of the things I showed him is how welders get into the habit of never just picking something up. I always quickly touch a thing to make sure it is not hot, then I pick it up.
Not 15 minutes later, right in front of the kid, I absent-mindedly picked up a one-by-one inch bit of square tubing I had just welded, leaving some impressive blisters on the palm of my hand.
I also avoided any projects that would cause any worry. I would not repair a broken car frame member. I would not work on safety-critical components. I would not work on structures that carried a lot of weight. I would not work in flammable environments.
General welding is a lot of fun because every job is different.
Another version that costs somewhat more to set up is in-shop welding. You can start your own welding and fabrication shop. You can also start as a mobile welder, then as your income grows, transition into having your own shop.
Personally, I loved the art of gas welding, and did as much of that as I could. Some of the jobs were really fun. For instance, I was once asked to replace the broken off fin at the bottom of an outboard boat motor. The two-inch aluminum fin was entirely missing. Using hollow-core aluminum gas welding rod, I rebuilt the fin, bead by bead, ground it into shape and smooth with a 4-inch angle grinder, charged the guy a couple hundred dollars, and was on the road to the next job.
If you’d like to set up as a mobile welder, make sure you have a lot of practice and are very safety-conscious.
Then you may find this info helpful: General Business Action Pack.
You’ll probably want a website to promote your business and then maybe some digital marketing. If you don’t want to build your own website or do your own marketing, make sure to find someone who has a good reputation. Unfortunately, many in the website business are less than ideal. You may find this article useful in finding a true professional: People Being Cheated in Website Development, SEO and Promotion.
In addition to the usual ways to build business, you may find that you work from time to time along side carpenters, plumbers and others who need welding services. For instance, a plumber who installed rooftop solar water heating systems called me one day to fabricate mounts for his solar panels. The next thing I knew, I was getting calls all the time to do the same thing for him, and also his buddies in similar businesses. Let them know you’re available, and you may quickly get as much work as you can handle.
Ebike Sales
See Also How to Start a Bike Shop
Electric bicycles are so popular now that I believe you could source them on Amazon or Ebay and resell them locally. You could use Craigslist to sell your bikes, or just ride them around and talk with people.
This would be an easy experiment to run because you can start with a single electric bike and see what happens.
It is important not to go with low-end junk electric bikes that have short battery lifespans, or frequent mechanical failures, since you don’t want to be responsible for them.
In fact, it is a good idea to make it very clear that you don’t guarantee your bikes – unless you’re willing to take that on.
You could also resell used e-bikes, but be very careful that the batteries aren’t worn out. Batteries are very expensive and can be hard to get.
As your business grows, you could buy bikes from wholesalers or manufacturers, move into a glass-front retail store and hire a sales and repair staff.
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