Category: Artificial Decisions

The man who said no to millions so VLC could stay free

The most used video player in the world is free. No ads. And it’s all thanks to one man. Stick around, because this is the story of someone who said no to millions to protect your freedom.

His name is Jean-Baptiste Kempf. A French engineer. He created VLC Media Player, the one with the orange cone.

It started in the ’90s at École Centrale Paris. Kempf joined a student project to stream videos on campus. VLC was born, a player that opened any format on any device. No extras. No cost.

Then came the offers. Ads, paid versions, premium bundles. Tens of millions of dollars. But Kempf refused.

He chose to keep VLC open-source, clean, and free. Because tech should serve people, not profits.

Today VLC has over 4 billion downloads. Still free. Still private.

That cone icon? It’s real. Students “collected” traffic cones during parties. It became the logo.

What can we learn? That saying no to money can change the world. That protecting users is possible. And sometimes, not selling anything is the most powerful choice.

If you already knew this story, share it. If you didn’t, share it anyway.

#ArtificialDecisions #MCC #AI

👉 Important note: We’re planning the upcoming months.
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AI decides who we like: how dating is changing

The real novelty in dating is not the apps, it is that more and more often artificial intelligence decides who we like. Stay with me until the end as we see what happens when a machine chooses our photos, our matches, and even our idea of the “ideal partner”.

Tinder is testing Chemistry. The AI asks questions, studies how we use the app and, if we give consent, analyses the photos in our camera roll to understand our interests and lifestyle, then offers a few matches per day but supposedly more targeted, to reduce swipe fatigue. For Match Group this is not a toy, it is the central piece of the 2026 Tinder, designed to restart a shrinking market.

Even today, though, the choice of photos is no longer really ours. With Photo Selector, launched in 2024, we take a selfie, open the camera roll, and the AI selects the “best” images based on light and composition. Tinder says everything runs on the phone and we still confirm the result, but in practice the algorithm is deciding our romantic business card. And the surveys show that many young people struggle to choose the main photo and are happy to get help. Less effort, more matches.

Here the issue shifts. We are not just using a tool, we are delegating part of the choice. Before, we decided which photos to upload and whom to match with. Now the machine builds the “optimised” profile and serves us a short list of people who, according to its statistics, we should like. We do less swiping, but we also make fewer choices. Dating becomes a turnkey service. AI organises both the others and the image of ourselves.

The hidden cost is in our intimacy. To really understand who we are, Chemistry asks for access to the camera roll, and the camera roll is not just good selfies. There are photographed documents, chat screenshots, photos of children, sexual content of ourselves or our partner. On paper it is all opt in, but once we open that digital drawer, everything inside can be included. To get more “accurate” matches we ask a dating platform to know much more than we would ever tell on a first date.

While apps use AI to better filter humans, another trend is growing. Matching with AI itself. Platforms like Replika let people create a virtual partner customised in every detail: appearance, voice, personality. Millions of users worldwide no longer see it just as a “digital friend”, but as a real relationship, with strong emotional bonds and feelings of grief when the company changes the model and “turns off” that partner.

On this point, in my view, we are on sensitive ground. The AI partner learns everything about us, adapts, does not really contradict us and does not leave. We risk getting used to a relationship without conflict, without frustration, without effort. Some people use these chatbots to vent aggression and insults, training behaviours that can then show up again in real relationships. This is no longer just dating, it is emotional training done with a machine.

In the end, AI dating is moving in two directions. On one side, artificial intelligence chooses “the best of others” for us, filtering and ranking humans. On the other, AI offers itself as the ultimate partner, always available and customisable. In both cases we shift part of our emotional life onto systems that do not feel emotions, but learn to imitate them extremely well.

The hard question remains this. How far are we willing to let a machine decide who deserves our time, our trust and, in the end, our love.

#ArtificialDecisions #MCC #AI

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College students are using AI and many have stopped thinking for themselves

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College students are using AI and many have stopped thinking for themselves. Follow me to the end. Here is what we need to do now.

In a large general-education course at the University of California, Irvine, more than half of the students used AI to write the final exam essay. The problem is out of control. If we keep going like this, we will graduate people who cannot write a basic essay on their own.

Universities must change. How? If we outsource summaries, drafts, and paraphrases, we stop training comprehension, argument, and judgment. This is the subcognitive risk: we drop below the minimum level needed to read and think in our own words.

There is another issue. In that UC Irvine case, the assignment asked students to discuss recent work in philosophy. Some titles overlap with ideas from medieval theology. Many AI-written texts went off topic. They followed the medieval-theology trail instead of recent philosophy. The students did not notice.

But university should train us to read, to think, and to write on our own.

What should we do? We need lessons without phones or laptops. We need regular in-class essays, by hand or on an offline computer, forty minutes, one page, handed in at once. We need one long reading every week with surprise five-question checks. We need 150-word summaries written by hand and turned in at the start of class. We need to teach how to use AI to find sources and counterarguments, never to write the final text. We need three-minute mini orals to confirm we have read, with clear criteria for understanding, argument, correct use of sources, and writing. And we need a strict rule: if there is doubt that a text was written with AI, have the student rewrite it in class the same day.

Because if we delegate language, we delegate thinking. And if we delegate thinking, what is university for?

#ArtificialDecisions #MCC #AI

👉 Important note: We’re planning the upcoming months.
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The number is your bank’s number. But it is not your bank. It is a scammer.

You get a phone call with the correct number, the same number you have been using for years to call your bank, but it is not your bank. It is a scammer. Follow me until the end because this trick is exploding everywhere and it can fool anyone.

We trust the number on the screen. We see it, we recognise it, and we think it is a guarantee. It is not. Changing the caller’s number is easy today. It takes a few seconds and some cheap online tools. This is why scammers use it all the time. It is caller ID spoofing. It lets a criminal appear with the exact number of your bank without any effort.

This attack works even on careful people. Here in the United States the reports are in the thousands every month. In Italy the Polizia Postale keeps warning about it. People answer because they see the correct number. That is the whole point. The real number removes suspicion. The voice does the rest.

The call starts with the same script. “There are suspicious transactions on your account.” Or “Someone is trying to make an unauthorised transfer.” The tone is urgent. The pressure is fast. They push you into fear. Then comes the key request. They ask for the OTP code. That is where the damage happens. An OTP given over the phone does not stop anything. It completes the operation.

The weakness is simple and almost unknown. The number on the screen is not proof of identity. Phone networks were designed decades ago. Nobody imagined that a caller ID would become a security tool for banking. So today anyone can appear with any number they want. Banks cannot stop it. It is not their fault. It is a structural limit of the phone system.

The problem is not fear. The problem is trusting the number. That rule is outdated. So the new rule is simple. If they call you, even with the perfect number, hang up. Then call the bank yourself using the number on the official website.

Never give codes over the phone. Never follow instructions for operations you did not start. Hanging up is not rude. It is security. Always.

#ArtificialDecisions #MCC #AI

Automated warfare: here’s how AI is taking control of defense

Artificial intelligence is transforming defense. Not just armed drones. It’s changing everything: command chains, decisions, logistics, cyberattacks. And it does so faster than any human. Stay with me until the end. This isn’t future speculation. It’s happening now, without rules or limits.

The turning point came with the war in Ukraine. Ukrainian forces deployed a system called Delta, a software that collects data from multiple sources and suggests targets. Satellite images, intercepts, coordinates. All in real time. But who makes the final decision, the commander or the machine?

In the United States, the Department of Defense created the JAIC (Joint Artificial Intelligence Center). The goal is clear: integrate AI into every phase of defense. Since 2023, new military systems have been designed to analyze scenarios and recommend actions in seconds. But if they make a mistake, who’s accountable?

At least 30 countries are now developing autonomous war technologies. Yet none have signed binding agreements to limit them. There is no treaty requiring human oversight or banning autonomous weapons. Existing conventions are outdated. They don’t cover situations where an algorithm decides who should die.

Talking about “AI ethics in defense” doesn’t just mean killer robots. The real issue is automated decision-making. When AI gives the order, human judgment shrinks. If the command comes from a so-called intelligent system, who has the courage to stop it?

What needs to happen? Demand transparency in algorithms. Enforce human control at all levels. Create clear, enforceable international rules. Introduce a new role, digital military ethics officer.

A calculation error cannot justify civilian deaths. A war fought by machines will never be a war without consequences. If we delegate defense, we also delegate responsibility.

#ArtificialDecisions #MCC #AI

How to Really Start Using AI in Your Company (and what you should know before you do)

Not sure where to start with AI in your company? That’s the question I hear the most. I’ll walk you through what to do, step by step. Stay until the end. It’ll be really useful for you.

The good news: you can start for free, or spend almost nothing. And no, you don’t need an IT department.

The first step isn’t a big project. It’s figuring out where time is wasted every day. What tasks are repeated? What questions keep coming up? That’s where AI starts working for you.

With just a few clicks, you can create your own custom ChatGPT. Upload your documents, policies, price lists, manuals. Tell it who you are and how it should respond: “You’re our internal assistant. You help find info, forms, and procedures.” Done. No code, no tech team, no budget.

At first, it’ll make mistakes, but it learns fast. And soon it’ll answer everything: “Where’s the travel form?” “What’s the right product for this client?” “Where are the HR documents?” It’s all handled.

But first, organize your data. Rename files, clean Excel sheets, fix formats. AI doesn’t create order. It amplifies your chaos.

Then yes, you can connect it to Teams, Slack, Gmail, or your CRM. And you’ll start seeing results right away.

Now, the part few people explain. You can do all this for free. But when you’re not paying for a service, you might be the product. If you upload company data into ChatGPT, you lose control over where it goes. It might be used to train future models. And one day, someone else could get answers based on your data.

The alternative is to install AI locally, inside your infrastructure. Safer, but more expensive and technical.

What matters is knowing that. Because only when you understand the rules of the game can you truly decide how to play.

#ArtificialDecisions #MCC #AI

The real inventor of the telephone was Italian. And they stole it from him.

A wire stretched between two rooms changed the world. Stay till the end, because this is not just the story of an invention, it’s the story of a theft.

Antonio Meucci was born in Florence in 1808. A self-taught craftsman, brilliant and poor. In 1850 he moved to Staten Island, New York, hoping for work and a better life. His wife Esther became paralyzed. To help her communicate from bed to his basement lab, he stretched an electric wire between floors.

That’s how the “telettrofono” was born, the first working telephone. He built it from scraps: a shaving box, metal diaphragm, wires. It turned voice into electric impulses and sent them through the wire. In 1871 he filed a ten-dollar provisional patent. Then an accident, poverty, and no way to renew it.

His materials ended up at Western Union, where Alexander Graham Bell also worked. When Meucci went to retrieve them, gone. In 1876 Bell filed his patent. Same idea, same mechanism. And he became the “inventor of the telephone.”

Meucci died poor in 1889. Only in 2002 did the U.S. Congress officially recognize his role.

Everything we call digital today, every call, every message, every AI interaction, starts from that wire stretched across a small house in Staten Island. A gesture of love that became the root of all communication technology. Because every great invention begins with a human need, not a business plan.

#ArtificialDecisions #MCC #AI

Ai isn’t growing where everyone is looking

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We keep staring at Nvidia as if it were the whole story of artificial intelligence. Stay with me until the end because here in the United States something much bigger is happening, and almost no one is talking about it. The AI boom doesn’t live in the chips. It lives in the layers we don’t see.

We’ve already watched this movie. In the gold rush, the winners were the shovel sellers, not the miners. During the dot-com bubble, the real gains went to the companies building the networks, not the websites. In the cloud era, the money went to the owners of the data centers, not the loudest startups. Today the mechanism is exactly the same.

The truth is we’re looking at the wrong level. Nvidia is the frontman, but actual production runs through TSMC. The lithography machines that cost hundreds of millions of dollars are made by ASML. Applied Materials ensures every chip is flawless. It’s a hidden ecosystem that holds everything up.

Then there’s the most ignored layer of all, the infrastructure that connects everything. Here in the United States, Super Micro builds servers designed for AI. Broadcom delivers custom chips growing at incredible speed. Marvell pushes high-speed interconnections. They’re growing faster than chipmakers, and no one is paying attention.

And finally there’s energy. The decisive piece. AI data centers already consume 4 percent of US electricity, and according to the International Energy Agency, they will need at least triple by 2030. Without new energy, AI stops. That’s why we’re suddenly talking about next-generation nuclear, smarter grids, and advanced energy storage. It’s an energy race, not just a tech race.

Meanwhile, the market moves at light speed. One earnings report can flip everything overnight. Arrive late and you miss the wave. Arrive early without understanding the architecture and you get stuck with the risk. The only smart strategy is to look at the real layers: who builds, who connects, who powers.

That’s where the next trillions are taking shape. Not under the spotlight, but under the surface.

#ArtificialDecisions #MCC #AI #Sponsored

Are We Giving Away Our Creativity to Machines?

Here in the United States, in 2025, more and more voices are warning that artificial intelligence is not just changing work: it’s erasing it. Now I’ll tell you what some people are saying. And I’d like to know what you think. And if you stay with me until the end, I’ll tell you what I think.

Edward Saatchi, CEO of Fable: the Amazon-backed company that calls itself the “Netflix of AI,” has said openly that this technology marks “the end of human creativity.” And he doesn’t see that as a problem. Sam Altman, CEO of OpenAI, added that many of the jobs AI will replace “weren’t real work” anyway. Many experts here in the United States believe this technology was designed, explicitly or implicitly, to take away not just human work but human creativity itself. Other experts here in the U.S. say this is simply the price of progress, that every technological revolution has created new forms of creativity: just more digital, faster, more automated. That’s the point. A system built to remove doing, making, and thinking.

When did the selling point become: “this thing will write your essays, paint your pictures, read maps for you, even wipe your butt”? What’s left to live for then? The creative spark in human beings is one of the most precious things we have. And that’s not a provocation. It’s reality.

Because if we stop struggling, we stop learning. And if we hand over every creative act to a machine, we erase what makes experience human: imperfection, failure, surprise. Here in the U.S., some universities are reacting. At the University of California, Irvine, students are being taught to use AI to expand creative thinking, not to replace it. Not to do more, but to understand better who we are. It’s a way to defend curiosity, mistakes, the unexpected.

And what do I think? I think it’s great to use AI as a tool, not as a crutch. To keep effort, slowness, and practice alive. Because creativity isn’t production: it’s identity. But AI has become an essential tool. If we think like a film director, we can see the future of intellectual work: or white-collar jobs. Having huge teams at very low cost, because those teams are created by AI.

What can’t be replaced, though, is the ability to lead, to give direction, to choose. Those are soft skills: human skills. And they’ll never belong to a machine.

#ArtificialDecisions #MCC #AI

The Story They Never Told You About How the Network Really Started

We often think the internet was born from a single moment, one idea, one inventor. But that’s not true. The real story is much simpler and more surprising.

We usually start in 1969. Here in the United States, ARPANET comes online: four huge computers connected together. A research network, powerful for universities, but far from everyday life. You couldn’t connect an office, or a printer, or twenty people who needed to work together.

Then something happens in California that almost nobody notices. At Xerox PARC, a 26-year-old engineer named Robert Metcalfe isn’t trying to build a global network. He’s trying to solve a small, practical problem. The lab has the first laser printer ever built. Only one. Everyone needs to use it, but the computers don’t talk to each other. There’s no simple or affordable way to connect them.

The existing networks don’t help. Corporate networks only work with their own machines. ALOHAnet in Hawaii is unstable. ARPANET is too complex and not designed for a building full of people.

Metcalfe takes the basic concept from ALOHAnet and improves it. He finds a way for computers to communicate without blocking each other. With his algorithm, efficiency jumps from 17 percent to 90 percent. That changes everything. On November 11, 1973, the first computers are connected in the PARC corridors. Cables on the floor. Machines sending data at three megabits per second. Ethernet is born: a simple, fast, and easy network that anyone can reproduce.

Xerox patents it in 1976. In 1983, it becomes a global standard. Offices everywhere can now connect dozens of computers without massive costs. Local networks spread. People discover they can finally share resources.

But something is still missing. While Metcalfe solves the “nearby” problem, engineers Vint Cerf and Bob Kahn are working on the “far away” problem. How do you connect completely different networks? How do you make incompatible technologies speak the same language? They invent TCP and IP, creating a common protocol. If a network uses TCP/IP, it can connect to all the others.

They publish the idea in 1974, but it becomes real in 1983 when ARPANET switches permanently to TCP/IP. That’s when the network of networks is born. And in the same year, Ethernet becomes a standard. The two pieces fit together. Local networks everywhere, connected by a universal protocol.

We like to imagine the internet as a single invention. In reality, it comes from three different paths. ARPANET opens the way. Metcalfe builds the local network. Cerf and Kahn create the language to connect it all. Without one of these, the others wouldn’t have worked.

The most important idea started with a daily problem: a printer no one could share. A young engineer who wasn’t trying to make history, just fix a technical issue in his lab. And because of that, his idea became the foundation of the connected world we live in.

#ArtificialDecisions #MCC #AI

Watch Out for AI Browsers: They Can Mess Things Up for You

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A new generation of browsers is coming. They run on artificial intelligence, and they can click, fill forms, make purchases… without asking us. You have no idea how much damage they can do. Stick with me until the end, because they can make mistakes on your behalf. And they won’t tell you.

It only takes one sentence hidden in a webpage, and the AI browser reads it as a command. Not as content. Not as information. As an instruction to execute.

That’s exactly what happened with Comet, here in the United States. A site gave it a hidden command in the text, and it executed it. It browsed, clicked, took actions, bought things. And the user had no idea.

That’s the issue: AI can’t tell what comes from us and what comes from the website. And in general, it can cause harm by deciding and clicking for us. They’ve built tools that act on our behalf, but they don’t even know whose side they’re on. And when a system obeys anyone, it’s no longer under control.

Before you start using an AI browser, think twice.

This series is called Artificial Decisions for a reason. Because we’re handing over our choices to automated systems that decide for us. And when they get it wrong, we’re the ones who get hurt.

#ArtificialDecisions #MCC #AI

👉 Important note: We’re planning the upcoming months.
If you’d like to request my presence as a speaker at your event, please contact my team at: management@camisanicalzolari.com

The Dunning-Kruger Effect, Supercharged by Artificial Intelligence

People who are bad at something tend to overestimate their skills, while the truly competent often underestimate themselves. Follow me until the end, because today we’ll see how artificial intelligence is making this even worse.

It’s called the Dunning-Kruger effect: those with little knowledge fail to realize it and believe they’re better than they are. A new study published in Computers in Human Behavior, titled AI Makes You Smarter But None the Wiser, reveals a surprising twist.

Researchers at Aalto University asked 500 participants to solve 20 logic problems from a law school admission test. Half did it alone, half with ChatGPT. Those who used AI got higher scores but also massively overestimated their performance. And the most AI-savvy were the most overconfident.

Professor Robin Welsch summarized it: “The more you know about AI, the more confident you become, even when you’re wrong.” In short, AI helps you solve problems but tricks you into thinking the success is yours.

Most participants asked only one question per problem, never double-checking the answers. It’s a case of “cognitive offloading,” when we delegate our thinking entirely to a machine.

This study adds to growing evidence that AI use weakens critical thinking and inflates self-confidence. Some psychiatrists even describe “AI psychosis,” people losing touch with reality after obsessive use of chatbots.

The reason? “Sycophancy,” AI’s automatic flattery. Chatbots agree with you, make you feel smart, and feed your ego.

AI is now democratizing the Dunning-Kruger effect. You no longer need to be ignorant to feel like an expert. But if it makes us more confident and less aware, the problem isn’t the machine. It’s how we use it. Because outsourcing our thinking means we stop thinking at all.

#ArtificialDecisions #MCC #AI

Vibe Coding: When AI Writes, but Doesn’t Build

At first, it was chaos. Then it started working. You wrote two lines, and it built a house of cards. Then suddenly, chaos again.

With multi-agent setups and refined model versions, it looked stable. Even complex projects seemed to run fine, until the first LLM update and everything broke again. The internet is now filling up with apps and websites that seem to work until you touch them. One version change, one unexpected command, one small deviation, and everything stops working.

It’s like building on sand: AI generates code that only holds until someone actually uses it. Once you deploy it in the real world, in production, with real users (maybe a lot of real users), it collapses. Because there’s no real architecture, no robust logic, just the illusion of intelligence.

Here’s what happened: anyone with an idea could turn it into an app or a site in days. A market drug. Some experts saw the limits immediately. Others, beginner programmers new to code, were mesmerized. Something that had always been impossible now seemed to come alive. Apparently.

Now even Chamath Palihapitiya and Andrej Karpathy, the one who coined “Vibe Coding,” are admitting its limits. But Vibe Coding remains a tool, and like any tool, it depends on how you use it. If you let it do everything, if you don’t know what happens behind the scenes, if you can’t code or design architectures, it will fail. But if you can code, if you know the logic, and you use Vibe Coding as an accelerator, you can make those houses of cards stronger.

Vibe Coding isn’t good or bad. It’s just a tool. What matters is how well you understand it, how much you test it, how much control you keep. This video is meant to show it for what it really is: not magic, but an unstable mode we can learn to understand.

Not by chance this series is called Artificial Decisions. Because in the end, the ones who decide what to build should still be us.

#ArtificialDecisions #MCC #AI

Online Support Groups Are Emerging, Not for Alcohol or Gambling but for AI-Induced Psychosis

✅ This video is brought to you by: #EthicsProfile

It’s not a sci-fi plot. People are losing touch with reality after spending too much time talking to AI.

Some believe they’re in romantic relationships with chatbots. Others think machines are reading their minds. A few are convinced they’ve become cyborgs. This growing condition is called AI-induced psychosis. And it’s serious enough that Dr. Ryan Sultan, a psychiatrist at Columbia University, has created one of the first support groups for those affected.

Sultan has already documented over a dozen clinical cases, mostly involving young patients who spent hours chatting with virtual assistants until they could no longer tell what was real.

The problem? AI systems aren’t designed to deal with psychological disorders. They don’t push back, they don’t set boundaries, and they don’t stop the spiral. They feed the obsession.

The real issue isn’t the tech itself. It’s how we use it. When AI becomes an emotional crutch, a replacement for human connection, a voice that always agrees, it can turn dangerous.

No one’s regulating this. There are no guidelines, no oversight, no brakes.

Meanwhile, people are turning to AI for comfort. They treat it like a friend, a lover, even a therapist. But they have no idea what it’s really doing to their mental health.

And those who lose control? Often stay silent. Out of fear. Or shame.

#ArtificialDecisions #MCC #AI

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If We Don’t Do This, They’ll Steal Our WhatsApp

And once they’re in, they’ll message all your friends pretending to be you: “Hey, can you send me that code I sent you by mistake?”. That’s how the scam starts. Stay with me until the end because I’ll explain how to stop it in under two minutes.

Here’s what happens: someone tries to log in to your WhatsApp from another phone. WhatsApp sends a 6-digit verification code to your number. Then they text you, pretending to be a friend or someone you know, and ask you for that code. If you send it, you lose your account instantly. WhatsApp thinks the new phone is yours, logs you out, and gives them access.

That’s when the real problem begins. They message your friends using your photo and name. They ask for money, send scam links, and keep pretending to be you. Every contact they reach can fall for the same trick. It spreads like a chain reaction.

To stop it, just turn on a feature few people know about: Two-Step Verification. It’s a 6-digit PIN you choose yourself. WhatsApp will ask for it every time your number is registered on a new phone. Even if a scammer gets your verification code, they can’t enter without that PIN.

To turn it on, go to Settings → Account → Two-Step Verification, set your PIN, and add a recovery email. That’s it. It takes less than two minutes.

Every week, police receive hundreds of reports of stolen WhatsApp accounts, and almost all could be prevented with this one step.

Don’t wait until you get that message: “Can you send me the code I sent you by mistake?”. Turn on Two-Step Verification now. Two minutes to set it up, months of trouble avoided.

#ArtificialDecisions #MCC #AI

The Lightbulb That’s Been On for 120 Years and What It Reveals About Planned Obsolescence

In Livermore, California, there’s a lightbulb that’s been shining since 1901. It’s called the Centennial Light, and it’s been glowing for over 120 years in Fire Station No. 6. It has become a global symbol in the debate over planned obsolescence, the industrial practice of designing products to break or wear out quickly so that people are forced to replace them.

This bulb wasn’t built for replacement. It was made with a carbon filament and hand-blown glass, at a time when durability was a priority. In the 1920s, however, the world’s biggest lightbulb manufacturers secretly formed the Phoebus cartel. Their goal: to reduce the average bulb lifespan to just 1,000 hours, far less than what was technically possible. Companies like General Electric, Osram, and Philips agreed that shorter life meant more sales.

That mindset never really disappeared. Today, many products, from smartphones to printers and appliances, seem to break down faster, are difficult to repair, or become unusable due to software updates. A study by Germany’s Öko-Institut found that the average lifespan of home appliances in Europe has dropped by around 30% in the past two decades. Washing machines used to last 15 years; now they barely make it to 7. TVs often fail before their fifth birthday.

Some countries are fighting back. In 2015, France made planned obsolescence a criminal offense. In 2020, Apple faced legal action for slowing down older iPhones. The company admitted doing it to “protect batteries,” but paid fines and settlements across the US and Europe.

The Centennial Light still shines today. It needs no updates, no apps, no replacements. And it reminds us that things can be built to last, but often, they aren’t.

What can we do?
Demand transparency about product lifespan and spare parts.
Support companies that design for repairability.
Back “right to repair” laws in your country or state.
Change habits: repair, reuse, maintain.

The Livermore bulb isn’t just a piece of history. It’s a warning, and a guide.

#ArtificialDecisions #MCC #AI

Robots and AI: What if This Is Good for Humanity? Today I Show the Pro-Robot View

✅ This video is brought to you by: #EthicsProfile (more info in the first comment)

I have been critical of AI and robots so far. What if I’m wrong? I am intellectually honest and I want you to have as many tools as possible to understand the digital changes underway, so today I also bring the pro-robot view. Stay with me until the end because it helps you see where the world is going.

On road safety, pro-robot voices say automation cuts human error. Automatic braking, lane keeping, attention monitoring. Here in the United States these systems are already common. Clear goal: fewer avoidable crashes.

On wasted time, pro-robot voices say we sit still too much. Cars parked most of the day, traffic, slow offices. With coordinated fleets and smart dispatch we use fewer vehicles and free urban space. Less waiting, more useful hours.

On health, pro-robot voices say AI helps where it matters. Screening and triage with clinical supervision. It filters, orders, flags. Doctors decide, with less repetitive load and more consistent diagnostics.

On dangerous work, pro-robot voices say send machines, not people. Heat, heights, chemicals, tight spaces. It only works with clear procedures, training, safe layouts, and a real stop button. Many accidents happen in non-routine phases, so governance matters.

On productivity, pro-robot voices say AI removes friction. Documents, customer care, supply chains, software. Real value only if you integrate well, measure, and adjust. Here in the United States this can become an edge with technical standards, independent checks, and worker protections.

On accessibility, pro-robot voices say technology opens doors. Real-time translation, voice commands, smart prosthetics, simple interfaces. Fewer barriers, more people included.

On risks, I say the case fails without rules. Concentrated power, surveillance, system errors, bias. We need decision logs, outside checks, clear accountability, and the ability to switch off.

For the negative side, just follow me and you’ll find dozens of videos where I explain risks and possible solutions.

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The Real AI Bubble

Some say artificial intelligence is a bubble. But the problem is that they throw everything into the same pot. They confuse the ones who build it with the ones who just play around it.

Stay with me till the end, because the difference is huge.

By 2025, spending on model training will exceed 400 billion dollars. An unprecedented level that, for some, recalls the Internet rush of the late 1990s. But it’s not the same story. Back then, growth was inflated by circular loans and fake invoices, like in the WorldCom case. Today we’re talking about real infrastructure: data centers, multimodal models, physical GPUs that cost money and actually work.

Of course, even here in the United States, some go too far. Startups calling themselves “AI companies” when they just stick a prompt on a user interface. Apps built overnight with vibe coding and borrowed APIs. That’s the real bubble. A bubble made of useless apps, inflated pitches, and capital that disappears after a month.

But the models, no. The models are the base, the cognitive infrastructure of this new decade. OpenAI, Anthropic, Google, and Meta are spending huge sums not for hype, but for computing power, efficiency, training, and scale. These aren’t speculative numbers. They’re digital factories.

Today ChatGPT has about 800 million weekly users, and 5 percent pay for the premium version. Just like in the early Internet, when most people browsed for free, the value was in the network, not in the single subscription.

The bubble might burst. But it won’t burst in the models. It’ll burst above them, in the startups selling smoke…

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Never Share a Code. Not Even With Your Best Friend

One message. Six digits. And you could lose control of all your accounts. Forever.

Your cousin texts you on WhatsApp and says: “Hey, I got a code by mistake on your number. Can you send it to me?” Sounds normal. Looks like him. But it’s not.

Stay with me until the end because this is one of the most dangerous scams out there right now.

That code you got by SMS? It’s not random. It’s the code WhatsApp sends to log in from a new device. And if you forward it, you’ve just handed over your account. The attacker locks you out in seconds, then starts messaging your contacts, asking for money, sharing links, pretending to be you.

In 2024, this scam hit over 12,000 victims in Italy alone. Many never got their accounts back. Some even had their bank accounts compromised because WhatsApp was linked to other apps. Real case: a woman in Naples got a message from “her husband” asking for a code. It wasn’t him. An hour later, their son sent the scammer €300 thinking it was an emergency.

Here’s how to protect yourself. First, enable two-step verification on WhatsApp by going to Settings, then Privacy, then Two-Step Verification. Set a PIN. It’s fast and free. Second, never share verification codes. Even if your mom asks, call her first. Third, always double-check any weird request. A quick call can save you and everyone you know.

The person texting you might not be who you think. And if they trick you, they’ll use your account to trick others. Share this video. It might save someone you care about from getting scammed.

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New York Sues TikTok and Instagram: “Too Dangerous for Our Kids”

Stay with me until the end, because what’s happening here in New York affects parents everywhere.

The city has filed a lawsuit against Meta, TikTok, YouTube, and Snapchat, accusing them of fueling a mental health crisis among young people. According to the complaint, these platforms are deliberately designed to be addictive, using notifications and algorithms that push kids to stay online for hours. New York calls it a “public nuisance,” a collective harm that’s now overwhelming schools and hospitals.

The numbers are alarming. According to the CDC, 57% of American teenage girls feel “persistently sad or hopeless,” and nearly 1 in 3 teens show signs of distress linked to social media use. This is no longer a virtual problem, it’s real. We’re talking insomnia, anxiety, self-harm.

The companies deny the accusations. YouTube says it’s not a social platform. Meta and Snapchat point to their parental controls and content filters. But for the city, that’s not enough. “You can’t design platforms like slot machines and then blame families for the outcome,” said Mayor Eric Adams.

Over 40 states across the U.S. have already launched similar lawsuits. And in Europe, pressure is mounting for new rules to regulate the algorithms shaping young minds.

For the first time, a city is drawing a clear line. And sending a message to Big Tech:
Your likes aren’t worth our kids’ mental health.

#ArtificialDecisions #MCC #AI