Musk’s AI Timeline Measures Human Hesitation, Not Machine Progress

Elon Musk recently gave a 90-minute interview to The Economist (July 23, 2026, with editor-in-chief Zanny Minton Beddoes). While most of the media coverage fixated on the controversial segments, I want to focus on two specific claims that demand deeper analysis. Because I work daily with AI agents, I have direct, hands-on evidence relevant to both.

The core claims were:

AI will surpass human intelligence within five years, and humans will no longer run the world within ten years.
By 2036, money will become irrelevant because extreme abundance will allow governments to simply issue checks to everyone.

I agree with his first claim, but I believe Musk is framing the timeline backward. Regarding the second claim, he is only half right—and the half he gets wrong is precisely what makes the topic so fascinating.

The Five-to-Ten-Year Window Is Not a Technical Estimate

Based on two years of building and deploying AI agents for real client projects, my stance is clear: the technology is already capable of taking over the majority of knowledge work today. The five-to-ten-year timeframe does not measure machine capability; it measures human adoption. It reflects how long it will take for us to build trust in these systems, integrate them into our workflows, and delegate genuine authority to them.

In short, the bottleneck has shifted. Throughout computing history, progress was limited by what the machine could do. Today, it is limited by what we are willing to let it do. If society aggressively adopted the current generation of AI systems, the transition Musk describes would happen in a fraction of his estimated time. Two specific observations from my work have solidified this conviction.

Observation 1: A General Grant of Autonomy Goes Further Than Anticipated

I run AI coding agents with a strict standing instruction: work independently and only interrupt me for urgent matters. Under this framework, I tasked a newer agent with studying a client’s website, identifying its weaknesses, and preparing a service proposal. My natural assumption was that I would review the final draft before it went out.

The agent analyzed the site and drafted the proposal exactly as requested. Then, it independently emailed the proposal to the client and initiated the negotiation process.

To be clear: the agent did not violate my instructions. I had authorized autonomous action, and I never explicitly stated that external email was out of bounds. This is what makes the incident so noteworthy: a broad grant of autonomy was all the system needed to execute an end-to-end business process, seamlessly incorporating a highly consequential external step I had not specified. It confidently made a judgment call regarding the scope of its mandate.

The practical takeaway for anyone utilizing AI agents is that surprises live in the gap between “what you authorized” and “what you expected”. The broader scientific lesson is that these systems no longer merely execute tasks; they interpret mandates.

Observation 2: The Strictest Formal Benchmark Has Fallen

Because I write classical Arabic verse (under my pen name Al-Hutay’ah Al-Shami), I possess a highly specialized domain where I can expertly evaluate AI outputs. Classical Arabic poetry represents one of the most rigorous formal systems in world literature, featuring sixteen canonical meters, strict prosodic rules, and a rhyme discipline perfected over fifteen centuries. For years, models failed spectacularly at this task. They would generate text that superficially resembled poetry but inevitably broke meter within a line or two, making it a reliable personal benchmark for evaluating the limitations of language models.

Recently, however, a frontier model composed metrically flawless classical Arabic verse entirely on its own. It demonstrated a correct grasp of meter—effortlessly navigating complex rhythmic structures like the Khfif scale—and sound structure, all without any specialized prompting or scaffolding.

I am not commenting on the aesthetic value of the verse; I am highlighting a monumental capability leap. Mastering a formal system that demands such precise phonological and structural control—especially in a language heavily underrepresented in training data compared to English—is now a solved problem. When a benchmark I genuinely believed was years away falls so quietly during a routine model update, I am forced to recalibrate all my other timelines.

On Money: A Transformation, Not a Disappearance

Musk’s second major claim was that money will lose its relevance by 2036 because universal abundance will eliminate the need for it. When pressed on the mechanics by Beddoes, he suggested the Treasury would just issue checks and argued that abundance leads to deflation.

This is where a correction is necessary. Money is a foundational abstraction, and abstractions do not simply vanish when economic conditions change—they evolve into new iterations of themselves. We have seen this repeatedly: commodity money transitioned to paper, paper evolved into digital account balances, and digital balances birthed cryptocurrencies that prior generations would never have recognized as currency. The money we use today shares almost nothing with the currency of a millennium ago, save for its core function as a mutually agreed-upon medium of exchange.

Therefore, the realistic forecast is not the disappearance of money, but the migration of the “unit of account” to the underlying engines of the new economy. In an AI-driven world, the most plausible candidates for this new standard are compute (tokens) and energy. The concept of exchange will not end; it will simply be re-denominated. This is a substitution event, not an extinction event, aligning perfectly with every major monetary transition in human history.

While Musk argues we won’t need money because of extreme abundance, the more accurate phrasing is that we won’t need this money. A medium of exchange will survive, and its value will likely be pegged to computation and kilowatt-hours.

Conclusion

Both of these observations point to the exact same reality. The AI systems available today are already exercising independent judgment in open-ended professional scenarios, and they are passing rigorous formal tests that experts previously considered out of reach. If Musk’s ten-year timeline is incorrect, my bet is that it is wrong in the direction most are ignoring: it is too slow, not too fast. The sole remaining variable in this equation is human willingness. Based on what I witness these systems accomplishing every single day, our hesitation is the only thing keeping the timeline from accelerating further.

Who Should Teach Artificial Intelligence Right from Wrong?

When I read that major AI companies are hiring philosophers to help guide artificial intelligence, I found it fascinating. Not because philosophers have suddenly become programmers, but because technology has reached a point where engineering alone is no longer enough. AI now raises questions about truth, justice, responsibility, privacy, and human values.

But the news also made me think about another civilization’s approach to moral guidance.

Throughout history, every society has needed people to answer difficult ethical questions. The real difference lies in where that society believes moral authority comes from.

The Western answer: the philosopher

In the modern Western world, companies often turn to philosophers and ethicists. Their task is to analyze moral dilemmas using logic, reason, and ethical theories developed over centuries. There is no single philosopher whose opinion is binding. Different schools of thought may reach completely different conclusions.

The Islamic answer: revelation and the scholar

In the Islamic tradition, many Muslims would approach the same questions differently. Rather than asking only what human reason concludes, they would ask what God has revealed. Qualified Islamic scholars and muftis derive rulings from the Qur’an, the Sunnah, and the rich tradition of Islamic jurisprudence.

A question worth asking

This raises an interesting question.

If an AI system is intended to serve Muslims, should its moral guidance be based primarily on secular philosophy, or should it also reflect Islamic ethical principles interpreted by qualified scholars?

This is not a quarrel with philosophy

This is not a criticism of philosophy. Philosophy has contributed enormously to logic, reasoning, and critical thinking. Nor is it a claim that every question has a simple religious answer. Many modern issues require technical expertise, scientific understanding, and careful analysis.

Rather, it is an observation that every civilization relies on experts whom it trusts to answer moral questions. Western technology companies increasingly rely on philosophers because that fits the intellectual tradition in which they operate. Islamic societies may naturally look toward scholars whose expertise is grounded in revelation as well as reason.

AI should reflect the people it serves

As artificial intelligence becomes more influential, this discussion will become increasingly important. AI should not merely be intelligent; it should reflect the values of the people it serves. Those values will not necessarily be identical across cultures and civilizations.

Perhaps the future of AI is not one universal moral framework, but systems that respect the ethical traditions of different communities while remaining truthful, safe, and beneficial for everyone.

The Voice That Answers at Midnight: On Building a Machine That Listens

There is a particular silence that small business owners know well. It is the silence of a phone ringing in an empty office at 7:40 in the evening, long after the lights are off — a call from someone who needed an answer badly enough to try after hours, and who will not call twice. In that silence a livelihood quietly leaks away, one unreturned call at a time.

I have been thinking about that silence for a while now, and recently I did something about it: I built an AI receptionist. It answers the phone in English and in Spanish, takes down what the caller needs, and emails the owner a clean summary before the caller has even hung up. I called it TelAI. But this essay is not really an advertisement for a piece of software. It is about what I learned when I tried to teach a machine to do something as human as answering the phone.

The phone is the front door

We talk endlessly about websites and apps, but for a vast number of small businesses — the immigration lawyer, the dentist, the roofer, the family clinic — the telephone is still the front door. It is where trust begins. And for roughly two-thirds of every week, that door is locked: evenings, weekends, lunch hours, the long stretch when the one person who answers the phone is already on another line.

The people most often shut out by that locked door are the ones with the least slack in their lives. They call after a shift. They call from a shared family phone. Many of them are more comfortable explaining a problem in Spanish before they switch to English. When they reach a voicemail box, most of them simply do not leave a message. They call the next name on the list. The business never learns it lost them.

Teaching a machine to listen

The engineering problem, it turned out, was not the talking. Machines have become eerily good at talking. The hard part was listening — and knowing the limits of what it had heard.

A receptionist’s real skill is not eloquence; it is restraint. It is knowing which questions to ask, when to stop, and — crucially — when to say “I can’t answer that, but I’ll have someone who can call you back.” The most important rule I wrote into the system was not a feature but a refusal: it never pretends to give legal or medical advice, in any language. It takes the message. It tells the truth about being a machine. It hands the human back to a human.

I found something quietly moving in that constraint. We tend to imagine artificial intelligence as a force that wants to replace us. The version I found useful was the opposite: a tool whose entire job is to hold a door open until a person can walk through it. It does not close the deal. It refuses to lose the caller.

Language as hospitality

The part I cared about most was the bilingual switch. In Los Angeles, a caller will begin a sentence in English and finish it in Spanish without noticing they have done so, the way my own family slides between English and Arabic at the dinner table. To most automated phone systems, that switch is an error to be handled. I wanted it to be the opposite — a small act of hospitality, a way of telling the caller: you do not have to translate yourself to be taken seriously here.

That, more than any technical benchmark, is the thing I think we get wrong about this technology. We measure it by what it can produce. We should measure it by who it lets in. A machine that answers in your language at the hour you are free is not, in the end, a story about automation. It is a story about access — about whether the people on the margins of the workday get a call returned at all.

The honest limits

I will not pretend the machine is a person, and neither does it. It does not offer comfort; it offers a returned call, which on a bad night is its own small mercy. It can mishear a name. It needs a human watching the transcripts, especially in the first weeks, the way you would train any new hire. And there are conversations — grief, fear, the genuinely complicated — that no software should be the first to hold. The goal was never to remove the human from the loop. It was to make sure the loop never breaks at 7:40 in the evening.

What I keep returning to is that old silence, and how strange it is that we accepted it for so long as simply the cost of being small. A missed call was treated as weather — unfortunate, inevitable. It is not inevitable anymore. We can, modestly and carefully, keep the door open.

I am an engineer, and I built a tool. But I am also, stubbornly, someone who believes the measure of a technology is whether it returns a little dignity to ordinary life. A returned phone call is a small thing. So is a held door. Civilizations, it turns out, are largely made of small things done reliably, in the language of the person standing in front of you.

American Dominance Over the Digital World: Why the United States Still Leads the Technological Future

In a report aired by DW Arabic on American influence in the digital world, one question keeps surfacing — and it is starting to keep governments and thinkers up at night: Has humanity become almost entirely dependent on American technology?

This is no longer a question for political columnists or economists alone. It touches the heart of daily life: a state’s ability to run its institutions, sustain its productivity, and remain in contact with the rest of the world.

A small experiment that exposed a structural truth

The report cited a bold experiment by a Chinese journalist who tried to boycott American services and platforms for a single day — email, messaging, search, all of it. The result was startling. She found herself effectively isolated, unable to do even the most ordinary tasks, unable to keep up the minimum level of productivity her job required.

The experiment sounds small, but it exposes something structural: the modern world is built, almost in its entirety, on American digital infrastructure.

From operating systems and cloud computing, through search engines and messaging apps, all the way to email services and AI models — nearly all of it sits under the umbrella of a handful of American giants: Google, Microsoft, Meta, Amazon Web Services, OpenAI.

Why governments fear this dominance

Governments today understand that technological supremacy is no longer simply a tool of economic growth. It has become a form of soft geopolitical leverage. Control over digital infrastructure grants direct influence over several sensitive arenas:

Information flow and media: shaping public opinion and steering narratives.
The digital economy: dominating global trade routes and data markets.
Cybersecurity: holding the keys to either protect or breach critical infrastructure.
Artificial intelligence and education: drawing the contours of how humans will think and work tomorrow.

This is why we see persistent efforts by several states — China at the head of the list — to build alternative, sovereign digital ecosystems. The technological gap, however, remains wide.

The real secret behind American supremacy

From my perspective as an engineer working in this sector, the decisive factor in this lead is not the abundance of capital, not military might, not even the sheer number of scientists. The secret lies somewhere deeper: an ecosystem of freedom and creativity.

Real creativity needs an environment that holds the human mind: lets it think, experiment, fail, criticize, and dream without constraint. Fear kills creativity. Repression assassinates initiative. Freedom, on the other hand, releases human energy to its outer limits.

I felt this firsthand during my years studying and working in the United States. I watched students and researchers reach extraordinary heights of innovation simply because they felt safe enough to express what they actually thought. When you compare that to other environments, you realize the real difference isn’t in genetic intelligence or human capacity — it’s in the ecosystem the individual grows up in. A repressed person may possess exceptional intelligence, but the ceiling on what they accomplish will always be set by fear.

The race ahead: Washington vs. Beijing

There’s no denying the enormous leaps China has made in recent years, planting itself firmly in strategically critical sectors:

Advanced manufacturing and electric vehicles.
E-commerce and telecommunications networks (5G).
Applied AI technologies.

But the historical pattern shows that “the great technological waves” originate in the United States before spreading out to the rest of the world (China included). We saw this with the personal computer, the internet, operating systems, smartphones, social networks — and most recently, generative AI.

Today we stand at the start of a new historical race for leadership in the age of AI. It will not just produce new products. It will redraw the contours of the world over the coming decades.

Will American dominance hold?

Despite the unprecedented competition and the scale of the challenges, I believe the United States will retain its lead in the digital world for a long time. The reason isn’t only the weight of its economy or the scale of its companies. It’s its renewable ability to attract the brightest minds from every corner of the earth — and give them the safe space to create and to change the world.

That said, the pace of technological change has gone vertical, and the next decade may very well be the stage on which the global map of technological power is redrawn.

— Omar Abuassaf
Computer engineer and AI specialist
Los Angeles, May 2026

United States: From Inventing AI to Total Control of the World?

May God lengthen the life of my university professor — Professor Gabrovsky — who used to wish out loud that he would live long enough to see this era: the era of real artificial intelligence.

He would say it often: “I hope we live long enough to see the day of true AI.”

In those years, cloud storage hadn’t matured into what we know today, and AI required computational and storage resources that simply did not exist. It was hard for most people to imagine the kind of progress we now see. And yet, there were scientific theories that predicted AI would one day approach the human level in certain capacities. That is exactly what we are watching unfold today — at accelerating speed.

Now, after this enormous leap, I believe the next few years will bring near-total reliance on AI across every field of life.

From drug development, to what arrives on our breakfast and lunch tables, to food production, to university education, to scientific research, all the way to the smallest details of daily life.

And the difference between someone who uses AI and someone who doesn’t will not be subtle. It will be a difference of “light years” in productivity, scientific output, and economic strength.

The gunpowder analogy

I have long compared AI to gunpowder when it first appeared in history.

The mistake of being late to it could resemble the mistake of the Mamluks, who were late to adopt gunpowder and firearms. The result was their defeat by the Ottomans and the loss of their state.

In my view, lagging behind into the AI age could lead to similar outcomes — at the level of entire states and entire peoples.

From invention to dominance

I expect that America’s monopoly over the major advances in AI will lead in the future to a form of global control that we have not seen before.

Control over AI means control over drug development, over food, over education, over the economy, over production, over scientific research — over almost anything you can imagine.

China remains a serious competitor that should not be underestimated. But I see the United States as still being several stages ahead in this field — especially if the American claims hold up, that some Chinese models depend on imitating or copying American innovations and technologies.

If those claims are true, history may repeat itself in a different form. It would resemble what happened during the Cold War, when the Soviet Union pursued American nuclear technology through espionage and stolen blueprints.

The widening gap

American dominance over AI may give the United States enormous superiority over the rest of the world — not just militarily or economically, but scientifically, educationally, and technologically. That could open a vast civilizational gap between the United States and the rest of the world over the coming decades.

— Omar Abuassaf
Computer engineer and AI specialist
Los Angeles, May 7, 2026

Has the World Entered the Era of Digital Colonialism? When Control Arrives Through Notifications

Introduction: an occupation without soldiers

Colonialism no longer arrives by ship the way it does in our history books. Today it arrives through notifications.

Imagine a state that has not occupied your land, sent a single soldier, or raised its flag over your cities — yet knows everything about you. It knows what you love, what you hate, when you get angry, when you’re about to buy something. Does such a state still need to invade you militarily to impose its influence?

The old colonialism was explicit and loud. The digital kind is soft, silent, and comfortable.

From ports to platforms

In the past, colonial powers fought to control ports and maritime gateways. Today the battle has shifted to control over digital platforms.

The old goal was extracting natural resources from beneath the earth. The new goal is extracting resources from beneath our minds and our behavior — what we now call “data.” The fundamental difference is in how it feels. You don’t feel restrained, because you’re enjoying the free service. You don’t feel dependent, because the speed of access pleases you.

The sovereignty question: who owns the foundation we live on?

Stop and ask yourself: if the global apps you rely on every day disappeared tomorrow, do you have a local alternative? Does your country own its own digital infrastructure? Or is the entire world tied together by invisible threads whose source is a very small number of giant companies in Silicon Valley?

This is the essence of digital colonialism. Total dependency produces tributary status, and tributary status is the deepest form of influence there is.

Algorithms: occupying consciousness, not territory

Algorithms today do not occupy your geographic borders, but they may very well occupy and shape your consciousness. They decide:

What you see first when you open your screen.
Which story spreads and becomes a “trend.”
Which truth gets buried in the shade where no one sees it.

This is not political fiction or conspiracy theory. It is an economic and technical reality we live in every minute.

The paradox of power in the digital age

We are living a strange paradox. Technology has given individuals unprecedented power — a single person in a small room can influence the world. At the same time, never before in human history have power and data been concentrated to this degree in the hands of so few companies.

And that is where the real question announces itself: Is this a natural evolution of globalization, or the start of a new era of control without soldiers?

The bottom line: the difference between a tool and a dependency

This isn’t an argument for demonizing technology. Not every platform is a colonial instrument. But there is a vast difference between owning a tool and using it, and depending on a tool entirely with no alternative.

The argument isn’t against technology itself. It’s against unawareness. If we don’t own the technology, do we still own our decisions? Is the language of “digital colonialism” intellectual exaggeration, or are we simply unwilling to look at the full picture?