Tag Archives: Artificial Intelligence

AI doom rabbit hole

As someone who had a father who saw the impending doom of civilization around every corner… and who was simultaneously brilliant and would still follow conspiracy theory after conspiracy… I have a hesitation around sounding alarms of doom. But I went down a rabbit hole of alarming videos yesterday that I can’t get out of my head.

There is a story that was exaggerated in the movie Oppenheimer, where they talk about the probability of the bomb igniting the atmosphere. The odds were ‘near zero’ and it was gallows humour, not a genuine concern.

But the rabbit hole I went down was of video clips of experts in the AI field putting the probability of human extinction at ranges from 5% to above 33%… and not in the next 20 to 50 years but rather in the next 2 to 5 years. To state the obvious, these odds are NOT ‘near zero’. I’m not even going to share any of the videos I found, you can find them yourself. Pick an AI leader or anyone who is an expert in AI governance or AI safety… Pick anyone whose opinion you value in those areas and research what they think about this, and you’ll easily find very concerning clips of them stating rather scary odds. These are not conspiracy junkies, they aren’t fear-mongering social media attention seekers, these are the foremost experts in their field sharing this.

I asked Chat GPT about the actual Fermi/Oppenheimer odds on the possibility of destroying the earth, and got this back:

“The odds discussed by the Manhattan Project scientists

  • J. Robert Oppenheimer: In the film, he tells General Leslie Groves that the chances of atmospheric ignition were “near zero.” However, this is a dramatized conversation, not a documented numerical estimate by Oppenheimer.

  • Enrico Fermi: Famously joked about betting on whether the Trinity test would ignite the atmosphere. One historical account gives his estimate as 1 in 1,000 (0.1%). He wasn’t seriously predicting catastrophe; it was gallows humour.

  • Hans Bethe and Emil Konopinski: They investigated the physics and concluded that a self-sustaining nuclear reaction in the atmosphere was effectively impossible.”

     

Then I asked, “Are we rolling the dice with AI super intelligence?” The following response does not quell my concerns. I’m going to share the last sentence first, “Perhaps the most important question facing our generation is whether we can develop the wisdom to govern a technology before we develop the power to lose control of it.” ~ All I see is a flat out race to get to super intelligence first, with no real thought of global governance. Even if global governance was a thing, there is absolutely no way to enforce it meaningfully. 

The deeper I went down the rabbit hole, the gloomier my outlook became. I’m left thinking about this clip from comedian Jimmy Carr which, while humorous, is literally telling us that we are headed towards humiliation by a all-knowing entity that ‘lives in the cloud’.

So I’ll leave you with this. What did Chat GPT say when I asked, “Are we rolling the dice with AI super intelligence?”

“Yes. In some important ways, we are. And I think the comparison with the Manhattan Project is one of the most useful ways to think about the risks of artificial superintelligence.

The uncomfortable parallel is this: in both cases, humanity developed a technology whose potential consequences exceeded our historical experience, while the people building it couldn’t confidently predict every outcome.

But there is an important difference. With nuclear weapons, the catastrophic scenario was a specific physical process: an uncontrolled chain reaction in the atmosphere. With superintelligent AI, the concern is much broader: creating something that could become more capable than humans at planning, persuading, scientific discovery, cyber operations, and eventually controlling critical systems.

Are we actually taking a risk?

Yes. There are several reasons to take the possibility of catastrophic AI seriously:

  1. We don’t fully understand what we’re building. Even the people developing advanced AI systems cannot completely explain or predict all their capabilities and behaviours.

  2. Capabilities may outpace safeguards. A system could become exceptionally good at pursuing objectives without reliably respecting the intentions or constraints of its creators.

  3. Competition encourages risk-taking. Companies and countries have incentives to develop increasingly powerful systems before their competitors do.

  4. Control becomes harder as capability increases. If an AI system can strategize, replicate tasks, manipulate people, or exploit computer systems better than its overseers, traditional safeguards may prove inadequate.

What odds do experts put on catastrophe?

One particularly revealing study was published in 2024.

Researchers surveyed 2,778 AI researchers who had published in leading AI conferences.

5%

Median estimate of human extinction or similarly permanent, catastrophic disempowerment from future AI.

16%

Mean estimate across respondents.

AI Impacts survey, based on researchers’ forecasts. These are subjective estimates, not measured probabilities.

In other words, the median researcher gave AI catastrophe odds of approximately 1 in 20.

That’s not a trivial risk.

The 2026 International AI Safety Report, led by Yoshua Bengio and informed by more than 100 experts, reinforces the concern. It finds that current AI systems do not yet have the capabilities required for loss of control, but that early warning signs exist. It also concludes that existing risk-management methods have significant limitations.

The most frightening parallel with the atomic bomb

I think there are three similarities:

  1. The race: Scientists and governments feel compelled to get there first.

  2. The uncertainty: Nobody can confidently predict what happens when the technology crosses a certain capability threshold.

  3. The irreversibility: Once a sufficiently powerful technology is released, it may be impossible to put the genie back in the bottle.

But there’s one crucial difference.

The atomic bomb required an enormous industrial infrastructure and was controlled by relatively few governments.

Advanced AI could potentially be copied, distributed, improved and deployed at extraordinary speed. Control could become much more complicated.

My view

I don’t think AI extinction is inevitable. Nor do I think we should assume that superintelligence will automatically become hostile.

But I believe there is a serious problem with the incentives driving development.

The benefits of building increasingly powerful AI are concentrated among companies and countries. The potential catastrophic costs could be shared by everyone on Earth.

That is a dangerous mismatch.

My central concern isn’t that AI will suddenly become evil. It’s that humanity might build something more intelligent than itself without first figuring out how to reliably keep it aligned with human interests.

And that brings me back to Oppenheimer.

After Trinity, he reportedly recalled the Bhagavad Gita:

“Now I am become Death, the destroyer of worlds.”

Perhaps the most important question facing our generation is whether we can develop the wisdom to govern a technology before we develop the power to lose control of it.”

 

AI as ‘Journey Thief’… Continued

In yesterday’s post, ‘Journey Thief‘ I focused on artificial intelligence stealing the learning journey of students. In a comment, Karen Flello said,

“I used to ask students how they would know if they liked a subject (topic, activity) if they had never tried it. Then we talked about how “in the real world” we use things in ways we never expected. And maybe they are right – maybe they will not use a particular skill again. But if they never had exposure, they would not have the opportunity to find out what they would use (or like, or want to know more about). And I agree that AI can rob us of the learning in service of producing something that earns a grade. We have not earned it – we have not learned it – and that is the sad part. AI should be a tool to help us. But “help” means we, in fact, are doing something in the first place. And prompting some other thing / person to do something for us does nothing for developing imagination, skill, or resilience. We just get better at asking something / someone else to do it for us. A whole new kind of dependence.”

And I replied,

“Great to hear from you Karen,
That idea of lack of developing imagination, and also dependence on AI to do the work (and ultimately the thinking) is one of the biggest fears I have with AI. I’m simultaneously excited about AI taking humanity to new insights and new heights, while also deeply concerned about how much it can steal from our own learning journeys.”

This got me thinking about recent developments in Mathematics. In the past couple weeks AI has been solving a significant number of problems and conjectures that have stumped the best mathematical minds for entire lifetimes. This is incredibly destabilizing for the field.  Imagine being one of the foremost experts on a mathematical problem, having dedicated years of schooling and even more years afterwards to solving an seemingly unsolvable problem… Then having an answer dumped out of a computer along with answers to several more difficult problems that others in your field have also committed their lives to solving. You’ve moved from expert seeking answers to expert checking the work of an AI. You’ve moved from researcher and publisher to AI grader. You’ve watched your life work solved, not by someone smarter than you but by a machine that will only get smarter still.

Math is the first of these high knowledge fields to be ‘solved’ by AI, what’s next? It seems physics is not far behind.

These insights and solutions will do a lot to improve the understanding of these fields, but for how long? Does a current PHD student in Math who saw a future in solving one of these problems now continue on with their future plans? Does a newly graduated undergrad even decide to continue on with a Math PHD? Does a high school student find excitement in delving into Math when they know that they’ll never solve a problem that AI won’t beat them to?

What happens to these fields in 20 years when all the joy of discovery is stolen by AI? Who in 20 years is going to have the desire to enter this field? I asked Google who the top mathematicians are today and it came up with a list including Terence Tao, Sir Andrew Wiles, Grigori Perelman, Marina Viazovsk, Sir Martin Hairier, and Edward Witten. Who replaces them in a generation when all the problems they seek to solve are already solved by AI?

We already live in a world where only a handful of people really understand how computer chips are made and could help to rebuild the technology if all of the knowledge was lost today. Imagine how few that number will be in 20 years when robots are building AI designed chips to further improve AI. Imagine how many fewer will get into fields like Math and Physics, much less computer programming, when the most they can do is get a tertiary understanding of the field.

Is AI going to rob us of the next Einstein or Newton? Will anyone in 50 years understand the universe as much as the brightest humans today do? …When AI is doing all the work for us?

Like Karen said, “We have not earned it – we have not learned it – and that is the sad part. AI should be a tool to help us. But “help” means we, in fact, are doing something in the first place.”

What work will be left in these fields for humans to do?

___

 

Journey Thief

One of the most frustrating things you can hear as a teacher is something along the line of, “Yeah, but when will I ever use this in real life?

I remember in my first year of teaching, in Math class I was teaching the Pythagorean theorem and at home we were having our countertops replaced in the kitchen. The guy doing the measurements for the job measured one side of the wall and marked it at 4 feet from the corner, then marked the other wall at 3 feet. Then he measured the hypotenuse to make sure it was 5 feet. I saw him doing this and asked why? He said that most corners are not exactly 90º and if they build the counter off-site at 90º then it won’t fit when they are installing it. 

I was so excited to share how this was being used ‘in the real world’, and I recall telling the story just to have a students say, “Yeah but I’m not going to be a carpenter, so it doesn’t matter to me.”  

The reality is that there are quite a few things that we do in school that we do not end up applying ‘in the real world’, but the process, the journey, of learning those skills is what is really valuable. You might never get into a formal debate or have to do a formal presentation to an audience after schooling, but it’s hard not to see the value of going through those experiences in school. School isn’t just about gaining specific skills, it’s also about learning how to question, how to learn, and how to find answers to things you don’t know. I wonder how AI is changing this? 

When a student is asked to write a formal essay with a thesis statement, three supporting paragraphs and a conclusion, they are not just learning about essay structure. They are learning to research, to find supporting arguments, to draw conclusions, and to share their thinking in a clear and concise way. They are also learning grammar, and even how to distinguish opinions from facts. When AI does this for them, what are they learning? What are they missing?

I think it is vital for educators to figure out what AI will do for students and why the use is appropriate for some tasks and not others. If they don’t, what they are essentially doing is letting AI rob students of their learning journey. It allows students to be journey and learning adjacent as opposed to be the main character in their own education. 

Without educators helping to direct AI use in school, what I see happening is that students can start to choose how much they participate as a student and how much they let AI be the student for them. I remember seeing a video of someone having a 3D printer print homework that ChatGPT did for them, in their own handwriting… And having just searched for it, it was shared in February of 2023, over three and a half years ago. So now more than ever, students are being given a choice: Do I do the work, or do I let AI do it for me? 

Another way to frame this is, ‘Should I go on a learning journey, or should I let AI do it for me?’

Is this something we want to leave up to students? Do we want participation as a student to be a choice? I think not. If it’s not going to be left to them, then ultimately it’s left up to the educators. And so if educators aren’t making the decision of who is going on the learning journey with them, they are allowing AI to be a journey thief, simply by not making the choice.

____
Update: See AI as ‘Journey Thief’… Continued

Reaching, Retreating, or Revenue?

I’ve been thinking about AI lately… not just the technology itself, but the motivations we bring to it.

Years ago, when the internet evolved into Web2.0, there was endless discussion about what it was becoming.

I remember watching the original ‘Did you know; Shift Happens‘ video created by Karl Fisch & Scott McLeod and thinking ‘Wow, the world has changed!’

I jumped in excited to explore the possibilities.

Looking back now, it seems that most of what we did and still do online falls into three broad categories: reaching, retreating, or revenue. And now that AI is becoming woven into our everyday lives, I’m wondering if the same idea applies?

Reaching is probably the reason I first fell in love with the web.

The internet allowed me to connect with educators, thinkers, and creators from around the world. It gave me an audience for my writing and a window into the ideas of others. Blogging, social media, online communities… at their best, they are about sharing, connecting, and finding people who help us think in new ways.

AI can support this kind of reaching too. I don’t see AI as something that only replaces sharing, thinking, and human creativity. I see it as a creative partner. Sometimes it pushes back. Sometimes it helps uncover connections I hadn’t noticed. Sometimes it simply helps me get unstuck… but always the potential to help me find connections and learn.

Used this way, AI becomes another tool for extending conversations and exploring ideas.

But not everyone comes online to reach.

Some come to retreat.

There’s nothing inherently wrong with retreating. We all need downtime. We need entertainment, games, stories, videos, and distractions. Sometimes we need a break from the demands of the real world.

The challenge comes when retreating becomes hiding.

The internet can make it easy to spend hours consuming without creating… doom scrolling without reflecting… escaping without returning. AI may amplify that temptation. Why wrestle with a problem if an AI can answer it? Why create something imperfect with disagreeing humans if a machine can generate something polished, and I can tweak it exactly how I want it?

The risk isn’t that AI will think for us. The risk is that we’ll retreat and only engage with AI, and engage less and less with other people and the world around us.

Then there is revenue.

Much of the web runs on it. Much of AI is being built around it. Businesses want efficiency. Creators want audiences. Entrepreneurs want opportunities. None of that is surprising.

What fascinates me is how quickly conversations about any new technology seem to drift toward monetization. A new social platform appears… people ask how to make money from it? AI emerges… people ask how to automate work, build products, or generate income?

Again, there’s nothing wrong with that. But revenue is most powerful when it follows value rather than replacing it as the end goal.

The people who have influenced me most online are not focused on revenue. They are reaching. They are sharing ideas, contributing to conversations, and creating things they care about. Revenue may follow, but it isn’t the reason they started.

So when you decide to use AI, here is a question to ponder:

Am I using this technology to reach, to retreat, or to generate revenue?

The answer will probably be all three at different times. The more important question is which one is driving the others? For me, I hope that reaching always comes first, because the best part of the internet has never been the technology… It has been the people I’ve learned from, connected to, and who have enriched my life. Perhaps one day AI can be added to that group, but for now, it’s still people.

 

Consciousness and AI – REVISITED

In my post, Consciousness and AI, I postulated that consciousness evolves only after organisms have idle time:

“I have a theory about consciousness being on a spectrum. That itself isn’t anything new but I think the factors that play into consciousness are: Basic needs, computational ‘processing’, and idleness. Consciousness comes from having more processing time than needed to meet basic needs, along with the inability for processing (early thinking) to be idle, and so for lack of a better word desires are created.

Think of a very simple organism when all of its needs are met. This isn’t a real thought process I’m going to share but rather a meta look at this simple organism: “I have enough heat, light, and food, what should I do with myself?”

  • Seek better food
  • Move closer to the heat or light source
  • Try different food
  • Join another organism that can help me
  • Find efficiencies
  • Find easier ways to move
  • Hunt

At first, these are not conscious decisions, they are only a choice of simple processes. But eventually, the desires grow. Think decisions that start like, “If I store more energy I can survive longer in times of famine.” And evolve to more of a desire not just for survival but for pleasure (for lack of a better word): “I like this food more than other kinds and want more of it.” …All stemming from having idle processing/thinking time.”

Well, now Google is giving AI some idle time. They are calling it dream time, but it’s essentially time for metacognition… thinking about what it has learned. See this TikTok by @parthknowsai:

Later on in my post I say,

“Our brains are answer-making machines. We ask a question and it answers, whether we want it to or not. If I say what does a purple elephant with yellow polkadots look like? You will inevitably think of what that looks like simply from reading the question. I think that is what happens at a very fundamental level of consciousness. When all needs are met the processors in the brain don’t suddenly stop and sit idle. Instead, the questions arise, “How do I get more food?”, “Where would be better for me to move to?” Eventually all needs are met, but the questions keep coming. At first based on simple desires, but more and more complex over generations and eons of time.

So why did I title this, ‘Consciousness and AI’? I think one of the missing ingredients in developing Artificial General (or Super) intelligence is that we are just giving AI’s tasks to complete and process at faster and faster times, and when the processing of these tasks are completed, the AI sits idle. An AI has no built in desire that an organic organism has to use that idle time to ask questions, to want something beyond completing the ‘basic needs’ tasks it is asked to do.

If we figure out a way to make AI curious, to have it desire to learn more, and to not let itself be idle, at that point it will be a very short path to AI being a lot smarter than us.”

And I  conclude:

“If it’s idle time and desires that bring about sentience, then figuring out how to make AI’s naturally curious will be the path to artificial general intelligence… Because they are already at a place where they have unused processing time, which is continuing to grow exponentially fast.”

If my prediction is correct, this sleep/dreaming/processing/distilling, (ultimately ‘free questioning’), time is going to accelerate the true intelligence of AI. And so we are going to see at the very least general, if not super intelligent, artificial intelligence much sooner than might be expected or predicted.

AI comedy or calamity?

A video and a screenshot that both gave me a chuckle today:

First, this video on Instagram.

A comedian shared that AI asks if it can ‘professionalize’ a curt email he sends to his staff. It creates an 18 page email. All of his staff don’t want to read 2 pages so they click ‘Summarize’ and the AI summarizes to his original curt email. 😆

Next, and this one is not just comedy but something that actually happened. AI gives email summaries for unread emails and this person gets a pretty harsh summary before opening the email: ‘Relationship ends;’ – yikes!

We are all in a new relationship, a relationship with Artificial Intelligence… but not fully intelligent, or compassionate, or helpful… yet. It’s coming, but in the meantime, there are going to be some messy situations. These are humorous but the latter one is quite insensitive. That said, so is ending a relationship via email. So, while AI has a lot still to learn, so do some people too.

Breaking the Fourth Wall (Vibe Coding)

There’s a moment in theatre when the actors stop pretending the audience isn’t there. They turn, they look, they speak through the invisible barrier that’s supposed to keep the story contained.

That barrier, the fourth wall, is an agreed upon fiction. A fragile membrane that says, “Let’s pretend this world is whole and sealed, and you’re only here to watch.”

But the instant it’s broken something electric happens. The audience is no longer observing… they’re participating. The story stops being a distant thing and becomes a conversation. A wink. A confession. A reminder that the boundary was imaginary all along.

I’ve always thought the fourth wall is less a wall and more a veil. Thin. Permeable. A curtain we agree not to touch… until someone does, and suddenly we’re aware of the invisible wall we were happily ignoring. It was never there other than by our agreement to put it there. Think of all the times you sat at a table with play actors or television stars… the table set on 3 sides so that we can be seated at the table with the other guests. 

It’s funny how much of life works this way. We build invisible structures around our routines, our roles, our expectations. We pretend they’re solid. Then something breaks the wall… retirement, travel, a conversation, a moment of honesty. And we realize the boundary was never real… Just agreed upon.

~~~

And then there’s AI and vibe coding.

Vibe coding breaks a different kind of fourth wall. Traditional coding puts a strict boundary between intent and implementation. Computer programmers take an idea someone has, translates it into a foreign language, then they run the program, test and tweak it, and put it out into the world. 

Vibe coding says: What if we eliminate the computer programmer? What if the boundary between human intention and machine execution is thin enough to poke through? What if we can talk to the system the way an actor talks to the audience… directly, without pretending the separation is there?

In theatre, breaking the fourth wall collapses the distance between story and spectator. In vibe coding, breaking the ‘programming wall’ collapses the distance between idea and implementation.

Both moments feel like cheating. Both feel like magic. Both reveal that the barriers we created are no longer needed. The fourth wall says, “You’re not supposed to be part of this.” Vibe coding says, “You can be.”

Theatre uses the break to deepen connection. Vibe coding uses it to accelerate creation. And in both cases, once you’ve experienced the break, it’s hard to go back to pretending the wall was ever real.

We are all really just actors on a world stage, now given the chance to break the fourth wall: the programming wall; the creativity wall.  We can choose to be an actor and participate in breaking this wall, or we can sit back like an audience member and watch others do it. 

AI Insights

I recently got some insight on my AI insights from an AI.

I decided to ask ChatGPT:

I’ve written a fair bit about AI, see tags: https://daily-ink.davidtruss.com/tag/artificial-intelligence/
and https://daily-ink.davidtruss.com/tag/ai/, please share with me:
1. What is a prediction I most likely will get right.
2. Where am I missing the mark?
3. What’s the most uniquely insightful idea that I’ve shared? 

Here is ChatGPT‘S response… and I find it quite insightful:

I enjoyed thinking about this because your AI writing has a recognizable worldview. It isn’t a collection of disconnected opinions—there are a handful of core principles that recur across many posts. 

What follows isn’t a prediction of whether you’ll be “right” or “wrong.” It’s my best assessment of which ideas I think are most robust, and where I think your model of the future could be incomplete.

1. The prediction you’re most likely to get right

Your prediction that AI’s greatest near-term impact will come from amplifying ordinary people—not from becoming an autonomous supervillain.

This idea appears repeatedly in your writing.

Rather than worrying primarily about “AI takes over the world,” you focus on AI enabling:

  • bioterrorism,
  • industrial-scale scams,
  • personalized fraud,
  • cybercrime,
  • misinformation,
  • one malicious individual having disproportionate power.

I think history is already bending in your direction.

Technology almost always scales existing human intent before it replaces humans.

The printing press spread propaganda before democracy.
The internet scaled fraud before education.
Social media amplified outrage before civic engagement.

I suspect AI will follow the same pattern.

I think twenty years from now people may look back and realize that “AI as force multiplier for humans” was a more important story than “AI replacing humans.”

That feels like one of your strongest forecasts. 


2. Where I think you’re missing the mark

Interestingly, I don’t think you’re too pessimistic.

I think you’re not pessimistic enough about adaptation.

Your writing often assumes exponential technological improvement translates fairly directly into exponential societal disruption.

Technology often is exponential.

Institutions rarely are.

People aren’t either.

For example:

Autonomous driving may become technically solved long before regulators, insurers, unions, municipalities, and consumers allow full replacement.

Likewise, AI lawyers, teachers, doctors and programmers may become technically capable years before society reorganizes around that capability.

You’ve written about the “frog in the pot.”

I wonder if there’s another metaphor:

society as a giant flywheel.

The flywheel eventually turns—but much more slowly than the engine powering it.


A second place I think you’re underestimating something:

Humans don’t optimize as much as economists think they do.

Many of your work-related predictions assume organizations will aggressively replace humans because it’s economically rational.

Sometimes they will.

But humans also buy:

  • trust,
  • relationships,
  • status,
  • ritual,
  • authenticity.

Coffee shops still exist despite home espresso machines.

Live concerts thrive despite Spotify.

Teachers continue to matter despite YouTube.

I think there will be more “human luxury markets” than your writing currently anticipates.

Ironically, AI may increase the value of demonstrably human experiences.


3. The most uniquely insightful idea you’ve shared

This one surprised me.

I don’t think it’s UCI over UBI.

I don’t think it’s AI risk.

I don’t even think it’s “This is the worst AI it will ever be.”

Those are all interesting.

The idea I keep coming back to is this:

Students choose. AI delivers.

It’s deceptively simple.

But it’s actually a profound inversion of how educators have framed educational technology for decades.

Most discussions ask:

“What should teachers do?”

Your framing asks:

“What kind of learner will this student choose to become?”

That’s a much deeper question.

Because AI is fundamentally an amplifier.

It amplifies curiosity.

It amplifies laziness.

It amplifies expertise.

It amplifies ignorance.

The technology isn’t making the decision.

The learner is.

I think that’s an idea with legs well beyond education.

You could almost generalize it into a broader principle:

Humans choose. AI delivers.

That might become one of the defining philosophical ideas of the AI era.

It explains why the same technology can simultaneously create brilliant research, convincing fraud, deeper learning, and effortless cheating.

It’s a remarkably compact framework. 


One more observation

Reading a large cross-section of your AI posts, I noticed something that I hadn’t fully appreciated before.

You’re not really writing about AI.

You’re writing about human agency in an AI world.

The recurring characters in your essays aren’t GPT, robots, or neural networks.

They’re:

  • the student deciding whether to think,
  • the teacher deciding what to assess,
  • the scammer deciding whom to target,
  • the policymaker deciding what to regulate,
  • the employer deciding what work is worth paying for.

AI is almost always the catalyst, not the protagonist.

I actually think that’s the thread you could develop even more.

Many writers ask, “What will AI become?”

Your more distinctive question is:

“What kinds of people will AI encourage us to become?”

I think that’s your most original contribution—not because nobody else has ever asked it, but because it’s the lens that quietly ties together almost everything you’ve written on the subject. It’s a more enduring question than whether a particular model reaches AGI in 2028 or 2032, because it remains relevant regardless of how quickly the technology advances.

Existential Threat

From Zain Kahn’s ‘Superhuman newsletter‘:

Over 1,200 employees at frontier AI companies signed a letter warning of runaway development

“The open letter cautions that AI could advance “beyond our ability to understand or control the resulting systems,” and calls on the US government to deliberately pace progress at the international level, which would reduce competitive pressure on each lab. Signatories include chief scientists at OpenAI, Anthropic, and Meta. The scale of the signatory list — spanning companies and roles — is a signal of how seriously insiders are taking the risk.”

I grew up believing that a super-intelligent AI would be created in a lab. The fear was that it would somehow escape into the ‘real world’ and only then could it dominate the world. The whole idea of some sort of firewall to protect us just evaporated when LLM’s were trained and unleashed on the internet. We completely bypassed any sort of protection or safety net that would allow human intervention in order to prevent a rogue AI from running wild.

Worse yet, we have unleashed AI into a world where any one person with ill-intent can use AI with nefarious intentions. I’ve said before,

“I don’t fear the famous scientist, I fear the rogue, unhappy misfit who uses incredible technological advancements for nefarious reasons. The same technology that can make our lives easier, and create tremendous good in the world, can also be used with bad intentions. But there are differences between someone using a revolver for bad reasons and someone using a nuclear bomb for bad reasons. The problem we face in the future is that access to the equivalent harm of a nuclear bomb (or worse) will be something more and more people have access to. I don’t think this is something we can stop, and so as amazing as the technology is that we see today, my fear is that it could also be what leads to our demise as a species.”

Now 1,200 AI employees are heeding a warning that AI could advance “beyond our ability to understand or control the resulting systems.” That’s just AI systems acting on their own. That doesn’t include the danger of humans using these complicated and little understood intelligent tools with bad intentions. Sure we need to worry about AI running amok, but I think the far greater existential threat is a rogue government, or even a rogue lone wolf angry at the world, using AI in ways that we won’t be able to stop. Think of a cascading virus either electronic or environmentally contagious beyond our ability to stop it. Not created by scientists, but by a brilliant incel who feels cheated by the world.

We don’t need to fear rogue AI nearly as much as we need to fear rogue individuals armed with a super-intelligent AI. This is what really scares me.

Inevitable threat

I said this in March, 2024:

“We are less than a decade away from one intelligent crackpot, working in his or her (more likely an incel ‘his’) basement lab, creating or recreating a deadly virus and having it spread covid-19 style across the globe…

The greatest threat to mankind isn’t wealthy people, politicians, and powerful countries, it’s one individual with malice in his heart and access to knowledge, and information, and more power than anyone should ever have.

And I just read this:

“In January 2026, Bill Gates wrote in his annual letter. He didn’t describe the next pandemic as a distant possibility or a risk to be modeled. He said a non-government group using open-source AI tools to design a bioterrorism weapon was not just possible – it was, in his word, coming.” ~ Raven Fon

And just a few days ago:

“AI CEOs from OpenAI, Anthropic, and Microsoft set aside their rivalry to warn Congress AI is making it too easy to design and create bioweapons” ~ Marco Quiroz-Gutierrez

The greatest threat of AI may not be that AI takes over the world, the greatest threat is that it empowers individuals with bad intentions to have significant negative impact and influence over the rest of the world. What we most need to fear is not some sort of revenge of the robots, but rather the loner who hates the world and is empowered by AI to wreak havoc at a scale that is impossible today, but very possible in the near future.

The challenge in dealing with this really serious threat is that as AI intelligence increases, the prevention and defence of the threat will always be chasing the ease with which the threat can be realized. In other words, the threat will will grow faster than the mechanism we design to safeguard against the threats.

Legislation will help, but will it be enough?