Tag Archives: AI

Inevitable threat

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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?

Humankind’s End – Pet, Child, or Colleague? 

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Part 1: Frog in the Pot

There is the story of the frog in the pot of boiling water which goes like this: Toss a frog into a boiling pot of water and it will instantly hop out, recognizing the danger of the hot water. However, put a frog in a cold pot of water, very slowly bring it to a boil, and the frog will swim around oblivious to the gradual change in temperature and it will swim until it boils to death. I’ve heard conflicting evidence that questions if this will actually happen, but I think this story is relevant to what we are seeing with AI – Artificial Intelligence – today. 

The reality is that AI is getting smarter and smarter. While there is debate as to when we will have AGI – Artificial General Intelligence or ASI – Artificial Super Intelligence, like the pot set to slowly boil, this time is coming, even if the timeline is unknown. 

What does this mean for us? Well, I would be hard pressed to tell you exactly when this happened, but at some point in the past people stopped doing complicated math calculations by hand and eventually relied more and more on calculators and computers. I could solve a problem like 12,458 divided by 27 to 5 decimal places by doing long division, but why would I? I can use a calculator. I’d know the answer would be accurate, and I’d get that answer much faster than doing the math myself. 

What happens when we get to the point when we have ASI, and all the answers to (almost) all the questions we can ask, can be answered faster and better by the super intelligent AI? Would we want to govern ourselves when the AI can do a better job? Would we want to trust a potentially crooked politician to make expensive economic decisions or would be pick the ASI? Would we want to trust a fallible doctor for a medical diagnosis or would we rather the doctor confer with a super intelligence that has access to every possible diagnosis, and which has looked at many million more scans than the doctor ever did, before making the diagnosis? 

We are approaching the ‘water boiling point’ where we are going to have Artificial Intelligence making most key decisions for us because we would be dumb to try to make those decisions ourselves when we know the ASI can do it so much better than we ever could. 

Part 2: Pet, Child, or Colleague? 

So, assuming that we are going to reach a metaphorical boiling point where we decide to let ASI make many if not most key decisions in our lives, what does the mean for humanity? I think there are one of three inevitable outcomes: We will either become AI’s pet, child, or colleague.

Here are the scenarios as I see them playing out:

Pet: We might think our dogs are pretty smart, but don’t want our dog to make decisions for us. A super intelligent AI may see us as only slightly more intelligent animals, who perhaps should be kept around. However, the super intelligence might not want to align with a warring, superstitious, short lived being who seems to have problems getting along as a species… a species who builds arbitrary borders and exclude each other rather than attempt to get along in any meaningful way. Why wouldn’t an ASI treat us more like pets than as equals? 

Child: We know children will make mistakes and bad decisions, that’s part of growing up. That’s why we have age limits for things like driving and drinking. Maybe an ASI will look at us like children who don’t fully understand how things work, and it will take care of us and manage us like children, taking our wishes into consideration, but not letting us make any crucial decisions on our own… of course it will do this ‘for our own good’… but ultimately treat us like immature children, never really ready to accept full responsibility for ourselves. 

Colleague: This might play out where we maintain our true humanity, but I don’t see it that way. Sure a super intelligent AI might look to collaborate and make our lives better while governing us, while also giving us a voice and some choice about how we are governed. But I envision a different kind of colleague experience. I envision an integration of humans and ASI to create a  cyborg – a being that features both organic and biomechatronic body parts… Essentially connecting our human form with AI integrated assistive parts. Why put up with a slow human with poor sensor capabilities when enhancements will make them much easier to work with? 

Part 3: Inevitability 

While I suspect that most of us would want the outcome to be Colleague, rather than Child or Pet, I don’t believe this is our decision.

We can try to design ASI such that it sees value in working with us, but when our intelligence compared to a super intelligent AI is the equivalent to how we look at chimps, dolphins, or Octopus, we really have to consider why they would want to integrate our intelligence with theirs? While we might look at a chimpanzee and think, “Oh how cute, that one can do sign language, and knows 350 signs,” we don’t also think, “Lets create a relations with that chimp in a way that we share intelligence with them and let them make decisions with or for us. And in the same vein, ASI is unlikely to look at a very bright human and think, “Oh how cute, that human can do abstract calculus or astrophysics in his head… let’s integrate ourselves with this simple creature.” 

Ultimately, an Artificial Super Intelligence is going to make the decision. Maybe there is something unique about the human brain or the human condition that would make an ASI want to integrate with us, but we can’t pretend to know if this would be of interest to the super intelligence or not. We can only hope that’s the case. The reality is that the metaphorical water is boiling, we don’t really know when it’s going to boil, and when it does the fate of humankind will not be up to us.

Right and wrong

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I was talking with a colleague yesterday and he shared two interesting things with me. The first was that he has a friend who works for a large company, I think he said Oracle, but I’m not 100% sure. He told me that this friend has unlimited holidays, but the output expectations are so high that she can’t really take advantage of this. The premise is that you can take more time off than just the designated 10-15 days a year (as a traditional US company would allow) as long as you get your job done. The catch is, the workload probably doesn’t even allow that much time off.

That’s a case of ‘The right idea but the wrong outcome’.

The other thing he said was a prediction that I agree with. He predicts that very soon we’ll see the implementation of 4-day work weeks. The reason he thinks this will happen sooner rather than later is AI and robotics. Essentially the economy requires citizens to have buying power, and so you need a paid workforce… but there won’t be enough jobs to sustain everyone putting in 40-hour, 5-day work weeks, and there will also be efficiencies each worker has, thanks to their use of AI and robotics.

That’s a case of ‘The right idea but for the wrong reason’. The societal benefits of a 4-day work week shouldn’t have to wait for technological advancement in my humble opinion.

I would like to think that we are advanced enough as a species that we could do the right things for the right reasons, but more often than not we have to accept the wrong to get the right. We have ‘just’ wars, citizen surveillance to fight terrorism, over-censorship to reduce perceived conflict… the morality of these is dependent on how one is affected.

If you live in country where you have many freedoms but fear violence, you might appreciate heavy surveillance. If you live in a country where expressing your opinion could get you jailed, surveillance feels Orwellian.

‘The right idea but the wrong outcome.’

‘The right idea but for the wrong reason.’

Right and wrong.

“Don’t Bring a Résumé. Bring Receipts.”

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In the article, ‘The Proof Economy’ Anand Sanwal says, “Don’t Bring a Résumé. Bring Receipts.” Anand starts with two definitions saying that we’ve moved from the Parchment Economy to a Proof Economy,

“We’ve entered the Proof Economy, a world where the most valuable signal isn’t where you went to school, what your GPA was, or which honors you collected, but what you’ve actually done and can do. In this new landscape, demonstrated ability trumps pedigree, and what you’ve built matters more than where you studied.

Meanwhile, the Parchment Economy, that centuries-old system where formal credentials and institutional validation serve as proxies for capability, is losing its monopoly on opportunity. The elaborate dance of transcripts, recommendation letters, diplomas and prestige markers is becoming increasingly irrelevant in field after field.”

This is something I’ve been describing for a while now, without properly defining the difference in the two ‘economies’. Beyond credentialed professionals like doctors, engineers, and lawyers, what now matters most is your portfolio, not your schooling certificates. ‘What is it that you can do better than others to earn you a spot in our organization?’ (Regardless of your credentials.)

Anand says,

“When anyone can access expertise through prompts and build a prototype video, software product or design via AI, the value shifts decisively from knowledge possession to knowledge application.”

But for me the most interesting section in his article is:

What Education Needs to Become

If we accept that we’re entering the Proof Economy, schools can’t just add a few electives or rethink assessment to focus on progress and not perfection..

They need to rewire what they reward.

We should expect:

  • Projects over problem sets: Real-world challenges that apply knowledge, not just recall it.
  • Portfolios over transcripts: A body of work that shows thinking, skill, and growth.
  • Public work over private grading: Output that lives in the world, not a Google Doc.
  • Coaching over compliance: Adults who challenge and support, not just evaluate.
  • Failure as fuel: A system that treats failed attempts as essential steps, not permanent marks.

At Inquiry Hub Secondary our students are still entrenched in the old public education system in that they complete required courses to meet provincial high school graduation requirements, and most of them still head off to university, college, or a technical institute to further their studies. However, along the way they are given the time, space, and credits (towards their graduation), to produce documentation of learning in areas of interest. They have an opportunity to design and build projects, (documented receipts), most other students could only get done on their own time, outside of traditional classrooms.

They also get to live in an environment where they have to cooperate with fellow students in scrum projects with tight timelines and defined roles (not just group projects with everyone having identical outcomes and expectations). They have to do frequent presentations, alone and in groups, with training to give and receive feedback with radical candour. They understand iteration, they pivot based on where their learning takes them, and they embrace failure as learning opportunities because sometimes obstacles become the way. And they are provided with greater and greater autonomy over their time as they progress from Grade 9 to 12.

Essentially, Inquiry Hub students still get their resume of courses, but they are also provided the opportunity to bring receipts too.

Students choose, AI delivers

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Thinking about AI use in schools, the vast majority of assignments are currently pretty easy to use AI to assist. Students can use this to extend their learning or to do the work for them/make the work significantly easier to do. And then teachers become police… not teachers, trying to figure out how a student is using AI to cheat.

Two big takeaways, one being a positive shift the other being a challenge:

  1. Process matters more than final products.
  2. Students will choose if they want AI to help them or do the work for them. Will they choose to have AI assist their thinking or do the thinking for them?

We have control over whether we focus on process or content. Students have the choice as to whether they use AI to help them think or to think for them. A focus on process can reduce how much a student relies on AI… but a student can always get AI to assist them with the next step.

I’m excited about how students will use AI to dig deeper and extend their learning. I’m equally concerned for students who are choosing to use AI to take the friction out of leaning… opting out of thinking for themselves. Whichever of these approaches students choose, AI will deliver.

A bigger gig economy

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The gig economy is a system where people work as freelancers or take on side jobs for companies instead of having a regular full‑time position. Uber drivers are a great example of this. There are a few reasons why I think the gig economy is going to grow:

  1. High prices are making a side hustle of some sort essential if you want to enjoy things beyond what salaries allow.
  2. Companies like the structure because pay is based on performance rather than a set salary.
  3. Entertainment is shifting to live performances, gigs, as a primary form of earnings. Getting your music to stream is not enough to keep most musicians going without a concert tour.
  4. A trend now in social media, is to see a lot of affiliate marketing. Only the biggest of social media stars can make this a full-time living. For the vast majority affiliate marketing is nothing more than a gig economy.
  5. We are going to see a wave of AI trainers needed to train robots to do everyday skills. Work as a maid in a hotel? We’ll pay you to wear a GoPro for two weeks while you work. That video will train an AI that’s going to take your job less than a decade later.

Companies are afraid to hire full time staff. Money is better spent on technology than on training a human on a fixed salary. As a result, the gig economy is just going to get bigger and bigger.

UCI rather than UBI

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As AI and robotics continue to scale at unimaginable speeds, with AI getting exponentially smarter and robots increasingly more agile, we’ve got to realize how many jobs will disappear in a very short time period. This isn’t a gradual transition, it’s not a move from one field to another like farmers transitioning into factory workers during the industrial revolution. It’s a massive shift from human labour to machine labour that the world’s economies simply aren’t designed to absorb.

I’ve seen a growth in the number of people talking about the need for Universal Basic Income (UBI), but I fear this isn’t enough. I fear that the idea of giving millions if not billions of people a basic income, but no real means for most of them to supplement those incomes as an insufficient solution. We don’t need UBI, we need UCI – Universal Comfortable Income. It’s not going to be enough to give people a basic survival income. We are going to need to see governments, and maybe even companies, share their resources and wealth with people, or else who is going to have the resources to buy the products and services AI and robots will offer?

The potential for dissatisfaction and ultimately unrest seems scary to me. A world with a couple dozen trillion-dollar companies, and a handful of trillionaires running them, is also a world with vast populations of people eking out a subsistence lifestyle, unable to do more than meet their survival needs. A basic income, requiring additional sources of income to appreciate the offerings of a fully automated economy, will not survive without a revolt for too long.

Maybe I’m wrong. Maybe there are other solutions to this problem. Maybe I’m too bullish about to how far things will advance in a short time. That said, the potential for the scenario above to occur in the next decade is not zero. It might be a pessimistic bad-case or even worse-case scenario, but it’s possible… and scary. If things advance as fast as I think they will, we can’t continue to have UBI conversations, we need to move the goal posts and start really thinking of UCI.

A tidal wave of spam

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Head of products at Twitter/x.com, Nikita Bier, said this on February 11th, 2 months ago today:

“Prediction: In less than 90 days, all channels that we thought were safe from spam & automation will be so flooded that they will no longer be usable in any functional sense: iMessage, phone calls, Gmail.

And we will have no way to stop it.”

Anthropic’s newest AI model, called Claude Mythos, is not being released to the public due to concerns about its ability to uncover high-severity cybersecurity flaws in major operating systems and web browsers. But make no mistake, this AI version and more (some privately owned and some free and open source) will be available in the next month. With this will come a tidal wave of security breaches, identity theft, and corporate as well as personal blackmail crimes.

The fact is that these AI models are professional lock pickers put in the hands of anyone who wants to use them. Almost no skill needed. Unlike the movies where the people doing a heist needed to recruit that one-of-a-kind safe cracker with crazy skills, now a 15 year old in his parent’s basement can do it without leaving the house.

This wave of ‘safe crackers’ is going to be let loose soon. But something else is headed this way and that’s the scammer coming for you and me via our phones, laptops, and social media accounts. These used to show up in poorly written emails, or broken English texts and phone calls that made them easy to detect. Now three things have fundamentally changed:

1. The quality of the messaging is flawless;

2. The ability of spammers and scammers to target you and share enough information to seem legitimate;

3. The sheer volume of spam coming our way. 1 spammer used to mean 1 phone call at a time being followed up with a real person. But with AI agents, one command could unleash wave upon wave of simultaneous emails, phone texts, and messages across many social media platforms.

The biggest problem with AI in the next 5 years isn’t what AI can do on its own, but rather what people with bad intentions can… and will… do with AI. It’s bad faith actors who will be our nemesis. Ultimately, the tidal wave is coming, “And we will have no way to stop it.”

So easy to cheat

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We aren’t far away from contact lenses that can do the same. The article, ‘Smart Glasses for Exam Cheating: Best Models, Prices and Risks in 2026’, shares multiple options that can provide AI delivered test answers, in seconds, via a small ear piece or even projected text answers which can only be heard or seen by the user. Banned? Of course. Easily detected? Not all models, with more sleuth and hidden models being developed every day. And as mentioned, what happens when these are as invisible as contact lenses?

Make no mistake, cheating has been around as long as tests have. In some respects this is not new. But most methods of cheating demand guessing what questions will be on the test in advance. Methods like these are responsive to every question asked. And the speed of responses are natural. While you are still reading the question, a response is already headed your way. No need to shift your eyes from the screen or test paper. No hidden notes to conceal, and no wrong answers unless you are choosing to get less than a perfect score, to not seem suspiciously smart.

I remember a friend telling me about him and his friends getting hold of their ethics exam a couple days before they had to write it. The irony of cheating on an ethics exam is not lost on me. They memorized the questions and answers, and all chose different ones to get wrong, while still achieving high ‘A’s. Then on the day of the test my friend was horrified when his friend raised his hand 30 minutes into a 3-hour exam, and shared a typo on a question that no one should have gotten to in such a short time. Despite this poor choice, they all got their ‘A’s.

That’s going to be the new challenge in cheating, how to not do too well to bring attention to yourself. A good problem to have for a cheater.

So here we are in a new era of cheating. Prescription glasses, hidden cameras and microphones, and curated wrong answers. And in all honesty, less and less opportunity for detection. Ultimately, it’s the tests that will need to change.

Way more Waymo

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Here is a statistic from the company Waymo:

“In less than two years, the company’s average weekly paid robotaxi trips have grown tenfold, from 50,000 per week in May 2024 to 500,000 per week today.” Source: Waymo’s skyrocketing ridership in one chart

This is amazing growth. It’s not an isolated statistic. We are seeing this kind of growth in robotic focused manufacturing, and we are seeing it in the use of AI to do many jobs that humans used to do.

Are we ready for this? Are we ready for the gig economy to be eaten up by automation? Are we ready for not just blue collar but also white collar jobs to dwindle as AI takes over these jobs at an exponential rate? Are we ready for AI teachers, AI servants, AI drivers, AI delivery, AI accountants, AI lawyers, AI programmers, and AI in fields we thought would always need humans in them? Are we ready for way more of this kind of Waymo growth occurring simultaneously across many sectors?

We aren’t ready. Yet this is coming our way. It’s that simple.

Our responses in each case will be reactionary. For every current Waymo passenger there are probably a few potential customers thinking, ‘That’s scary, I’m not ready to put my life in the hands of a robot driver on the highway or the busy streets of downtown at rush hour.’ But those stats will dwindle. For every worker who thinks, ‘My job is safe, they’ll always need me,’ there are others who thought the same just a few years ago, and they are now looking for a job, often in a different sector than what they’ve been in.

Yes, there are limitations to this growth in some sectors. Yes, new jobs may come up that are uniquely human in nature. Yes, there are yet unharnessed opportunities for people to make a greater income (with less effort) in areas that they would not have imagined just a few months ago. It’s not all doom and gloom… but make no mistake, the exponential growth of AI powered advances will be drastically affecting all of our everyday lives sooner than most people realize. Waymo’s growth is emblematic of the kind of growth we will see in almost every aspect of our lives.

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Update: This video on LinkedIn is worth sharing here.