the pulse
Why I’m Betting Against an AI Apocalypse
4 Reasons Why I Think It’s Unlikely
By Michael Hyatt
September 6, 2025
History’s scariest predictions rarely come true. There’s a reason for that—and it might just save us from an AI doomsday.
In 1998, I published a New York Times bestseller called The Millennium Bug: How to Survive the Coming Chaos. It stayed on the list for seventy-two weeks. I did over two thousand interviews about the book and even testified before a joint session of Congress.
Behind the scenes, I was quietly preparing for disaster. I bought an eighty-eight-acre farm, installed giant solar panels, wired in backup generators, stocked two years’ worth of food, and planted a garden that could feed my family indefinitely.
I had credible sources inside the FBI, CIA, and major corporations. They were all telling me the same thing: they were hoping for the best, but preparing for the worst. The risk of total technological collapse seemed real, and I was determined not to be caught unprepared.
Then, January 1, 2000, arrived.
The lights stayed on. The banks stayed open. Planes didn’t fall from the sky. Within days, it was clear the worst-case scenario was never going to happen.
And over the next couple of years, I came to an uncomfortable conclusion: I’d gotten swept up in mass hysteria. I had solid evidence, sure. But I had underestimated the most important variable in the human story—our capacity to innovate.
I was reminded of that lesson recently while listening to Steven Bartlett interview Mo Gawdat, a former Google executive, on The Diary of a CEO. Gawdat laid out a well-reasoned case for a 15-year AI-driven dystopia. He’s smart, experienced, and articulate. It’s the kind of argument that can make even optimistic people start scanning the horizon for mushroom clouds.
But I’d seen this movie before. There are four reasons why I don’t believe his scenario is likely to happen.
Reason 1: Dire Predictions Have a Track Record of Being Wrong
Throughout my life, I’ve watched wave after wave of expert-driven, data-backed doom scenarios:
- The Coming Ice Age (1970s) warned of global cooling that would devastate agriculture and economies. Didn’t happen.
- The Population Bomb (late 1960s–1970s) predicted mass starvation from overpopulation. Didn’t happen.
- Acid Rain (1980s) was supposed to destroy forests and lakes. Didn’t happen.
- AIDS Epidemic (1980s–1990s) forecast to wipe out entire populations in some countries. A serious health crisis, but not the extinction-level event many predicted.
- The Ozone Hole (1980s–1990s) was going to cook us with deadly UV rays. Didn’t happen.
- Peak Oil (1990s–2000s) forecast a permanent energy crisis. Didn’t happen.
- Y2K (late 1990s) was going to send us back to the Stone Age. Definitely didn’t happen.
- The Great Recession (2008–2009) was predicted to trigger a decades-long global depression. Painful and disruptive, but recovery came faster than expected.
- COVID-19 (2020) while devastating in loss of life and economic disruption, it didn’t produce the societal collapse some feared.
Every one of these predictions followed the same logic: If this trend continues, catastrophe is inevitable. But trends rarely continue in a straight line. People step in. They invent solutions. They adapt.
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Reason 2: Human Innovation Changes the Story
That’s the fatal flaw in most dystopian forecasts: they leave out human innovation. We are not passive passengers on a doomed ship. We spot the iceberg. We build a better rudder. We change course.
AI could absolutely create serious problems if we sit on our hands. But that’s not what history suggests we’ll do. We are already seeing a massive push for AI governance, ethics, and safety. Entire industries are emerging around making AI more transparent, accountable, and aligned with human values.
Reason 3: We’re Already Building Guardrails
Gawdat’s scenario assumes exponential AI capability with little to no corresponding advancement in oversight or safeguards. But here’s why I think the odds tilt in a different direction:
- We’re building guardrails now, not later. Governments, companies, and nonprofits are working on this before disaster strikes.
- Ethics are in the conversation early. We’re not waiting decades to recognize unintended consequences.
- Innovation solves innovation’s problems. The same tech that creates risk can be harnessed to mitigate it.
- Humans adapt quickly. From the printing press to the internet, we’ve integrated new tech faster than the pessimists predicted.
- Fear skews the forecast. Worst-case scenarios grab headlines, but they rarely define the future.
Reason 4: The Real Risk Isn’t AI—It’s Complacency
If we accept dystopia as inevitable, we might make it so. The antidote is not blind optimism, but active engagement. Innovators, ethicists, policymakers, and everyday citizens must help shape the trajectory.
This isn’t a call to ignore risk. It’s a call to remember our agency. The future is not something that happens to us—it’s something we build.
So, could Gawdat be right? Sure, if we do nothing. But I’m betting on the same force that’s saved us before: the relentless human drive to create, adapt, and solve.
I know which team I’m on.
What about you? Team Dystopia or Team Innovation?In pursuit of the Double Win,
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Michael Hyatt
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