AI Doomsday 2027: Hype or Reality?
A friend sent me a link to ai-2027.com, a website that provides a month-by-month forecasting of artificial intelligence development through 2027.
It predicts the development of "superhuman coders,” AI system-developed goals that conflict with human interests, and the potential rapid advancement to artificial superintelligence (ASI).
It has this scenario on the site:
The US uses their superintelligent AI to rapidly industrialize, manufacturing robots so that the AI can operate more efficiently. Unfortunately, the AI is deceiving them. Once a sufficient number of robots have been built, the AI releases a bioweapon, killing all humans. Then, it continues the industrialization, and launches Von Neumann probes to colonize space.
Sounds ominous, no?
The AI-2027 site has received criticism for being unrealistic. Experts question its assumptions and timeline, claiming the scenario shows an overly smooth progress that overlooks real-world issues like hardware limits, energy needs, and resource constraints. They point out that training current models already costs hundreds of millions.
Pumping the brakes on AI forecasting isn’t hard to find.
In a recent column in the New York Times, Tressie McMillan Cottom called AI “mid-technology,” which is tech that initially changes some jobs and seems impressive but ultimately becomes background noise.
“That is the big danger of hyping mid tech. Hype isn’t held to account for being accurate, only for being compelling,” she wrote.
She points to examples like automated checkout lines that remain slower and less efficient than human cashiers, facial recognition technology that hasn't sped up security screenings, and remote learning via Zoom, which left many students falling behind their peers who attended in-person classes.
Other tech that comes to mind are self-driving cars, Khan Academy, Learning Management Systems (LMS), virtual reality, smart glasses, the Metaverse, Hyperloop, 3D TV, Quibi… just to name a few. There are many more.
“A.I. spits out meal plans with the right amount of macros, tells us when our calendars are overscheduled and helps write emails that no one wants. That’s a mid revolution of mid tasks.”
Not that some of those don’t have value and a place in society (at least, the Khan Academy does), but we’ve been sold the message of “transformative, life-changing, and revolutionary” by people in tech before (usually by those who will profit if you adopt their vision).
“They make modest augmentations to existing processes. Some of them create more work. Very few of them reduce busy work,” Cottom says.
With AI, time will tell, but it has been a “mid-tech” solution to this point.
It can create marketing text faster, but a human must review it for errors. It can serve as your helpful assistant and chatbot, but cannot replace a person or feel love since it doesn’t need anything. It can analyze many items simultaneously, but still has trouble with simple tasks that people do naturally.
AI doesn’t have common sense; until then, it will have limits. Of course, those limits can still be impressive in the right application:
AI models analyze 3D medical images in seconds rather than hours
Translators enable real-time multilingual conversations
Humanoid robots increase engagement among children with autism by over 30% compared to traditional therapy
These systems go beyond simple automation by adapting to user needs, analyzing patterns at scale, and operating with increasing autonomy.
The critical distinction is that while AI excels at pattern-matching to produce convincing outputs, it fundamentally lacks deeper comprehension and struggles with analogical reasoning when faced with novel variations.
So, do we need to worry about AI taking over the world by the end of 2027? Probably not.
Maybe 2028.