January 28, 2026
Robots write, humans riot
Will AIs Take All Our Jobs and End Human History–Or Not?
Commenters clap back: “2023?!” vs “Humans still matter” in job-doom showdown
TLDR: A 2023 essay argues AI can write like us but people still set the goals, so work won’t just vanish. Comments split between “this is outdated” and “humans still matter,” with a standout take that even with smarter machines, we’ll keep debating what’s meaningful—shaping how future jobs and purpose evolve.
The internet saw Stephen Wolfram’s long think-piece asking if AI will take all our jobs—and the comments immediately turned into a town hall brawl. The loudest opening volley? A collective eye-roll: “AI is evolving so fast, and you post an article from 2023?” scoffed one reader, setting the tone with a meme-ready vibe of “yesterday’s AI is ancient.”
But then came the big-brain TL;DR that stole the thread. One commenter boiled it down to: AI won’t erase work—it’ll just keep moving the goalposts, because the universe is too messy to automate. Translation: even with super-smart machines, we’ll still be arguing about what’s worth doing. Call it the “infinite robots, infinite debates” theory, and it had people nodding and nervously laughing in equal measure.
On the hopeful side, another voice chimed in: even if machines do the tasks, human experiences still sell. Concerts, travel, hand-made anything—the “people factor” stays in demand. That sparked a split-screen mood: doomers warning we’re training our replacements, optimists saying we’ll just change the jobs, not lose purpose. The meta-drama? Fans defending the 2023 essay as still relevant vs. speedrunners shouting “old link, who dis?” Meanwhile, jokesters imagined future office life: bots writing reports while humans argue which report is “meaningful.” It’s messy, it’s funny, it’s very online—and it’s exactly where this fight over AI and jobs lives now.
Key Points
- •ChatGPT is presented as an AI trained on vast human-written text to generate human-like essays.
- •Its architecture is described as a neural network with millions of neurons and billions of connections refined through training.
- •Meaningful, human-aligned output depends on leveraging human context captured in training data.
- •Humans define goals and prompts, guiding AI toward outcomes beyond raw computation.
- •Wolfram introduces the Linguistic User Interface (LUI) concept, contrasted with GUI, to explain AI-mediated text interaction.