A writer who learned to code after losing his job reflects on AI chatbots, which repackage ideas and lack lateral thinking, and why humans are irreplaceable
Silicon Valley wants to make us believe humans are predictable and our skills replaceable. I've learned that's nonsense Tweets: @neilturkewitz , @sarahbadr , @tristandross , @jjvincent , and @david_rudnick Tweets: Neil Turkewitz / @neilturkewitz : “There's a concerted effort on the part of Silicon Valley to make us believe...the arts are reducible to a set of equations & keywords, because they've spent billions creating machines that can now knock out FORGERIES OF CREATIVE ENDEAVOR.” 🔥 from @tristandross h/t @jjvincent https://twitter.com/... @sarahbadr : “...we need to start refusing attempts to make us forget how valuable our humanity really is.” — @tristandross https://www.theguardian.com/ ... [image] @tristandross : wrote about resisting the tech world's concerted attempt to convince us that all humans are replaceable and our creative endeavours can simply be outsourced to machines https://www.theguardian.com/ ... James Vincent / @jjvincent : “It speaks to such a paucity of imagination on the part of AI's exponents that they're asking us to imagine having an imagination” — great from @tristandross on the dynamic between AI and human creativity https://www.theguardian.com/ ... @david_rudnick : great article; this in particular really nails the fundamentals of so much of what we are seeing play out across so many creative fields at the moment: https://twitter.com/... [image]
Context & Ripple Effects
This essay is the argumentative core of a story arc the related coverage documents from the ground up: Tristan Ross — a writer who retrained in code after losing his job — pushes back on the Silicon Valley framing, amplified by commentators like [[a:none|Neil Turkewitz]] and James Vincent, that creative work is reducible to equations and keywords. His claim that chatbots repackage ideas rather than think laterally lands against measurable damage: interviews with copywriters describe training data use, layoffs, and rates in free fall.
The essay also predates and frames the structural moves that followed, from Duolingo's AI-first announcement to the emergence of personalized AI-generated entertainment — making it the normative counterpoint to coverage that mostly tracks the labor-market numbers.
First-order effects
- Working writers are affected now: the copywriters in the related coverage report lost clients, collapsing freelance rates, and their published work being used as training data without compensation.
- The essay gives named defenders of creative labor — Ross, Turkewitz, Vincent — a shared thesis to organize around: that AI output is forgery of creative endeavor, not substitution for it.
Second-order effects
- A degraded secondary labor market is forming around the gap Ross identifies: copywriters report taking new, lower-paid work making AI-generated text sound more human — humans paid to patch what the machines lack.
- Companies adopting AI-first messaging, as Duolingo did, face a counter-narrative they must answer: if chatbots merely repackage, the quality and originality cost of substitution becomes a live argument in hiring and brand decisions.
Third-order effects
- If the pattern holds, creative labor splits into two tracks — humans as training-data suppliers and post-editors at the low end, and human originality as a premium, explicitly non-AI good at the high end — with personalized AI-generated entertainment raising the stakes for which track dominates.
- The dispute over whether machine output is creation or forgery sets up the terms for future fights over copyright, attribution, and compensation for writers whose work trains the models.
The trend: Generative AI is restructuring creative labor markets faster than it can replicate creative judgment, forcing a split between commoditized AI-assisted output and human originality as a defended premium good.