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Everywhere you look, AI is making a mess of things. The internet is clogged with machine-generated slop: endless bland blog posts and identical résumés. Students use chatbots to evade learning, employees lean on them to churn out poor-quality work, and the rest of us scroll through an ocean of hallucinations. Some days, this feels like less of a revolution and more like a slow-motion collective breakdown.
Nowhere is this playing out more clearly than in the workplace. Companies are adopting generative AI at breakneck speed, and instead of raising standards, it's often lowering them. On the employee side, AI is enabling the mass production of "workslop," polished-looking outputs that are shallow, generic, and sometimes flat-out wrong. Research by the firm BetterUp found that 40% of full-time U.S. employees have encountered workslop.
Why wrestle with a hard idea when a chatbot can produce something passable? Why revise critically when the AI sounds so confident? It's not simply laziness. The challenge is compounded by the fact that nearly half of large language model users, according to a study by Elon University, think the models are smarter than they actually are. With that mindset, people skip the scrutiny and hand off slop as if it were solid work. Reports, memos, and proposals get drafted in seconds, passed along without much review, and eventually dumped on someone else to fix.
Meanwhile, employers are making a parallel mistake. Convinced that AI is already, or will soon be, capable of matching or surpassing human workers, some companies are racing to cut staff. Amazon plans to lay off 14,000 workers, citing the productivity promise of AI as the cause for the cuts. Entire teams are being hollowed out, not because AI has proven it can replace them, but because leadership assumes it inevitably will.
As an AI researcher myself, and a founder/CEO of one of the earliest generative AI startups, this shift runs directly counter to what I believe the field's pioneers envisioned. Generative AI should be built to elevate human capability. So why is the workplace using it to undermine itself?
There's nothing inherent in the technology that forces low-quality work. And on the employer side, firing people prematurely is a strategic decision, not a technological demand.
So what's driving this? At the root is a myth we've carried for decades: the all-knowing AI oracle.
From HAL 9000 to Skynet, pop culture has long portrayed AI as a godlike entity that inevitably surpasses and ultimately replaces us. By the time generative AI went mainstream in 2022, many people were primed to believe that they were witnessing the realization of a longstanding prophecy.
Marketing only fueled the story. AI was sold as faster, smarter, and more capable than us. And so when a chatbot says, "Great idea!" people believe it. If the oracle approves, I must be right. If it can write my report, why think at all? And if AI is smarter, then maybe I should replace my team with "faster, better, cheaper" AI agents.
If that's the diagnosis, the remedy becomes clearer. We're not going to shut down the technology, as far too much money flows through it. But we can dismantle the mythology. We can stop treating generative AI as a god-like oracle and start seeing it for what it is: a fallible, yet fascinating, partner in the workplace and beyond.
The key to using AI effectively is to lean into human creativity. When the machine drafts something, you edit it. When it suggests an idea, you question it. Across all industries, people who apply a critical, collaborative approach to AI are getting ahead. And when you lead a company, you don't gut your workforce. Instead, you take the time to assess what the actual technology, not an idyllic science-fiction myth, can do to elevate your business.
Start by exploring what today's AI tools can actually do. It's important to test the tools yourself so you can separate hype from real capability. Look for places where AI can raise quality, not just speed: improving your workflow, strengthening ideation, or elevating the final product. Because the technology is still young, the advantage goes to those who experiment and find imaginative uses for it. And if you're in a managerial role, don't jump straight to headcount cuts. Instead, take a broader view: How could AI help your existing team serve more customers, deliver better results, or open new revenue streams?
We're at a critical moment. Swinging wildly between panic and worship won't help. If we strip away the oracle myth, we can reclaim our role in the collaboration. Employers must stop treating AI as a ready-made replacement for human intelligence. Employees must stop handing over their minds to the machine. Drop the myth, and the real opportunity emerges: AI that strengthens human capabilities while keeping us firmly in charge.