It was supposed to be the crown jewel of AI infrastructure. Backed by $14 billion from Meta, Scale AI positioned itself as the quiet force behind your favorite AI models. But behind the curtain, Scale AI wasn’t a sleek Silicon Valley machine. It was a clown car on fire - overrun by fraud, incompetence, and a chaotic flood of AI-generated nonsense.
As the AI arms race accelerates, a massive truth is becoming impossible to ignore: bad data ruins good AI. And Scale AI? It’s been serving up junk food for AI brains on a silver platter.
In what’s now being described as one of the biggest hidden failures in AI development, a devastating Inc Magazine investigation unearthed the truth about Scale AI’s "Bulba Experts" program—a secretive annotation pipeline feeding Google’s Bard AI (now Gemini). The job was simple in theory: hire credentialed experts to label and contextualize training data across domains like physics, economics, law, and medicine.
But Scale did the unthinkable.
They turned over this incredibly delicate, high-stakes task to a globally scattered, unvetted gig workforce paid pennies per task—often less than minimum wage—and armed with zero oversight.
That’s a direct quote from a former Scale contributor. For over 11 months, Scale’s platforms - Remotasks and Outlier AI -descended into utter mayhem. Lacking even basic security protocols or credential verification, Scale ended up:
Let’s be clear: these weren’t a few bad apples. This was organized spam at scale, flowing directly into Google’s data pipelines.
“There were no background checks whatsoever,” said a former Queue Manager. “People were just writing gibberish, submitting AI-generated answers, and still getting paid.”
“At one point,” they added, “the Allocations team dumped 800 spammers into our queue. All of them were flooding the tasks with trash.”
Scale AI had to resort to ZeroGPT, a third-party tool for detecting ChatGPT content, just to stem the bleeding. And even then, no one could be sure how much nonsense had already made it into Google’s AI.
The implications are staggering. Every mislabeled dataset, every GPT-parroted explanation, could now be part of the training bedrock for a global search engine. Imagine relying on that AI for legal advice, medical recommendations, or business planning.
This wasn’t just sloppy. This was AI malpractice.
So why did Google, Meta, and others keep pouring money into Scale?
Because the AI industry, in its rush to dominate, mistook speed and scale for quality. Scale AI optimized for quantity—more annotators, more data, more throughput. But what they ended up delivering was a spam-saturated factory where no one really knew who was doing the work, how it was done, or whether it was even accurate.
And it wasn’t just bad actors. It was bad systems. There were:
This is what happens when you try to build foundational AI with digital sweatshops and hope no one looks too closely.
Now that the world is watching, the AI industry faces a reckoning.
If Scale AI represents everything broken about data labeling today, Hirecade is everything it should be. While others outsource responsibility to anonymous gig workers on the other side of the world, Hirecade builds AI training data with in-house, full-time professionals sitting in secure U.S.-based delivery centers.
Let’s break down how Hirecade is rewriting the rules—and restoring trust.
Every data annotator at Hirecade is a verified employee. No fake IDs. No VPN loopholes. No “who really did this task?” mystery.
These professionals work from physical offices in the U.S., where activity is monitored, output is quality-checked, and access is secure. You’re not just buying data - you’re buying peace of mind.
While Scale AI drowned in AI-generated garbage, Hirecade enforces strict zero-tolerance policies on GPT or any generative tool for annotation. All work is:
You get clean, handcrafted data—not Frankenstein responses from a rogue annotator using ChatGPT.
Need law school grads for legal data? Hirecade gets them. Need PhDs for science-related annotation? Done.
Unlike Scale, where contributors were faking credentials and bluffing their way through, Hirecade verifies education, background, and domain skills before assigning anyone to a project.
The result? You get answers from people who actually know what they’re talking about.
Hirecade doesn’t run on gig work—it runs on career work. These are full-time jobs with training, benefits, and advancement paths. That means annotators are:
And crucially, Hirecade owns the delivery center. No hidden third parties. No partner firms. Just clean, direct control.
Here’s the brutal truth no one wants to say out loud: if you’re using Scale AI, you don’t really know what’s in your training data.
You don’t know who labeled it.
You don’t know if it’s true.
You don’t know if it’s even human-generated.
That’s not just risky. That’s reckless.
Hirecade believes that foundational AI deserves foundational integrity. And it’s clear: the companies that take data seriously will build better AI—and win.
Scale AI showed us what happens when the data pipeline is treated like an afterthought. Hirecade shows what’s possible when it’s treated like a core asset.
So ask yourself:
❌ Do you want your AI trained by anonymous spammers with no oversight?
✅ Or by vetted professionals, working under supervision, in secure delivery centers?
The future of AI is being built right now.
Don’t build yours on sand. Build it with Hirecade.
📞 Ready to ditch the chaos and embrace quality? Contact Hirecade today.
