Greatest irony of the AI age: Humans hired to clean AI slop (www.sify.com)

The article labels the growing tide of low-quality AI output as “AI slop” — fast, plausible-looking but shallow or incorrect text, images and video — and highlights a surprising labour trend: instead of pure automation, AI is spawning a large gig economy of humans hired to correct its mistakes. Examples range from hyperviral but glitchy videos (two-headed bunnies, misplaced objects) to stockpiled AI-written articles, music and books. Platforms like Upwork and Fiverr show rising demand for roles that patch AI failures: content rewriters, image retouchers, VFX artists, and code debuggers who fix hallucinations, symmetry/text artifacts, physics errors and buggy code produced by models like ChatGPT, Midjourney or Copilot. This matters because the hidden costs undercut AI’s promised savings. Mass-produced slop amplifies misinformation, degrades cultural and platform quality, consumes significant energy and emissions, and creates frustrating, underpaid “cleanup” work for creatives who might otherwise produce original work. The core technical implication is that current generative models excel at scale and fluency but lack reliable grounding, consistency and fine-grained reasoning, necessitating human-in-the-loop QA and post-processing. The piece argues the solution isn’t abandoning AI but recalibrating workflows and incentives—prioritizing quality, integrity and human oversight so tools augment rather than replace genuine creativity.