The Internet Was Always Bad at Writing. Now It's Just More Obvious.

2026-03-24 · Source: HackerNoon · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Publishing & Journalism, Marketing, Branding & Advertising · Depth: Intermediate, medium

Summary

The article argues that the perceived decline in writing quality predates large language models (LLMs) like ChatGPT, asserting that amateur blogs and newsrooms already contributed to widespread mediocrity. It contends that AI-assisted writing often exhibits better technical execution, such as grammar and structure, than average human writing. While LLMs excel in technical aspects, a study in the Journal of Intelligence (2026) found humans retain an edge in creative tasks requiring depth, though this study used students, not professional writers. The piece highlights that many readers cannot distinguish between well-prompted AI content and mediocre human writing. It compares LLM hallucinations, like the fabricated legal cases in Mata v. Avianca, Inc. (S.D.N.Y. 2023), with historical journalistic failures such as Janet Cooke's Pulitzer-winning hoax, attributing both to a lack of verification. The author emphasizes that true expertise is crucial for identifying AI errors, advocating for using AI to amplify judgment rather than replace it. Ultimately, the article suggests that "voice, judgment, and responsibility" are the only ways for human writers to stand out amidst the proliferation of AI-generated content.

Key takeaway

For content creators and editorial teams navigating the rise of AI, your focus should shift from mere technical correctness to cultivating a distinct voice and rigorous judgment. If you are producing content that needs to resonate or be remembered, ensure it reflects genuine expertise and a unique perspective that AI cannot replicate. Use AI for efficiency in low-stakes tasks, but never let it replace the critical human verification step, especially for factual accuracy, to avoid costly errors and maintain credibility.

Key insights

AI amplifies existing writing quality issues, making human voice, judgment, and responsibility more critical than ever.

Principles

• Verification is paramount, regardless of content source.
• Expertise is essential to detect AI-generated errors.
• Voice and judgment differentiate human writing from AI.

Method

Use AI for mundane, repetitive writing tasks. For impactful content, rely on human judgment, unique voice, and thorough verification to ensure authenticity and depth.

In practice

• Apply AI for boilerplate emails and summaries.
• Develop deep subject matter expertise.
• Prioritize unique voice in creative content.

Topics

• Large Language Models
• AI Writing
• Content Verification
• Journalistic Integrity
• AI Hallucinations

Best for: Product Manager, Tech Journalist, AI Product Manager, Marketing Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.