I recently read a thought-provoking post on Medium titled It’s Official, The World Doesn’t Want AI-Generated Content. The author argues that AI content “defeats the purpose of the content before it even begins” because it reflects what “math decides the groupthink wants to hear based on what’s already been said in the past.”
I can see where they’re coming from—but I think it’s more nuanced than that. In my view, AI content falls into four broad categories:
1. Fully Human-Created Content
The traditional way we’ve been creating for centuries—every idea, sentence, and paragraph originates from a human mind.
Example: A hand-written short story or an investigative article built entirely on original interviews and research.
2. Human-Created with AI Editing
The core content is human-written, but AI tools assist with grammar, spelling, and style improvements. Think of it as the digital equivalent of having an ever-present editor.
Example: A blog post you write in MS Word, with AI suggesting clearer phrasing or fixing typos.
3. Human-Directed, AI-Generated
A human decides the topic, structure, and key points, but the AI does the heavy lifting—research, drafting, even fact-checking. The direction is human, the execution is largely machine.
Example: You outline a post on renewable energy trends, feed it to AI, and refine the output before publishing.
4. Fully Automated Clickbait
AI agents scrape trends, chase hot keywords, and churn out articles at scale—often shallow, repetitive, and formulaic. This is the type of output the Medium post criticizes most harshly.
Example: Endless “Top 10” listicles that recycle existing content with minimal value.
Why This Matters
AI isn’t going away. The question isn’t if it will be part of the content ecosystem, but how we choose to use it. By understanding these categories, we can push AI toward enhancing human creativity—rather than drowning it in noise.
This experiment is my way of exploring where those boundaries are today, and how they shift as technology develops.