AI models are trained to find the most probable answer, reflecting the average of their data. Truly great, tasteful work is often unique and statistically unlikely, a quality that current models, which regress to the mean, struggle to produce. They can solve PhD-level math but fail at creative tasks like writing a good tweet.

The auto-regressive, next-token-prediction nature of current LLMs is a 'really, really weird way to produce stuff.' True human creativity and writing insight involve knowing precisely when to make an unpredictable, non-obvious move. This is directly contrary to the model's core process, which is a slave to its immediate context and favors predictable outputs.

AI makes it easy to generate mediocre content, shrinking the gap between bad and passable. However, the effort required to create truly good, differentiating content has increased, widening the gap between what is passable and what is excellent, making true differentiation more difficult.

True creative mastery emerges from an unpredictable human process. AI can generate options quickly but bypasses this journey, losing the potential for inexplicable, last-minute genius that defines truly great work. It optimizes for speed at the cost of brilliance.

AI excels at replicating patterns from its training data. However, top-tier authors provide value by subverting expectations and introducing surprising connections—a skill rooted in creative, pattern-breaking thought that AI struggles with. The act of writing is the act of thinking, which can't be outsourced.

AI models produce poor creative writing because they are trained to optimize for superficial proxies for quality, like the number of metaphors. This 'reward hacking' caters to quick judgments from human evaluators on leaderboards, mistaking flashy complexity for genuine literary taste.

LLMs conform to the average of their training data. When used for creative tasks like writing, they act as "memetic conformity machines," sanding off originality and producing work that sounds like everything else—the literal definition of mediocre.

AI can generate output, but it cannot discern what is truly 'good.' To create high-quality, differentiated content, humans must cultivate their own sense of taste by actively consuming excellent writing and journalism. This discernment is the key human advantage over automation.

Using AI to overcome writer's block is a mistake because it aggregates existing data to provide the most popular response, which is the opposite of original thinking. True creativity comes from exploring wrong turns and unexpected paths.