Do AIs Use Em Dashes to Save Computational Power? Unpacking a Common Misconception
If you've spent any time reading AI-generated text lately, you may have spotted a curious trend: the frequent, almost enthusiastic, use of em dashes — those long horizontal lines that link thoughts more stylishly than a mere comma or semicolon. This observation has sparked a reasonable hypothesis among readers and writers alike: Is AI using em dashes as a way to save computational power and tokens, compressing language through a kind of punctuation shortcut?
At first glance, the theory seems logical. Large language models like GPT break down text into tokens — discrete units made up of words, parts of words, or characters — which are then processed to predict and generate fluent responses. Em dashes are succinct, capable of connecting ideas quickly without the grammatical "overhead" that parentheses or conjunctions might require. Could AI be strategically choosing this punctuation to keep token counts low and responses efficient?
It’s a compelling idea — but it turns out, it isn’t quite accurate.
Understanding Tokens and Computational Cost
To understand why, it helps to dive a little deeper into how AI models handle text. Every response an AI generates is constructed token by token. In English, a token might be a whole word ("apple"), a meaningful fragment ("un-"), or a piece of punctuation ("!").
In this system, an em dash (—) typically counts as one token, depending on the tokenizer used. Crucially, common alternatives like a comma (,), period (.), or parentheses (( )) also consume about the same amount — usually one token each.
Thus, whether the AI opts for an em dash, a comma, or parentheses has negligible impact on the computational cost or the number of tokens used. There’s no significant “efficiency hack” happening when an em dash appears instead of other punctuation.
In short: AI isn’t using em dashes to save power or space — because it doesn’t need to.
So Why the Love for Em Dashes?
The true reason behind the AI’s affinity for em dashes is far less mechanical and far more human: stylistic imitation.
Modern large language models are trained on enormous datasets compiled from books, articles, essays, websites, and other written forms. Within these datasets, em dashes feature prominently, especially in English writing that aims to sound natural, conversational, and fluid. Journalists, bloggers, and essayists often favor the em dash over more formal or fussy punctuation because it offers flexibility: it can signal an aside, an abrupt turn in thought, or a dramatic pause without the stiffness of a colon or the formality of a semicolon.
When AI models generate text, they’re not calculating "how can I use fewer tokens?" Instead, they are optimizing for coherence, fluency, and the statistical patterns they’ve learned from human writing. Since em dashes often appear in contexts where writers are connecting related thoughts in a lively, natural tone, the models tend to reproduce that habit.
In particular, em dashes are useful in:
Softening transitions between clauses
Introducing clarifications or examples without breaking rhythm
Creating emphasis in a less formal, more inviting way than parentheses or colons
Thus, the heavy use of em dashes isn’t an efficiency trick — it’s a style choice, one picked up through exposure to countless examples of human prose.
A Quick Historical Aside
Interestingly, the em dash itself has a long history in English typography. Emerging prominently in the 18th century, the em dash became a favorite of authors like Emily Dickinson, who used it liberally to convey sudden breaks in thought and emotional nuance. Over time, its versatility made it a staple in both formal and informal writing — a tradition that AI, unwittingly, continues today.
The Bottom Line
While it’s tempting to assume that AI’s choices are coldly optimized for speed or space, the reality is often richer and more human. The prevalence of em dashes in AI-generated text isn’t about computational shortcuts. It’s about stylistic fluency, learned from the best (and quirkiest) of human writing.
The next time you see an em dash casually bridging two ideas in an AI's response, appreciate it for what it is: not an engineering hack, but a tiny echo of centuries of literary tradition — and a reminder that even in the world of algorithms and neural nets, the art of communication still matters.
