Orwell and the Jargon That Passes for Explanation

Why the Phrase “Gungmin Jeongseo” Bothers Me

“It doesn’t fit gungmin jeongseo (national sentiment).”

I feel uneasy every time I hear this line. It’s hard to know exactly whose reaction, or what kind of reaction, it’s describing. The phrase lets someone end a debate without ever saying how many people object, or to what.

I was thinking about a similar problem while reading George Orwell’s 1946 essay “Politics and the English Language.” Orwell argued that vague language doesn’t just fail to convey a thought clearly — it can also stop the speaker from thinking clearly in the first place. Read the original essay

This critique isn’t aimed only at politicians. It made me think about the consulting documents and AI explanations I write myself. It made me ask whether I’d ever mistaken a familiar term for an actual explanation.

Applying Orwell’s Four Complaints to Everyday Work Writing

Orwell took issue with stale metaphors, wordy phrases standing in for simple verbs, pretentious vocabulary, and words with no clear meaning. Here’s what happens when I apply that framework to Korean business writing.

When a familiar metaphor stands in for an explanation

Reading a line like “we will open a new horizon of growth” gives you a positive feeling. But it’s hard to tell whether the company means acquiring more customers or entering a new country. Stating directly what you plan to do removes the burden of guessing from the reader.

When a phrase stretches out something that could be said briefly

A sentence like “we plan to conduct a review to solve the problem” leaves a lot undecided. It’s better to state who will review what. I think naming the actor and the object of an action matters just as much as trimming the sentence itself.

When jargon appears without explanation

Using a term like “AX” or “digital transformation” doesn’t automatically make a plan concrete. You still have to explain whether you’re introducing AI into customer service or changing inventory forecasting. A term that feels familiar inside an industry may not be familiar to the reader at all.

When a phrase sounds good but sets no standard

An expression like “customer-centric” is easy for anyone to agree with. But a team trying to shorten refund procedures and a team trying to push more product recommendations can both use the exact same phrase. Unless you spell out what choices the phrase actually implies, it’s easy to mistake it for genuine agreement on a shared goal.

Changing the Words Can Blur Who’s Responsible

Orwell also pointed to the way violence — bombing, forced relocation — gets described in neutral-sounding administrative terms. When the actual act isn’t named directly, it becomes harder for the reader to picture its real consequences. Orwell’s essay

I feel a similar discomfort about the phrase gungmin jeongseo. If someone explains whose opinion was checked, and how, that claim can be examined. But framed as the will of an entire nation, it becomes almost impossible to ask for evidence.

Corporate documents show the same kind of responsibility-blurring language. A sentence like “a schedule change has occurred” drops out who changed it and why. What the reader often needs isn’t just the fact of the change but the reason and the new schedule. Writing clearly, I think, is a way of giving the other person the information they need to make a judgment.

Writing Principles Exist to Convey Meaning, Too

Orwell closes his essay with six principles. In my own words, they come down to this:

• Don’t reach for a metaphor just because it’s familiar.
• Choose the shorter word if it conveys the same meaning.
• Cut any word that isn’t doing work.
• Look for a way to use the active voice.
• Don’t insist on jargon if you can explain it in plain language.
• Break any of these rules before writing something outright barbarous.

That last principle should be read as a warning against applying the previous five mechanically. I think this point matters a great deal. If you shorten a sentence to the point of cutting explanation you actually need, you can end up making it harder to understand, not easier. And a metaphor or a technical term still has a place if it conveys meaning more precisely.

Oswarld’s Lens

The first time I read this essay, I felt genuinely unsettled. I work with AI and data every day, and I use words like “AX,” “AI transformation,” and “data-driven” constantly. There have been times I moved on without fully explaining what, concretely, I meant to change.

Doing GTM strategy consulting, I’ve repeatedly noticed a connection between the language a team uses and the clarity of its execution plan. Teams that describe their goals concretely tend to be the ones that also know clearly what needs to be done.

For example, “we will revolutionize the customer experience” and “we will cut onboarding time from 72 hours to 6 hours” raise entirely different questions. The second phrasing forces a discussion about which stage is slow, what needs to change, and how “completion” will be measured. What matters isn’t attaching a number for its own sake — it’s making the actual target of change explicit.

I think this newsletter should be held to the same standard. What matters first isn’t whether a sentence sounds convincing, but whether a reader could explain back what it means. And when I’m describing something I experienced myself, I need to show what situation I was in and what I actually observed to reach that judgment.

This problem doesn’t disappear when you use generative AI. When a smoothly flowing sentence comes back to you, it’s easy to feel like your thinking has been organized. But sometimes all that’s really happened is that words like “innovation,” “transformation,” and “new possibilities” repeat themselves while no actual content fills in behind them. The fact that a text can be produced quickly doesn’t remove the need to check it.

When I look at a sentence AI has polished, I try to ask myself: is what I meant to say still in here? If making something easier to read ends up erasing the original judgment or experience behind it, that’s not good editing. I try to start by checking whether it’s still a sentence I could explain again in my own words.

The author is Oswarld (Kwangseob Ahn). Current roles: Adjunct Professor at Sejong University, Strategy Consultant at INLEVEL9. Career, research, books, and recent work are kept current on the About page. Latest · July 2026: HEMA-2: A Consolidation-Aware Tri-Memory Architecture with Multi-Channel Scheduling for Lifelong Conversational AI.