Keeping the buzz in buzzwords

A thought-terminating cliché limits conversation by capturing a complex (but potentially debatable) subject within a reductive term or phrase. Merlin Mann references this idea in episode 164 of Back to Work when discussing curiosity and buzzwords.

Thought-terminating clichés can be used to avoid discourse on a subject: by never unpacking the components of an idea that are debatable, those components go unexplored. They can also be exploited to veil ignorance or illogic—the speaker can state the complex term and allow the implication to have impact without contextualizing/explaining it while the intimidated audience shies away from critique or questioning.

This explanation makes the phenomena seem villainous, but many of us are prone to committing these crimes—through buzzwords! Buzzwords are terms that catch on because they represent something exciting to a discourse. Then, because they’re popular, they get used frequently, by many people. Because they are somewhat novel, these different uses attach slightly different meanings to the same word. Eventually the buzzword’s overused (reducing the novelty, and therefore the impact of its meaning) and/or overloaded with meaning.

Most of our buzzwords were real things at one point (and sometimes they still are). When buzzwords are used effectively they allow a good conversation to move faster between speakers who have the same mental models about the buzzwords.1

Sometimes, however, buzzwords are said to represent concepts that aren’t fully understood by everyone in the conversation. When my meaning of the word “design thinking” differs from yours, but we both refer to design thinking in conversation nonetheless, we can run into trouble.

In these situations, buzzwords obfuscate the ideas we’re actually talking about. In my experience, we also know when we’re using buzzwords. We can guess at when others are using them, too. As a result, the conversation loses meaning, and we lose trust in the conversation.

Buzzword meaning space. The three colored shapes are three different meanings attached to the same buzzword.

Dealing with buzzwords

So what can we do?

Well, the easy thing to do is to clarify. When you use a phrase with many potential interpretations, try to clarify how you’re using the phrase. When others use words that may have multiple meanings, ask specific questions about what they actually mean. This clarification might seem like extra work, but it only needs to happen when terms are first invoked—and it’ll prevent lost time and energy due to the consequences of thought-termination later on.

More importantly, though, we should try to avoid thought-terminating clichés altogether. Take time to break down the concepts you’re talking about in concrete terms. Explain them in ways you haven’t heard before to avoid relying on trite metaphors and anecdotes. If you can really get at what you mean, your language will be minimally re-interpretable: that is, it should be near-impossible to understand your explanations differently from how you intended.

As a result, your communication will become more impactful. The conversations you participate in will have more novelty, too, making it more exciting to discuss the ideas you’re sharing. This may result in more buzzwords emerging, but that’s okay—use the same approach to break those down, too.

  1. See the excellent Notes on the Role of Leadership and Language in Regenerating Organizations for more on this.

    Next → → “This is Sticking with Them:” Professor Explores Benefits of Model-Based Learning Through model-based learning, students use diagrams as a way to think about and reason with systems—and to think about how complex systems interact ← Previous → README.txt: Introducing Into the Dataverse, the article series There is a significant gap in research about Canadian data collection activities on a granular scale. This lack of knowledge regarding data
    Latest posts
    Intuition is confident abductive-inferential thinking
    The Verge → Researchers detail huge hack-for-hire campaigns against environmentalists
    Conversations, cybernetics, and Theory of Mind
    → Why are we exceeding the Earth’s carrying capacity?
    IDEO U's Creative Confidence Podcast → Roger Martin, Bianca Andreescu, and systemic strategy
    Reuters → Systemic lessons from South Korea’s Patient 31
    Axle → Divide & conquer
    FSG → Can Snow Clearing Be Sexist?
    The Verge → As Lambda students speak out, the school’s debt-swapping partnership disappears from the internet
    The Talk Show → “Bring It On, Haters”, With Special Guest Ben Thompson
    Facebook → Starting the Decade by Giving You More Control Over Your Privacy
    Motherboard → Leaked Documents Expose the Secretive Market for Your Web Browsing Data
    The Verge → Google’s ads just look like search results now
    MacMillan → Interference by Sue Burke
    Systemics and design principles in support of Tiago Forte’s PARA framework
    → Microsoft wants to capture all of the carbon dioxide it’s ever emitted
    → US announces AI software export restrictions for China
    → Science Conferences Are Stuck in the Dark Ages
    → This wireless power startup says it can charge your phone using only radio waves
    → Segway’s newest self-balancing vehicle is an egg-shaped wheelchair
    → Twitter announces Bluesky: a team seeking and developing an open standard for social media
    → Elon Musk attempts to explain Twitter to normal people in court
    → TED and YouTube launch global climate initiative
    → Embracing multilingualism to enhance complexity sensitive research
    → The ‘Amazon effect’ is flooding a struggling recycling system with cardboard
    → John Kerry, Arnold Schwarzenegger wage ‘World War Zero’ on climate change
    → Combining semantic and term frequency similarities for text clustering
    → Bad RCS implementations are creating big vulnerabilities, security researchers claim
    → 2019 Tech Trends Report — The Future Today Institute
    → Medical Crowdsourcing: Harnessing the “Wisdom of the Crowd” to Solve Medical Mysteries
    → Report Launch - OPSI Primer on AI for the Public Sector