“Clichés, stock phrases, adherence to conventional, standardized codes of expression and conduct have the socially recognized function of protecting us against reality, that is, against the claim on our thinking attention that all events and facts make by virtue of their existence.” – Hannah Arendt, The Life of the Mind

I’ve always been fascinated by language. I have a Bachelor of Arts and a Masters in English Language and Literature, including courses in American, European, and “World” literature, composition, linguistics, and philosophy. Paired with an undergraduate minor in History and a teaching degree, it’s no surprise that I often think about language and its connection to history and politics.

Like many taxonomists, I fell into this profession I didn’t even know existed. I never planned to be a business taxonomist, but I don’t think any other profession has quite captured my interest in language and keeping things organized quite the way taxonomy has. Taxonomists are typically methodical researchers, language savvy, and excellent at working with people. Many, but not all, come from a library science background.

I wonder, on nearly a daily basis—and especially at this moment in time—what our role as taxonomists is when building out semantic models. What is truth? Is there truth with a capital “t”? What are the ramifications of the words we choose as taxonomy concepts and the way we model ontologies? What power, if any, do we have in shaping thought and should we? Big questions, to be sure. But in those big questions, there are some very real consequences of our work. I believe we have the power to be conscientious at a minimum and thought-shapers with concerted effort.

You’ve Been Doing [Something] Wrong

I have never been a fan of clichés or hackneyed expressions no matter how accurate or timeless they are. Our pop culture world is full of them, from clickbait headlines to movie posters to commercials. Clichéd language is easy, familiar, and readily available. So easy, in fact, I wonder if we even really think about the meaning of these expressions anymore.

There’s a wonderful word I discovered a few years ago that describes a particular type of cliché, the snowclone:

“A snowclone is a phrasal template based on a cliché, substituting words to express a similar idea in a different context, often to humorous or sarcastic effect…The term snowclone was coined in 2004, derived from journalistic clichés that referred to the number of Inuit words for snow. The linguistic phenomenon of “a multi-use, customizable, instantly recognizable, time-worn, quoted or misquoted phrase or sentence that can be used in an entirely open array of different variants” was originally described by linguist Geoffrey K. Pullum in 2003.” (Wikipedia)

You already know exactly what a snowclone is because you’ve heard so many of them:

• The mother of all X,
• In space, no one can hear you X,
• X is the new Y,
• Have X, will travel, and
• X as a service.

In recent use, two of these snowclones—or to use a nuanced synonym, memechés—have been doing their best to drive me mad. The first is, “You’ve been doing X wrong.” I know it’s not deliberately directed at me, but I find it personally offensive in the insinuation that I am somehow so clueless that I’ve been doing so many things incorrectly my whole life. Since misery loves company (sigh), it only makes me feel slightly better that all of you have also been doing so many things wrong. Perhaps my favorite example was the email headline I received a few weeks ago claiming, “You’ve been sleeping wrong.”

The second, and this will speak to a larger point, is, “It’s not x, but y.” While negative parallelisms have been so long in use as to be cliché, there is also the overuse of such structures by LLMs:

“As a distinct element of style, however, it gained attention only in the 2020s when it became apparent that large language models (LLMs) such as ChatGPT use negative parallelism inordinately often (about three times more frequently than humans), to the point that such constructions came to be seen as a hallmark of machine-generated text.” (Wikipedia)

Memechés are the new clichés, but we’ve always had language that has become patterned and overused. Such use of language is to be, or not to be, but has never really been concerning enough to raise alarm bells. Until AI.

The Ouroboros and Model Collapse

Years ago I read a fantastic article about the death of journalism. Or, rather, journalism becoming a monoculture in which there were fewer and fewer media outlets, a polarization of the ones that still exist, and the reliance on single authorship and reuse from sources like the Associated Press (AP). It occurred to me even then that a lack of diversity of news sources would lead to a homogenization of viewpoints and facts. Perhaps with the ubiquity of self-publishing on social media and a distrust of traditional news outlets (actively fostered through misinformation campaigns), we actually have the opposite: so many varieties of truths and untruths as to be unable to determine fact from fiction, truth from falsehood.

The decline of investigative, fact-driven journalism has brought with it a polarized monoculture of thought, a dearth of interesting and novel ideas, and a replacement in the form of opinion and belief as fact. Without going into a deep dive on French Postmodern thought, the flattening of truth and the use of language as political power is not just philosophy (X), it is reality (Y).

I have been thinking if thoughtful content has been streamlined to surface homogenized ideas, and this homogenized content is food for LLMs, and LLMs in turn produce more homogenized output, then our bots are the electronic ouroboros, eating its own tail until it disappears into a point. In other words, garbage in, garbage out.

I felt absolutely vindicated in my thinking when I came across the article, “AI Is Becoming a Monoculture”, by Ayoub Nainia. I won’t summarize the whole article, because it is well worth the read, but I will focus on the notion of model collapse.

“Models trained on recursively generated data degrade, generation after generation, and the first thing to vanish is the tails of the distribution. The rare, the unusual, the outliers, the very diversity that gave the system its range, all of it erodes first, until the model converges toward a bland and increasingly wrong average.”

A monoculture of training data, and especially training data created by and then consumed by the models, leads farther and farther away from originality. The model may not be incorrect per se, but the idea of creating new and novel ideas may be harder and harder to achieve. Our LLMs are middling, averaging, and homogenizing their inputs.

Hierarchies as Power, Rhizomes as Truth

Ok, I said I wouldn’t say much about French Postmodern philosophy, but I will say this: Michel Foucault saw hierarchies as power structures dominated from the top; Gilles Deleuze and Félix Guattari (the absolute punk rockers of French Postmodernism) saw rhizomes as decentralized structures of connected points. Taxonomists should see the parallel right away: taxonomies are hierarchical and more or less rigid; graphs, and the ontologies and taxonomies built on them, are decentralized rhizomes. I’ve written and presented about this topic several times: Knowledge Graphs and Their Punk Rhizomatics, Why Graphs? Transcending the Limits of Hierarchical Thinking (with Bob Kasenchak), and Using Structure in Knowledge Organization. 

If taxonomies are hierarchical power structures, are taxonomists fascists? We do, after all, advocate for strong central governance and control and rule over a fortified complex of taxonomies and ontologies that only a few may enter. Are we benign dictators? Well-meaning autocrats?

If language, politics, and power are hopelessly entwined and the role of the taxonomist is to model domain truth, then you have power. You have both hierarchical fascist power and punk rock rhizomatic power. With every concept label choice and modeling decision, you advocate for truth and facts. Perhaps not capital “t” truth, if such a thing exists, but researched, fact-based truth. Truth to power. In the world of “X as a service”, go do taxonomy as a service. Make it a fact-based, truth to power, rhizomatic service. Make your service in the service of balancing probabilistic statistics with LLMs fed on deterministic semantic models. Be a part of the neurosymbolism. Fight brainrot.

We might not write the words that make the whole world sing, but we build the semantic models that feed the hungry ouroboros.