By Eric P. Harding
It should come as no surprise that I—an editor by trade—love the English language.
I adore the playfulness of words, and frequently trot out whimsical etymologies at parties (much to the consternation delight of my friends).
I enjoy exploring the intersection of technology and language, like how I was able to express two competing thoughts just above thanks to the strikethrough feature of this font set. Don’t get me started on the various languages / code-switching that happens across different communications channels (at least not if you have somewhere you need to be).
Precision! I admire how exacting the English language can be; my fellow word-nerds and I can hold forth on the shades of meaning between “anger” and “ire” till we’ve forgotten the original sentence in question.
At the risk of sounding like a Philosophy 101 student who’s partaken of a particular herb, I can effectively hijack your brain simply by making a few noises, or by showing you some arranged-just-so squiggles on a page. It’s frankly amazing.
I have a confession to make: I was once a staunchly prescriptivist editor. I believed that language was a thing that could be wrestled to the ground, defeated—that if I set up enough guideposts, the end-product that I was editing would be “correct.” In my dotage, though, I find myself more firmly in the descriptivist camp: I can offer my insights on best practices at the moment based on audience and intent, but so long as the meaning of the message is conveyed, who am I to say the trappings are “wrong”? (I came to this position largely out of expediency; language evolves, whether I want it to or not, and I want to understand what the heck my kids are talking about.)
Yes, mine has been a lifelong love affair with language. I wouldn’t have it any other way.
This issue’s features all concern themselves with the nuances of language in some fashion—some obvious, some a little more hidden.
In “Artificial Untelligence,” author Jim Lynch takes ChatGPT for a whirl. This much-ballyhooed technology—an AI-trained large language set that can draft blog posts and hold conversations—has been getting plenty of headlines lately, with some fearing that this chatbot is going to supplant human writing. Not so fast, Lynch opines—while the tech has its uses, it’s not going to sideline the professional wordsmiths anytime soon.
“Lingua Mathematica” is our second feature this issue. It offers a deep dive into the language of models, as seen through the lens of metalanguage and applied category theory. Models are ubiquitous in actuarial work; this feature hopes to present an innovative way of looking at the components that make up these invaluable tools.
In our final feature this issue, “Is the World Finally Ready for Nuclear Energy?” author Alyssa Oursler notes that thanks to a handful of tragic accidents, the language we most associate with nuclear power is replete with risk-related terms. But does reality jibe with the notion of danger that “nuclear” connotes? And in a world where the temperature is climbing and extreme weather events are increasing in frequency, are we really going to keep this highly efficient energy source on the shelf?
Thank you, as ever, for reading. Now, if you’ll excuse me, there’s a dictionary calling my name.
