Full of types

I’m obsessed with this essay “Raising a person in a culture full of types” by Dan Brooks. Before we get to the author’s message, let’s take a moment to appreciate his sense of comedic timing, e.g.:

My son talks incessantly about VSCO girls and Karens and other categories of people he has learned about from YouTube. He described a classmate as “the kind of person who borrows your pencil and doesn’t give it back,” i.e. she borrowed his pencil and didn’t give it back. For a while he tried to propagate a type of his own invention, “the Suzan,” whose behavior was ill-defined but tracked closely with that of my mother of the same name. It did not catch on, and eventually he concluded that he was not the kind of person who could come up with memes.

Is it just me, or is this a highly clever paragraph?

Brooks’s point, expressed better there than I will here, is that our culture’s emphasis on “being“ over “doing” prevents us from separating people’s actions from their destiny. At best, the idea that people belong to fixed, inescapable categories is merely the antithesis of the growth mindset; it saps motivation from our desire to try new things (why learn programming if I am not a “math person”?). At worst, as Brooks points out, “The illusion of a fixed nature gives us an excuse to repeat bad behavior,” because every mistake is like a movie trailer for the rest of your life. And like a TV commercial, the fixed mindset is an illusion with a slope (sorry): it inclines us toward the most automatic decision instead of assessing the alternatives on their merits.

I will not pretend to be a paragon of the growth mindset. I talk myself out of good ideas, such as learning how to actually cook, all the time. But if I could choose to have one impact on the world, it would be to motivate those around me to reject limiting beliefs and embrace challenge—even at the risk of failure. And if linking you again to this essay, which has a wonderful subplot about fatherhood, is the way to do it, then, OK.

Jekyll plugin to recommend related posts

I wrote my first plugin for the Jekyll static website builder: a tool that recommends related posts at the end of each page. It determines the similarity between post pairs using a fairly unremarkable token-counting algorithm, so it’s fast enough to rerun on every site build. You can configure the number of posts to recommend and a parameter factor which determines the algorithm’s sensitivity to rare vs. common words.

I made a little demo of the plugin with a fake blog whose posts are the articles of the UN Universal Declaration of Human Rights. You can also see a demo on the current version of this site if you click the “read more” link below to go to this post’s individual page. I think it works pretty well!

Read more →

Some things I tried recently

Kagi Search: It’s a paid search engine that promises to give better results than Google and friends. Indeed, the search results are a little more relevant, especially when researching technical topics. I made great use of the ability to filter and promote entire domains. However, the pricing doesn’t work for me: $5/month gets you 300 searches, which isn’t enough (I burned through the free 100 searches in a week), and for unlimited searches, you have to pay $10 for a bundle deal that also includes AI stuff I don’t care about. Kagi wants to become an everything app (probably adding email soon), which a tough sell while claiming to be a privacy-focused company. (Same issue with Proton, by the way.)

Fender Studio: Fender, the guitar company, just kind of threw this over the fence in May. It’s a free (but not open source) digital audio workstation, so it competes with the likes of Ardour and GarageBand. But Fender Studio runs on Linux, and quite well at that. On my machine, it supports JACK with minimal configuration and achieves lower latency than Guitarix while doing a lot more. The vendored backing tracks are a bit cheesy but well engineered.

Proselint: It’s a prose … linter, i.e. you feed it your draft blog post and it complains about vague wording and common typography problems like curly vs. straight quotes. I like that Proselint uses regex instead of an LLM, so there’s no creative interference; it’s more like an automated style guide than a chatty editor. But my homegrown typography.py script (I need to upload this to GitHub sometime) enforces a few lesser irks, such as en dashes in numerical ranges, that Proselint lets be, so I’m still using both.

CLS advice nobody asked for

Awesome people occasionally reach out to ask me about the US State Department’s Critical Language Scholarship (CLS) program. I participated in CLS Korean in 2016, and I still find myself learning from the experiences I had in Gwangju all those years ago (and that’s with four additional years of living in Korea and several visits in between).

This year’s CLS cohort is getting started now or so, so I thought I would write up a couple of tips for making the most of the program that I’ve collected and shared over the years.

1. Contribute ideas for activities to do with your language partner, because they may run out of them before long. Your outsider perspective might generate interesting adventures like visiting a family with young kids or sneaking into a college lecture.
2. Embrace a Zen attitude with respect to the language policy. Understand that some cohort members may need space to process new experiences and cultural differences in English; this doesn’t mean they are not getting the most of the program. Language acquisition doesn’t have to be your only goal. (Context: CLS is famously an immersion-based program and requires participants to sign a language pledge saying that they won’t use English for the duration or the program. In retrospect, I was too much of a stickler about it.)
3. Identify and recognize your own stress responses and consider how they may contribute to or ameliorate the stress experienced by others. This is especially true for “elder” CLS participants (grad students and up), whom younger participants tend to see as role models in adapting to unforeseen challenges.
4. Buy an umbrella in Korea and thank me later.

And please email me if you are on CLS this year and have any stories to share! I still have a few posts around from my CLS days, but nothing profound.

Is using a thesaurus cheating?

I remember taking mild offense when my middle school language arts teacher introduced our class to the thesaurus. I thought, if I let the thesaurus choose my words for me, then is it even my writing anymore? This seems like a flaw in my temperament: I always regard technology with suspicion when it threatens to supplant human creativity.

Inevitably, as I progressed through high school and college, I made peace with the thesaurus, and now I rely on it. A typical use case would be: “What’s that word that means deferential but like, in an obnoxious way?” I plug the obvious profanity into Merriam-Webster and it hands me back obsequious. I’ve trained myself not to regard it as a creative failure if I accept this sort of help. After all, it’s not like the thesaurus tells me which word to use; it just brings it forth from the tip of my tongue.

OK, so this post had to be about generative AI, right? After a few years of watching the world use and abuse large language models, I’m beginning to find ways to accept an LLM’s assistance without feeling like I’ve outsourced my creative process. Mostly, I use LLM chat as a better search engine. For example, one of my first questions was “Is there a NumPy built-in that does this?” with a quick example. The machine pointed me immediately to numpy.unravel_index(), which was exactly what I needed. It would have taken me much longer to get to the same answer with Google.

Sometimes, I have tried more involved discussions with the chatbot to improve my understanding of a technical concept. In lengthy conversations, I try to put a lot of thought into my questions. I ask the LLM to check my assumptions, issue corrections, and supply keywords I can look up in an official reference—but never to generate code, text, or ideas. (Sometimes it does that anyway, which I find highly annoying.)

“We use tools to embody their virtues,” writes Fernando Borretti. I guess I value authenticity or craftsmanship—my fingerprints on the finished product—more highly than laying down as much code or text as I can in a fixed amount of time. This value judgment (and it really is just that) precludes more aggressive uses of LLM tech that, yes, might make me more productive in the short term. I’ll own that tradeoff. When it comes to new technology, we often speak of “early” and “late” adopters—as though tech literacy means no more than finding the smooth part of a hype wave. My goal is to adopt tools not on the basis of urgent marketing or the fear of being left behind, but because I can use that tool to make myself smarter.