Romello Goodman, writing in the latest Logic(s), talks code and scale through a professional history with online obituaries and guestbooks, and hits at what happens when the systems in which we find ourselves living grow too large to any longer be fully human.

When companies design at scale they fail to see how each person’s interaction with their application is different. Or how each person’s experience and concerns are unique. These companies sand down the edges that make a person unique and, instead, turn them into a user whose behavior they can track and ultimately change—placing the desires of the company ahead of the user. For these companies, directly communicating with people who use their applications is too complicated. It’s easier to remove user desires from the conversation altogether. Other than opting out, there’s no real choice for people using the applications.

It put me a bit in mind of the A.I. industry’s notion of the median human (which I mentioned earlier), itself something of a kind of iteration on the so-called Reference Man. Beyond a certain limit, people get flattened into data. In the age of the algorithm, we’re even essentially trained how to more closely match the modern-day reference man with our behavior.

Clare L. Evans, writing for Grow, examines a potential distinction between scale (else production) and growth—the latter term having been misappropriated as a synonym for the former.

What the business world calls “scalability,” however, is precisely the capacity to expand without change, like a fractal — or a fast food franchise. […] In the name of progress, Tsing observes, we call such expansion “growth,” as though we were speaking of something alive. But it’s not alive; it’s a cousin of death, and it has made life, with its nonscalable elements […] seem like an impediment, a spanner in the works grinding the great churn of expansion to a halt. The great Canadian physicist and educator Ursula Franklin makes a similar observation in her book The Real World of Technology, contrasting “growth models,” systems in which things develop naturally to an appropriate size and scale, with “production models,” systems in which things are produced under controlled, predictable parameters. The key distinction: “growth occurs,” Franklin writes. “It is not made.”

This wasn’t meant to be a post about blogging, but, sure: writing regularly on your own site is a way to “normalize being whole persons” in the face of a communications and technology landscape that wishes you’d do otherwise for ease of calculation. Here, we can interact with each other in our own places and times, absent the algorithmic behests of trying to be social “at scale”.

Dunbar’s number might be oversimplified but nonetheless still feels generally right from our own lived experience. None of us is Reference Man, and we should take every opportunity to keep the rough edges that come from actual growth.