Resilience engineering has a working definition that I'm fine with adopting. But I want to get a bit more into what exactly resilience engineering is creating, if engineering is an act of creation.

The benefits of feedback are central to the cybernetic age we inhabit.

Clearly these two thinkers, despite their differences, chime. That is what I want to celebrate here.

What is the technical essense of AI systems, whether we’re discussing GOFAI, early connectionist models, or the deep learning methods prevalent today?

It’s time to stop referring to “generative” AI as creative. That fact of the matter is that there is nothing creative about Gen AI, and we all know it. The abstract models instantiated in computers don’t produce anything new, don’t genuinely create anything, and in principle never can.

For my purposes, I use the term “technosolutionism” here to refer to the idea in a capitalist economy that some given techne now available for purchase will solve its buyers’ problem(s). In other words, a given commodity has a use value. My experience has led me to be very critical of this idea…

The Trump administration, in its 2025 manifestation, is dead set on harming many. In this post I will focus on the harm they seek to do to trans people. I find it their goal unacceptable and repulsive, and urge other people of good will to join me in condemning and opposing it.

I’ve some mixed feelings about writing on this topic. The reason is that it’s so ordinary to solve problems that it’s almost not worth talking about. What is life, after all, if not the continual creating and solving of problems? And death simply what one calls a problem that one couldn’t solve? But a theory of problem-solving may itself be useful for solving some problems, so here we are.

Where does data come from and what does it mean?

There’s obviously a story to tell here about the construction of sophisticated storage methods, from old clay tablets in Mesopotamia to S3 buckets in AWS. That story is bound to include the history of writing techniques. A section of it would focus on cybernetics and information theory; perhaps it would cite Bernard Dionysius Geoghegan’s book Code. That might be because the 20th century was obsessed with language. That obsession remains with us today in a now-passé term “big data,” and the technology referred to as “Artificial Intelligence.”

This is what I’m getting at when I talk about noology as central to economic life today. I hold that we are called to attend to many more things than previously due to certain changes in our lifestyles, and those calls to attention effect continual learning and thinking. We’re continually forced to change against our will and to our detriment.

My basic premise is this: software works in a capitalist economy because it’s fundamentally a commodity. The code or “IP” isn’t the commodity, though; it’s the experience that code produces for customers and users. The business that owns the software uses it to provide its service.

In this post I want to focus on the book’s third chapter, Figures in the Soil. It is here that Harvey and Knox dwell on the topic of mathematics and data in the work of producing a road. I think this is important because it says something about how agents and institutions use math, and numbers more generally, and thus reveal something about their cultural values. It serves as a great touchstone, for me, as I consider how software engineers and their organizations use numbers.

The idea of a second victim, as far as I can tell, comes from the field of medicine when an MD named Albert W Wu wrote about it in Medical Error: The Second Victim. Over time the concept has come to mean that when an “error” occurs which induces harm, the person or people who serve as proximate cause of that harm are themselves victimized when they feel bad about having done so. They are themselves a victim because that behavior which was deemed an error is understood to be, in the greater theoretic framework, a result of several contributing factors.

What got me so angry is that this business saw fit to exclude people from the space, probably specifically targeting people living on the street who have used it as shelter at night (i.e. outside business hours). This sucks.

Nietzsche’s model was a Classical idea: the agon, a competition with a determinate winner or loser. For him a win or a loss is fine, so long as one wins or loses well. But what happens when one loses and then loses again? What about when one keeps on losing? Can’t that wear a person down? Even the strongest are only so strong.

Infrastructures are only infrastructures so long as they are useful for some other, primary end. Infrastructures are never ends in and of themselves.

I want to consider the idea that automation, specifically so-called “artificial intelligence,” is somehow immune to this and can provide a disinterested, impartial way of interpreting events and evaluating candidates for a “root cause.”

The concept of “root cause” has come under a lot of stress in certain parts of the software industry. For instance, take this blog post by Lorin Hochstein from 2021: Root cause of failure, root cause of success.