What an interesting and strange article. The author barely offers a definition of "systems thinking", only names one person to represent it, and then claims to refute the whole discipline based on a single incorrect prediction and the fact that government is bad at software projects. It's not clear what positive suggestions this article offers except to always disregard regulation and build your own thing from scratch, which is ... certainly consistent with the Works In Progress imprint.

The way I learned "systems thinking" explicitly includes the perspectives this article offers to refute it - a system model is useful but only a model, it is better used to understand an existing system than to design a new one, assume the system will react to resist intervention. I've found this definition of systems thinking extremely useful as a way to look reductively at a complex system - e.g. we keep investing in quality but having more outages anyway, maybe something is optimizing for the wrong goal - and intervene to shift behaviour without tearing down the whole thing, something this article dismisses as impossible.

The author and I would agree on Gall's Law. But the author's conclusion to "start with a simple system that works" commits the same hubris that the article, and Gall, warn against - how do you know the "simple" system you design will work, or will be simple? You can't know either of those things just by being clever. You have to see the system working in reality, and you have to see if the simplicity you imagined actually corresponds to how it works in reality. Gall's Law isn't saying "if you start simple it will work", it's saying "if it doesn't work then adding complexity won't fix it".

This article reads a bit like the author has encountered resistance from people in the past from people who cited "systems thinking" as the reason for their resistance, and so the author wants to discredit that term. Maybe the term means different things to different people, or it's been used in bad faith. But what the article attacks isn't systems thinking as I know it, more like high modernism. The author and systems thinking might get along quite well if they ever actually met.

I have a bone to pick with the paragraph:

> But, as we now know, the results were also wrong. Adjusting for inflation, world GDP is now about five times higher than it was in 1970 and continues to rise. More than 90 percent of that growth has come from Asia, Europe, and North America, but forest cover across those regions has increased, up 2.6 percent since 1990 to over 2.3 billion hectares in 2020. The death rate from air pollution has almost halved in the same period, from 185 per 100,000 in 1990 to 100 in 2021. According to the model, none of this should have been possible.

Okay, forest cover increasing and death rate from air pollution decreasing contradicts the prediction from 1970, but I feel these trends are a result of richer countries being able to outsource their environmental pollution/destruction to the global south and scavenging it for raw materials. I wonder if the forest cover statistics count the massive expanses of land deforested and replaced with monoculture plantations (palm oil, etc.) that end up having a giant effect on biodiversity (and will no doubt come back to bite us in the ass)? Even if this outsourcing of externalities couldn't be modeled 50 years ago, I feel like that doesn't detract from the spirit of the takeaways from the Club of Rome and The Limits to Growth.

This insight - that modeling human systems is hard because humans also respond to models of their world and then change it - is not all that new, it's called reflexivity [1] and has been around for about the same time as systems thinking.

[1] https://en.wikipedia.org/wiki/Reflexivity_(social_theory)

This is actually a critique of massive bureaucratic systems, not systems thinking as a practice. Gall's work is presented as an argument against systems thinking, while it's a contribution to the field. Popular books on systems thinking all acknowledge the limitations, pitfalls, and strategies for putting theory into practice. That large bureaucracies often fails to is, in my view, an unrelated subject.

I used to suffer from analysis paralysis when designing even basic things, be it software engineering or my next week's schedule. After all, paraphrasing, "Everyone has a plan until they get punched in the face".

I found it much better to take the first step and progress from there, even when the full solution is not known. Maybe it's a testament to the limits of my own context window. Having said, I'm not advocating for abandoning architecture or engineering principles. I like the idea of "Growing software" [0]. It's perhaps a more holistic metaphor.

In terms of short circuiting large bureaucracies, I found "Fighter Mafia" [1] to be an interesting example of this. A group of military officials/contractors managed to influence aircraft design, somewhat outside of the "official" channels. The outcome was better than if it went through normal channels.

[0]: http://www.growing-object-oriented-software.com

[1]: https://en.wikipedia.org/wiki/Fighter_Mafia

This article does not begin to cover systems thinking. Cybernetics and metacybernetics are noticably missing. Paul Cilliers' theory of complexity - unmentioned. Nothing about Stafford Beer and the viable system model. So on and so forth.

The things the author complains about seem to be "parts of systems thinking they aren't aware of". The field is still developing.

The citation to the beer game is a pretty fun one. About 15 years ago, John Sterman (a Forrester disciple) held a beer game "world championship" at a system dynamics conference, and my mother and I brought what we think is the optimal strategy and completely dominated the competition. Ironically, if you apply "systems thinking" in the right way, the beer game is a relatively simple thing to play extremely close to optimally. You can recognize that only one player can make choices that matter for the final outcome of the game, and then eliminate most of the claimed dynamics. The issues with systems thinking mostly show up with people being dumb panicky apes and with the pilot/modeler not understanding the system. The math works if you let the math work for you.

I'm glad that the author mentions Systemantics because their line of thinking seems heavily influenced by that book. I noted all the main ideas here: https://biodigitaljazz.net/systemantics.html

I just want to know if there exists a Factorio mod that changes the graphics to the cutesy, minimalist assets shown in the topmost image.

The article is right to be critical of "systems thinking", but only because people who advocate "systems thinking" usually don't have a concrete definition of "system" or any unique method of thinking.

The complicated systems that are alluded to here, are usually best modeled as optimizers or control systems. Both have clear definitions and vast mathematical corpi.

In a house with heating, it's difficult to cool the whole house or even a single room by leaving the freezer door open. Why? because the system is programmed to be a certain temperate and has a mechanism continuously driving it to that temperature. It's difficult to knock over one of the Boston Dynamics robots for the same reason.

If the government declares that rents cannot be higher than a certain price per square foot, then mysteriously only the renters with impeccable financials and renting history will be able to get houses. And some houses will stop being available for rent. Why? Because the market is optimizing for value creation. Honest, considerate renters devalue the property less during their stay, and some properties are worth more than the maximum rental price when used for another purpose. If you limit the price, agents will fallback to other mechanisms to determine the most valuable course of action. In this example that is minimizing missed payments, evictions, and property damage.

Unless you affect the controller or optimizer hidden in each system, you can't manipulate the system effectively. Usually you aren't able to do this, and so the system is difficult to control. It's easier to rip out a thermostat than to disable the desire of millions of humans to create value. If you can't model the system in a rigorous way, and then use math to predict and explain it, then you won't be able to manipulate it. Saying that you are using "systems thinking" won't change that.