Magical systems thinking

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.

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.

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 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.

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

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.

This essay focuses on a very narrow section of systems thinking and systems theory. There's an entire field, with many different subdisciplines beyond just the Club of Rome stuff (and which influenced them directly) that, quite explicitly also deals with systems that "fight back". In fact, any serious definition of systems thinking usually has said dynamics baked into it—systems are assumed to evolve from the start.

I'd encourage people to look into soft systems methodology, critical systems theory, and second order cybernetics, all of which are pretty explicitly concerned with the problem of the "system fighting back". The article is good, as works in progress articles usually are, but the initial premise and resulting coverage are shallow as far as the intellectual depth and lineage here goes.

Categorize this under a journalist with a passing interest/insufficient research/prejudiced agenda/narrow understanding of a field and making bold statements they're not qualified to make.

Within the current state of the world, we need more systems thinking+research, done with quality, sophistication and in the public. Not less - this article does not help and spreads the wrong ideas.

summary and smackdown by Opus 4.1: https://claude.ai/share/1e8fec5e-ec6a-4c6f-a3d7-b74b0801e5b9

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.

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 studied biology in college and this has always been obvious to me, and it shocks me that people with backgrounds in e.g. ecology don't understand that living systems are unpredictable auto-adaptive machines full of feedback loops. How a bunch of ecologists could take doomerism based on "world models" seriously enough to cause a public panic about it (e.g. Paul Ehrlich) baffles me.

Human cultural systems are even worse than non-human living systems: they actively fight you. They are adversarial with regard to predictions made within them. If you're considered a credible source on economics and you say a recession is coming, you change the odds of a recession by causing the system to price in your pronouncement. This is part of why market contrarianism kind of works, but only if the contrarians are actually the minority! If contrarianism becomes popular, it stops being contrarian and stops working.

So... predicting doom and gloom from overpopulation would obviously reduce the future population if people take it seriously.

Tangentially, everything in economics is a paradox. A classic example is the paradox of thrift: if everyone is saving nobody can save because for one to save another must spend. Pricing paradoxes are another example. When you're selling your labor as an employee you want high wages, high benefits, jobs security, etc, but when you go shopping you want low wages, low benefits, and a fluid job market... at least if you shop by comparing on price. If you are both a buyer and a seller of labor you are your own adversary in a two-party pricing game.

I personally hold the view that the arrow of time goes in one direction and the future of non-linear computationally irreducible systems cannot be predicted from their current state (unless you are literally God and have access to the full quantum-level state of the whole system and infinite computational power). I don't mean predicting them is hard, but that it's "impossible like perpetual motion" impossible.

I also wonder if we are being fooled by randomness when we think we see a person or a technique that yields good predictions. Are good prophets just luck plus survivorship bias? Obviously we forget all the bad prophets. All lottery winners are lucky, therefore lucky people should play the lottery. But who is lucky? The only way to find out is to play the lottery. Anyone who wins should have played, and anyone who loses should not have played.

> largely outside the typical congressional appropriation oversight channels

I've seen it happen more than a few times that when software needs to get made quickly, a crack team is assembled and Agile ceremonies and other bureaucratic decision processes are bypassed.

Are there general principles for when process is helpful and when it's not?

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.

Sounds like the Club of Rome was enamored of Isaac Asimov's Foundation series:

> "The Club of Rome asked an even more intricate question: how would social and economic forces interact in the coming decades? Where were the bottlenecks and feedback mechanisms? Could economic growth continue, or would the world enter a new phase of equilibrium or decline?"

The problem is, as systems grow more complex they often start to demonstrate sensitive dependence on conditions, eg with tiny variations in inputs to one node of the system resulting in wild swings in outputs from that node. Equally problematic, nodes in a complex system can change their connectivity to other nodes if conditions change enough (think of a breakdown in trade between nations due to wars, natural disasters, diseases etc).

The ideal systems to depend on are stable (not hypersensitive to small forcings, with predictable behavior) and have consistent structure. They can still be complicated but should fail gracefully back to simpler structures under stress, eg an emergency power supply for electricity at a hospital that normally relies on the grid.

From this perspective, our electrical grids are well-designed systems - not given to huge power fluctuations - that will nevertheless need major expansions and improvements if electricity demand keeps rising with data centers and eVs etc. However, expanding the grid isn't adding fundamental instabilities, it's just modular addition in the same pattern as the existing system.

In contrast, the USA's current financial-monetary system is not that stable, predictable, or reliable. All kinds of fundamental instabilities exist, and wild swings in behavior under pressure are expected - and since everything else relies on it, eg you can't update the electrical grid without capital input, you risk avalanching catastrophes by relying on such an unstable system.

If you think about it, all thinking is magical (in the sense that we, the universe and any of this exists at all.)

Having said that, there is no magical thinking in asserting that the government is bad at software. The government is bad at 99% of the things it does, but that 1% is keeping stuff running, despite the government trying really hard to fail at that 1%, too.

Stupid comment, I know.

I don’t think the author is accurately characterizing Systems thinking but is closer to talking about something like Agile vs Waterfall. Which i think they’re still correct about, and there has been a sharp turn into waterfall-like thinking (though they will never call it that) in software development recently.

I want to say “prediction is hard, especially about the future” and it is no surprise that the predictions of a model built in the ‘70s might not hold some 50 years later. That they held so well for so long should, perhaps, be the headline.

Does Forrester’s model get updated and re-run?

The suggestion, start with a small system and eventually replace the old one, is what we software engineers do to replace/evolve a legacy system.

Of course, software people have not had much success lately fixing physical/bureaucratic systems.

Great article. I think one missing piece is that if you kick a system too far from its current “equilibrium” it can create self reinforcing loops (rather than kicking back) that lead to uncontrollable runaway.

I like this saying better: every system is perfect until people get involved. People act irrationally because they are reacting to the nonsense that pervades their reality.

Writing an article like this in the current political climate seems extremely reckless

controversial opinion, while learnable to a degree, systems-orientated thought is fundamentally aligned with something biological, either born or developed in early years. People align more with "things" or "people". It's extremely rare someone is truly aligned with both.

If you want to experiment with a version of the world model the article references, you can play with an implementation I put together here:

https://insightmaker.com/insight/2pCL5ePy8wWgr4SN8BQ4DD/The-...

start small or fail big

Wait until "world models" fail to work along these lines. Models are always wrong. They're useful only as interpretations, they can never reproduce, reference, or mimic the events in question.

Another great example is Tansley's ecological systems model that he worked on for over many years with influence from Forrester only for the Odums to develop models, attempt to reproduce them in controlled environments and watch them fail miserably.

The cybernetic, computational, systems, world models are illusions all. AI has the same limitations simply because the infinity of tasks can never be modeled or automated.

Most of the ideas in the article can be seen, very clearly and cleverly narrated, in Curtis's best series "All Watched Over By Machines of Loving Grace" particularly episode 2.

I like this. The author is somewhat needlessly hopeless about the prospects of changing a complex system.

Basic summary is that once you start getting more than a handful of feedback loops, the author through many examples cautions that maps of the system becomes more like physical maps—necessarily oversimplified. When you have four feedback loops under the right control of management, it's still a diagnostic aid, but you add everything in the US healthcare system, say—fuggetaboudit! And because differences at the small scale add up for long term outcomes, the map doesn't let you forecast the long term, it doesn't let you predict what to optimize, in fact, the only value that the author finds in a systems map for a sufficiently complex system, is as a rhetorical prop to show people why we need to reinvent the whole system. The author thinks this works very well, but only if the new system is grown organically, as it were, rather than imposed structurally.

The first criticism is, this complaint about being unable to change a system, is actually too amorphous and wibbly wobbly to stand. Here's what I mean: the author gives the example of the ICBM project in US military contracting as a success of the "reinvent method", but if you try to poke at that belief, it doesn't "push back" at you. Did we invent a whole new government to solve the ICBM project? I mean we invented other layers of bureaucracy—but they were embedded in the existing government and its bureaucracy. What actually happened was, a complex system existed that contained two subsystems that were, while not entirely decoupled, still operating with substantial independence. Somewhere up the chain, they both folded into the same bureaucracy with the same president, but that bureaucracy minimized a lot of its usual red tape.

This is actually the conceit of Theory of Constraints folks, although I don't usually see them being bold about it. The claim is that all of those hacks that you do in order to ship something? “Colleague gave me a 400 line diff, eh fuckitapprove, we'll do it live” ... that sort of thing? Actually, say ToC folks, that is your system running well, not poorly. The complex system is being pinned to an achievable output goal and it is being allowed to reorganize itself to achieve that goal. This is ultimately the point of the whole ToC ‘finding the bottlenecks’ jargon. “But the safeties are off and someone will get hurt,” you say. And they say somewhat unhelpfully, “That’s for the system to deal with.” Yes, the old configuration had these mechanisms to keep things safe, but you need a new system with new mechanisms. And that's precisely what you see in these new examples, there actually is top-down systems engineering, but around how do we maintain our quality standards, how do we keep the system accountable.

If the first criticism is that the “organically grow a new system to take its place” is airy-fairy, the second criticism is just that the hopelessness is unnecessarily pessimistic. Yes, complex systems with lots of feedback loops do maintain a homeostasis and revert back to that as you poke and prod them. Yes, it is really frustrating how to change one thing, you must change everything. Yes, it is doubly frustrating that systems that nominally are about providing and promoting X, turn out to provide and promote Y while actually being X-neutral (think for instance about anything which you do which ultimately just allows your manager to cover their ass, say—it is never described as a CYA, just acknowledged silently that way in hallway conversation).

But, we know complex systems that find new homeostatic equilibriums. You, reading this, probably know someone (maybe a friend, maybe a friend of a friend) who kicked drugs. You also know somebody who managed to “lose the weight and keep it off.” You know a player who became a family man, and you yourself remember instances where you were a dumb kid reliving the same shitty day over and over when you could have just done this one damn thing differently—you know it now!—and your days would have gotten steadily better and better rather than the same old rut. So you know that these inscrutably complex things do change. Sometimes it's pinning the result, like someone who drops the pounds because “I just resolved to live like my friend Derek, he agreed to take me a week through everything in his life, I wrote down what he eats for breakfast, when he hits the gym, how much does he talk with friends and family, then I forced myself to live on this schedule for a month and finally I got the hang of it.” Sometimes it's literally changing everything, “Yeah I lost the pounds because I went to live in the Netherlands and school was a 50 minute bike ride from my apartment either way and then I didn't have any friends so I joined the university's competitive ultimate frisbee team, so like my dinner most days was bought that day after practice in a 5 minute trip through the grocery—a raw bell pepper, a ball of mozzarella, maybe some bread in olive oil—I didn't have time to cook anything big.” Or sometimes it was imposed top-down but with good motivation, “yeah, I really wanted to get a role as an orphan in this musical, so I dieted and dieted with the idea of ‘I can binge once I get the part, but I have to sell scrawny orphan when auditions come round soon’ and like it sucked for two weeks but then I got used to the lifestyle and I no longer wanted to binge, funny how that worked out.”

There are so many different stories, and yes they never look like we would imagine success to look like, but being pessimistic about the existence of the solution in general because there's nothing in common about the success stories, I don't know, seems to throw the baby out with the bathwater. There is hope, it's just that when you are looking at the systems map, people get in this rut where they're looking for one thing to change, but really everything needs to change on that map, you've created a big networked dependency graph of the spaces you need to interrogate to figure out whether they are able to cope with the new way of doing things and, if not, are they going to grind their heels in and try to block the change. There's still use in it, you just need to view the whole graph holistically.

Will Wright credits Jay Forrester for inspiring him to simulate a city on the computer:

https://www.gamedeveloper.com/business/the-replay-interviews...

>How did the leap from Raid's world editor, to SimCity with its urban design theories, happen?

>WW: First, it was just a toy for me. I was just making my editor more and more elaborate. I thought it would be cool to have the world come to life. So I started researching books on urban dynamics, and traffic, and things like that. I came across the work of Jay Forrester, who was kind of the father of system dynamics. He was actually one of the first people I found that actually simulated a city on a computer. Except in his simulation, there was no map; it was just numbers. It was like population level, number of jobs -- it was kind of a spreadsheet model.

>So I took his approach to it, and then applied a lot of the cellular automata stuff that I had learned earlier, and get these emergent dynamics that he wasn't getting in his model. I found when I was reading all these theories about urban dynamics and city behavior, that when I had a toy simulated version on the computer, it made the subject much more interesting than reading a book -- because I could go to my computer model and start experimenting.

>That just bought the whole subject to life for me and then, more and more, I started thinking, "Other people might enjoy this." But even then I never thought SimCity would have a broad appeal. I thought it might appeal to a few architects and city planner types, but not average people.

But Will's goal was to make a game that was fun to play, not to accurately simulate reality or make predictions. Intentionally inspiring magical systems thinking for entertainment, education, and storytelling!

Chaim Gingold's SimCity Reverse Diagrams:

https://smalltalkzoo.computerhistory.org/users/Dan/uploads/S...

>These reverse diagrams map and translate the rules of a complex simulation program into a form that is more easily digested, embedded, disseminated, and and discussed (Latour 1986).

>The technique is inspired by the game designer Stone Librande’s one page game design documents (Librande 2010).

>If we merge the reverse diagram with an interactive approach—e.g. Bret Victor’s Nile Visualization (Victor 2013), such diagrams could be used generatively, to describe programs, and interactively, to allow rich introspection and manipulation of software.

Will Wright on Designing User Interfaces to Simulation Games (1996) (2023 Video Update):

https://news.ycombinator.com/item?id=34573406

https://donhopkins.medium.com/designing-user-interfaces-to-s...

>Some muckety-muck architecture magazine was interviewing Will Wright about SimCity, and they asked him a question something like “which ontological urban paradigm most influenced your design of the simulator, the Exo-Hamiltonian Pattern Language Movement, or the Intra-Urban Deconstructionist Sub-Culture Hypothesis?” He replied, “I just kind of optimized for game play.”

https://news.ycombinator.com/item?id=22062590

>DonHopkins on Jan 16, 2020 | parent | context | favorite | on: Reverse engineering course

Will Wright defined the "Simulator Effect" as how game players imagine a simulation is vastly more detailed, deep, rich, and complex than it actually is: a magical misunderstanding that you shouldn’t talk them out of. He designs games to run on two computers at once: the electronic one on the player’s desk, running his shallow tame simulation, and the biological one in the player’s head, running their deep wild imagination. "Reverse Over-Engineering" is a desirable outcome of the Simulator Effect: what game players (and game developers trying to clone the game) do when they use their imagination to extrapolate how a game works, and totally overestimate how much work and modeling the simulator is actually doing, because they filled in the gaps with their imagination and preconceptions and assumptions, instead of realizing how many simplifications and shortcuts and illusions it actually used.

https://www.masterclass.com/classes/will-wright-teaches-game...

>There's a name for what Wright calls "the simulator effect" in the video: apophenia. There's a good GDC video on YouTube where Tynan Sylvester (the creator of RimWorld) talks about using this effect in game design.

https://en.wikipedia.org/wiki/Apophenia

>Apophenia (/æpoʊˈfiːniə/) is the tendency to mistakenly perceive connections and meaning between unrelated things. The term (German: Apophänie) was coined by psychiatrist Klaus Conrad in his 1958 publication on the beginning stages of schizophrenia. He defined it as "unmotivated seeing of connections [accompanied by] a specific feeling of abnormal meaningfulness". He described the early stages of delusional thought as self-referential, over-interpretations of actual sensory perceptions, as opposed to hallucinations.

RimWorld: Contrarian, Ridiculous, and Impossible Game Design Methods

https://www.youtube.com/watch?v=VdqhHKjepiE

5 game design tips from Sims creator Will Wright

https://www.youtube.com/watch?v=scS3f_YSYO0

>Tip 5: On world building. As you know by now, Will's approach to creating games is all about building a coherent and compelling player experience. His games are comprised of layered systems that engage players creatively, and lead to personalized, some times unexpected outcomes. In these types of games, players will often assume that the underlying system is smarter than it actually is. This happens because there's a strong mental model in place, guiding the game design, and enhancing the player's ability to imagine a coherent context that explains all the myriad details and dynamics happening within that game experience.

>Now let's apply this to your project: What mental model are you building, and what story are you causing to unfold between your player's ears? And how does the feature set in your game or product support that story? Once you start approaching your product design that way, you'll be set up to get your customers to buy into the microworld that you're building, and start to imagine that it's richer and more detailed than it actually is.

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.

Modernizing software systems take time because of inherent corruption in the procurement process or workings of consulting company involved. Those problems can be solved much faster and cheaper if a knowledgeable tech person was involved.

Hertz vs. Accenture: In 2019, car rental company Hertz sued Accenture for $32 million in fees plus additional damages over a failed website and mobile app project. Hertz claimed Accenture failed to deliver a functional product, missed multiple deadlines, and built a system that did not meet the agreed-upon requirements.

Marin County vs. Deloitte: In 2010, California's Marin County sued Deloitte Consulting for $30 million over a failed SAP ERP implementation. The county alleged Deloitte misrepresented its skills and used the county as a "training ground" for inexperienced consultants.

[flagged]