Dancing with Coronavirus

Why this is not a war, and why we should take a systems perspective.

I’ve been teaching systems thinking to postgraduate design students, and one key reference has been on my mind during the pandemic: Dancing with Systems by Donella Meadows. She was a renowned biophysicist, best known for the book The Limits of Growth, and I have used Dancing with Systems to introduce students to systems thinking. In it, Meadows offers 14 key points she learned over the years, and in this article I apply those directly to the Coronavirus pandemic in order to show (1) how Meadow’s metaphor of a dance is more useful than metaphors of war, and (2) how systems thinking is important during this time (indeed at all times). I will quote liberally from Meadows’ article, because her words are right on target today, and I encourage you to read her writings, as well as other ones about systems—I’ve included a brief listing at the end of this article of some that I’ve found useful. I will also reference some medical literature and a few other useful readings in this article. Disclaimer: I’m a researcher and not a medical doctor; I work across art and design, and I’ve found systems thinking more useful than “design thinking”.

Why war is the wrong metaphor

It’s a war, a battle, a conflict, with weapons and front lines, strategies and tactics. We have to defeat the enemy, “kick its ass” even. We hear these metaphors every day—from political leaders, medical professionals, the mass media. They are not specific to Coronavirus—we’ve had declared wars on cancer, drugs, terror, and more, and war metaphors in medicine go back centuries. It’s true we haven’t seen a global crisis like this since World War II, so in that sense the war metaphor is understandable.

Metaphors are important for helping patients, doctors and everyone else understand complex phenomena, and metaphors of war are useful for mobilising resources and motivating workers (“fighers”) and populations. Another disclaimer here: I realise that if you are suffering from a medical condition like Coronavirus, it can feel like a battle, and you just want to get rid of this thing and back to some state of balance. I respect and sympathise with anyone who is suffering.

Infection game for Epidemic exhibition, American Museum of Natural History. 3D modelling by Jim Stoop, design & programming by me.

In fact, I made a two-player game in which one player takes the role of a microbe invading the body, and the other plays the immune system – it was explicitly a fight, with one winner.

Notice, however, that war metaphors are used mostly by men. As doctor Paul Hodgkin points out, “Fighting wars is usually an unpleasant, boring, and masculine activity.” Wars place emphasis on prediction and control, and technological solutions, something Meadows warns against. As a predominantly male metaphor, Hodgkin says, thinking of disease as a war can discriminate against feeling and reflection.

A related metaphor noted by Hodgkin is that of the machine, particularly the body as machine—as something that can be fixed, or upgraded. Hodgkin was writing in 1985, and since then, the computer has become a pervasive metaphor, for everything from the brain to the universe; I use it myself, but mainly as a way of exposing both the value and the danger of computational thinking. Cybernetics, the science of systems, goes back almost a century now, and even feminist writers like Katherine Hayles and Donna Haraway have seen the value of viewing humans as cyborgs—this is especially relevant now that we are all suddenly glued to screens more than ever.

Another doctor, Dhruv Khullar, says, “By describing a treatment as a battle and a patient as a combatant, we set an inherently adversarial tone, and dichotomize outcomes into victory and defeat.” And here’s the upshot: He cites research that cancer patients “who view their disease as an ‘enemy’ tend to have higher levels of depression and anxiety, and poorer quality of life than those who ascribe a more positive meaning.”

Cancer is not Coronavirus, but another group of medical researchers found that the same applies to another virus—HIV. Here, too, they found war metaphors “ironic, unfortunate, and unnecessary.”

So, what are alternatives? The authors cited here offer metaphors of a journey, a marathon (also pervasive today), a rollercoaster, a chess match, a detective story, a collaborative exploration.

Screenshot from the game Journey by Thatgamecompany/Sony Computer Entertainment

The main point is that doctors, patients, people have a choice. And the way we frame something affects how we approach it, how we act, and what might result. And this can have broader consequences—there is a growing criticism warning about the broad wartime powers governments are granting themselves, which (like the Patriot Act in the US after 9/11) can become embedded and erode personal freedom and human rights—it can become implicitly a war on a government’s own population rather than on an unseen enemy. George Orwell long ago warned about the dangers of a perpetual state of war in 1984.

Note also the inverse: viruses are often used as a metaphor for other ills. Khullar cites a study in which people were asked to address a city’s crime problem, which was framed alternately as either a virus or a wild beast. Those to whom crime was described as a wild beast were more likely to agree to authoritarian measures over social reforms. I think this gets to a fundamentally political—or more accurately, ethical—truth: the essential difference between a conservative and a liberal view, I believe, is that the former thinks mainly of oneself, or one’s in group, whether family, race, culture or country; and the other thinks mainly of others, and how one’s own actions impact others.

So there’s value in seeing things from the perspective of the virus itself, and here we arrive at Meadows and systems thinking. In fact, regardless of metaphor, we tend to regard disease as an object rather than a process—as a foreign invader, in the war metaphor. And as Hodgkin points out, the corollary of this view that the patient is seen as a container for this object. Both patient and disease, in this view, become passive things to be treated or acted upon.

“We can’t find a proper, sustainable relationship to nature, each other, or the institutions we create,” writes Meadows, “if we try to do it from the role of omniscient conqueror.” So what happens when we adopt her metaphor of a dance, in this case between humans and virus? (In fact Hodgkin also offers this metaphor—the human body as a biochemical dance.)

Systems thinking

Thinking in terms of systems means looking at phenomena at different scales, from the microbial to the human, social, technological, political, ecological, and so on. Going back to the virus as a metaphor, this might mean, for example, looking at humans as a kind of virus in relation to the planet, and comparing the human immune system to a global one.

“But self-organizing, nonlinear, feedback systems are inherently unpredictable,” writes Meadows. “They are not controllable. They are understandable only in the most general way. The goal of foreseeing the future exactly and preparing for it perfectly is unrealizable. The idea of making a complex system do just what you want it to do can be achieved only temporarily, at best.”

She offers the following lessons about systems, which I will apply to the Coronavirus pandemic.

1. Get the beat

Any dance has a rhythm—not only literally in terms of music and movement, but life itself as a dance has certain rhythms. The philosopher Franco Berardi calls it “the vibration of the world”. With regard to a system like a disease outbreak, Meadows advises us to first observe what’s happening. This sounds obvious, but too many authorities rush in with policies and preconceptions without understanding what’s actually going on. “Starting with the behavior of the system,” she says, “forces you to focus on facts, not theories. It keeps you from falling too quickly into your own beliefs or misconceptions, or those of others.”

What does it mean to observe something? Social scientists differentiate between detached observation and participant observation, where in the former the “pure observer” typically uses some kind of instrument to observe something, and in the latter the observer is the instrument themself. But even a supposedly detached observer standing off to the side of some situation can affect it — in a social situation, total detachment can come across as antisocial and can affect the behaviour observed [1]. And we could say that even a “pure observer” cannot be totally detached or objective—instruments frame what we observe just as metaphors do (think of all the charts and infographics you’ve been looking at).

I teach this by getting students to draw—how you literally frame what you draw, including certain things and not others, tells a subjective story. Remember this as you are looking at charts and numbers—any time data is collected, interpreted and represented involves selection and bias [2].

Observation, especially when people are directly involved, is a form of surveillance, and this raises ethical issues. The biologist Humberto Maturana eloquently discusses this in relation to observing systems—how do we feel about what we observe? This is one of the most important points—if you take anything away from this article, remember the importance of quality, not quantity. Observation isn’t simply counting things. “Systems thinking,” Meadows writes, “has taught me to trust my intuition more and my figuring-out rationality less, to lean on both as much as I can, but still to be prepared for surprises.”

The Coronavirus pandemic has developed and spread very quickly, leaving little time for reflection or analysis. Meadows advises looking at the history of a system; as Covid-19 is a new virus, scientists have wisely been looking to related viruses and historical outbreaks. Starting with history, she says, “discourages the common and distracting tendency we all have to define a problem not by the system’s actual behavior, but by the lack of our favorite solution.”

And observing how the outbreak has developed also shifts focus from disease as object to disease as process: “Starting with the behavior of the system directs one’s thoughts to dynamic, not static analysis–not only to ‘what’s wrong?’ but also to ‘how did we get there?’ and ‘what behavior modes are possible?’ and ‘if we don’t change direction, where are we going to end up?’”

2. Listen to the wisdom of the system

Listen to your body—it’s not just you speaking. The human body contains more nonhuman cells than human ones. You are a system—indeed one composed of sub-systems for circulation, digestion, etc. Your immune system is closely tied to your identity, constantly figuring out what is part of you and what is not [3]. What happens if we apply this to social systems, countries, the global climate? “Don’t be an unthinking intervener and destroy the system’s own self-maintenance capacities,” says Meadows. “Before you charge in to make things better, pay attention to the value of what’s already there.”

3. Expose your mental models to the open air

There’s lots of talk about computer models during this crisis, but no talk of mental models. Remember, Meadows tells us, that “everything you know, and everything everyone knows, is only a model.”

What exactly does this mean? Just what is a mental model? We can think of the metaphors discussed above as mental models: How do we frame something, conceptualise it? Computer models are one way of externalising these models; so are diagrams and infographics. And this is why we should approach them critically, read between the lines to see the assumptions on which their based, how they might be biased or incomplete. All models, by their very nature, are incomplete. Think of a 3D model, or a physical model – of a car, a microbe, a building, whatever. It’s a miniature version of the world, and as such, some information is lost in making it.

The same with maps: Jorge Luis Borges wrote a story about a map that became so big and detailed that it took up the same amount of space it depicted. The map becomes the territory. And that is itself a good metaphor for how models can affect the physical world. Just look at all the buildings that have obviously been designed on the computer.

Another way we can avoid a way of thinking that’s constrained by a model, Meadows advises, is to not only expose your own assumptions and those of others, but to collect as many models as possible. Doing that, she says, “you will be emotionally able to see the evidence that rules out an assumption with which you might have confused your own identity.” Think of ideas and memes that go viral on the internet. (The seminal reference on memes is Chapter 11 of Richard Dawkins’ book The Selfish Gene – a book I’ll return to below.)

“Mental flexibility,” writes Meadows, “– the willingness to redraw boundaries, to notice that a system has shifted into a new mode, to see how to redesign structure – is a necessity when you live in a world of flexible systems.”

4. Stay humble. Stay a learner.

Relatedly, Meadows tells us, “The thing to do, when you don’t know, is not to bluff and not to freeze, but to learn.” Note to political leaders! She continues:

In a world of complex systems it is not appropriate to charge forward with rigid, undeviating directives. “Stay the course” is only a good idea if you’re sure you’re on course. Pretending you’re in control even when you aren’t is a recipe not only for mistakes, but for not learning from mistakes. What’s appropriate when you’re learning is small steps, constant monitoring, and a willingness to change course as you find out more about where it’s leading.

5. Honor and protect information.

This one particularly resonates with me because I’ve been writing about information (see my other recent articles on Medium), and until recently I ran a design programme with “information” in the name.

“I would guess,” writes Meadows, “that 99 percent of what goes wrong in systems goes wrong because of faulty or missing information.” But again, it’s not just about quantity – remember that all models are incomplete. She proposes a kind of Eleventh Commandment: “Thou shalt not distort, delay, or sequester information.”

Again, think of viral memes, disinformation and misinformation on the internet. And we know that it’s not only individual criminals or the unaware who spread such things – it’s governments as well, acting in their own self-interest. I heard author Yuval Harari on the radio last week speaking eloquently about this – asked about apps to monitor people’s symptoms, he said he’s not bothered by surveillance, as long as it’s two-way: as long as we can monitor those collecting the information and as long as they are transparent about it (again, exposing those models).

6. Locate responsibility in the system.

This is the one place I disagree with Meadows. She refers to events outside the system being observed: “Sometimes those outside events can be controlled (as in reducing the pathogens in drinking water to keep down incidences of infectious disease.) But sometimes they can’t.”

It may be that the internet was not used as widely when she was writing, but what I see today is lots of interlocking and interacting systems. The “outside events” she refers to are themselves part of one or more other systems, whether political, biological, ecological or technological. And let’s not forget food systems – look at where the virus came from. The link between biological and technological systems is also interesting: besides the virus metaphor for memes, because Coronavirus is spread by physical contact, this makes touchscreens interesting – forget conspiracy theories about 5G; might phones themselves play a small role in transmission?

But in general, I agree with Meadows’ approach – instead of locating responsibility on an individual person or a particular virus, we need to zoom out to the system as a whole. I worked on a major exhibition on infectious disease, and one thing I learned is that disease is caused not by a microbe alone, but in an interaction between microbe, person and the environment.

A useful model from social science is activity theory, which applies a systems perspective to investigate social phenomena in terms of an activity system, which is comprised of a subject, object and tools that mediate interactions between them, sometimes expanded to include rules, a community, and the division of labour therein. [4]

Locating responsibility at the system level, according to Meadows, “means that the system is designed to send feedback about the consequences of decision-making directly and quickly and compellingly to the decision-makers.” This means we all bear some responsibility for each other, being so interconnected.

7. Make feedback policies for feedback systems

Speaking of feedback and decision-makers: “It’s easier, more effective, and usually much cheaper to design policies that change depending on the state of the system,” writes Meadows. “Especially where there are great uncertainties, the best policies not only contain feedback loops, but meta-feedback loops – loops that alter, correct, and expand loops.”

The level of policy is the level of strategy. That means how best to turn a complex and developing set of affairs to one’s advantage – and here of course it makes sense to ask, “Whose advantage, exactly? What are their goals and models?”

More than a plan, strategy accounts for goals and capacity, aiming for the sensible application of resources. And importantly, maintaining flexibility in the face of randomness and unpredictability. Ideally it looks at causes, not symptoms – often overlooked in a fast-moving disease outbreak as we seek to treat symptoms at both the individual and societal level. Models, simulations, decision theory and systems thinking generally are all strategic tools.

While strategy accounts for goals, to maintain flexibility (see feedback above), it is ideally governed by the start point, not a foreseen end. In this regard, might we forgive our officials for not seeing and “end game,” a way out, either epidemiologically or economically? Strategy is balancing the ends, ways and means; thinking through consequences; and understanding how others view the world (mental models again). Worth noting here is that combining with others is often the best strategy. [5]

In terms of systems, tactics take place at a lower level than strategy. Here I like Michel de Certeau’s view: strategy comes from the top down, in the form of policies, laws, rules and regulations; tactics are the practices we undertake day to day to either work within them or get around them.

Two words here: social distancing. I write this as the weather is warming up in London but everyone is urged to stay home except for exercising once a day. The tactics are obvious – one the one hand, many people might be fitter and more relaxed after all this; others stretch the definition of “exercising once a day.” Similarly, we’ve all been asked not to stockpile food, but many people were clearly stocking up in a very British way – politely, not buying a lot at once, but making more trips to the store.

8. Pay attention to what is important, not just what is quantifiable

Again, quality, not just quantity. One of my mentors told me, “If you start off defining research as only what is measurable you will miss a lot.” Validity is just as important as reliability or generalisability: Can we learn from it? Is there a good reason for doing it?

“Our culture, obsessed with numbers,” says Meadows, “has given us the idea that what we can measure is more important than what we can’t measure. You can look around and make up your own mind about whether quantity or quality is the outstanding characteristic of the world in which you live.” Going back to observation, we can think not merely of counting things, but asking how we feel about what we observe.

The philosopher Federico Campagna has written an important book about exactly this: looking beneath politics, culture, technology, systems even, to the metaphysical level underlying our whole reality, he sees measurement as central to our society: Only that which can be measured, described or categorised in language can legitimately exist in the world. Things we cannot adequately described – like time, emotions, our very existence – get pushed to the side. Might the pandemic prompt us to question basic values like this? Could we imagine a world that instead values the ineffable?

Another useful tool here is something called conversation theory. This came out of systems thinking in the 1960’s, and conceives of learning (see Point 4 above) as a conversation between two or more entities (either of which may or may not be human), separated into a level of descriptions (grounded in language and measurement) and a level of actions (observable but inevitably ineffable).

It’s useful to view Coronavirus through this lens, with language and measurement perhaps also related to the level of strategy, and actions to the level of tactics. The other important part of this model is that there are feedback mechanisms throughout – between the levels, and between the participants. In fact, this kind of conversation can also be seen as a dance – Meadows’ preferred metaphor for dealing with systems. [6]

Screenshot from the trailer for the game Everything by David O’Reilly

9. Go for the good of the whole

Another philosopher, Alan Watts, beautifully articulates a systems perspective as a dance in this video —it’s well worth nine minutes to watch it. “Don’t maximize parts of systems or subsystems while ignoring the whole,” says Meadows. “Aim to enhance total systems properties, such as creativity, stability, diversity, resilience, and sustainability–whether they are easily measured or not.”

Crucial here is choosing the right level of focus when dealing with systems; any given system is, of course, composed of multiple sub-systems and is itself part of some larger system. Not only that, but zooming in to look at the various sub-systems, and out to look at the broader context. The video elegantly shows this, as well as the interconnectedness of everything; we zoom out to the universal scale, then it loops right back to the microscopic level. Physicians understand this interconnectedness of micro and macro. And this video answers a question you might have by this point: What is a system? Everything. You, your cells, a single Coronavirus microbe, the world, the internet, and so on ad infinitum.

Meadows also articulates the value of looking at different levels of scale: “When you’re walking along a tricky, curving, unknown, surprising, obstacle-strewn path, you’d be a fool to keep your head down and look just at the next step in front of you. You’d be equally a fool just to peer far ahead and never notice what’s immediately under your feet. You need to be watching both the short and the long term—the whole system.”

COVID-19 microbe in glass by artist Luke Jerram. Used with permission, image courtesy the artist.

What do we see when we zoom in to level of the Coronavirus microbe? Viruses are really interesting—they occupy a strange space between living and nonliving things. They are relatively simple, with only a few dozen genes, compared to the 20,000 to 25,000 that we have; yet they have more genetic diversity than any other living organism—there are millions of types, and scientists have only investigated a small proportion of these in detail. New (or undiscovered) ones come about through a reshuffling of their genes. Yet they have a much simpler structure than cells and cannot reproduce themselves—they get host cells to do that for them. But unlike, say, crystals, they inherit these genetic changes, and as such can evolve by natural selection. So they have some kind of structure and some kind of agency, but are not “alive” in the way cellular organisms are. Here we come up against the limitations of language, of scientific description.

Richard Dawkins, in The Selfish Gene referenced above, finds the locus of evolution in genes, not in individual organisms – in other words, at a relatively low-level system, below even that of the simple virus. In the extreme version of this view, both humans and viruses are therefore just containers for genetic evolution, and genes drive us to do all sorts of irrational (to us) behaviours just to ensure that those selfish genes replicate themselves from one generation to the next.

But as one of my anthropology professors pointed out when turning us on to Dawkins’ book, it’s not simply a matter of genetic determinism, or cultural determinism for that matter (nature or nurture). Because there’s a third force often overlooked in that debate—free will. So if we start from the scale of the Coronavirus, we can zoom down a level to look at the way it mutates and replicates; and we can zoom out to human scale to see other mechanisms at work.

In zooming in and out, Meadows cautions us to “realize, that, especially in the short term, changes for the good of the whole may sometimes seem to be counter to the interests of a part of the system. It helps to remember that the parts of a system cannot survive without the whole.” The health of individual organs depend on the health of the body; the health of individuals depends on that of social bodies and institutions; humanity needs a sustainable planet.

10. Expand time horizons

Relatedly, “The official time horizon of industrial society doesn’t extend beyond what will happen after the next election or beyond the payback period of current investments,” writes Meadows. I view this similarly as zooming and out – not only at different size scales but time scales. Viruses mutate and replicate at a much shorter time scale than humans. Look in general at natural rhythms – from heart rate and breathing to the day and night cycles: certain medical treatments, and the perception of pain, differ depending on time of day, for example.

“In the strict systems sense,” according to Meadows, “there is no long-term/short-term distinction. Phenomena at different time-scales are nested within each other. Actions taken now have some immediate effects and some that radiate out for decades to come. We experience now the consequences of actions set in motion yesterday and decades ago and centuries ago.”

11. Expand thought horizons

“Defy the disciplines,” advises Meadows. “In spite of what you majored in, or what the textbooks say, or what you think you’re an expert at, follow a system wherever it leads. It will be sure to lead across traditional disciplinary lines.” If you’re reading this, I suspect you’re likely to ignore disciplinary boundaries. This is also why cooperation and collaboration are vital at this time – I would add, not only across disciplines but across local and national borders. Viruses don’t respect them.

12. Expand the boundary of caring

By this point, you might think of Meadows as a leftie or a hippie. But she was also a scientist at MIT. And we all know by now that not only were the hippies right; they also went on to start Silicon Valley.

Why can’t we also ignore the traditional political boundaries between “left” and “right”? This is another of those false binary distinctions. On the other hand, I would go back to the fundamental difference of caring for oneself or one’s in-group versus caring for others.

I’m not making a political argument for one side or the other, just pointing out Meadows’ take on systems thinking that looks to the care of the whole system, not just one part. “There are moral reasons for doing that, of course,” she writes. “And if moral arguments are not sufficient, then systems thinking provides the practical reasons to back up the moral ones.”

13. Celebrate complexity

Nothing is static, everything is in motion, heading towards entropy, and all we can do is try and hold things together as long as we can – our individual bodies and minds, the social body, the political and global climate. Coronavirus shows how the universe is messy, turbulent and chaotic, as Meadows writes.

Trær som vokser seg skakke by Espen Tollefsen, 2017

Yes, celebrate complexity. But going back to the very first point, I would remind us not to forget history. After the UK’s last general election, Walter Russell Mead wrote this insightful analysis of why the Conservatives won so decisively over the left: The progressives were so focused on breaking with history, changing the whole system, moving away from capitalism and into socialism.

But Mead points out that most people generally like the benefits that capitalism brings; they don’t like what they perceive as negatives: “Large-scale immigration, job losses to automation and foreign competition, the unequal distribution of capitalism’s rewards, and the financial instability and risk associated with innovation are all massively disruptive and inspire backlash – a global surge of populism and identity politics.”

The Conservatives, he says, recognised that in the midst of such turbulence, people need some perceived stability to cling onto. Identity politics take place on the left as well as the right, but don’t forget history and tradition, and – what we tell our design students – if you place your future far away from today, you need to build a bridge, give people something recognisable to hold onto, to lead them there.

We should note again the need for criticality here – whose history? As Berardi says, “When we speak of ‘history,’ when we view events from a historical perspective, we are imposing a certain modulation of our perception and projection of time.”

14. Hold fast to the goal of goodness.

Good news is often not news, Meadows points out, but I see hope: this crisis is so extreme, so disruptive, that both the media and the public are hungry for bright spots amidst all the bad news. “Don’t weigh the bad news more heavily than the good,” she concludes. “And keep standards absolute.”

In conclusion

I hope a perspective from design is useful during this crisis. “Systems can’t be controlled,” says Meadows, “but they can be designed and redesigned.” The key here is in how we define design – I don’t subscribe to the view of design as problem solving, a magic way of thinking involving sticky notes. Design over the past century has had as many negative consequences as it has improved health, productivity or “experience”.

I like Daniel Dennett’s systems-thinking definition of design as a process undertaken by nature as well as humans – we could say, a bottom-up tactic as opposed to a top-down strategy. Not a war but a dance. With a rhythm we can tune into and observe as an active participant, recognising our role and perspective (both ethical and spatial), exposing our mental models and those of others. Maintaining flexibility, questioning the quantifiable, respecting the ineffable, zooming in and out to look at interacting systems at different spatial and temporal scales, ignoring national and political and disciplinary boundaries but grounding our decisions in history and observable facts.

“Living successfully in a world of systems requires more of us than our ability to calculate,” Meadows teaches us. “It requires our full humanity – our rationality, our ability to sort out truth from falsehood, our intuition, our compassion, our vision, and our morality.”

I’ll end with another long quote from her:

The real system is interconnected. No part of the human race is separate either from other human beings or from the global ecosystem. It will not be possible in this integrated world for your heart to succeed if your lungs fail, or for your company to succeed if your workers fail, or for the rich in Los Angeles to succeed if the poor in Los Angeles fail, or for Europe to succeed if Africa fails, or for the global economy to succeed if the global environment fails.

Notes & further reading

  1. For more on observation in social science, see Colin Robson’s Real World Research—it’s a kind of bible of research methods for me.
  2. For more on bias in data visualisation, see Critical Visualisation by Peter Hall.
  3. Neuroscientist Leah Kelly provides a very eloquent and clear explanation of the human immune system in a chapter of this book.
  4. For a good introduction to activity theory, see this book by my colleague Victor Kaptelinin.

5. Much of my perspective on strategy comes from this excellent book.

6. Conversation theory was developed by cyberneticist Gordon Pask, and developed further by Diana Laurillard. I’ve applied it to design and to machine learning. The connection between a conversation and a dance comes from Paul Pangaro.

More on systems thinking

Here’s a good introduction to cybernetics.

This book introduces key readings and thinkers about systems, as well taking an artistic perspective (I recommend the MIT/Whitechapel series in general as a nice way in to various topics.)

If you’re looking to go into real depth in design & systems, head to Portland.