Thinking in Systems, Donella Meadows, 2008 - I should have found this book long ago. I have learnt these concepts from a diverse of disciplines from control systems, economics, game theory and so on. It was a thoroughly enjoyable read as I have always been curious about large systems and the way they behave.
My notes -
• A system is a set of things - people, cells, molecules that produces own behavior over time
• Most problems aren’t independent of each other but inter-dependent and interacting with each other in complex systems
• To change results produced by systems, its important to understand and change the structure and the behavior
• Our linear thinking minds are always looking for cause-and-effect and simplistic explanations to complex problems (News headlines)
• Feedback delays within complex systems - by the time the problem becomes apparent, it may be unnecessarily difficult to solve
• For he that hath, to him shall be given, and he that hath not, from him shall be taken even that which he hath (Mark 4:25) - The rich get richer and poor get poorer (Reinforcing feedback loops in money, confidence, capability)
• A diverse system is more stable and less vulnerable to external shock than uniform system with little diversity
• Psychologically and politically, its easy to assume problems are “out there” than “in here”. No one creates these problems deliberately, yet they persist. Only stopping blame and restructuring the system will fix it.
• We must hone our abilities to understand parts, see interconnections, ask what-if questions about future behaviors and be creative and courageous about system redesign
• While a system maybe made of elements, interconnectedness and function/purpose - it is more than sum of its parts. It may exhibit adaptive, dynamic, goal-seeking, self-preserving and even evolutionary behavior
• Elements can be intangibles (like “pride”)
• The best way to deduce purpose of a system is to observe its behavior (not its stated goals)
• Even if a system’s parts and interconnectedness are changed, it may not change the outcome unless its “purpose” is changed.
• Understanding behavior over time - a river meanders but leaves memory on the earth’s crust
• Stock changes over time through the actions of flow (Stock is memory of the history of changing flows within the system)
• Human mind finds it easy to focus on stocks than flows. Also within flows, we find it easy to focus on inflows than outflows (addition vs subtraction)
• A stock takes time to change because a flow (noun) takes time to flow (verb)
• Balancing feedback loops are goal/stability seeking keeping the stock within a range of values
• Reinforcing feedback loops are amplifying, reinforcing, self-multiplying, snowballing virtuous or vicious cycles (exponential as in the economy to runaway collapses as in ecology)
• A stock governed by linked reinforcing and balancing loops will grow exponentially if the reinforcing loop dominates the balancing one
• The greater the fraction of output a society invests, the faster its capital stock will grow. Systems that are similar to each other share same repertoire of behaviors
• Any long term model of a real economy should link together structures of population and capital to show how they affect each other
• Oscillations happen in systems that have delayed feedback (Eg. sales and inventory moving in tandem). Moving averages damp these oscillations - but what period to consider matters as well - a wrong choice here could make oscillations worse
• Economies are extremely complex systems filled with balancing loops and delays (inherently oscillatory, causing business cycles)
• Limits-to-growth architype - Any physical growing system will run into some kind of constraint, sooner or later - a balancing loop may kick in and reduce in-flows or increase outflows weakening a self-reinforcing loop. A new product, a virus or a nuclear reaction, will all eventually run out of resources
• The higher and faster you grow, the farther and faster you fall, when building up capital stock from a non-renewable resource. A quantity growing exponentially toward a limit reaches it in surprisingly short time. Reducing extraction rate will make you get rich slow but stay that way longer (only applicable for non-renewables)
• Renewable resource system - a virus that spares victims so it can persist or fish in the ocean that can renew when not over-fished. Higher extraction rate can potentially destroy the resource beyond repair as well leading to extinction - if higher capital is employed and better technology is found that improves extraction rate which regeneration rate is constant (fishing, logging)
• Resilience is a measure of system’s ability to persist and survive within a variable environment. Arises from several feedback loops working to restore system after a perturbation (human body). There are limits to resilience
• Just-in-time production system has made us vulnerable to changes in fuel supply, traffic flow, breakdowns, labor availability etc. (We are experiencing this right now with Covid disruption of supply-chains)
• Large organizations fail to be resilient because of the large number of layers of delay and distortion in the feedback process
• Systems need to be managed not just for stability and productivity but also for resilience (don’t focus just on the play but also the playing field)
• Self-organization - Capacity of a system to make its own structure more complex
• Like resilience, self-organization is also sacrificed for productivity and stability (Usual excuses for turning creative human beings into mechanical adjuncts to production processes. Always makes be uncomfortable when people are referred to as “resources” or “capacities”)
• koch snowflake - shapes formed by relatively simple rules of self-organization. (fractal geometry of the lung is what gives it same surface area of a tennis court)
• Hierarchy - self-organizing system often generate hierarchy. Simple forms give way to complex forms through stable intermediate forms. resilience, self-organization and hierarchy are the reasons why dynamic systems function so well
• Everything we think about the world is a “model”
• We often draw illogical conclusions from accurate assumptions or logical conclusions from inaccurate assumptions
• Our knowledge is amazing, our ignorance even more so
• Behavior of a system is its performance over time - its growth, stagnation, decline, oscillation, randomness or evolution
• Structure of a system is key to understanding not just what is happening, but the “why”
• Non-linearity - the act of playing the game has a way of changing the rules. When we know small push produces small response, a twice as big push may cause one-sixth or response-squared or no response at all in non-linear systems instead of twice as big as a linear system would.
• System rarely have real boundaries (What we think of as a system might have crucial missing pieces that affect it)
• A systems boundaries may not coincide with an academic discipline or a political boundary (man-made abstract boundaries)
• Limiting factor - rich countries may transfer capital and technology to a poor labour-rich nation and still not cause growth because they may not be the limiting factors. When an economy grows relative to an ecosystem, limiting factors might be clean air, water, energy, dump space and availability of raw materials (apart from capital, labour and technology)
• Bounded rationality - people make decisions based on the information they have/can process
• We don’t make decisions that even optimize our own good, much less the system as a whole
• System traps (and opportunities) - addiction, policy resistance, arms races, drift to low performance and the tragedy of the commons
• Policy resistance - fixes that fail - no amount of change brings a change to behavior of a system that appears intractably stuck. The alternative to policy resistance is counter-intuitive - let go
• If everyone can work harmoniously toward the same outcome (if all feedback loops serving same goal), the results can be amazing
• Tragedy of the commons - Every user benefits individual from use of resource but the costs are shared with everyone else (over grazing, over fishing). To fix, educate and exhort the users, privatize it, regulate the access
• Drift to low performance - We know what we ought to do, but for some reason, we don’t do it. Falling market share in a business, eroding quality of service, dirtier air and rivers etc. The actor tends to believe bad news more than good and thinks things are worse than they are and desired state is influence by perceived state (goal erosion) - lower expectations, lower effort, lower performance.
• Keep standard absolute, regardless of performance. Make goals sensitive to best performances of the past, instead of the worst (reinforcing loop upward)
• Escalation - arms races - exponential build-up of arms. only way out is to refuse getting into one. Or if already in one, refuse to compete, thereby interrupting the reinforcing loop
• Success to the successful - competitive exclusion - to him that hath, shall be given - redistribute wealth through potlatches, have antitrust laws that limit fraction of pie anyone may win
• Addiction - we understand addiction of alcohol or nicotine but same is seen in dependence of industry to govt. subsidy, reliance of farmers on fertilizers, addiction to cheap oil or weapons manufacturers to govt. contracts
• Seeking the wrong goal - confuse effort with result. Eg. GDP measures everything in short, except that which makes life worthwhile. It is a measure of throughput, flows of stuff made and purchased in a year - rather than capital stocks
• If a society chooses to maximize GDP, it will do so while not producing welfare, equity, justice or efficiency unless you define a goal and regularly measure and report these
• Stocks that are relatively big compared to their flows, (buffers) are very slow to react and inflexible
• Physical structure is rarely a leverage point because changing it is rarely quick or simple. Understanding limitations and bottlenecks can help maximize efficiency
• Short-delays in feedback can cause behaviors of “dog chasing its tail” while longer delays cause damped, sustained or explosive oscillations
• Incentives - Imagine if students graded teachers, or if tenure were awarded to professors based on ability to solve real problems, rather than publish papers, or suppose a class got graded as a group, instead of as individuals
• People who have intervened in systems at the paradigm level have hit a leverage point that totally transforms systems (Copernicus, Einstein, Adam Smith)
• Thomas Kuhn on how to change paradigms - you don’t waste time with reactionaries, you keep pointing anomalies and failures with the old paradigm, keep speaking and acting loudly and assuredly from the new one. Insert people in places of visibility and power, work with active change agents and a vast middle-ground of people who are open-minded
• Mastery of paradigms, let people throw off addictions, live in constant joy, bring down empires, get locked up or burned at the stake or crucified or shot, and have impacts that last for millennia
• The higher the leverage point, the more the system will resist changing it - thats why societies often rub out truly enlightened beings
• We have a distracting tendency to define a problem not by system’s actual behavior but by the lack of our favorite solution (the problem is we need to find more oil. The problem is we need more salesmen etc.)
• Our culture, obsessed with numbers has given us the idea that what we can measure is more important than what we can’t measure
• If something is ugly say so. If its tacky, inappropriate, out of proportion, unsustainable, morally degrading, ecologically impoverishing, or humanly demeaning, don’t let it pass (be a human geiger counter for quality. we are endowed not just with ability to count but also to register presence of absence of quality)
• We don’t talk about what we see but we see only what we can talk about
• Its one thing to understand how to fix a system but quite another to wade in and fix it
You must know by the exhaustiveness of my notes, the love I have for this book. 11/10.