![]() If it’s a piece of music or a whitewater rapid or a fluctuation in a commodity price, study its beat. Before you disturb the system in any way, watch how it behaves. But here, as a start-off dancing lesson, are the practices I see my colleagues adopting, consciously or unconsciously, as they encounter systems.ġ. The list probably isn’t complete, because I am still a student in the school of systems. These are the take-home lessons, the concepts and practices that penetrate the discipline of systems so deeply that one begins, however imperfectly, to practice them not just in one’s profession, but in all of life. ![]() I will summarize the most general “systems wisdom” I have absorbed from modeling complex systems and from hanging out with modelers. It requires our full humanity–our rationality, our ability to sort out truth from falsehood, our intuition, our compassion, our vision, and our morality. Living successfully in a world of systems requires more of us than our ability to calculate. It had never occurred to me that those same requirements might apply to intellectual work, to management, to government, to getting along with people.īut there it was, the message emerging from every computer model we made. All those endeavors require one to stay wide-awake, pay close attention, participate flat out, and respond to feedback. I had learned about dancing with great powers from whitewater kayaking, from gardening, from playing music, from skiing. I already knew that, in a way before I began to study systems. We can’t control systems or figure them out. We can listen to what the system tells us, and discover how its properties and our values can work together to bring forth something much better than could ever be produced by our will alone. We can’t surge forward with certainty into a world of no surprises, but we can expect surprises and learn from them and even profit from them. Systems can’t be controlled, but they can be designed and redesigned. It says that there is plenty to do, of a different sort of “doing.” The future can’t be predicted, but it can be envisioned and brought lovingly into being. Systems thinking leads to another conclusion–however, waiting, shining, obvious as soon as we stop being blinded by the illusion of control. If you can’t understand, predict, and control, what is there to do? We can’t find a proper, sustainable relationship to nature, each other, or the institutions we create, if we try to do it from the role of omniscient conqueror.įor those who stake their identity on the role of omniscient conqueror, the uncertainty exposed by systems thinking is hard to take. For any objective other than the most trivial, we can’t optimize we don’t even know what to optimize. Our science itself, from quantum theory to the mathematics of chaos, leads us into irreducible uncertainty. We can never fully understand our world, not in the way our reductionistic science has led us to expect. The idea of making a complex system do just what you want it to do can be achieved only temporarily, at best. The goal of foreseeing the future exactly and preparing for it perfectly is unrealizable. They are understandable only in the most general way. It was going to Make Systems Work.īut self-organizing, nonlinear, feedback systems are inherently unpredictable. Systems thinking for us was more than subtle, complicated mindplay. We did so not with any intent to deceive others, but in the expression of our own expectations and hopes. We exaggerated our own ability to change the world. More or less innocently, enchanted by what we could see through our new lens, we did what many discoverers do. We all assumed it, as eager systems students at the great institution called MIT. ![]() ![]() This mistake is likely because the mindset of the industrial world assumes that there is a key to prediction and control. They are likely to assume that here, in systems analysis, in interconnection and complication, in the power of the computer, here at last, is the key to prediction and control. People who are raised in the industrial world and who get enthused about systems thinking are likely to make a terrible mistake. Pay attention to what is important, not just what is quantifiable.ġ4. Make feedback policies for feedback systems.Ĩ. Expose your mental models to the open air.ħ.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |