(highlight:: Computers Enabled the Rise of Complexity Science
Key takeaways:
• All sciences are abandoning the idea of perfect rationality, order, and logic.
• Computers have allowed for the study of complexity in various fields including physics, mathematics, and economics.
• Complexity is not the cause of something in science, but rather an outcome.
• Phenomena can appear in certain circumstances when multiple elements are taken seriously and assumed to be different.
Transcript:
Speaker 1
And that is that all sciences are giving up their ideas of perfect rationality perfect order, perfect logic, and that many things you're dealing with are identical. We have to make those assumptions to make science work, but we're now entering a period in physics and in mathematics, and another fields, including economics, where it's starting To be okay to say, none of the above cold. The reason we can do that and get away with it. This we all have computers. So you can't describe easily on pencil and paper yellow paper legal pads, whatever we use. And I can't describe it. If you say I have 100 different agents, I'm going to put them in L for all. I can write equations even for their individual little predictors. And I am going to work at the solution because there's too much going on. I have a computer the computer contract that. So I don't think it is a coincidence that complexity, the idea of looking at multiple elements, creating a situation with those multiple elements react to. And I think it's a coincidence that this became a serious objective study, roughly at the time when we got computers. I think they're really smart people 100 years ago, Planck and others who would have realized that. So you can't track that. So in that sense, then complexity is not really the cause of something in science. It's more the outcome. If we get computers, we can take multiple elements seriously. We can assume they're different. We can track them. They don't have to have some perfectly logical, unique answer. They can do quite different things. And then under those circumstances, quite often you see phenomena appear like the ones I mentioned last time in the stock market.)
- Time 0:34:01
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(highlight:: Computers Enabled the Rise of Complexity Science
Key takeaways:
• All sciences are abandoning the idea of perfect rationality, order, and logic.
• Computers have allowed for the study of complexity in various fields including physics, mathematics, and economics.
• Complexity is not the cause of something in science, but rather an outcome.
• Phenomena can appear in certain circumstances when multiple elements are taken seriously and assumed to be different.
Transcript:
Speaker 1
And that is that all sciences are giving up their ideas of perfect rationality perfect order, perfect logic, and that many things you're dealing with are identical. We have to make those assumptions to make science work, but we're now entering a period in physics and in mathematics, and another fields, including economics, where it's starting To be okay to say, none of the above cold. The reason we can do that and get away with it. This we all have computers. So you can't describe easily on pencil and paper yellow paper legal pads, whatever we use. And I can't describe it. If you say I have 100 different agents, I'm going to put them in L for all. I can write equations even for their individual little predictors. And I am going to work at the solution because there's too much going on. I have a computer the computer contract that. So I don't think it is a coincidence that complexity, the idea of looking at multiple elements, creating a situation with those multiple elements react to. And I think it's a coincidence that this became a serious objective study, roughly at the time when we got computers. I think they're really smart people 100 years ago, Planck and others who would have realized that. So you can't track that. So in that sense, then complexity is not really the cause of something in science. It's more the outcome. If we get computers, we can take multiple elements seriously. We can assume they're different. We can track them. They don't have to have some perfectly logical, unique answer. They can do quite different things. And then under those circumstances, quite often you see phenomena appear like the ones I mentioned last time in the stock market.)
- Time 0:34:01
-