Learning From Complexity

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In their recent episode on the VALUE: After Hours Podcast, Taylor, Braziel, and Carlisle discuss Learning From Complexity. Here’s an excerpt from the episode:

Jake: Sure. I guess you call it a blog post at this point. It’s called What I Learnt from Complexity, and it was by Cedric Chin, who I’m a fan of mostly because he said nice things about my book, which always makes me feel good. So, that’s–

[laughter]

Tobias: He’s got taste.

Jake: He’s actually a good twitter follower too if you find him. He’s talking about Michel Waldrop’s book called Complexity that’s about the Santa Fe Institute. It kind of gives the story, the narrative behind that. I think we know a fair amount about these things already but let’s work through some of it. It’s a large network of components that they have no central control to them and they exhibit complex behavior that emerges from sophisticated info processing and adaptive learning that is more than the sum of the parts. The interplay between the nodes is what creates this emergent phenomenon.

He uses actually traffic as an example of a complex adaptive system. I really like it. I’ve tended to use more biological references like ant colonies and things like that for the analogies for complex adaptive systems. But actually, traffic might be better because more people have that as a mental model. We’ve all been stuck in a random ass traffic. We’re like, “What is going on here? There’s nothing, right?” Then, it lets up and there was never anything there to justify why you were stuck in traffic.

It’s impossible to predict. We know what it looks like right now. We could look up, go on to Waze, or Google Maps, or any of these other traffic apps, and we can see what it is right now. But making predictions about it in the future is so– the actual end state of the system at any point in time is incredibly difficult to predict, because there are little feedback loops that get turned on by some little random– the proverbial butterfly flapping its wings, and it leads to these cascading changes within the system that are just impossible to predict. But we know we can observe characteristics about it as it’s happening and we could see tendencies. So, the 405 on Friday night, Toby, what’s that going to look like?

Tobias: [unintelligible 00:23:05] Friday night.

Jake: The 405 at 3 AM on a Sunday night– [crosstalk]

Tobias: Christmas morning.

Jake: Yeah, Christmas morning. What’s it looks like? We can make generalizations about it and have some idea, but it’s incredibly difficult to predict it. So, let’s start with that, load that as a mental model into our minds. And then, I’m watching the 60 Minutes segment from Sunday night, where Ryan Petersen of Flexport, I don’t know if you guys know who he is, but he’s a pretty interesting guy.

Thomas: [crosstalk]

Jake: What’s that?

Thomas: I saw that interview.

Jake: Okay.

Thomas: I saw that interview.

Jake: He’s flying over the LA port with Bill Whitaker, and they’re talking through like, “What the hell? Why are all these boxes stacked up? What’s the problem here? The whole thing snarled up.” It’s a traffic jam effectively. And it’s getting worse. The ports are packed and a lot of it is because the shopping from home binge that took place while we were all stuck at home with COVID, it started to get worse from the beginning, and it’s been growing and getting, it’s cascaded into this. It’s taken much longer, I think, to play out than what maybe all of us wouldn’t imagine. But that’s how complex systems work. They’re really hard to predict like how they’re going to cascade.

Some people are blaming the shipping companies for jacking up rates a bunch because I think it’s like 10x what it was a couple years ago to ship a box from Asia to here. Some people are blaming the ports for not processing the containers fast enough. Some people are blaming the truckers for not being available to get the boxes out of the port, so they’re all stuck there. Some people are blaming the port that the truckers– There’re all these apparently empty chassis with just empty containers sitting on them all over LA that they can’t get back into the port to send them back. The whole thing is just FUBARed at this point.

Now, our governments are like, “Oh, this is a problem. We need a task force to come in here and figure this out.” But complex adaptive systems don’t work on from a task force. It’s this emergent property to it. It has to almost clear itself out, just like we couldn’t say, “Well, we put in a speed limit or even a speed minimum, why is there traffic? Everyone should be going 45 miles an hour on this road because that’s what we said it needs to be.” That’s just not how it works. My hunch is that this might actually take a long time to get figured out and it may take– I don’t know, we may have a snarled port for a couple of years from here and that wouldn’t be actually totally surprising to me.

Tobias: That’s the estimate that I have seen, back end of 2023. When I heard back end of 2023, that’s just like I don’t know. We don’t know how to fix that problem. It’s going to take so long. We don’t know how to do it.

Jake: Yeah, so what are the knock-on effects of that then as far as Christmas? Christmas of 2021 is-

Tobias: It’s off.

Jake: -obviously, has a question mark on it. Christmas of 2022, I don’t know. What does this change in our world? I think there’s actually probably some big stuff that could be a consequence of this and it’s even that these disruptions, like any system, have echoed out fractally into the system. So apparently, the Chicago rail system, that hub is just totally snarled as well right now, and they can’t get boxes to the right places and moved around. It’s echoed out through the supply chain.

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