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Why Bigger Animals Live Longer: The Relationship between Size, Energy, and Longevity Summary: The larger an animal is, the more efficient it becomes in terms of energy consumption. This is because the self-similar fractal structure of larger animals allows them to save energy. Bigger animals require less energy proportionally to run their bodies due to the massive amount of tissue per gram or per cell. As a result, bigger animals experience less wear and tear and live longer than smaller animals. The reason for less wear and tear is that bigger animals use less energy and create less damage, reducing entropy. This principle can also be observed in machines, where those subjected to less stress and driven at lower revs per minute tend to last longer. Transcript: Speaker 2 So that's why we don't need to double our metabolism when we double our weight. It's that fractal like self similarity that allows us to get these essentially efficient savings in the amount of energy we need. So it's better to be bigger, isn't it? Because you don't need as much energy proportionally to run yourself. Correct. Speaker 1 So you need massive tissue per gram of tissue or per cell. You need less energy, the bigger you are. And by the way, this has huge consequences throughout all aspects of biology and life. And maybe one just to tie it back to the beginning of this discussion where we started out by talking about aging and mortality. This means that the bigger you are, the less hard your cell is working. The bigger you are, there's less wear and tear the longer you live systematically. So this is the origin of why bigger things live longer than smaller things. Speaker 2 And why is there less wear and tear if you're bigger? Speaker 1 You're using less energy and creating less entropy. That is you're creating less damage the bigger you are because simply you're using much less energy if you have an engine, an automobile and you insist on racing it at 10,000 revs per Minute every time you drive it, I can assure you that car will not live as long as a car that's driven by a little old lady or a little old man like me who keeps the revs at about two or three Thousand revs per minute. So you know, cars and machines last much longer, the less stress you put on them.

Scaling 2 — You and I Are Fractals

Simplifying Complexity

The need for transparent and democratic decision-making: Human bullshit and algorithmic bullshit are two sides of the same coin Summary: Data and algorithms are not inherently bad, but they should be used in a transparent and democratic way that empowers everyone. Instead of arguing about whether computer or human decision-making is better, we should focus on accountable and transparent decision-making. This means avoiding human biases and stereotypes as well as naive machine learning without considering its real-world implications. Transcript: Speaker 1 So the point is that it's not that data and algorithms are bad it's that they need to be applied in a way which is transparent and which is democratic and which empowers all of us to carry On these debates rather than simply being tools which accurately or inaccurately are being used to buy the powerful to control the rest of us it's silly to argue about which is better You know computer decision making or human decision making that's really not the point I mean the point is we should have accountable transparent decision making instead of bs there's Human bs which comes in the form of stereotypes in ideology and there's algorithmic bs which comes in the form of naive machine learning without thinking enough about its applications

Glen Weyl & Cris Moore on Plurality, Governance, and Decentralized Society

COMPLEXITY: Physics of Life

Perspectives on Organizational Strategy & Coordination: Optimizing for Few Coherent Goals v.s. Many Incoherent Goals Transcript: Speaker 1 I think one of the things where the corporate world is actually much better at this than the academic world or the educational world, because their goal is profit. So it's very clear. It's much harder to say what the goal of an educational institution is. It feels like it should be obvious, but within the general goal of like we want to produce successful, well-rounded people, there's a lot of disagreement about what the goals are. And so shaping the institutional incentives around those goals becomes extremely difficult, because not only do we have to worry about perverse incentives, but we have to worry about Vigorous disagreement about the kinds of things that are valued in the first place. And I think exactly what you're talking about, T, is something that if you went to a bunch of university administrators, let's say, or medical school administrators or doctors, and You said, what is the point to what you're doing? Is it to produce wise, well-rounded people? Is it to minimize costs to insurance companies? Is it to increase donor contributions? What is it? And there are all these competing goals. And so there's this constant infighting about among different people who have different versions of what the best version of their institution is, and it's so difficult to articulate What that is. Speaker 2 I wonder if we're in different sides of this, because are you like worried about the hardness of it? It sounds like you think it's a problem that it's hard to come to agreement and articulate a goal, where I actually prefer the university that disagrees, has many incuit and plural goals, And worry that when it articulates an outcome clearly and starts orienting around that outcome, that's when it starts shedding a lot of what was good about the kind of pluralistic more. So let me just give you this is like from my life, right? So a university I've been employed at has started moving toward orienting everything around student success, where student success is defined as graduation rate, graduation speed, Salary after graduation. When you define that outcome, it becomes really easy to target, and the people that are targeting it, as you say, the people that target it well tend to rise, people that are willing to Go all in on targeting that stuff instead of caring about all the other weird shit that education might be for, tend to have better recordable outcomes and tend to rise in the university Structure. So I actually am happier for something as complicated with education, in which different groups have different conceptions of values about what they're doing, and we don't actually Try to settle it, and we don't hold them all to a high articulability constraint, because I think the business school and the CS department have more easily articulable outcomes than The creative writing department, art history department. A lot of the stuff that I'm writing right now is about like this defense of the inarticulable. Speaker 1 It's a hard question to answer because I think that there are multiple levels of organization going on here. There's like a top administrator level, because these institutions tend to be pretty hierarchical. I think at the top of the hierarchy, there has to be some sort of reasonably well-defined goal, even if it doesn't specify what every individual component of the organization or institution Would do it. And I think that that trickles down to those levels though, and creates incentives. Regardless of whether or not it's a good thing, I think there has to be some sort of coherence at the very top level, even if it doesn't dictate what each individual component is doing.

Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale

COMPLEXITY: Physics of Life

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