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author: niplav, created: 2024-01-30, modified: 2024-01-30, language: english, status: draft, importance: 5, confidence: certain

I collect civilizational inadequacies and perform an inadequacy analysis on some of them.

Contents

Some Civilizational Inadequacies

Fragile Tableware

Ceramic/porcelain plates and cups made of glass break easily, while the æsthetics we have around them seem mostly path-dependent (and perhaps even caused by their fragility, leftovers from a time where fragile tableware signaled wealth).

Cooling: Generally, porcelain plates have the advantage that food placed on them cools less quickly. Wikipedia states that porcelain has a thermal conductivity of ~1.4 to 1.9 $\frac{W}{K \cdot m}$ at ~400 Kelvin, and pyrex glass variants have thermal conductivities of 1-2 in the the range 273-373 Kelvin, while Aluminium (a contender for a substance out of which to make plates, glasses & cups) has a thermal conductivity of ~100 $\frac{W}{K \cdot m}$ at 273 Kelvin — which leads to faster cooling, and colder food is less enjoyable to eat. However, we don't have to be stupid about this: plastics lose heat even more slowly than porcelain (generally with thermal conductivities <1).

Æsthetics: The other advantage of porcelain and glass is that they just look so much nicer. I don't have any strong rejoinders here, my æsthetics rejoice in knowing that I'm doing a thing that is more economical—but I acknowledge that I'm in the minority there. The only guidepost I can offer is to look at the price and then ask: "Are the æsthetics worth this price?" If yes, go ahead! If not, I may have pointed out something interesting.

Code for a slightly more complicated Fermi estimate, (mis)using the probabilistic programming language Turing.jl:

    using Turing, Plots

    @model function ceramic_glass()
            people ~ Normal(8*10^9, 0.05)
            meals_per_day ~ truncated(Normal(2.5, 1), lower=0)
            proportion_tableware_users ~ Beta(5, 2.5) # Mean ⅔
            breakage_per_meal ~ Beta(1.5, 1000) # Mean ~0.0015
            cost_per_tableware ~ truncated(Normal(2, 0.5), lower=0) # In dollars
    end

    chains = sample(ceramic_glass(), IS(), 10000)
    sampled=get(chains, [:people, :meals_per_day, :proportion_tableware_users, :breakage_per_meal, :cost_per_tableware])
    total_cost_per_day=sampled[:people] .* sampled[:meals_per_day] .* sampled[:proportion_tableware_users] .* sampled[:breakage_per_meal] .* sampled[:cost_per_tableware]
    mean(total_cost_per_day)
    4.00195809996674e7
    gui(histogram(total_cost_per_day, label="samples", xlabel="cost", ylabel="number of samples"))

And using squigglepy:

import squigglepy as sq
import numpy as np
import matplotlib.pyplot as plt

people=sq.norm(mean=8*10**9, sd=0.05)
meals_per_day=sq.norm(mean=2.5, sd=1, lclip=0)
proportion_tableware_users=sq.beta(a=5, b=2.5)
breakage_per_meal=sq.beta(a=1.5, b=1000)
cost_per_tableware=sq.norm(mean=2, sd=0.5, lclip=0)
total_cost_per_day=(people*meals_per_day*proportion_tableware_users*breakage_per_meal*cost_per_tableware)@100000

np.mean(total_cost_per_day)
40423162.50675405

This is a clear case of where estimational programming has a strong advantage over probabilistic programming.

Note that this code only estimates the costs of fragile tableware, and makes no statements about the costs of e.g. switching to alternative materials.

Appendix A: Civilizational Adequacies

I use the term "civilizational adequacy" in a very strict sense here: Areas where our world surprisingly overperforms, implementing policies or having institutions that, given one were to observe them, would indicate our civiliation being adequate in many other dimensions too. "Mundane" but still impressive infrastructure doesn't count, even though it's really good. See also Croissanthology 2024.