Hypothesis: the kind of people who like cybernetics are similar to the kind of people who like category theory. Both fields are about abstract structures that can be applied to several different fields. I am one such person.

My housemate is going to teach a series titled "Baby Category Theory" to the logic students. I intend to go, but I'm a bit afraid that the math will be too fascinating, causing me to become a mathematician and never spend another day of my life as a productive human being.


Cybernetics has an image problem, unfortunately. Its name is frequently abused by the likes of spamferences and crackpots. I hope that respectable scientists don't dismiss its ideas, many of which are common sense.

When teaching us about the common ion effect (about the solubility of pairs of salts), my high school chemistry teacher used to say "equilibria retaliate" (I used to think that he was speaking Latin, but this was just his way of remembering Le Chatelier's Principle). But this is reminescent of the principle of diminishing returns from economics (how far can we make an analogy?). Are we applying chemistry to economics or vice-versa? Neither! That's why we need a more general framework... both of these results are special cases of more or less "universal" structures. This may not be saying much, but it provides me something with which to think: when I see a situation that is analogous, I will predict that adding twice as much of the stuff will give less than twice the return.

What about homeostasis? You see it in economics as well as biology. (keyword for later reference: qualitative reasoning)

Did anyone see Art De Vany - Our Body is Not Communist, arguing that the human body is kept living through an invisible hand? I think he would say that cancer is a market failure, caused by irrational agents.

On-line Pharmacokinetic Simulation, and the course Basic Principles of Dose Optimization

Computer Simulation and Drug Design

Knowledge-Based Simulation of DNA Metabolism
: "An automated simulation of metabolism can play a role analogous to that of ...
solution of systems of differential equations"
Qualitative Simulation of Large and Complex Genetic Regulatory Systems

btw, when I don't quote a paper here, that usually means I haven't read it thoroughly enough to judge it.

Thank you, Google.

thread at tdj's about carbon-dating individual human cells (it's a very clever idea):

In discussing the required experimental precision / error, I proposed:

Here's a causation network:

A: atmospheric levels of C14 at time of cell's birth
B: initial amount of C14 in cell's DNA (i.e. at birth)
C: time passed since cell's birth
D: amount of C14 in the cell's DNA
E: "measured" amount of C14 in the cell's DNA (this is actually an estimation based on a measurement of radiation emitted by the cell)

A
 \ 
  B   C
   \ /
    D
    |
    E

In order to infer C, we need to know B and D (this inference step is pretty much dead-on if you have enough C14 atoms (by the law of large numbers)). We estimate D as E (noisy, experimental measurement), and B from A (also noisy, say due to non-uniform C14 levels + random variation in the cell birth process (?); one estimation for each point in history, although this "estimation" may be analytic, not statistical).

How many carbons atoms are there in DNA?
...discussion continues...

I really love making models like this.

I'm sure I've linked to CMU's Tetrad Project / Causality Lab before. But it never hurts to give them another plug.