A Life of Starts

There’s too much to do! First, the weather this weekend looks beautiful and I get next Monday and Tuesday off, so I’m going to try biking from Boston to New York starting Saturday morning. Wish me luck!

I have three bite-sized ideas that I’ve been chewing on. I don’t know when I’ll have time to finish them, so here are some notes, take them as is.

Inner Lives of the Undead

Much has been said about the lives of the undead– the haunts of ghosts, the missions of zombies, the homes of vampires– but very little of their inner life. Their mental experience is assumed to be either empty (e.g. for zombies) or roughly human, if sociopathic (e.g. for vampires).

It is neither. The undead have a very active inner life. Even a manic one.

It is characterized by “deadness and excitement, stuckness and agitation”; perhaps best described as “petrified unrest.” (On Creaturely Life, Eric Santner, p. 81). In a word, their disposition is an ultimate melancholy. But melancholy is not depression– far from it. It is a kind of unrelenting pensiveness.

It is no surprise that there is a reawakening of interest in the undead now. Our lives are typified by the undead attitude: we live lives of political undeath and economic undeath, without hope of recourse or rest. This is also a time of deep capitalist supremacy, which is itself a kind of undeadness, characterized first by “uninterrupted disturbance of all social conditions, everlasting uncertainty and agitation”, and by endless commodities transformed by economic value to have “phantom-like objectivity”: they are “autonomous figures endowed with a life of their own” (Marx, Communist Manifesto and Capital). We are surrounded by the undead.

Senseless Economics for PhDs

Prof. — began his class on Microeconomics with a set of standards: economic theory, he said, should be testifiable (i.e., falsifiable) and identifiable (within the real world). By those standards, he refuted every one of his models: rational preferences, aggregation, the independence axiom for uncertainty, welfare measures, increasing utility. All of these are bunk.

We just entered the section on general equilibrium, and were presented with our model of an economy, and it is similarly senseless. There are no (and cannot be) externalities, no interdependencies, no public goods, no waste, no government; firms are mindless (but non-monopolistic) profit-maximizers, individuals are utility-maximizers, private ownership is universal, and equity is irrelevant.

I have learned nothing in two months of microeconomics. It’s true that I can manipulate more equations, but they have no relevance. Economics gives you a unicorn harvester, and sees everything as a unicorn. But there are no unicorns.

Perhaps it’s just a pedagogy problem. For me, a PhD student should be ready to work with real models, and the best way to teach something is to present it in its whole. Perhaps if I were to take years more of these classes, they would eventually teach applicable material. Personally, I don’t see the point of waiting. If you want to understand people individually, psychology has models that can run rings around economics. If you want to understand society, study sociology. Don’t waste your time hunting unicorns.

The Nature of Variability

Much of what I and my colleagues are currently studying hinges on an undefined concept: variability. A storm turns from a nuisance to a disaster because of climate variability; electrical power becomes useless to economic development when it has too high of variability. Some variable phenomena, like earthquakes, can be described by a power law, but this gives us only one theoretical handle on a complex mechanism. The question of variability is always deflected to some other quantity, because we don’t know what it is, and the loss to research is enormous.

Variability is not just statistical variance or power law exponents. It would need to involve at least both variance in time (which is entirely ignored) and variance in event intensity. In fact, I claim that a reasonable definition of variability requires at least four parameters: frequency and intensity variance, and how each of these evolve in time after an event (what I call the entropy rate and the collapse sensitivity). After an event (e.g. an earthquake, storm, or outage), and depending on its intensity, our knowledge of likely future events changes in predictable ways.

Furthermore, there’s an exciting potential to tie into quantum dynamics. The collapse of the probability functions after an event is eerily reminiscent of particle wave function collapse. And just as the uncertainty principle comes out of fundamental principles, applicable to much more than tiny particles, the results of Schrödinger’s equation may help us explain how these probability evolve in time. There’s a potential for re-envisioning the world, if we can just find time.

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