You have heard about Wall Street’s love of fancy computers and sophisticated trading platforms. But you may not realize just how important computers have become to Wall Street’s day-to-day trading operations.

Financial blogger Felix Salmon has posted a clearly-written, easy-to-digest summary of the rise of these (trading) machines.

Salmon’s piece is particularly good at describing the dependence of Wall Street traders on their algorithmic trading mechanisms for the precise identification of profitable trades. Here are some of the key points:

“The machines aren't there just to crunch numbers anymore; they're now making the decisions. That increasingly describes the entire financial system. Over the past decade, algorithmic trading has overtaken the industry [to the point that] computer code is now responsible for most of the activity on Wall Street. (By some estimates, computer-aided high-frequency trading now accounts for about 70 percent of total trade volume.)

“Algorithms have become so ingrained in our financial system that the markets could not operate without them. The result is a system that is more efficient, faster, and smarter than any human....At its best, this system represents an efficient and intelligent capital allocation machine, a market ruled by precision and mathematics rather than emotion and fallible judgment...For better or worse, the computers are now in control.” (emphasis added)

To help lighten the tone of the article, Salmon’s editor (or perhaps Salmon himself) decided to accompany the piece with pictures of colorful old wind-up toys, perhaps to say that no one should feel threatened by Wall Street’s robo-traders. Myself, after reading the article, I wondered if Salmon should have asked for a photo of the sinister Skynet system from the Terminator movies to appear alongside the article.

Salmon tries to capture algorithmic trading’s good points and bad points. On one hand, algorithmic trading has created a trading system he says “is more efficient, faster, and smarter” than one relying just on human input.

On the other, Salmon is concerned that the algorithmic trading model “has outgrown the humans that created it." And he touches on the risks of all these computers making trading decisions faster than their flesh-and-blood overseers can predict the consequences of those decisions.

Let’s accept, as Salmon says, that algorithmic trading allows Wall Street to “buy and sell stocks much faster, cheaper and easier than ever before.”

There’s still the question of what goal all that trading and stock churning serves.

Is it to help allocate capital to support the rest of the US economy – in particular, for lack of a better term, the “real” economy, like manufacturing, where actual physical things are made for domestic consumption and export?

If that’s the goal of algorithmic trading, then let’s call off the experiment right now. It is clearly not working out that way, as any report on unemployment or the state of US manufacturing will tell you.

Or is all the churn just a way to earn fees from clients and make a quick buck?

We can talk about the advantages that algorithmic trading has given Wall Street, and we can argue about the risks it creates.

However, unless we first establish whether algorithmic trading actually benefits the US economy – the “real” economy – such discussions are a lot like those disputes among medieval theologians over topics like “how many angels can dance on the head of a pin.”

That is, they are speculative at best – and a distraction, at worst, from more pressing matters.