Black-boxes, part I

Michel Trottier-McDonald
so many slugs
Published in
3 min readJun 18, 2015
IMG_0058
As close to a supercell you will see over Geneva. Nature is a black-box we didn’t make (but we still want to tinker with it).

I’m a big fan of the Skeptic’s Guide to the Universe. They do an excellent job at covering recent science-related news items in depth. On occasion, they have thematic discussions during which they explore the ramifications of a particular concept. In episode #513 and #514, they discussed black-box technology.

A black-box is a piece of technology that is disproportionally complex compared to how easy it is to use. Black-boxes are notoriously scary since there is the possibility that they behave in ways very few people (or even nobody) can understand. A good example is stock trading as it is currently done on Wall Street. It is an ecosystem made of a multitude of algorithms competing to find the safest trades first. They are capable booking tens of thousands of trades per second, a pace no human can compete with. This is an ecosystem so complex it is unpredictable, in the same way the weather is unpredictable. There was at least one incident which took years to fully understand. The ecosystem appears to be mostly stable, but the occurrence of the flash crash casts reasonable doubt on how safe it really is.

Adopting the use of a black-box amounts to delegating, and consequently relinquishing control. Human beings don’t usually enjoy doing so, especially if they take pride in the activity they are delegating. However, in practice, we do it all the time for obvious reasons. Black-boxes allow us to do things so complex we thought them impossible not so long ago. They enable us to do certain things faster and better than we would otherwise be capable of. This is not the kind of advance you turn down lightly.

The discussion on the SGU have a distinct taste of nostalgia for a simpler time when one could tinker with commercial technology. For example, not that long ago, it was frequent practice among computer geeks to buy pieces off the Internet and customize your desktop computer with extra RAM, disk storage, etc. This is not so easily done with your iPad.

I remember that time with nostalgia as well. When I started CÉGEP, the computer labs had just been equipped with with newer PCs. The old ones were sold very cheaply with a lottery. That’s how I got the first computer I owned. I had a lot of fun trying to make this old piece of junk more reliable and more powerful. I learned about computer hardware, and was eventually able to play Warcraft III with decent graphics performance on it, record music, watch Stargate SG-1, etc. It was tremendously fun and rewarding.

What I remember is that the impulse to improve my computer was driven by necessity and excitement. Today, that necessity is gone. The tools I need to accomplish what I wish to do are readily available. I have way more graphics power than necessary to run Warcraft III, I have first grade equipment and software to record music, and I can re-watch Stargate SG-1 on Netflix. The systems I now use to do what I wish are definitely more difficult to tinker with, but the need and desire to tinker has decreased in proportion.

The real thing to lament here is the loss of an opportunity to learn. I cannot learn about basic desktop computer architecture simply by trying to improve my own computer. However, computer architecture has evolved significantly since then, and a lot of what I learned doing this is now obsolete. To move on the discussion, let me bring an example of the “black-boxing” trend in technology that will make some of its consequences more clear. Next week, I’ll talk about programming languages.

Read part II here.

This time, here’s a very brief time lapse of a storm cell evolving over Geneva. It’s a different one than the one in the picture above, it was captured a year before. I don’t know how long I’ll be able to put a new time lapse video in every blog post, I’m bound to run out of material eventually :).

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Michel Trottier-McDonald
so many slugs

ex-particle physicist turned data scientist who spends way too much time reading about North American politics