Fun with representations VI – Sharing the load

In Cognition in the Wild, a book I’ll be coming back to later and often in this blog, Ed Hutchins expands on an observation by Herbert Simon, who said that the complicated movements and trajectories of an ant on the beach tell us more about the beach than about the ant.

Beach antSimon was emphasizing the importance of context in cognition, but Hutchins goes a step forward: “Let us assume that we arrive just after a storm, when the beach is a tabula rasa for the ants. Generations of ants comb the beach. They leave behind them short-lived chemical trails, and where they go they inadvertently move grains of sand as they pass. Over months, paths to likely food sources develop as they are visited again and again by ants following first the short-lived chemical trails of their fellows and later the longer-lived roads produced by a history of heavy ant traffic. After months of watching, we decide to follow a particular ant on an outing. We may be impressed by how cleverly it visits every high-likelihood food location. This ant seems to work so much more efficiently than did its ancestors of weeks ago. Is this a smart ant? Is it perhaps smarter than its ancestors? No, it is just the same dumb sort of ant, reacting to its environment in the same ways its ancestors did. But the environment is not the same. It is a cultural environment. Generations of ants have left their marks on the beach, and now a dumb ant has been made to appear smart through its simple interaction with the residua of the history of its ancestor’s actions.”

Of course, the whole point of the story is what it implies about us: I am as dumb as a barbaric caveman, but I got a better environment. We accumulate knowledge, we embed it in our surroundings, and the next generation will take for granted things that are unbelievably hard for ours to figure out. If humankind manages to stick around for some thousands of years more, when it looks back to our current intellectual and technological achievements they’ll appear as rudimentary to them as the Bronze Age seems to us.

This, in a nutshell, is the reason why good representations of information, which I have been discussing over and over, are so powerful. They synthesize the data we gather about the world into a format that is easily accessible for other people -and for ourselves- any time we need them. An encyclopedia represents centuries of inquiry and discovery; a name tag helps us remember the name of that stranger we just met. Both of them and all other representations in between help make us smart by holding knowledge in our stead.

This quality of representations, which may be referred to as cognitive offloading (since it saves us cognitive effort), comes in two flavours. I’ll call them memory offloading and rules offloading here.

Memory offloading: This is the easy type to spot – anything that holds data for us counts. Books are an obvious example – instead of having their authors talk to us, we conveniently get access to their thoughts whenever and wherever we want. Phonebooks, websites, and dictionaries, hold massive amounts of information that we’ll never need in full, but which we can query on demand. Keys in the computer keyboard in front of you have labels to indicate the characters to which they correspond. We take photographs because they hold much more detail, for a much longer time, than our natural memory can. And so on.

People that can perform at an expert level without the aid of these representations are pretty impressive. My favourite example is blind chess players. The point of blind chess is never looking at the board, having instead the “image” of the match in your mind. It’s a very serious handicap if only one opponent is playing blind – most chess players can’t hold a dozen moves before their mental image crumbles down. Still, my chess instructor fifteen years ago would consistently beat the crap out of me even with this advantage in my favour. How did he do it, I have no idea. And grandmasters can win some half-dozen simultaneous matches while playing blind!

Anyway, my point is that most people depend on memory-offloading representations to do most of their tasks, and we find it extraordinary when someone seems not to. This dependency extends to the other type of offloading as well –although people have a harder time seeing it.

Rules offloading: Remember the nine numbers game I talked about a while back? The relationship between that game and tic-tac-toe is that of a representation with poor rules offloading versus one with rich rules offloading. When playing the nine numbers game, you need to keep track of several rules:
• Addition rules and additive properties
• That the purpose of the game is to add up to 15
• That you need to get to 15 with three numbers exactly

Instead, when playing tic-tac-toe, these rules get lumped into a visually intuitive one:
• That the purpose is to form a straight line from one end of the grid to its opposite end

As I’ve said before, this makes the game much easier, and accessible even to people with no arithmetic knowledge. Similarly, one can always make the nine numbers game more complex by adding rules that increase our cognitive load –for example, representing the numbers in the binary system (1, 10, 11, 100, …, 1001), instead of the decimal system (1, 2, 3, …, 9); which would force us to perform some extra, unusual calculations.

Software tools are particularly helpful when it comes to offloading rules. In a way, this is precisely what they do. Spreadsheets simplify a multitude of tasks –for instance, preparing a detailed budget or calculating the standard deviation of a series of numbers. Email clients connect to servers using a complex protocol that is unreasonable for us to follow personally. In general, computers have come a long way from the card systems of the past to the commodity of our monitors and connectivity, simply because so many of the rules necessary to operate them are embedded in the devices.

Offloading knowledge in representations is so powerful that I’m often surprised to find resistance to doing so. I guess this is what bothers me about developers who don’t comment their programs because “the code speaks for itself” – those who dismiss syntactic enhancements as sugar, who proclaim that Real Programmers code in assembly, or who brag that they don’t need and never will need debuggers. Maybe code speaks for itself, but it speaks slowly. Rejecting these advantages now and then, as a habit to train yourself, may be a good idea (just as it’s a good idea to be able to perform mathematical operations without a calculator); but rejecting them in your professional life is frankly foolish, as foolish as competing as playing blind chess in a world-class tournament.

We are as smart as our environment allows; if we want to achieve greater goals we should free our minds by sharing as much of the work as possible with it.

(Beach ant photo by kitsu)

About Jorge Aranda

I'm currently a Postdoctoral Fellow at the SEGAL and CHISEL labs in the Department of Computer Science of the University of Victoria.
This entry was posted in External cognition, XCog. Bookmark the permalink.

3 Responses to Fun with representations VI – Sharing the load

  1. Yoni says:

    Thanks for the wonderful post, Jorge. I find your explanation of memory offloading and rules offloading very interesting. A couple of thoughts, though:

    1) I completely agree with your dissatisfaction with programmers who write unreadable code. It reminds me of this article (, particularly the part about maintainability. I think you are confusing the issue of maintainable, readable code with that of syntactic sugar, but that’s a different topic.

    2) You draw a conclusion (or perhaps a prediction), based on the ants analogy, that future generations will be much more advanced, both technologically and intellectually, because of the accumulation of prior knowledge.
    Now, I think that evolution gave ants the ability to tap on previous knowledge in a superb, and almost instant, way. An ant can use all of the prior knowledge that it finds, of previous generations, in its own lifetime.
    I am not sure if that is true about humans as well. It still takes about 7 years to finish an MD, or a PhD in Physics; those sciences have advanced tremendously in recent centuries. Even after finishing their studies, Doctors and physicist specialize on a small fraction of that knowledge.
    A NASA engineer can use centuries of information to build a shuttle to the moon; he specializes; it may take him 20 years; but the rest of us won’t understand how he did it, even if he draws a diagram to explain it. His representation, however good it is, won’t do the trick.
    Sure, encyclopedias help, and previous knowledge is there for us to use, but we are limited by the speed at which we can absorb new information. I guess this limit imposes an upper limit on how powerful your representation can be.
    (Unless, of course, you live in The Matrix, and all barriers are broken loose. Trinity learned how to fly a chopper in mere seconds)

    3) I always wanted to tell you that you are as dumb as a barbaric caveman. I am just glad you said it first🙂

  2. Jorge says:

    I have consistently demonstrated I’m as dumb as a caveman -I’m just stating the obvious🙂

    You’re right in that it’s been a while since we reached the point where specialization is required, and I see your point about progress flattening because of the inherent difficulties of the problems we now deal with. Will there ever be High School courses on quantum mechanics or genetic engineering, just as we now have courses on Calculus? Perhaps not (and perhaps they would not be useful for everyone anyway). But the fact that we need to specialize has not negated the impact of learning from previous experiences -we may not understand the NASA engineer explaining the detailed workings of a shuttle, but another qualified engineer will, and an even better shuttle will come from this understanding.

    And if enough rules are embedded in an helicopter, why wouldn’t we be able to “learn” to fly it in seconds, if all we need is to get in and state where we’re going?

  3. Pingback: Offloading and evolution « Catenary

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