Another post related to Clark’s “Being there” (see previous post on this). The central thesis of Clark’s book is that we should look at people as reactive creatures acting in the environment, not as disembodied minds acting on it. I agree wholeheartedly with this non-dualist view of mind/body, but every so often Clark’s enthusiasm leads a little too far – but then this forces reflection on just what is too far.

In this case the issue is the distributed nature of cognition within the brain and the inadequacy of central executive models. In support of this, Clark (p.39) cites Mitchel Resnick at length and I’ll reproduce the quote:

“people tend to look for the cause, the reason, the driving force, the deciding factor. When people observe patterns and structures in the world (for example, the flocking patterns of birds or foraging patterns of ants), they often assume centralized causes where none exist. And when people try to create patterns or structure in the world (for example, new organizations or new machines), they often impose centralized control where none is needed.” (Resnick 1994, p.124)¹

The take home message is that we tend to think in terms of centralised causes, but the world is not like that. Therefore:

(i) the way we normally think is wrong

(ii) in particular we should expect non-centralised understanding of cognition

However, if our normal ways of thinking are so bad, why is it that we have survived as a species so long? The very fact that we have this tendency to think and design in terms of centralised causes, even when it is a poor model of the world, suggests some advantage to this way of thinking.

Of course, this may simply be an accident of our neural architecture — in which case it would be important for (ii), or may be adapted for a hunter gatherer life, but not 21st Century living – but again would be interesting for (ii). However, the fact that we are still here means it is certainly not too unsuccessful.

Whatever the reason, the fact that we think in these terms is itself an empirical data point for understanding human cognition. We have brains that tend to seek centralised solutions – what are the neural and cognitive mechanisms that drive this and what are the environmental reasons that make it work.²

There are two factors at work here, one is about the way we see the world and the other about the way we plan and act on it.

At the level of perception, one of the Gestalt laws is that things that move together belong together. Even if bushes hide most of a predator from view, the several disconnected tiny moving fragments still form one large animal you need to avoid.

Yes this is a gross simplification of reality. Look at a rock – it is an ‘it’, a single thing – but in fact it is not, it is simply the decentralised activities of millions of millions of millions of millions of atoms interacting, largely locally, with one another. It is not so far unlike Resnick’s flock of birds. However, their general coherence of motion and substance makes it sensible to regard it as one thing. As a scientist understanding the decentralised emergent phenomenon is interesting, but as a gardener wanting to move the rock it is an intellectual luxury and the (incorrect) centralised view of a the rock makes sense.

In real world problems, sometimes decentralised solutions work, other times they don’t.

I was once driving in Rome on a Saturday night (happily with a native Roman to guide me). It was after 11pm so they turned off all the traffic lights (as Italians ignore them anyway) and we came to a massive crossroads with completely full three lane roads in all directions. The space was filled with a criss-cross of apparently grid-locked cars and I thought we would be stuck there until a policeman came, but my navigator told me to simply drive. Every time the slightest gap opened, be it only a few inches, I would edge forward. Eventually, but after a relatively short time, we found ourselves at the other side. Thinking afterwards I realised that always some car was able to get out and I fact the ‘greedy’, decentralised algorithm worked perfectly.

Driving is different in north-west Scotland where there are long stretches of narrow single-track roads with passing places. When you spot a vehicle coming you watch out for a passing place and whichever of you gets to the one first waits there. If you notice too late and meet, then the person closest to a passing place may need to reverse. This is another local, slightly more polite, but semi-greedy algorithm, with each person making independent choices and trying to proceed, but taking into account immediately close road users. However, when single track roads get too full, this can fail. In situations, like the passing goods-train puzzles, where lines of vehicles have to pass with only single passing place, then often long lines of vehicles have to backup, go forward again, reverse again, in apparently disorganised ways – and ways in which each single driver cannot understand from local conditions alone. People have to get out their cars and start to coordinate their efforts.

Note that the decentralised strategies work remarkably well, and when they do require less effort than coordination. However, the reason that we do more than that, and think in ways that have an (at least behavioural) appearance of centralised control is because for certain problems this is needed – not least in complex social and technological situations.

With a HCI hat on, when we come to designing for people, we get the best solutions not when we ignore one aspect or another, but when we recognise the relative strengths of the two and how they can work together.

I recall when I was a child (yes over 30 years ago), seeing a television report about Benetton’s new CAD systems. The problem was cutting out rolls of cloth to make pieces for clothing. Traditionally an experienced cutter would arrange the pieces for a single garment as tightly as possible (to avoid waste), whilst ensuring proper orientations. These were then cut using a special form of guillotine. The new system of cutting from the roll allowed them to take the pieces for several garments and organise them over a long run of cloth for cutting. Doing several garments at once offered savings in terms of less wastage, but was a more challenging arrangement tasks — hence computer aid. The computer would take pieces initially arranged on (virtual) fabric and ‘jiggle’ them until they fitted closer with les waste. However, an experienced cutter would oversee this process and make large scale changes, “what if we tried this large piece over here?” The computer’s activity would have been serial, but could have been parallelised as it involved effectively lots of small local decisions. However, the human made strategic decisions, that themselves made use of the human’s internal associative pattern recognition, but from the point of view of the large system were effectively more centralised. Here a combination of centralised and decentralised thinking/computation together addressed a problem neither could solve on their own.

Finally, it is interesting to reflect on the ability demonstrated in both Clark and Resnick’s writing. They look in at our modes of thinking, see that they are often over-simplistic in terms of assuming central control when there is none, and then consider how to address this. This highly reasoned and reflective process does not arise naturally from decentralised thought that would simply go on using the same old ways of thinking, but is the product of exactly the more ‘rational’ linear, centralised thinking that they seek to expose as outmoded.

1. Mitchel Resnik (1994). Turtles Termites and Traffic Jams: Explorations in Massively Parallel Microworlds. MIT Press.[back]
2. This is similar to the argument in my previous post on the power of sequential thinking, where I pondered the complexity of establishing sequence within an underlying parallel and distributed neural superstructure — but also discussed the advantages it brings. Sequentiality and central control are of course closely linked. [back]