Tag Archives: collaboration social+signaling complexity open+space

Clippinger on collaboration.

Tim Kitchin pointed me to this fascinating paper: Human Nature and Social Networks by John H Clippinger. As Tim summarises this gives strong evidence that humans are biologically programmed to collaborate tending to undermine the ravings of “Social Realists” who think the only way to get economic man to do things is to bribe or cajole him.

Clippinger quotes Robin Dunbar’s work Grooming

Could it be that language evolved as a kind of vocal grooming to allow us to bond larger groups than was possible using the conventional primate mechanism of physical grooming? …If conversation serves the same function as grooming, then modern humans can at least groom with several others simultaneously.

This idea really lodged in my mind last week. I increasingly sense that beneath the surface of our supposedly rational conversations something rather more significant is going on. I rather like taking the notion of grooming from the animals and seeing social discussions between humans as a variation of it. Even heated arguments and flame wars may on some level be like the play fighting of animal cubs.

Clippinger explores how we use language to create social signals that support collaboration:

Instead of having to impose such cooperative mechanisms from above or through formal monitoring and intervention processes, highly sophisticated cooperative behaviors can be evoked by creating a context in which the appropriate social signaling takes place. Once given the appropriate signals and rules, groups can spontaneously self-organize and control themselves.

This tends to support the notion of creating simple rules for groups that leave them more scope for self-managment, rather than overspecifying. Open Space facilitaiton strikes me as a very good example of an approach that provides simple social signalling and allows large groups of people to self-organise very effectively.

He also examines how our language can be classified into higher and lower registers. High register language is intended to reduce ambiguity by raising precision. By limiting meaning in this way, it supports precision but also may tend to exclude more people from understanding. (Jargon would be a low-register term to describe high-register language.) Clippinger goes on to note that

Often in an attempt to be more precise and therefore less subject to misinterpretation, high register terms are used to issue orders and tasks on the mistaken assumption that the more specified a term is, the better command intent is communicated.

If I follow Clippinger correctly, he argues that high register language requires more rational processing by the listener in an effort to understand the speaker’s intent; with low register language, the process is nore intuitive. Here’s how he puts it, see if you think I’m interpreting this right.

Unless the task is very technical and well-specified (which even many technical tasks are not), the more effective and reliable course is to use low register terms. Low register terms provide clear signaling, whereas high register terms require the recipient to interpret and improvise within the context that the commander has identified.

The reason that people are able to infer command intent is that, over tens of thousands of years, they have evolved mirror neurons and the ability to construct and confirm common theories of mind through shared experiences. These are extremely important and often undervalued competences that are overlooked because of the mistaken assumption that interpersonal directives can be fully and unambiguously specified through high register communications, or less graciously, bureaucratese. The challenge from an edge command and control perspective is to understand those conditions whereby intent can be most readily and deliberately framed – appropriate language registers, shared experiences, and internalized social protocols.

I think when working with improvisation games, or using Open Space facilitation, the “undervalued competences” Clippinger describes have more space to emerge. I also think this is part of what makes highly function networks, such as those creting Open Source software, formidable.

Finally, I really liked Clippinger’s working defintion of trust:

Trust is the consequence or state when one or more members of a network perform according to mutual expectation.