Re: Resistance to Change LO1165

Michael McMaster (
Fri, 12 May 1995 07:03:02 +0000

Replying to LO1140 --

Peter suggests that there might be an "innate resistance to change".
This rekindles my interest in the resistance conversation. I've
already had my say about resistance to change as a phenomenon that
we've generated in our way of speaking - and which can be transformed
or reframed by our speaking. Others too have said this in different
and creative ways.

But now we have a new perspective or at least a new scale of view.
> >This phrase (resistance to change) implies that we humans >have some innate
> resistance to change, which of course is >nonsense.
> I wouldn't jump to the conclusion that an innate resistance to change is
> nonsense.
> Some research work (including computer modeling) I'm doing seems to be
> pointing in the direction that there may in fact be an innate tendency to
> resistance change.

The phenomenon Peter is referring to has good evidence to support it.
What it does, is reveal that we can call many things or conditions
"resistance to change". For instance, we might call the resistance
of a wire to electricity passing through it "resistance to change".
We don't do that, of course, because wires (inanimate matter) can't
doesn't have the requirement for the _kind_ of resistance that we are
talking about.

However in living systems, individual or organisational, we may have
a similar situation. The natural "resistance" we frequently call
"conservatism". That is, in any system with an historical nature
(any living system) there is a force - which we might call
organisation or design - to maintain what _is_. The survival value
of this is that whatever _is_ has survived so far and its maintenance
or reproduction is likely to be successful in the future. In
language with less potential for anthropomorphising, a particular
organisation unity (identity) has discovered a fit with the larger
environment or organisation and its continuation is built in by
staying the same.

Now, is that entity - whether individual or organisational -
exhibiting "resistance to change" when a force attempts to alter its
relationships to its surroundings? Or might it be more powerful to
simple consider that it is exhibiting its nature? In the latter
case, I have more freedom to alter its environment and allow it to
adapt in its own ways as part of its natural survival activity. As
Peter says later (and in the sense suggested by his communication and
developed here) "I sense that resistance to change is an essential
part of a learning organisation." Sure. It's in the nature of the
entity that is learning - its what we call identity.

To make the point: the individual or organisation may have no more
"choice" about its nature of "resisting change" than the wire. The
choice (or at least variety of response) is greater due to its nature
but the "resistance" may be as strongly in its nature.

Peter then mentions genetic algorithms and their operations.
> Work in the area of genetic algrorithms clearly points
> to an optimum rate of change resulting from mutations. Too many mutations
> too quickly results in "learning" being lost by the system. On the other
> hand, too few mutations too slowly results in the system not learning
> quickly enough.

Genetic algorithms demonstrate "resistance to change" in that they
can only "be what they are" or follow the rules for change that have
been assigned. These rules are usually some crossover funtion
applied only to the more successful of those in the population - that
is, the ones that are successful "swap genes" (or bits of computer
code) according to some formula. In this sense, "resistance to
change" is built in - not too different from any historically based
entity. This, by the way, is more properly referred to as crossover
or recombination rather than mutation. Mutation is generally
considered to refer to random changes from outside forces and is not
a major factor in change - and certainly not a mainstay of learning.
(For those who are interested, there are people on this list - I'm
not one of them - who have papers dealing with genetic algorithms
and production processes and requests may make them available.)

Experiments with genetic algorithms do also show that too much
learning or learning too rapidly has certain costs and that there is
an optimum rate of learning for a set of entities.

The leap that Peter took to this "lesson", however, introduces a very
different conversation or logical thread. The rate of learning that
is appropriate is a major conversation in its own right. It is
related to the nature of an historical entity but not particularly to
the thread of "resistance to change" that is this conversation.

Michael McMaster