Pharmacology and the limits of accumulation

A notion to incorporate in the patterns, and related to the ability to read and react on signals to enable self-correction is the notion of pharmakon a concept broadened by Bernard Stiegler.

Pharmakon is the Greek word meaning both poison and medicine.

As much as a medicine can become a poison when abused, a poison can become a medicine in small quantities (re arsenic in homeopathy). Patterns can become anti-patterns if abused, and small doses of anti-patterns can be beneficial if only to keep the system in 'watch'.

Anything that is over applied reduces the variety and resilience of the system and makes it brittle or ends up by poisoning the system. One of the reasons our system is going into the wall is that we over apply recipes, loosing track of why they were used in the first place. We over-apply models or patterns and concentrate on measuring the rate of application of the models not the outcome and the accumulated effects of the model, or we apply the wrong models to situations.

For example positive feedback loops are wonderful in our system because they are sources of growth, expansion, and abundance. But the more they are at work, the more they drive the system into one direction at faster paces the momentum and course of which is extremely difficult to change, turning abundance into overexploitation, making the system easier to game and unresponsive to signals of decay or overshoot, unable to engage in self-correction or meaningful disruptive innovation, powerless in the face of systemic risk and instantaneously breakable by glitches or black swans. An analysis I have expanded in a Spanda Journal article.

The window of viability (Lietaer & al 2010) in which all sustainable natural ecosystems operate, at the point of optimal balance between two polarities such as efficiency and resilience offers a good example. Similar approaches could be taken with other polarities such as competition and collaboration.

We will be looking at which 'pairs' of patterns can help optimize each other, and at incorporating in our patterns some heuristics to explore the points at which a pattern can become an anti-pattern.