Back from Chaos

See also: Beyond Nudge Theory RtoL Quick Guide: Strategic Advice for “Nudging” (Transitioning States)

Central to Systems Thinking is the ability to nudge, manage or otherwise cajole the systems into one state or configuration in preference to others it echoes Vicker's comments of 'why this not that' or Ashby's comment that 'a cyberneticist is a man who observes what could have happened but did not' what approaches and techniques do the authors in 'v2-combined' suggest can be employed to manage this choice contingency especially when moving a system from a state of random dynamism to a more ordered and predictable state (from Weaver's disorganised complexity to organised complexity)

To move a system from disorganized complexity (random, stochastic dynamism) to organized complexity (structured, predictable function), the authors in the provided collection suggest that practitioners must act as “selectors” of reality.

Managing “choice contingency”—the ability to steer a system toward one state over others—requires moving beyond direct force. Instead, it involves identifying and manipulating the constraints that filter random flux into ordered patterns.

1. The Mechanism of Choice: Configurable Switches

For a system to move from randomness to order, it must possess “configurable switches”—physical nodes that are not determined by natural laws and can therefore be set by formal choice.

• Dynamic Inertness: To exercise choice, one must find elements whose state is “dynamically inert,” meaning physical forces (like gravity or chemical valency) do not dictate their arrangement.

• Prescriptive Information: Once these switches (e.g., bits in code or specific organizational roles) are identified, choice contingency is exercised by applying “Prescriptive Information”—instructions that direct the system toward a specific pragmatic goal.

2. The Technique of “Negative Explanation”

Rather than asking what caused an event, the authors suggest focusing on what prevented all other possibilities.

• Filtering the Flux: James Wilk suggests that continuous, random change (flux) is the natural state. Management is the act of filtering complexity by identifying the “local constraints” that maintain a specific pattern against that flux.

• Why This, Not That: Following Vickers and Ashby, practitioners should identify the “moulds used to cast the parts” (the environment/constraints) rather than focusing on the parts themselves. By changing the gears of the “Spirograph” (the environment), the “pen” (the system) spontaneously reorganizes into a new, preferred state.

3. Managing Probability via Constraints

Alicia Juarrero suggests that “choice” in complex systems is the management of a system’s probability distribution within its phase space.

• Context-Independent Constraints: These are fixed limitations or boundaries (like physical walls or rigid laws) that take a system away from absolute randomness and create a “canvas” for work.

• Context-Dependent Constraints: These are relational rules (like feedback loops, catalysts, and social norms) that correlate previously independent parts into a coherent whole.

• The Nudge: To move toward order, the practitioner does not apply force (efficient causality) but modulates these constraints to deepen a “basin of attraction,” making the preferred state more likely to occur than others.

4. Variety Engineering: Absorbing Randomness

To move from disorganized to organized complexity, a regulator must adhere to Ashby’s Law of Requisite Variety: “Only variety can destroy variety”.

• Attenuators and Amplifiers: Management manages choice contingency by designing “attenuators” to filter out environmental noise (randomness) and “amplifiers” to boost the system’s internal response capability.

• Variety Engineering: This is the deliberate process of matching the internal complexity of the organization to the external complexity of the environment to ensure the system remains “in control”.

5. Transitioning through “Generating Systems”

Christopher Alexander provides a technique for moving into organized complexity by designing generating systems rather than fixed objects.

• The Rule-Set: Instead of a blueprint (a static answer), the practitioner designs a “kit of parts” and a set of “combinatory rules” (a syntax).

• Wholeness-Extending Transformations: Every “nudge” or change must strengthen the “existing wholeness” by identifying and emboldening “latent centers” already present in the environment. This allows a system to “unfold” predictably like a seed into a flower, rather than being haphazardly fabricated.

Summary of Techniques for Choice Contingency

Technique	Proponent	Action	Goal
Minimalist Intervention	Wilk	Identify and change a small “context-marker”.	Trigger an instant “flip” to a new state.
Idealized Design	Ackoff	Design the system from scratch as if the old one were destroyed.	Dissolve “messes” by bypassing existing constraints.
Constraint Modulation	Juarrero	Alter the probability distribution of the landscape.	Destabilize bad states; stabilize desirable ones.
Configurable Switching	Abel	Active selection at dynamically inert logic gates.	Instantiate formal intent into physical systems.
Variety Engineering	Ashby/Beer	Match internal variety to environmental variety.	Regulate and control high-variety environments.
How would you like to apply these “nudge” techniques to a specific system or challenge you are currently facing?