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Conflict - James Ladyman

5 min read

Based on the provided sources, the ideas of Philip Ladyman (often presented alongside Ross Ashby) represent a cybernetic and structural approach to complexity. His views on incrementalism, abstraction (“lumping”), and adaptation present distinct contradictions to the “soft systems,” “agile,” and “idiosyncratic” approaches found elsewhere in the collection.

Here are the specific ways Ladyman’s ideas contradict or conflict with the other sources:

1. Incrementalism: Rejection vs. Recommendation

Ladyman argues for radical systemic change in the face of failure, placing him in direct conflict with the proponents of “small steps.”

• Ladyman’s View: He explicitly advises that when dealing with large-scale systemic failures, one should “reject incremental improvements” that merely treat symptoms. He argues for solutions that scale across the “entire system”[1].

• The Conflict (Eden, Checkland, TOG):

Colin Eden advocates for “Robust Action” in the form of “small incremental wins”. He argues that defining future states is impossible, so small steps foster learning and engagement[2].

Peter Checkland advises proceeding “experimentally and incrementally” by trial and error, specifically because cause-and-effect links are obscure[3].    ◦ TOG (Mastering the Muddle) advises against “boiling the ocean” (system-wide change) and instead promotes “strategic nudges” and minimalist interventions[4].

2. Abstraction: The “Lump Law” vs. “Video Descriptions”

Ladyman believes that ignoring detail is essential for science, while others argue that detail is the only place reality exists.

• Ladyman’s View: He proposes the “Lump Law,” stating that to learn anything, the observer must “lump” many states together to discern patterns. He asserts that “science cannot deal with unique ‘miracles’” (idiosyncratic events) and must focus on repetitive patterns[5].

• The Conflict (Wilk, Pirsig, Allen):

James Wilk directly contradicts this, arguing that we must “climb down the ladder of abstraction” to reach “video descriptions”. He asserts that we should treat every situation as a “sample size of one” (a miracle/unique event) because real-world mechanisms are “utterly unique” and idiosyncratic[6],[7].

Robert Pirsig advises that when stuck, one should focus on the specific, unique detail (e.g., a single bolt), rather than the “lumped” class of objects[8].

3. Adaptation: Failure vs. Virtue (“The Used Car Law”)

Ladyman frames adaptation as a cost of failure, contradicting the “Agile” view that adaptation is a virtue.

• Ladyman’s View: Citing the “Used Car Law,” he argues that a system doing a good job of regulation “need not adapt.” In his view, adaptation is a response to stress (failure of regulation) and is an expensive way to simplify future regulation[9].

• The Conflict (Shannon, Snowden, Checkland):

The “Agile” Sources (Shannon): View adaptation as a primary goal. They argue for “rapid learning” and “constant feedback” because rigid regulation fails in complex systems[10].

Dave Snowden: Argues that practice is “emergent,” meaning the system must constantly adapt to new patterns. He implies that a system that stops adapting (as Ladyman suggests a “good” regulator does) is likely in the “Complicated” or “Simple” domain, not Complex[11].

4. Precision: Vigour vs. Rigour

Ladyman prioritizes effectiveness over precision in the early stages, conflicting with the “hard” systems thinkers.

• Ladyman’s View: He advises choosing “vigour over rigour,” using forceful lessons and “first few thoughts” rather than becoming paralyzed by a demand for absolute precision[5].

• The Conflict (Dettmer, Triz, Warfield):

William Dettmer (Theory of Constraints): Demands extreme rigour using “Logic Trees” (Current Reality Trees) to trace “root causes” without gaps in logic[12]. 

Triz: Relies on “Mathematical Objectification” and tensor calculus to determine solutions with “exact mathematical precision”[13]. 

John Warfield: Rejects “first few thoughts” (intuition) as “linguistic pollution” and demands a “disciplined collective work program” to achieve rigor[14],[15].

5. Variety: Discovering Constraints vs. Enabling Constraints

Ladyman suggests reducing the system’s variety to match the regulator, while others warn this leads to collapse.

• Ladyman’s View: Following Ashby’s Law, he argues that if a regulator’s capacity is fixed, the only hope is to “discover constraints” in the system that reduce its actual variety, thereby making it controllable[16].

• The Conflict (Snowden, Cilliers):

Dave Snowden: Warns that if you over-constrain a complex system (reducing its variety to make it fit your control model), it is liable to suffer a “catastrophic collapse into chaos”. He advocates for “enabling constraints” (increasing possibilities) rather than governing constraints (reducing variety)[17].

Paul Cilliers: Argues that systems need “excess diversity” (variety) to survive. Reducing the system’s variety to match the regulator destroys the system’s resilience[18].

6. Methodology: “Middle-Number” vs. “One-Off”

Ladyman focuses on “Middle-Number” systems, whereas others focus on the extremes of “messes” or “logic.”

• Ladyman’s View: He utilizes the Weaver-Weinberg trichotomy, focusing systems thinking on “middle-number systems”—situations with a moderate number of variables that are significantly interrelated[19].

• The Conflict (Rittel, Ackoff):

Horst Rittel and Russ Ackoff focus on “Messes” and “Wicked Problems” where the number of variables is potentially infinite or “transcomputational” (e.g., 1077), explicitly placing their work outside the “middle-number” statistical range Ladyman targets[20],[21]. Ladyman’s approach implies these systems can be “nearly decomposed” and analyzed, while Rittel argues they cannot be formulated at all.

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