From: jimruttshow8596
Hierarchical complexity is a concept studied in psychology, emerging from the field of developmental psychology [00:03:08]. Its application extends to education and leadership, providing a framework for understanding and fostering cognitive growth and skill acquisition.
Understanding Hierarchical Complexity
The notion of hierarchical complexity first emerged almost a century ago with Jean Piaget’s 1923 publication, “The Language and Thought of the Child” [00:04:02]. Earlier hints can be found in the works of James Mark Baldwin and Herbert Spencer [00:04:15]. It’s considered a ubiquitous property of mental processes [00:04:25].
In the 1980s and 1990s, a “neo-Piagetian consensus” emerged, formally defining stages across lifespan development [00:04:32]. This consensus distilled a core property that characterizes the fundamental developmental differences seen from infancy to advanced theoretical thinking, providing universal characteristics of development across lifespan and culture [00:04:58]. Hierarchical complexity became a measurable construct in psychology [00:05:52].
Hierarchical vs. Horizontal Complexity
- Horizontal complexity refers to doing more of the same task at the same level of complexity [00:06:36]. For example, tying a thousand shoes [00:07:14], or performing a sequence of discrete, independent tasks like taking an elevator [00:11:25].
- Vertical or Hierarchical complexity involves performing a qualitatively more complex task [00:06:47]. An example is making a shoe versus tying a shoelace [00:07:02]. A more complex example would be disassembling, replacing a part, and reassembling a lawnmower engine, where each step is interdependent [00:11:55].
All skills involve some degree of Hierarchical complexity [00:13:22]. The transition from manipulating individual shoelaces to tying a knot is a basic example of hierarchical integration [00:08:19]. This process involves many lower-order skills becoming a single, qualitatively new, more complex skill [00:09:01].
Hierarchical Integration and “Chunking”
The concept of Hierarchical complexity is closely related to “chunking,” where a lot of information can be loaded into a single term or concept as experience grows [00:16:37]. For example, a baby’s many sensory-motor experiences of getting ready for bed, brushing teeth, etc., become integrated into the single representation “bedtime” [00:14:50]. These representations can then be further integrated into abstractions, such as “quality family time,” which generalizes across “bedtime,” “dinner time,” and “TV time” [00:15:42].
This process of hierarchical integration is fundamental to the construction of skill [00:08:13]. It’s a ubiquitous property, extending to reflexes and nervous system action, like the eye’s signal-noise distillation for the visual cortex [00:18:01]. Early psychologists like William James and Charles Sanders Peirce observed aspects of Hierarchical complexity as a basic property of the nervous system [00:18:19].
Emergence and Hierarchical Complexity
Hierarchical complexity aligns with complexity science’s understanding of emergence [00:19:54]. Complexity science describes the emergence of multiple levels of complexity from simplicity, as seen in the progression from atoms to cells to multicellular organisms to ecosystems [00:20:00]. Hierarchical complexity in cognition is another example of this phenomenon [00:21:13].
Kurt Fischer, a prominent neo-Piagetian, pioneered the application of dynamical systems modeling techniques from complexity science to model human development [00:25:21]. This approach views the individual mind-brain as a complex ecosystem with organic processes of emergence and regression [00:25:31].
Drivers of Hierarchical Complexity
The primary driver for the emergence of Hierarchical complexity is thought to be the limited capacity of working memory (e.g., Miller’s 7 ± 2 for sound, or 3-4 for images) [00:27:13]. To process more difficult problems, the brain must make “chunks” of information bigger, allowing more complex concepts to be held simultaneously [00:27:57].
However, the “working memory bottleneck” is not the sole driver [00:29:50]. Two other factors are crucial:
- Demands of the world: The inherent complexity and abstraction of the environment necessitate increasingly complex cognitive structures [00:29:31].
- Epistemic motivation: Humans possess an innate drive to understand, beyond merely succeeding [00:29:50]. This motivation propels information through the memory bottleneck to higher levels of complexity [00:30:41].
The lawful, non-random nature of the universe is also important; if patterns were truly random, investing in the biological cost of extracting abstract patterns would be useless [00:31:39].
Stages of Hierarchical Complexity
Within the neo-Piagetian framework, various models like Michael Commons’s orders of Hierarchical complexity, Kurt Fischer’s skill levels, and Theo Dawson’s Lectical Levels are largely isomorphic, triangulating a similar underlying reality [00:39:56]. These models propose multiple tiers of development, such as:
- Actions (Sensory-Motor): The earliest stage, where infants develop skills like focusing vision, reaching, grasping, and drinking from a cup [00:43:00]. This stage is crucial, and deprivation of rich sensory-motor environments can lead to developmental delays [00:45:36].
- Representations: The emergence of symbols or words to summarize sprawling sensory-motor experiences [00:47:22]. Children can entertain counterfactuals, lie, and construct complex narratives [00:48:19].
- Abstractions: Integrating many representations into higher-order concepts that cannot be directly pointed to, such as “quality family time” [00:50:22]. This level is crucial for civilization and requires formal education, enabling hypothetical-deductive reasoning and understanding of democratic processes [00:51:00].
- Principles (Meta-Systematic): The highest levels, involving multi-systemic integration of different fields or ethical frameworks, allowing for the norming of norms and making rules about rules [01:09:31].
It’s important to note that development is highly domain-specific; individuals can operate at different levels of Hierarchical complexity in different areas of their lives [00:34:32]. This contradicts simplistic “color-coded” stage theories [00:34:45].
Hierarchical Complexity and “General Intelligence”
While there are correlations between Hierarchical complexity and “general intelligence” (Spearman’s g) [00:58:21], they are not the same [00:59:00]. “General intelligence” is viewed as a summary statistic, whereas Hierarchical complexity is assigned to a specific task or performance, not an entire person [00:59:23]. Classifying individuals or populations by a single “intelligence number” is seen as an oversimplification [01:00:56] and a holdover from eugenics [01:00:08].
Application in Education and Leadership
Lectica and Developmental Assessments
Lectica, co-founded by Zach Stein and Theo Dawson, developed a psychometric system based on Hierarchical complexity to reform standardized testing [00:01:50]. Theo Dawson pioneered applying psychometric tools, specifically the Rasch model, to Hierarchical complexity to create standardized cognitive development assessments [01:14:01].
These Lectical assessments aim to replace traditional standardized tests, which merely pass or fail, with diagnostic tools [01:15:46]. They identify what a person understands and suggest the next best thing for them to learn, based on empirically grounded learning sequences [01:15:50].
Leadership Development
Lectica’s work extended to adult contexts, particularly leadership development in business and government [01:17:06]. The early work involved identifying and developing leaders in the intelligence community [01:18:23].
A key insight was the “complexity gap” between the increasing demands of leadership roles and the capacities of leaders [01:19:19]. While leaders might be highly complex in their technical or engineering problem-solving skills, struggles often emerged in the domains of:
- Perspective taking: The ability to imagine another’s viewpoint [01:19:54].
- Perspective seeking: Proactively seeking out the perspectives of others (e.g., employees) [01:19:57].
- Perspective integration: The ability to synthesize multiple perspectives [01:20:01].
Lectica developed learning sequences specifically addressing perspective-taking skills in leadership [01:20:04]. It was observed that individuals highly developed in one area of expertise might have a “complexity deficit” in others and fail to recognize it [01:20:41]. For example, a medical doctor might apply pattern-matching algorithms from their field inappropriately to investment [01:21:22].
The shift in management structures from rigid hierarchies to flatter organizations, with managers overseeing more direct reports, likely contributed to the stress on perspective-taking [01:28:06]. Furthermore, non-democratic or zero-sum competitive work environments can disincentivize perspective-taking and seeking [01:30:07].
Lectical assessments for leaders use open-ended essays to evaluate decision-making complexity on the job [01:23:50]. The goal is not hiring or firing but promoting leadership development by providing diagnostic reports that support growth [01:24:08]. These measures are designed to be more “ecologically valid” than generic psychometric tests, directly relating to job performance [01:25:20].
The application of Hierarchical complexity in these domains highlights the need for careful and responsible use of quantitative assessments, ensuring they support development rather than merely classifying or judging individuals [01:26:14].