From: jimruttshow8596
Hierarchical complexity is a concept that describes the qualitative increase in complexity of a task or skill, emerging through a continuous process of integrating lower-order capacities into new, more complex structures [00:06:44] [00:09:00]. It has been a central focus of psychological research for nearly a century [00:03:53].
Defining Hierarchical Complexity
The concept of hierarchical complexity emerged from the longest continuous research project in the field of psychology [00:03:53]. It first appeared around 1923 with Piaget’s work, building on earlier ideas from thinkers like James Mark Baldwin and Herbert Spencer [00:04:04] [00:04:15]. By the 1980s and 1990s, a “neo-Piagetian consensus” distilled this property into a formal definition of stages across lifespan development [00:04:36] [00:04:46]. This core property characterizes the fundamental developmental differences observed from infancy to adulthood, such as a baby’s reflexes versus an adult’s ability to perform theoretical physics [00:05:01] [00:05:14].
Hierarchical vs. Horizontal Complexity
A key distinction is drawn between hierarchical complexity (also called vertical complexity) and horizontal complexity [00:02:22] [00:06:44]:
- Horizontal complexity involves doing more of the same type of task at the same level of complexity, like tying a thousand shoes once you know how to tie one [00:06:31] [00:06:40]. An example given is taking an elevator, where each step is a discrete sequence at roughly the same level of complexity [00:11:25].
- Hierarchical complexity involves performing a qualitatively new and more complex task, integrating lower-order skills into a higher-order mastery [00:06:50] [00:07:54]. For instance, making a shoe is hierarchically more complex than tying a shoelace [00:07:07]. Another example is disassembling, repairing, and reassembling a lawnmower engine, where every move depends on previous ones and requires ancillary skills [00:11:55].
Even seemingly simple actions, like focusing the eyes or pressing an elevator button, involve pre-built hierarchically complex sensory-motor skills [00:12:49] [00:13:01].
Core Mechanisms: Hierarchical Integration and Chunking
The fundamental process underlying hierarchical complexity is hierarchical integration, where many lower-order skills become a single, qualitatively new, and more complex skill [00:08:15] [00:09:00]. This process is ubiquitous in the construction and creation of new skills from existing ones [00:08:10].
A related concept is chunking, where a lot of information or experience is loaded into a single term or concept [00:16:11] [00:16:37]. Hierarchical complexity models suggest a definable scale of chunking, from sensory-motor systems to abstract theories [00:17:33] [00:17:49]. This process of lower-order processes being integrated by an emergent higher-order process is a deep, almost ontological, property [00:19:42] [00:19:50].
According to Theo Dawson, hierarchical complexity refers to the number of non-repeating recursions that coordinating actions must perform on a set of primary elements [00:35:28]. Actions at a higher order organize and transform lower-order actions, producing new, non-arbitrary organizations that cannot be accomplished by the lower orders themselves [00:35:41] [00:35:53] [00:35:57]. When a higher-order task integrates lower-order tasks, the lower-order tasks are no longer the same as they were before integration [00:36:59] [00:37:34].
Drivers of Development
Several factors contribute to the emergence of hierarchical complexity:
- Working Memory Limitation: A key driver is the remarkably small capacity of human short-term or working memory (e.g., “seven plus or minus two” items for sound, three or four for images) [00:27:30] [00:27:43]. To tackle more difficult problems, the brain must make “chunks” of information bigger, allowing more complex information to be held and processed simultaneously [00:27:57] [00:29:00].
- Complexity of the Environment: If the world were not complex, the working memory bottleneck wouldn’t matter as much [00:29:33] [00:29:40]. The demands of the environment drive the nervous system to adapt and survive [00:30:28]. Children exposed to complex sensory-motor environments are better equipped developmentally [00:45:40] [00:45:53].
- Epistemic Motivation: Humans have an innate drive to understand, distinct from merely wanting to succeed [00:29:50] [00:30:13]. This motivation, which can be fostered socially, propels information through the memory bottleneck [00:30:41] [00:30:48].
- Lawfulness of the Universe: The fact that the universe is lawful and patterns can be extracted incentivizes the biological cost of developing complex cognitive machinery [00:31:38] [00:31:45] [00:32:31].
Hierarchical Complexity, Emergence, and Evolution
Hierarchical complexity is not exclusive to human cognition. It can be observed across the biological spectrum, from neuronal organization to the behavior of monkeys and pigeons [00:19:02] [00:19:18] [00:19:26]. This suggests that hierarchical complexity is almost a general property of information, linking human psychological experience to universal cosmological and evolutionary processes [00:19:07] [00:21:28].
The science of complexity is fundamentally about the emergence of complexity from simplicity across multiple levels [00:19:54] [00:20:00]. Human development, from atoms to complex organisms, mirrors this pattern of emergence [00:20:06] [00:21:00]. Piaget’s insight was that understanding the human person or mind requires weaving it into this larger evolutionary story [00:22:56] [00:23:03]. The application of dynamical systems modeling techniques from complexity science to human development was pioneered by Kurt Fischer in the 1990s [00:25:21].
Stages of Hierarchical Complexity in Human Development
Several models, including those by Michael Commons (15 levels), Kurt Fischer (skill levels and tiers of actions, representations, abstractions, principles), and Theo Dawson (Lectical levels), converge on a similar understanding of developmental stages [00:39:56] [00:40:03] [00:41:14]. These models are not identical but triangulate a form of realism in understanding development [00:41:40].
Hierarchical complexity unfolds over a lifespan and minute-to-minute during learning [00:08:03]. It’s a “fractal-like property” where closer inspection reveals constructions and levels within levels [00:42:38] [00:42:51].
Key tiers/stages include:
- Sensory-Motor Tier: This foundational stage begins with single actions like focusing vision [00:42:57]. Skills progress from coordinating actions (e.g., looking and reaching) to coordinating systems of sensory-motor skills (e.g., looking, reaching, grasping, bringing to mouth, and drinking) [00:43:08] [00:43:17]. Early childhood engagement with diverse sensory-motor environments is crucial for building this foundational “pyramid” of skills [00:45:29] [00:46:03].
- Representational Tier: This tier involves the emergence of “representations” or “semiotic function” [00:14:34] [00:15:04]. A single representation (e.g., “bedtime”) can summarize a sprawling array of dense, lower-order sensory-motor experiences [00:15:10] [00:15:20]. Children can use linguistic signs to represent non-present realities, entertain counterfactuals, and develop complex narrative architectures [00:48:12] [00:48:28].
- Abstract Tier: This stage corresponds to Piagetian formal operational levels [00:49:44]. Abstractions integrate many examples of representations into higher-order concepts [00:50:25]. Unlike representations, abstractions cannot be directly pointed to; they are more abstract concepts like “quality family time” [00:50:46] [00:50:55]. Many essential aspects of civilization, like democratic processes and understanding law, rely on abstract reasoning [00:51:00] [00:51:22].
- Principled Tier (Meta-systemic): This highest tier involves multi-systemic integration, such as creating a single theory of justice from different fields of ethics (e.g., John Rawls’s work) [01:09:31] [01:09:41]. This level allows one to “norm the norms” and make rules about the making of rules [01:10:37].
Development is typically domain-specific, meaning individuals can exhibit different levels of hierarchical complexity in different areas of their lives [00:40:50] [00:40:53] [00:34:31]. For example, someone might display highly complex reasoning in physics but only sensory-motor level understanding in small engine repair [01:01:29].
Applications of Hierarchical Complexity Models
Hierarchical complexity can be operationalized in educational and research contexts [00:09:36]. It helps diagnose the quality of knowledge and understand the emergence of knowledge [00:34:01].
Education
Lectica, co-founded by Zach Stein and Theo Dawson, is a non-profit dedicated to research-based, justice-oriented reform of large-scale standardized testing [01:50] [01:53]. Lectica developed standardized developmental assessments based on hierarchical complexity [01:14:01].
Unlike traditional standardized tests that offer a pass/fail outcome, Lectical assessments diagnose what a person understands and suggest the next best thing for them to learn [01:15:46] [01:15:50]. This is possible because they rely on empirically grounded “rational reconstructions” of specific learning sequences within particular domains [01:16:03] [01:16:37].
Leadership and Organizational Context
Hierarchical complexity models have been applied to leadership development, particularly in discerning the “complexity gap” between leadership task demands and leaders’ capacities [01:19:01] [01:22:27]. In leadership, the most significant struggles often emerge in domains of perspective-taking, perspective-seeking, and perspective-integration [01:19:54] [01:20:01].
Lectica’s assessments can identify where these complexity deficits occur [01:23:42]. For example, some leaders might be good at imagining others’ reactions (perspective-taking) but not at actively soliciting input (perspective-seeking) [01:22:16] [01:22:24]. The assessments provide diagnostic reports that support educational growth rather than merely serving for hiring or firing [01:23:58] [01:24:04].
The increasing complexity of modern society and technology also puts greater educational demands and complexity demands on individuals [00:56:30] [00:56:42].
Nuances and Misconceptions
It’s crucial to understand that hierarchical complexity describes the level of a task or performance, not an inherent classification of a whole person [00:59:16] [01:00:29]. General intelligence (Spearman’s G or IQ tests) is considered a “demi-reality” that oversimplifies human psychology, akin to a GDP statistic [00:59:00] [00:59:58] [01:00:46]. While IQ tests may correlate with hierarchical complexity in specific domains, they lack the richness and diagnostic value of hierarchical complexity assessments [01:00:40] [01:02:15].
Applying hierarchical complexity to categorize entire populations or cultures (e.g., indigenous people as “children”) is a misapplication [00:55:03] [00:55:10]. While historical documents can be analyzed for their hierarchical complexity, assuming a linear, universal cultural evolution based on these stages is inappropriate [00:55:34] [00:56:14].
Furthermore, higher levels of complexity are not always “better,” as sophisticated understanding can be used for harmful purposes, such as a highly complex person using perspective-taking for strategic advantage rather than good faith [01:32:26].