From: jimruttshow8596
Developmental psychology represents one of the longest continuous research projects in the field of psychology [00:03:53]. Its core construct, hierarchical complexity, emerged almost a century ago with Jean Piaget’s 1923 publication, The Language and Thought of the Child [00:04:02]. While earlier thinkers like James Mark Baldwin and Herbert Spencer touched upon similar ideas, the formal definition of developmental stages solidified with the Neo-Piagetian consensus in the 1980s and 1990s [00:04:15] [00:04:49].
Core Concepts
Hierarchical vs. Horizontal Complexity
Hierarchical complexity describes the qualitative leap in a task’s difficulty when new, more complex skills integrate lower-order capacities [00:06:50]. For instance, making a shoe is hierarchically more complex than merely tying a shoelace [00:07:07]. In contrast, horizontal complexity refers to performing more of the same task at the same level of difficulty, like tying a thousand shoes [00:06:36]. Hierarchical complexity is a ubiquitous property of mental processes and a fundamental difference in developmental stages from infancy to advanced theoretical physics [00:04:25] [00:05:19].
Hierarchical Integration and Chunking
The process of hierarchical integration involves many lower-order skills combining to form a single, qualitatively new, more complex skill [00:09:01]. This concept is closely related to “chunking,” where a large amount of dense, lower-order information (e.g., sensory-motor material) is captured by a single, higher-order representation or term [00:15:10] [00:16:37]. This allows for a definable scale of chunking, from basic sensory-motor actions to abstract theoretical concepts [00:17:33].
Connection to Emergentism and Complexity Science
The notion of hierarchical complexity aligns with complexity science’s understanding of emergence [00:19:55]. It suggests a continuity of evolutionary process, specifically the emergence of higher-order or hierarchical complexity, across cosmological and human development [00:21:42]. This implies that psychological experience reflects universal laws of nature [00:22:11]. Kurt Fischer, a Neo-Piagetian, pioneered the application of dynamical systems modeling techniques from complexity science to model human development [00:25:21].
The Role of Working Memory
The small capacity of working memory (e.g., Miller’s seven plus or minus two items) is hypothesized to be a significant driver for the emergence of hierarchical complexity [00:27:57] [00:28:28]. To handle more difficult problems, the brain must make chunks larger, enabling the simultaneous processing of more complex information [00:29:00].
Epistemic Motivation and Understanding
Piaget distinguished between “success” (accomplishing a task) and “understanding” (knowing why it worked) [00:29:59]. A critical threshold in human development is crossed when children shift from merely wanting to succeed to wanting to understand [00:30:12]. This innate “epistemic motivation,” fostered socially, drives information processing through the memory bottleneck [00:30:41] [00:30:48]. The lawful, non-random nature of the universe is also a prerequisite; if patterns were truly random, investing in machinery to extract abstract patterns would be useless [00:31:39].
Key Figures and Theories
- Jean Piaget: Credited with formalizing the construct of hierarchical complexity in 1923 [00:04:02]. His major insight was to integrate human psychology into a larger evolutionary story [00:22:43].
- Michael Commons: Coined the term “Model of Hierarchical Complexity” and developed a formal definition, often articulated in almost mathematical terms [00:03:38] [00:36:22]. His model identifies 15 distinct levels of complexity [00:40:17].
- Kurt Fischer: A foremost Neo-Piagetian who conducted important empirical work to validate hierarchical complexity [00:03:23]. His “Dynamic Skill Theory” places the abstract construct within the context of the embodied and embrained person [00:09:40]. Fischer also argued that neurological structures are hierarchically organized [00:18:55].
- Theo Dawson: Co-founder of Lectica and a key figure in psychometric innovation around hierarchical complexity [00:03:18]. She refined the scoring procedures to create standardized assessments of cognitive development, known as Lectical Levels [01:14:01].
- Lawrence Kohlberg: Applied Piagetian concepts to moral development, creating stages of moral reasoning [01:09:04].
- Jürgen Habermas: Extended these ideas to the evolution of societies, examining the requisite complexity for social coordination [00:52:30].
- Pascal Leone: Developed a Neo-Piagetian theory called “m-power,” suggesting that the density, depth, and abstraction of memory units are central to intelligence [00:28:51].
Levels of Hierarchical Complexity (Illustrated via Moral Development)
Within Fischer’s framework, there are three tiers: actions, representations, and abstractions, followed by principles [00:41:47]. These roughly correspond to Commons’s sensory-motor, operational/primary concrete, and formal/abstract/systemic stages [00:41:56].
- Sensory-Motor Tier (Actions): Early levels are egocentric and punishment-reward oriented [01:08:06]. For example, a child’s understanding of “fairness” on a playground is concrete: literally seeing if each child has the same amount of M&Ms [01:08:24]. This involves coordinating basic sensory-motor skills like focusing, reaching, grasping, and drinking [00:43:00]. Exploration of complex sensory-motor environments is crucial for early development [00:45:43].
- Representational Tier: This tier marks the emergence of the “semiotic function,” where sprawling sets of sensory-motor experience are summarized into a single utterance or gesture, like the word “bedtime” [01:15:20] [01:47:32]. Representations allow for entertaining counterfactuals (e.g., talking about Santa Claus) [01:48:19]. In moral development, this might involve understanding fairness as conforming to simple, agreed-upon rules of a game [01:08:43] [01:10:27].
- Abstract Tier: Abstractions integrate many representations into higher-order concepts [00:50:25]. Unlike representations, abstractions cannot be simply pointed at (e.g., “quality family time” is an abstraction of bedtime, dinner time, etc.) [00:50:36]. In moral judgment, this involves understanding fairness in terms of whether abstract rules promote the overall purpose of a game, ensuring it remains fair for all [01:08:46].
- Principled Tier: This highest tier involves meta-systematic integration, allowing for the formation of overarching theories or principles that transcend and include prior notions [01:09:31]. An example is John Rawls’s work on “justice as fairness,” where multiple fields of ethics are integrated into a single theory of justice [01:09:41]. At this level, one can critique the norms of society and make rules about rule-making [01:10:37].
Applications of Hierarchical Complexity
Educational Neuroscience and Reform
Lectica, co-founded by Theo Dawson, developed standardized assessments based on hierarchical complexity [01:14:01]. Unlike pass/fail standardized tests (like the SAT), Lectica assessments provide diagnostic insights, indicating what a student understands and the next best thing for them to learn [01:15:46]. These assessments can rationally reconstruct specific learning sequences, tailoring educational support to an individual’s developmental level [01:16:03].
Leadership and Business Development
Lectica’s assessments have been applied to leadership development, particularly within intelligence agencies and businesses [01:18:10]. A key finding is the “complexity gap” between the demands of leadership roles and the capacities of leaders [01:19:22]. Struggles often emerge in domains of perspective-taking, perspective-seeking, and perspective-integration, rather than solely in technical problem-solving [01:19:54]. The assessments provide diagnostic reports for leaders, promoting leadership development rather than just hiring/firing decisions [01:24:06].
Human Development and Societal Evolution
The evolution of societies can be viewed through the lens of requisite complexity needed for social coordination [00:52:42]. Modern civilization has become increasingly complex, placing greater educational demands on individuals and requiring higher levels of hierarchical complexity from citizens [00:56:27]. This is driven by factors like the demands of legal processes (e.g., reflectively consenting to governance) and the proliferation of technology, especially the internet, which presents a significant influx of signals and complexity [00:56:53] [00:57:17].
Important Distinctions and Warnings
- Task vs. Person Assessment: It is crucial not to classify an entire person by a single hierarchical complexity level [00:59:18]. Instead, hierarchical complexity should be assigned to specific tasks or performances accomplished by a person within a domain [00:59:23]. An individual can operate at different levels of complexity across various domains (e.g., highly complex in physics but sensory-motor in car repair) [00:34:32].
- Critique of General Intelligence (IQ): The concept of “general intelligence” or Spearman’s g is seen as a “demi-reality” [01:00:35]. While IQ tests correlate with hierarchical complexity in specific domains, they radically oversimplify human intelligence, inviting misuse and problematic categorization of people [01:00:29] [01:00:53].
- Misapplication to Cultural Evolution: Applying hierarchical complexity directly to the evolution of cultures (e.g., suggesting indigenous people are “like children” compared to modern people) is a misapplication [00:55:03]. While historical documents can be analyzed for their hierarchical complexity, classifying entire cultures or historical periods is problematic and risks reinforcing inaccurate stereotypes [00:55:34].
- Politics of Quantitative Objectivity: The use of metrics and psychometrics in fields like leadership development must be carefully managed [01:25:45]. Measures can be misused as a “bludgeon” or distort social practice if not embedded in appropriate educational practices and used responsibly by trained individuals [01:26:22].