Tag: psychology

The Unknowable Engine: Blind Spots as Foundational Features of Situated Cognition

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The Unknowable Engine: Blind Spots as Foundational Features of Situated Cognition argues that intelligence does not rest on perfect knowledge but on structural limitations that guarantee perpetual motion. The Dynamic Quadranym Model (DQM) identifies two blind spots of orientation: the epistemological blind spot, rooted in the opacity of perception, and the procedural blind spot, rooted in the opacity of action. These blind spots are not errors but essential design features: they ensure that coherence is never final and that reorientation is always necessary. Distinguishing them from perturbations—situational disruptions that launch new arcs—the essay shows how blind spots are permanent constraints that make process thinking indispensable. Intelligence, in this view, is not the elimination of uncertainty but the art of navigating it, turning the opacity of being into an engine of change.

Situated AI Semantics: The Simple and Powerful DQM

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The DQM orientation grammar and scaffolding approach to situated semantics in AI offers a highly effective and elegant framework for understanding how meaning and context can be navigated dynamically. It’s an semantic approach that reflects how humans process the world: dynamically, flexibly, and with a focus on the big picture while attending to immediate details. The overlap between various semantic categories with sensory motor areas suggests that a common mechanism is used by neurons to process action, perception and semantics. Body & environment play important roles in thinking

From System 1 & 2 to Adaptive Intelligence: Extending Kahneman and Tversky’s Insights

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Introduction In cognitive science, Daniel Kahneman and Amos Tversky revolutionized our understanding of human decision-making with their dual-system framework—System 1 (fast, intuitive) and System 2 (slow, analytical). This dual-system model has become a cornerstone in both psychology and artificial intelligence (AI), offering a structured way … Continue reading From System 1 & 2 to Adaptive Intelligence: Extending Kahneman and Tversky’s Insights

Understanding the Q Model’s Nested Systems: A Journey Through Scripts

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In our exploration of cognitive semantic frameworks, we highlight the significance of harnessing situatedness and its insights and applications for NLP. This approach plays a crucial role in elucidating the complexities of human cognition and communication. The Q model emerges as a sophisticated representation of … Continue reading Understanding the Q Model’s Nested Systems: A Journey Through Scripts

The Q Model: Triadic Semantic Architecture

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A Theoretical Look at the Role of Words for AI

A system summary.

In this framework, we conceptualize the system as analogous to a nervous system, operating through natural language processing. The connections between systems function like neural pathways, facilitating the seamless flow of information and insights. This interconnected structure enables a nuanced understanding of user input, as each system plays a role in interpreting and responding to situational contexts. Serving as the central processor, and guided by Minsky’s six-layer model (The Emotion Machine, 2006), the framework integrates emotional and cognitive dynamics with the situational and dynamical contexts of the Q model.