[x.com](https://twitter.com/burny_tech/status/1772503096851087613) Map of definitions of intelligence 1. Psychometric Approach - General Intelligence (g factor): A latent variable that accounts for the positive correlations among different cognitive abilities, often estimated using factor analysis. a. Fluid Reasoning (Gf): The ability to solve novel problems, use logic in new situations, and identify patterns. It is considered a key component of general intelligence and is often measured using tasks such as matrix reasoning, series completion, and visual analogies. b. Working Memory Capacity (Gwm): The ability to hold, manipulate, and update information in mind for a short period. It is closely related to attention and executive control and is often measured using tasks such as digit span, n-back, and complex span tasks. c. Processing Speed (Gs): The ability to perform simple cognitive tasks quickly and efficiently. It reflects the speed at which an individual can execute basic mental operations and is often measured using tasks such as digit symbol substitution, visual matching, and simple reaction time. d. Verbal Comprehension (Gc): The ability to understand and reason with verbal information, including vocabulary, general knowledge, and language development. It is often measured using tasks such as vocabulary tests, reading comprehension, and verbal analogies. e. Visual-Spatial Processing (Gv): The ability to perceive, analyze, synthesize, and manipulate visual patterns and spatial relationships. It involves skills such as mental rotation, spatial visualization, and visual memory and is often measured using tasks such as block design, object assembly, and visual puzzles. f. Long-Term Storage and Retrieval (Glr): The ability to store, consolidate, and retrieve information over extended periods. It involves skills such as associative memory, meaningful memory, and ideational fluency and is often measured using tasks such as paired-associate learning, free recall, and category fluency. - Cattell-Horn-Carroll (CHC) Theory a. Fluid Intelligence (Gf): The ability to solve novel problems using inductive and deductive reasoning, often measured by tasks such as matrix reasoning and pattern completion. b. Crystallized Intelligence (Gc): The ability to apply acquired knowledge to solve problems, often measured by tasks such as vocabulary tests and general knowledge assessments. 2. Triarchic Theory of Intelligence (Robert Sternberg) - Analytical Intelligence: The ability to break down problems and analyze their components, often measured by tasks such as logical reasoning and critical thinking. - Creative Intelligence: The ability to generate novel ideas and solutions, often measured by tasks such as divergent thinking and originality. - Practical Intelligence: The ability to apply knowledge to real-world situations, often measured by tasks such as situational judgment tests and practical problem-solving. 3. Artificial Intelligence (AI) and Machine Learning - Narrow AI (Weak AI): AI systems designed to perform specific tasks, often using machine learning algorithms such as: a. Supervised Learning: Given a set of input-output pairs (x_i, y_i), the goal is to learn a function f: X → Y that maps inputs to outputs, minimizing a loss function L(f(x_i), y_i) over the training data. b. Unsupervised Learning: Given a set of inputs x_i without corresponding output labels, the goal is to discover hidden patterns or structures in the data, often by minimizing an objective function such as the reconstruction error or maximizing the likelihood of the data. c. Reinforcement Learning: An agent learns to make a sequence of decisions by interacting with an environment, receiving rewards or penalties for its actions, and aiming to maximize its cumulative reward over time. This can be formalized using Markov Decision Processes (MDPs) and optimized using algorithms such as Q-learning and policy gradients. - Artificial General Intelligence (AGI or Strong AI): Hypothetical AI systems with human-like intellectual capabilities, often conceptualized using frameworks such as: a. Turing Test: An AI system is considered to have achieved AGI if it can exhibit behavior indistinguishable from a human in a conversational setting, as judged by a human evaluator. b. Kolmogorov Complexity: The intelligence of an AI system can be measured by the length of the shortest program that can generate its behavior, with more intelligent systems requiring shorter programs. c. Universal Intelligence: A formal definition of intelligence as the ability of an agent to achieve goals in a wide range of environments, measured by the expected performance of the agent across all possible environments, weighted by their simplicity (Legg and Hutter, 2007). d. Intelligence as skill-acquisition efficiency: A formal definition of intelligence using algorithmic information theory. The ability to mine previous experience, to make sense of future novel situations. The sensitivity to abstract analogies, to what extend a system can analogize the knowledge that it already has into simulacrums that apply widely across the experience space. Using the concepts of scope, generalization difficulty, priors, and experience. (Francois Chollet, 2019). - Superintelligence: An intellect that vastly outperforms human intelligence, linked to concepts such as: a. Intelligence Explosion: The idea that once an AI system reaches a certain level of intelligence, it will be able to design even more intelligent systems, leading to a exponential increase in AI capabilities. b. Singularity: A hypothetical future point in time at which artificial intelligence surpasses human intelligence, leading to rapid technological growth and unpredictable changes to human civilization. 4. Ecological Intelligence - Adaptation to the Environment: The ability to understand and navigate one's environment, often measured using tasks such as wayfinding and environmental problem-solving. - Practical Problem Solving in Real-World Contexts: The capacity to apply knowledge and skills to solve everyday problems, often assessed using methods such as situational judgment tests and performance-based assessments. 5. Biological and Neuroscience Perspectives - Neural Efficiency Theory: The idea that intelligence is related to the efficiency of neural processing, often measured by techniques such as event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). - Parieto-Frontal Integration Theory (P-FIT): A model suggesting that intelligence arises from the interaction of brain regions in the parietal and frontal lobes, often investigated using structural and functional brain imaging methods. - Minimal Cognitive Architecture: The idea that intelligence emerges from a set of basic cognitive processes, often modeled using computational methods such as artificial neural networks and cognitive architectures. 5. Collective Intelligence - Wisdom of Crowds: The idea that the aggregated judgments of a group can be more accurate than individual judgments, often demonstrated using statistical methods such as the Condorcet Jury Theorem and the Diversity Prediction Theorem. - Collaborative Problem Solving: The ability of a group to solve problems effectively, often measured using metrics such as the collective intelligence quotient (CIQ) and the team performance on problem-solving tasks. - Emergent Intelligence in Social Systems: The intelligence that arises from the interactions and self-organization of individuals, often modeled using techniques such as agent-based modeling and complex network analysis. 6. Multiple Intelligences Theory (Howard Gardner) - Linguistic Intelligence: The ability to manipulate language, as measured by tasks such as verbal fluency, reading comprehension, and writing ability. - Logical-Mathematical Intelligence: The capacity for inductive and deductive thinking, often measured by tasks such as numerical reasoning and problem-solving. - Spatial Intelligence: The ability to mentally manipulate 2D and 3D objects, often measured by tasks such as mental rotation and spatial visualization. - Musical Intelligence: The ability to perceive, discriminate, and express musical forms, often measured by tasks such as pitch discrimination and rhythm reproduction. - Bodily-Kinesthetic Intelligence: The ability to control one's body movements precisely, often measured by tasks such as dexterity tests and coordination assessments. - Interpersonal Intelligence: The ability to understand and interact effectively with others, often measured by tasks such as emotion recognition and social problem-solving. - Intrapersonal Intelligence: The ability to understand one's own thoughts and emotions, often measured by tasks such as self-reflection and metacognition. - Naturalist Intelligence: The ability to discriminate among living things and sensitivity to features of the natural world, often measured by tasks such as species classification and pattern recognition in nature. 7. Emotional Intelligence (EI) - Ability Model (Mayer, Salovey, and Caruso) a. Perceiving Emotions: The ability to detect emotions in oneself and others, often measured by tasks such as facial emotion recognition and vocal emotion discrimination. b. Using Emotions: The ability to harness emotions to facilitate cognitive processes, often measured by tasks such as mood-congruent memory and emotional facilitation of thinking. c. Understanding Emotions: The ability to comprehend emotional language and dynamics, often measured by tasks such as emotion vocabulary and understanding emotional transitions. d. Managing Emotions: The ability to regulate emotions in oneself and others, often measured by tasks such as emotional self-control and social emotional management. 8. Cultural Intelligence (CQ) - Metacognitive CQ: The ability to acquire and understand cultural knowledge, often measured using self-report scales and situational judgment tests. - Cognitive CQ: General knowledge about cultural differences, often assessed using tests of cultural knowledge and cross-cultural understanding. - Motivational CQ: The drive to learn about and function in culturally diverse situations, often measured using self-report scales of cultural curiosity and cross-cultural self-efficacy. - Behavioral CQ: The ability to exhibit appropriate verbal and nonverbal behaviors in cross-cultural interactions, often assessed using behavioral observations and situational judgment tests.