Intelligence characteristics are foundational abilities that define what it means to be intelligent. These can be used to model the intelligence of humans, animals and machines. Generally speaking, humans have far greater scope of intelligence than machines. The following are the basic characteristics of intelligence.
Self-AwarenessThe ability to examine and understand one's own nature, motivations, characteristics and emotions.
IntentionalityIntentionality is the ability to develop a sense of purpose and work towards it. Humans clearly exhibit this but it is an open question whether machines can have any self-directed sense of purpose.
ImaginationThe ability to think about things that do not exist. This is the foundation for invention, design and storytelling that are the basis for human culture and economic growth.
LearningThe ability to acquire knowledge, improve thinking and develop talents. This is the primary difference between artificial intelligence and traditional information technology. Humans are also extremely capable in this area.
Crystallized Intelligence Crystallized intelligence is the ability to solve problems that you have seen many times in the past.
Fluid IntelligenceFluid intelligence is the ability to solve problems that are completely new to you such as an outside context problem.
AbstractionAbstract thinking is the ability to develop and think in concepts that differ from concrete reality. For example, developing a thought experiment to solve a problem. Human language is full of abstract concepts such that humans think mostly in abstractions.
LogicThe ability to think in a formal and structured way that can be shown to be valid given a set of assumptions. Traditional logic is garbage in garbage out and has weaknesses such as excluded middle whereby it can't handle grey areas. Logic should not be considered synonymous with intelligence as it only applies to extremely well defined problems.
Fuzzy LogicSystems of logic that use techniques such as probability models to handle uncertainty. Modern artificial intelligence mostly resembles fuzzy logic with self-learning.
Rational ThoughtRational thought is the ability to apply logic-like thinking to situations that are complex and ambiguous such as the human experience. For example, composing a story that captures the spirit of a culture.
Pattern RecognitionThe ability to find meaningful patterns in information. Both humans and artificial intelligence are good at this but both can develop biases based on misuse of patterns. Machines are particularly prone to this due to their ability to test for a large number of possible patterns in data such that they can easily find meaningless patterns.
Strategic ThinkingStrategic thinking is the ability to thrive in an environment of constraint and competition. Artificial intelligence is good at this if the rules are well defined as computers can quickly check all possible future outcomes of a move by backward induction. AI is considerably less impressive in areas where strategy is unconstrained such as a business that can invent any product.
EmotionsEmotions are mental states that color all thoughts. This makes humans delightfully unpredictable such that the same person has different modes of personality. Machines may exhibit emotional intelligence whereby they try to read emotions and react in some logical way or record this as data on someone's permanent record. It is unclear if machines can have emotions themselves. Certainly this can be simulated but it is likely that machines do not really feel emotion.
SynthesisSynthesis is the ability to create non-obvious value. For example, composing a great work of literature or inventing a new industry. This may benefit from human elements such as imagination and intentionality.
Quantitative ProcessingThe ability to process and calculate numbers. Machines are so good at this that humans simply can't compete. For example, a fast computer such as NEC's SX-9 can perform more than 100 billion mathematical calculations a second with a single core. A human couldn't directly do this in a lifetime.
Quantitative ReasoningIt is unclear if machines really understand the numbers they are calculating. For example, humans are required to develop theories and models of mathematics despite being slow at actual calculations.
Reaction TimeReaction time is the time that it takes to think about something and come up with a reasonable response. People can be extremely intelligent but slow. As a hypothetical example, consider a scientist who develops a revolutionary theory but can't safely drive a race car 300 km/hour because their reaction time is too slow.
Systems ThinkingSystems thinking is the ability to think about the effects of changes to complex systems. Both humans and machines can be good at this but as usual, they approach the problem in completely different ways. Machines accomplish systems thinking with their ability to calculate extremely complex probabilities that involve a large number of variables such as a weather prediction algorithm or AI. Humans can only approach system thinking in an elegant way such as reducing complexity with a thought experiment.
Visual ThinkingThe ability to express and understand things as pictures. This is an example of how different human thinking is from machine processing as machines convert everything to numbers but humans think natively in high level constructs such as pictures, language and emotion.
Spatial Reasoning Spatial reasoning is the ability to solve problems that concern three dimensional space such as how big a truck you need to move the furniture in your house. This is easy to translate to numbers such that machines can theoretically perform well in this area.
Kinesthetic IntelligenceIntelligence that relates to physically moving such as dancing or snowboarding.
Linguistic IntelligenceTalents with language such as easily learning new languages or mastering your native language.
Social IntelligenceThe ability to navigate human relationships, emotions and politics successfully.
Musical IntelligenceA talent for understanding, performing and composing music.
Naturalist IntelligenceThe ability to understand the natural world such as animals, plants or ecosystems.
Existential IntelligenceThe ability to offer value towards foundational and intractable questions about the universe. Applies to areas such as philosophy, ethics and physics.
NotesThe human brain has about 86 billion neurons, more than 100 trillion synapses and more than 100,000 miles of nerve fibers. It has processing advantages such as native thought in pictures, abstraction and emotion. By comparison, it is common for modern computer processors to have around 2 billion transistors that only process numbers i.e. binary data. A neuron is far more complex, specialized and adaptive than a transistor. There are a large number of different types of neurons that are adapted to different functions. Neurons can have up to 10,000 connections each where a typical transistor has three connections.
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ReferencesAnanthanarayanan, Rajagopal, et al. "The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses." Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis. 2009.Wan, Chang Jin, et al. "Proton‐Conducting Graphene Oxide‐Coupled Neuron Transistors for Brain‐Inspired Cognitive Systems." Advanced Materials 28.18 (2016): 3557-3563.
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