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In computer science, artificial intelligence(AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[1] More in detail, Kaplanand Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”.[2] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[3]
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet."[4] For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology.[5] Modern machine capabilities generally classified as AI include successfully understanding human speech,[6] competing at the highest level in strategic game systems (such as chess and Go),[7] autonomously operating cars, and intelligent routing in content delivery networks and military simulations.
Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems: analytical, human-inspired, and humanized artificial intelligence.[8] Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[9][10] followed by disappointment and the loss of funding (known as an "AI winter"),[11][12] followed by new approaches, success and renewed funding.[10][13] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[14] These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"),[15] the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences.[16][17][18] Subfields have also been based on social factors (particular institutions or the work of particular researchers).
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In computer science, artificial intelligence(AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[1] More in detail, Kaplanand Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”.[2] Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".[3]
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip in Tesler's Theorem, "AI is whatever hasn't been done yet."[4] For instance, optical character recognition is frequently excluded from "artificial intelligence", having become a routine technology.[5] Modern machine capabilities generally classified as AI include successfully understanding human speech,[6] competing at the highest level in strategic game systems (such as chess and Go),[7] autonomously operating cars, and intelligent routing in content delivery networks and military simulations.
Borrowing from the management literature, Kaplan and Haenlein classify artificial intelligence into three different types of AI systems: analytical, human-inspired, and humanized artificial intelligence.[8] Analytical AI has only characteristics consistent with cognitive intelligence generating cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive as well as emotional intelligence, understanding, in addition to cognitive elements, also human emotions considering them in their decision making. Humanized AI shows characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence), able to be self-conscious and self-aware in interactions with others.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[9][10] followed by disappointment and the loss of funding (known as an "AI winter"),[11][12] followed by new approaches, success and renewed funding.[10][13] For most of its history, AI research has been divided into subfields that often fail to communicate with each other.[14] These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"),[15] the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences.[16][17][18] Subfields have also been based on social factors (particular institutions or the work of particular researchers).
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