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Artificial intelligence (AI) is
intelligence Intelligence has been defined in many ways: the capacity for abstraction, logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem-solving. More generally, it can be des ...
—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to
intelligence Intelligence has been defined in many ways: the capacity for abstraction, logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem-solving. More generally, it can be des ...
displayed by
animals Animals are multicellular, eukaryotic organisms in the biological kingdom Animalia. With few exceptions, animals consume organic material, breathe oxygen, are able to move, can reproduce sexually, and go through an ontogenetic stage in ...
and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''
Oxford English Dictionary The ''Oxford English Dictionary'' (''OED'') is the first and foundational historical dictionary of the English language, published by Oxford University Press (OUP). It traces the historical development of the English language, providing a co ...
'' of
Oxford University Press Oxford University Press (OUP) is the university press of the University of Oxford. It is the largest university press in the world, and its printing history dates back to the 1480s. Having been officially granted the legal right to print books ...
defines artificial intelligence as:
the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
AI applications include advanced
web search Web most often refers to: * Spider web, a silken structure created by the animal * World Wide Web or the Web, an Internet-based hypertext system Web, WEB, or the Web may also refer to: Computing * WEB, a literate programming system created by ...
engines (e.g.,
Google Google LLC () is an American Multinational corporation, multinational technology company focusing on Search Engine, search engine technology, online advertising, cloud computing, software, computer software, quantum computing, e-commerce, ar ...
), recommendation systems (used by
YouTube YouTube is a global online video sharing and social media platform headquartered in San Bruno, California. It was launched on February 14, 2005, by Steve Chen, Chad Hurley, and Jawed Karim. It is owned by Google, and is the second mo ...
, Amazon and
Netflix Netflix, Inc. is an American subscription video on-demand over-the-top streaming service and production company based in Los Gatos, California. Founded in 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California, it offers a fi ...
), understanding human speech (such as
Siri Siri ( ) is a virtual assistant that is part of Apple Inc.'s iOS, iPadOS, watchOS, macOS, tvOS, and audioOS operating systems. It uses voice queries, gesture based control, focus-tracking and a natural-language user interface to answer qu ...
and
Alexa Alexa may refer to: Technology *Amazon Alexa, a virtual assistant developed by Amazon * Alexa Internet, a defunct website ranking and traffic analysis service * Arri Alexa, a digital motion picture camera People * Alexa (name), a given name a ...
),
self-driving car A self-driving car, also known as an autonomous car, driver-less car, or robotic car (robo-car), is a car that is capable of traveling without human input.Xie, S.; Hu, J.; Bhowmick, P.; Ding, Z.; Arvin, F.,Distributed Motion Planning for S ...
s (e.g., Tesla),
automated decision-making Automated decision-making (ADM) involves the use of data, machines and algorithms to make decisions in a range of contexts, including public administration, business, health, education, law, employment, transport, media and entertainment, with var ...
and competing at the highest level in strategic game systems (such as chess and Go). As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the
AI effect :''For the magnitude of effect of a pesticide, see Pesticide application. Of change in farming practices, see Agricultural intensification.'' The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by argu ...
. For instance, optical character recognition is frequently excluded from things considered to be AI, having become a routine technology. Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an "
AI winter In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. followed by new approaches, success and renewed funding. AI research has tried and discarded many different approaches since its founding, including simulating the brain, modeling human problem solving,
formal logic Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the science of deductively valid inferences or of logical truths. It is a formal science investigating how conclusions follow from premis ...
, large databases of knowledge and imitating animal behavior. In the first decades of the 21st century, highly mathematical-statistical
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
has dominated the field, and this technique has proved highly successful, helping to solve many challenging problems throughout industry and academia. The various sub-fields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects.
General intelligence The ''g'' factor (also known as general intelligence, general mental ability or general intelligence factor) is a construct developed in psychometric investigations of cognitive abilities and human intelligence. It is a variable that summarizes ...
(the ability to solve an arbitrary problem) is among the field's long-term goals. To solve these problems, AI researchers have adapted and integrated a wide range of problem-solving techniques – including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability and
economics Economics () is the social science that studies the production, distribution, and consumption of goods and services. Economics focuses on the behaviour and interactions of economic agents and how economies work. Microeconomics analyzes ...
. AI also draws upon
computer science Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to practical disciplines (includi ...
,
psychology Psychology is the scientific study of mind and behavior. Psychology includes the study of conscious and unconscious phenomena, including feelings and thoughts. It is an academic discipline of immense scope, crossing the boundaries between ...
,
linguistics Linguistics is the science, scientific study of human language. It is called a scientific study because it entails a comprehensive, systematic, objective, and precise analysis of all aspects of language, particularly its nature and structure ...
, philosophy, and many other fields. The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it". This raised philosophical arguments about the mind and the ethical consequences of creating artificial beings endowed with human-like intelligence; these issues have previously been explored by myth, fiction and philosophy since antiquity. Computer scientists and philosophers have since suggested that AI may become an
existential risk A global catastrophic risk or a doomsday scenario is a hypothetical future event that could damage human well-being on a global scale, even endangering or destroying modern civilization. An event that could cause human extinction or permanen ...
to humanity if its rational capacities are not steered towards beneficial goals.


History

Artificial beings with intelligence appeared as
storytelling device A narrative technique (known for literary fictional narratives as a literary technique, literary device, or fictional device) is any of several specific methods the creator of a narrative uses to convey what they want —in other words, a stra ...
s in antiquity, AI in myth: * * and have been common in fiction, as in
Mary Shelley Mary Wollstonecraft Shelley (; ; 30 August 1797 – 1 February 1851) was an English novelist who wrote the Gothic novel '' Frankenstein; or, The Modern Prometheus'' (1818), which is considered an early example of science fiction. She also ...
's '' Frankenstein'' or
Karel Čapek Karel Čapek (; 9 January 1890 – 25 December 1938) was a Czech writer, playwright and critic. He has become best known for his science fiction, including his novel '' War with the Newts'' (1936) and play '' R.U.R.'' (''Rossum's Universal ...
's '' R.U.R.'' These characters and their fates raised many of the same issues now discussed in the ethics of artificial intelligence. The study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity. The study of mathematical logic led directly to Alan Turing's
theory of computation In theoretical computer science and mathematics, the theory of computation is the branch that deals with what problems can be solved on a model of computation, using an algorithm, how algorithmic efficiency, efficiently they can be solved or t ...
, which suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction. This insight that digital computers can simulate any process of formal reasoning is known as the Church–Turing thesis. This, along with concurrent discoveries in
neurobiology Neuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions and disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developme ...
, information theory and cybernetics, led researchers to consider the possibility of building an electronic brain. The first work that is now generally recognized as AI was McCullouch and Pitts' 1943 formal design for Turing-complete "artificial neurons". By the 1950s, two visions for how to achieve machine intelligence emerged. One vision, known as Symbolic AI or
GOFAI GOFAI is an acronym for "Good Old-Fashioned Artificial Intelligence" invented by the philosopher John Haugeland in his 1985 book, ''Artificial Intelligence: The Very Idea''. Technically, GOFAI refers only to a restricted kind of symbolic AI, name ...
, was to use computers to create a symbolic representation of the world and systems that could reason about the world. Proponents included Allen Newell,
Herbert A. Simon Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist, with a Ph.D. in political science, whose work also influenced the fields of computer science, economics, and cognitive psychology. His primary ...
, and Marvin Minsky. Closely associated with this approach was the "heuristic search" approach, which likened intelligence to a problem of exploring a space of possibilities for answers. The second vision, known as the connectionist approach, sought to achieve intelligence through learning. Proponents of this approach, most prominently
Frank Rosenblatt Frank Rosenblatt (July 11, 1928July 11, 1971) was an American psychologist notable in the field of artificial intelligence. He is sometimes called the father of deep learning. Life and career Rosenblatt was born in New Rochelle, New York as son o ...
, sought to connect
Perceptron In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belon ...
in ways inspired by connections of neurons. James Manyika and others have compared the two approaches to the mind (Symbolic AI) and the brain (connectionist). Manyika argues that symbolic approaches dominated the push for artificial intelligence in this period, due in part to its connection to intellectual traditions of Descarte, Boole, Gottlob Frege,
Bertrand Russell Bertrand Arthur William Russell, 3rd Earl Russell, (18 May 1872 – 2 February 1970) was a British mathematician, philosopher, logician, and public intellectual. He had a considerable influence on mathematics, logic, set theory, linguistics, ...
, and others. Connectionist approaches based on cybernetics or artificial neural networks were pushed to the background but have gained new prominence in recent decades. The field of AI research was born at a workshop at
Dartmouth College Dartmouth College (; ) is a private research university in Hanover, New Hampshire. Established in 1769 by Eleazar Wheelock, it is one of the nine colonial colleges chartered before the American Revolution. Although founded to educate Native ...
in 1956. The attendees became the founders and leaders of AI research. They and their students produced programs that the press described as "astonishing": computers were learning
checkers Checkers (American English), also known as draughts (; British English), is a group of strategy board games for two players which involve diagonal moves of uniform game pieces and mandatory captures by jumping over opponent pieces. Checkers ...
strategies, solving word problems in algebra, proving logical theorems and speaking English. By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense and laboratories had been established around the world. Researchers in the 1960s and the 1970s were convinced that symbolic approaches would eventually succeed in creating a machine with
artificial general intelligence Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fictio ...
and considered this the goal of their field. Herbert Simon predicted, "machines will be capable, within twenty years, of doing any work a man can do". Marvin Minsky agreed, writing, "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved". They had failed to recognize the difficulty of some of the remaining tasks. Progress slowed and in 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off exploratory research in AI. The next few years would later be called an "
AI winter In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. First
AI Winter In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research.Lighthill report,
Mansfield Amendment Michael Joseph Mansfield (March 16, 1903 – October 5, 2001) was an American politician and diplomat. A Democrat, he served as a U.S. representative (1943–1953) and a U.S. senator (1953–1977) from Montana. He was the longest-serving Sena ...
* * * * *
In the early 1980s, AI research was revived by the commercial success of expert systems, a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan's
fifth generation computer The Fifth Generation Computer Systems (FGCS) was a 10-year initiative begun in 1982 by Japan's Ministry of International Trade and Industry (MITI) to create computers using massively parallel computing and logic programming. It aimed to create ...
project inspired the U.S. and British governments to restore funding for academic research. Funding initiatives in the early 80s: Fifth Generation Project (Japan), Alvey (UK),
Microelectronics and Computer Technology Corporation Microelectronics and Computer Technology Corporation, originally the Microelectronics and Computer Consortium and widely seen as the acronym MCC, was the first, and at one time one of the largest, computer industry research and development co ...
(US),
Strategic Computing Initiative The United States government's Strategic Computing Initiative funded research into advanced computer hardware and artificial intelligence from 1983 to 1993. The initiative was designed to support various projects that were required to develop ma ...
(US): * * * * *
However, beginning with the collapse of the
Lisp Machine Lisp machines are general-purpose computers designed to efficiently run Lisp as their main software and programming language, usually via hardware support. They are an example of a high-level language computer architecture, and in a sense, they ...
market in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began. Second
AI Winter In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research.symbolic approach would be able to imitate all the processes of human cognition, especially perception, robotics, learning and
pattern recognition Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics ...
. A number of researchers began to look into "sub-symbolic" approaches to specific AI problems.
Robotics Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrate ...
researchers, such as
Rodney Brooks Rodney Allen Brooks (born 30 December 1954) is an Australian roboticist, Fellow of the Australian Academy of Science, author, and robotics entrepreneur, most known for popularizing the actionist approach to robotics. He was a Panasonic Profes ...
, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move, survive, and learn their environment. Interest in neural networks and " connectionism" was revived by
Geoffrey Hinton Geoffrey Everest Hinton One or more of the preceding sentences incorporates text from the royalsociety.org website where: (born 6 December 1947) is a British-Canadian cognitive psychologist and computer scientist, most noted for his work on a ...
, David Rumelhart and others in the middle of the 1980s. Soft computing tools were developed in the 1980s, such as neural networks,
fuzzy system A fuzzy control system is a control system based on fuzzy logic—a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, ...
s, Grey system theory, evolutionary computation and many tools drawn from statistics or mathematical optimization. AI gradually restored its reputation in the late 1990s and early 21st century by finding specific solutions to specific problems. The narrow focus allowed researchers to produce verifiable results, exploit more mathematical methods, and collaborate with other fields (such as statistics,
economics Economics () is the social science that studies the production, distribution, and consumption of goods and services. Economics focuses on the behaviour and interactions of economic agents and how economies work. Microeconomics analyzes ...
and mathematics). Formal and narrow methods adopted in the 1990s: * * By 2000, solutions developed by AI researchers were being widely used, although in the 1990s they were rarely described as "artificial intelligence". AI widely used in late 1990s: * * * * Faster computers, algorithmic improvements, and access to large amounts of data enabled advances in
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
and perception; data-hungry deep learning methods started to dominate accuracy benchmarks around 2012. According to Bloomberg's Jack Clark, 2015 was a landmark year for artificial intelligence, with the number of software projects that use AI within
Google Google LLC () is an American Multinational corporation, multinational technology company focusing on Search Engine, search engine technology, online advertising, cloud computing, software, computer software, quantum computing, e-commerce, ar ...
increased from a "sporadic usage" in 2012 to more than 2,700 projects. He attributes this to an increase in affordable neural networks, due to a rise in cloud computing infrastructure and to an increase in research tools and datasets. In a 2017 survey, one in five companies reported they had "incorporated AI in some offerings or processes". The amount of research into AI (measured by total publications) increased by 50% in the years 2015–2019. Numerous academic researchers became concerned that AI was no longer pursuing the original goal of creating versatile, fully intelligent machines. Much of current research involves statistical AI, which is overwhelmingly used to solve specific problems, even highly successful techniques such as deep learning. This concern has led to the subfield of
artificial general intelligence Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fictio ...
(or "AGI"), which had several well-funded institutions by the 2010s. ;


Goals

The general problem of simulating (or creating) intelligence has been broken down into sub-problems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention.


Reasoning, problem-solving

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions. By the late 1980s and 1990s, AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and
economics Economics () is the social science that studies the production, distribution, and consumption of goods and services. Economics focuses on the behaviour and interactions of economic agents and how economies work. Microeconomics analyzes ...
. Many of these algorithms proved to be insufficient for solving large reasoning problems because they experienced a "combinatorial explosion": they became exponentially slower as the problems grew larger. Intractability and efficiency and the
combinatorial explosion In mathematics, a combinatorial explosion is the rapid growth of the complexity of a problem due to how the combinatorics of the problem is affected by the input, constraints, and bounds of the problem. Combinatorial explosion is sometimes used to ...
: *
Even humans rarely use the step-by-step deduction that early AI research could model. They solve most of their problems using fast, intuitive judgments. Psychological evidence of the prevalence sub-symbolic reasoning and knowledge: * * * *


Knowledge representation

Knowledge representation and
knowledge engineering Knowledge engineering (KE) refers to all technical, scientific and social aspects involved in building, maintaining and using knowledge-based systems. Background Expert systems One of the first examples of an expert system was MYCIN, an appli ...
allow AI programs to answer questions intelligently and make deductions about real-world facts. A representation of "what exists" is an ontology: the set of objects, relations, concepts, and properties formally described so that software agents can interpret them. The most general ontologies are called upper ontologies, which attempt to provide a foundation for all other knowledge and act as mediators between domain ontologies that cover specific knowledge about a particular knowledge domain (field of interest or area of concern). A truly intelligent program would also need access to commonsense knowledge; the set of facts that an average person knows. The
semantics Semantics (from grc, σημαντικός ''sēmantikós'', "significant") is the study of reference, meaning, or truth. The term can be used to refer to subfields of several distinct disciplines, including philosophy, linguistics and comp ...
of an ontology is typically represented in description logic, such as the
Web Ontology Language The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for vario ...
. AI research has developed tools to represent specific domains, such as objects, properties, categories and relations between objects; situations, events, states and time; causes and effects; knowledge about knowledge (what we know about what other people know);. default reasoning (things that humans assume are true until they are told differently and will remain true even when other facts are changing); as well as other domains. Among the most difficult problems in AI are: the breadth of commonsense knowledge (the number of atomic facts that the average person knows is enormous); Breadth of commonsense knowledge: * , * , * , * and the sub-symbolic form of most commonsense knowledge (much of what people know is not represented as "facts" or "statements" that they could express verbally). Formal knowledge representations are used in content-based indexing and retrieval, scene interpretation, clinical decision support, knowledge discovery (mining "interesting" and actionable inferences from large databases), and other areas.


Learning

Machine learning (ML), a fundamental concept of AI research since the field's inception, is the study of computer algorithms that improve automatically through experience.
Unsupervised learning Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and t ...
finds patterns in a stream of input.
Supervised learning Supervised learning (SL) is a machine learning paradigm for problems where the available data consists of labelled examples, meaning that each data point contains features (covariates) and an associated label. The goal of supervised learning alg ...
requires a human to label the input data first, and comes in two main varieties: classification and numerical regression. Classification is used to determine what category something belongs in – the program sees a number of examples of things from several categories and will learn to classify new inputs. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. Both classifiers and regression learners can be viewed as "function approximators" trying to learn an unknown (possibly implicit) function; for example, a spam classifier can be viewed as learning a function that maps from the text of an email to one of two categories, "spam" or "not spam". In
reinforcement learning Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine ...
the agent is rewarded for good responses and punished for bad ones. The agent classifies its responses to form a strategy for operating in its problem space. Transfer learning is when the knowledge gained from one problem is applied to a new problem.
Computational learning theory In computer science, computational learning theory (or just learning theory) is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms. Overview Theoretical results in machine learning m ...
can assess learners by computational complexity, by
sample complexity The sample complexity of a machine learning algorithm represents the number of training-samples that it needs in order to successfully learn a target function. More precisely, the sample complexity is the number of training-samples that we need to ...
(how much data is required), or by other notions of
optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
.


Natural language processing

Natural language processing (NLP) allows machines to read and understand human language. A sufficiently powerful natural language processing system would enable natural-language user interfaces and the acquisition of knowledge directly from human-written sources, such as newswire texts. Some straightforward applications of NLP include information retrieval, question answering and machine translation. Symbolic AI used formal syntax to translate the
deep structure Deep structure and surface structure (also D-structure and S-structure although those abbreviated forms are sometimes used with distinct meanings) are concepts used in linguistics, specifically in the study of syntax in the Chomskyan tradition of t ...
of sentences into logic. This failed to produce useful applications, due to the intractability of logic and the breadth of commonsense knowledge. Modern statistical techniques include co-occurrence frequencies (how often one word appears near another), "Keyword spotting" (searching for a particular word to retrieve information), transformer-based deep learning (which finds patterns in text), and others. They have achieved acceptable accuracy at the page or paragraph level, and, by 2019, could generate coherent text.


Perception

Machine perception is the ability to use input from sensors (such as cameras, microphones, wireless signals, and active lidar, sonar, radar, and
tactile sensor A tactile sensor is a device that measures information arising from physical interaction with its environment. Tactile sensors are generally modeled after the biological sense of cutaneous touch which is capable of detecting stimuli resultin ...
s) to deduce aspects of the world. Applications include
speech recognition Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the ...
, facial recognition, and
object recognition Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the ...
. Computer vision is the ability to analyze visual input.


Social intelligence

Affective computing is an interdisciplinary umbrella that comprises systems that recognize, interpret, process or simulate human feeling, emotion and mood. For example, some virtual assistants are programmed to speak conversationally or even to banter humorously; it makes them appear more sensitive to the emotional dynamics of human interaction, or to otherwise facilitate
human–computer interaction Human–computer interaction (HCI) is research in the design and the use of computer technology, which focuses on the interfaces between people (users) and computers. HCI researchers observe the ways humans interact with computers and design te ...
. However, this tends to give naïve users an unrealistic conception of how intelligent existing computer agents actually are. Moderate successes related to affective computing include textual
sentiment analysis Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjec ...
and, more recently, multimodal sentiment analysis), wherein AI classifies the affects displayed by a videotaped subject.


General intelligence

A machine with general intelligence can solve a wide variety of problems with breadth and versatility similar to human intelligence. There are several competing ideas about how to develop artificial general intelligence.
Hans Moravec Hans Peter Moravec (born November 30, 1948, Kautzen, Austria) is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University in Pittsburgh, USA. He is known for his work on robotics, artificial intelligence, and writings ...
and Marvin Minsky argue that work in different individual domains can be incorporated into an advanced multi-agent system or cognitive architecture with general intelligence. Pedro Domingos hopes that there is a conceptually straightforward, but mathematically difficult, " master algorithm" that could lead to AGI. Others believe that anthropomorphic features like an artificial brain or simulated
child development Child development involves the Human development (biology), biological, developmental psychology, psychological and emotional changes that occur in human beings between birth and the conclusion of adolescence. Childhood is divided into 3 stages o ...
will someday reach a critical point where general intelligence emerges.


Tools


Search and optimization

AI can solve many problems by intelligently searching through many possible solutions. Reasoning can be reduced to performing a search. For example, logical proof can be viewed as searching for a path that leads from
premise A premise or premiss is a true or false statement that helps form the body of an argument, which logically leads to a true or false conclusion. A premise makes a declarative statement about its subject matter which enables a reader to either agre ...
s to conclusions, where each step is the application of an
inference rule In the philosophy of logic, a rule of inference, inference rule or transformation rule is a logical form consisting of a function which takes premises, analyzes their syntax, and returns a conclusion (or conclusions). For example, the rule of ...
.
Forward chaining Forward chaining (or forward reasoning) is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of ''modus ponens''. Forward chaining is a popular implementation strategy ...
, backward chaining, Horn clauses, and logical deduction as search: * * * *
Planning algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called means-ends analysis.
State space search State space search is a process used in the field of computer science, including artificial intelligence (AI), in which successive configurations or ''states'' of an instance are considered, with the intention of finding a ''goal state'' with the ...
and planning: * * *
Robotics Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrate ...
algorithms for moving limbs and grasping objects use local searches in configuration space.Moving and configuration space: * Simple exhaustive searchesUninformed searches ( breadth first search, depth-first search and general
state space search State space search is a process used in the field of computer science, including artificial intelligence (AI), in which successive configurations or ''states'' of an instance are considered, with the intention of finding a ''goal state'' with the ...
): * * * *
are rarely sufficient for most real-world problems: the search space (the number of places to search) quickly grows to astronomical numbers. The result is a search that is too slow or never completes. The solution, for many problems, is to use "
heuristics A heuristic (; ), or heuristic technique, is any approach to problem solving or self-discovery that employs a practical method that is not guaranteed to be optimal, perfect, or rational, but is nevertheless sufficient for reaching an immediate, ...
" or "rules of thumb" that prioritize choices in favor of those more likely to reach a goal and to do so in a shorter number of steps. In some search methodologies, heuristics can also serve to eliminate some choices unlikely to lead to a goal (called "
pruning Pruning is a horticultural, arboricultural, and silvicultural practice involving the selective removal of certain parts of a plant, such as branches, buds, or roots. The practice entails the ''targeted'' removal of diseased, damaged, dead, ...
the
search tree In computer science, a search tree is a tree data structure used for locating specific keys from within a set. In order for a tree to function as a search tree, the key for each node must be greater than any keys in subtrees on the left, and less ...
"). Heuristics supply the program with a "best guess" for the path on which the solution lies. Heuristic or informed searches (e.g., greedy best first and A*): * * * * Heuristics limit the search for solutions into a smaller sample size. A very different kind of search came to prominence in the 1990s, based on the mathematical theory of
optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
. For many problems, it is possible to begin the search with some form of a guess and then refine the guess incrementally until no more refinements can be made. These algorithms can be visualized as blind
hill climbing numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to find a better solutio ...
: we begin the search at a random point on the landscape, and then, by jumps or steps, we keep moving our guess uphill, until we reach the top. Other related optimization algorithms include random optimization,
beam search In computer science, beam search is a heuristic search algorithm that explores a graph by expanding the most promising node in a limited set. Beam search is an optimization of best-first search that reduces its memory requirements. Best-first sea ...
and metaheuristics like
simulated annealing Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. ...
.
Optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
searches: * * *
Evolutionary computation uses a form of optimization search. For example, they may begin with a population of organisms (the guesses) and then allow them to mutate and recombine, selecting only the fittest to survive each generation (refining the guesses). Classic
evolutionary algorithms In computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduct ...
include
genetic algorithms In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to gene ...
, gene expression programming, and
genetic programming In artificial intelligence, genetic programming (GP) is a technique of evolving programs, starting from a population of unfit (usually random) programs, fit for a particular task by applying operations analogous to natural genetic processes to t ...
.
Genetic programming In artificial intelligence, genetic programming (GP) is a technique of evolving programs, starting from a population of unfit (usually random) programs, fit for a particular task by applying operations analogous to natural genetic processes to t ...
and
genetic algorithms In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to gene ...
: * *
Alternatively, distributed search processes can coordinate via swarm intelligence algorithms. Two popular swarm algorithms used in search are particle swarm optimization (inspired by bird flocking) and
ant colony optimization In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial ants stand for multi ...
(inspired by
ant trail Ants are eusocial insects of the family Formicidae and, along with the related wasps and bees, belong to the order Hymenoptera. Ants evolved from vespoid wasp ancestors in the Cretaceous period. More than 13,800 of an estimated total of 22,0 ...
s).
Artificial life Artificial life (often abbreviated ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry ...
and society based learning: * *


Logic

Logic Logic: * , * , * is used for knowledge representation and problem-solving, but it can be applied to other problems as well. For example, the satplan algorithm uses logic for planning Satplan: * , * , * and inductive logic programming is a method for learning. Explanation based learning, relevance based learning, inductive logic programming, case based reasoning: * , * , * , * Several different forms of logic are used in AI research.
Propositional logic Propositional calculus is a branch of logic. It is also called propositional logic, statement logic, sentential calculus, sentential logic, or sometimes zeroth-order logic. It deals with propositions (which can be true or false) and relations b ...
Propositional logic Propositional calculus is a branch of logic. It is also called propositional logic, statement logic, sentential calculus, sentential logic, or sometimes zeroth-order logic. It deals with propositions (which can be true or false) and relations b ...
: * , * *
involves truth functions such as "or" and "not".
First-order logic First-order logic—also known as predicate logic, quantificational logic, and first-order predicate calculus—is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantifie ...
First-order logic First-order logic—also known as predicate logic, quantificational logic, and first-order predicate calculus—is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantifie ...
and features such as
equality Equality may refer to: Society * Political equality, in which all members of a society are of equal standing ** Consociationalism, in which an ethnically, religiously, or linguistically divided state functions by cooperation of each group's elit ...
: * , * , * , *
adds quantifiers and
predicates Predicate or predication may refer to: * Predicate (grammar), in linguistics * Predication (philosophy) * several closely related uses in mathematics and formal logic: **Predicate (mathematical logic) **Propositional function **Finitary relation, ...
and can express facts about objects, their properties, and their relations with each other. Fuzzy logic assigns a "degree of truth" (between 0 and 1) to vague statements such as "Alice is old" (or rich, or tall, or hungry), that are too linguistically imprecise to be completely true or false. Fuzzy logic: * * Default logics,
non-monotonic logic A non-monotonic logic is a formal logic whose conclusion relation is not monotonic. In other words, non-monotonic logics are devised to capture and represent defeasible inferences (cf. defeasible reasoning), i.e., a kind of inference in which re ...
s and
circumscription Circumscription may refer to: *Circumscribed circle * Circumscription (logic) *Circumscription (taxonomy) *Circumscription theory, a theory about the origins of the political state in the history of human evolution proposed by the American anthrop ...
are forms of logic designed to help with default reasoning and the qualification problem. Default reasoning,
Frame problem In artificial intelligence, the frame problem describes an issue with using first-order logic (FOL) to express facts about a robot in the world. Representing the state of a robot with traditional FOL requires the use of many axioms that simply impl ...
, default logic,
non-monotonic logic A non-monotonic logic is a formal logic whose conclusion relation is not monotonic. In other words, non-monotonic logics are devised to capture and represent defeasible inferences (cf. defeasible reasoning), i.e., a kind of inference in which re ...
s,
circumscription Circumscription may refer to: *Circumscribed circle * Circumscription (logic) *Circumscription (taxonomy) *Circumscription theory, a theory about the origins of the political state in the history of human evolution proposed by the American anthrop ...
, closed world assumption, abduction: * * * * (Poole ''et al.'' places abduction under "default reasoning". Luger ''et al.'' places this under "uncertain reasoning").
Several extensions of logic have been designed to handle specific domains of knowledge, such as description logics; Representing categories and relations: Semantic networks, description logics, inheritance (including frames and scripts): * , * , * , * situation calculus, event calculus and fluent calculus (for representing events and time);Representing events and time: Situation calculus, event calculus, fluent calculus (including solving the
frame problem In artificial intelligence, the frame problem describes an issue with using first-order logic (FOL) to express facts about a robot in the world. Representing the state of a robot with traditional FOL requires the use of many axioms that simply impl ...
): * , * , *
causal calculus; Causal calculus: * belief calculus (belief revision); and modal logics. Representing knowledge about knowledge: Belief calculus, modal logics: * , * Logics to model contradictory or inconsistent statements arising in multi-agent systems have also been designed, such as paraconsistent logics.


Probabilistic methods for uncertain reasoning

Many problems in AI (including in reasoning, planning, learning, perception, and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of tools to solve these problems using methods from probability theory and economics. Bayesian networks Bayesian networks: * , * , * , * are a very general tool that can be used for various problems, including reasoning (using the Bayesian inference algorithm), Bayesian inference algorithm: * , * , * , * learning (using the expectation-maximization algorithm),
Bayesian learning Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and e ...
and the expectation-maximization algorithm: * , * , * *
planning (using decision networks)
Bayesian decision theory In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the po ...
and Bayesian decision networks: *
and perception (using
dynamic Bayesian network A Dynamic Bayesian Network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. This is often called a ''Two-Timeslice'' BN (2TBN) because it says that at any point in time T, the value of a variable c ...
s).Stochastic temporal models: *
Dynamic Bayesian network A Dynamic Bayesian Network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. This is often called a ''Two-Timeslice'' BN (2TBN) because it says that at any point in time T, the value of a variable c ...
s: * Hidden Markov model: *
Kalman filter For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estima ...
s: *
Probabilistic algorithms can also be used for filtering, prediction, smoothing and finding explanations for streams of data, helping perception systems to analyze processes that occur over time (e.g., hidden Markov models or
Kalman filter For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estima ...
s). A key concept from the science of economics is " utility", a measure of how valuable something is to an intelligent agent. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using
decision theory Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical ...
,
decision analysis Decision analysis (DA) is the discipline comprising the philosophy, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifyi ...
,
decision theory Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical ...
and
decision analysis Decision analysis (DA) is the discipline comprising the philosophy, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifyi ...
: * , *
and information value theory. Information value theory: * These tools include models such as Markov decision processes, Markov decision processes and dynamic decision networks: * dynamic decision networks, game theory and
mechanism design Mechanism design is a field in economics and game theory that takes an objectives-first approach to designing economic mechanisms or incentives, toward desired objectives, in strategic settings, where players act rationally. Because it starts a ...
. Game theory and
mechanism design Mechanism design is a field in economics and game theory that takes an objectives-first approach to designing economic mechanisms or incentives, toward desired objectives, in strategic settings, where players act rationally. Because it starts a ...
: *


Classifiers and statistical learning methods

The simplest AI applications can be divided into two types: classifiers ("if shiny then diamond") and controllers ("if diamond then pick up"). Controllers do, however, also classify conditions before inferring actions, and therefore classification forms a central part of many AI systems. Classifiers are functions that use
pattern matching In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be ...
to determine the closest match. They can be tuned according to examples, making them very attractive for use in AI. These examples are known as observations or patterns. In supervised learning, each pattern belongs to a certain predefined class. A class is a decision that has to be made. All the observations combined with their class labels are known as a data set. When a new observation is received, that observation is classified based on previous experience. A classifier can be trained in various ways; there are many statistical and
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
approaches. The decision tree is the simplest and most widely used symbolic machine learning algorithm. K-nearest neighbor algorithm was the most widely used analogical AI until the mid-1990s. Kernel methods such as the support vector machine (SVM) displaced k-nearest neighbor in the 1990s. The naive Bayes classifier is reportedly the "most widely used learner" at Google, due in part to its scalability. Neural networks are also used for classification. Classifier performance depends greatly on the characteristics of the data to be classified, such as the dataset size, distribution of samples across classes, dimensionality, and the level of noise. Model-based classifiers perform well if the assumed model is an extremely good fit for the actual data. Otherwise, if no matching model is available, and if accuracy (rather than speed or scalability) is the sole concern, conventional wisdom is that discriminative classifiers (especially SVM) tend to be more accurate than model-based classifiers such as "naive Bayes" on most practical data sets.


Artificial neural networks

Neural networks Neural networks: * , * , * , * * were inspired by the architecture of neurons in the human brain. A simple "neuron" ''N'' accepts input from other neurons, each of which, when activated (or "fired"), casts a weighted "vote" for or against whether neuron ''N'' should itself activate. Learning requires an algorithm to adjust these weights based on the training data; one simple algorithm (dubbed " fire together, wire together") is to increase the weight between two connected neurons when the activation of one triggers the successful activation of another. Neurons have a continuous spectrum of activation; in addition, neurons can process inputs in a nonlinear way rather than weighing straightforward votes. Modern neural networks model complex relationships between inputs and outputs and find patterns in data. They can learn continuous functions and even digital logical operations. Neural networks can be viewed as a type of mathematical optimization – they perform
gradient descent In mathematics, gradient descent (also often called steepest descent) is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. The idea is to take repeated steps in the opposite direction of the ...
on a multi-dimensional topology that was created by
training Training is teaching, or developing in oneself or others, any skills and knowledge or fitness that relate to specific useful competencies. Training has specific goals of improving one's capability, capacity, productivity and performance. I ...
the network. The most common training technique is the
backpropagation In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforward artificial neural networks. Generalizations of backpropagation exist for other artificial neural networks (ANNs), and for functions gener ...
algorithm.
Backpropagation In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforward artificial neural networks. Generalizations of backpropagation exist for other artificial neural networks (ANNs), and for functions gener ...
: * , * , * Paul Werbos' introduction of backpropagation to AI: * ;
Automatic differentiation In mathematics and computer algebra, automatic differentiation (AD), also called algorithmic differentiation, computational differentiation, auto-differentiation, or simply autodiff, is a set of techniques to evaluate the derivative of a function s ...
, an essential precursor: * ;
Other learning techniques for neural networks are
Hebbian learning Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptatio ...
("fire together, wire together"),
GMDH Group method of data handling (GMDH) is a family of inductive algorithms for computer-based mathematical modeling of multi-parametric datasets that features fully automatic structural and parametric optimization of models. GMDH is used in such fiel ...
or competitive learning. Competitive learning,
Hebbian Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation ...
coincidence learning,
Hopfield network A Hopfield network (or Ising model of a neural network or Ising–Lenz–Little model) is a form of recurrent artificial neural network and a type of spin glass system popularised by John Hopfield in 1982 as described earlier by Little in 1974 b ...
s and attractor networks: *
The main categories of networks are acyclic or feedforward neural networks (where the signal passes in only one direction) and
recurrent neural network A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic ...
s (which allow feedback and short-term memories of previous input events). Among the most popular feedforward networks are
perceptron In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belon ...
s, multi-layer perceptrons and radial basis networks. Feedforward neural networks,
perceptron In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belon ...
s and radial basis networks: * *


Deep learning

Deep learning uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces. Deep learning has drastically improved the performance of programs in many important subfields of artificial intelligence, including computer vision,
speech recognition Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the ...
, image classification and others. Deep learning often uses convolutional neural networks for many or all of its layers. In a convolutional layer, each neuron receives input from only a restricted area of the previous layer called the neuron's
receptive field The receptive field, or sensory space, is a delimited medium where some physiological stimuli can evoke a sensory neuronal response in specific organisms. Complexity of the receptive field ranges from the unidimensional chemical structure of o ...
. This can substantially reduce the number of weighted connections between neurons, and creates a hierarchy similar to the organization of the animal visual cortex. In a
recurrent neural network A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic ...
(RNN) the signal will propagate through a layer more than once; thus, an RNN is an example of deep learning. RNNs can be trained by
gradient descent In mathematics, gradient descent (also often called steepest descent) is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. The idea is to take repeated steps in the opposite direction of the ...
, however long-term gradients which are back-propagated can "vanish" (that is, they can tend to zero) or "explode" (that is, they can tend to infinity), known as the
vanishing gradient problem In machine learning, the vanishing gradient problem is encountered when training artificial neural networks with gradient-based learning methods and backpropagation. In such methods, during each iteration of training each of the neural network's ...
. The long short term memory (LSTM) technique can prevent this in most cases.


Specialized languages and hardware

Specialized languages for artificial intelligence have been developed, such as Lisp,
Prolog Prolog is a logic programming language associated with artificial intelligence and computational linguistics. Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is intended primarily ...
,
TensorFlow TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. "It is machine learnin ...
and many others. Hardware developed for AI includes AI accelerators and neuromorphic computing.


Applications

AI is relevant to any intellectual task. Modern artificial intelligence techniques are pervasive and are too numerous to list here. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the
AI effect :''For the magnitude of effect of a pesticide, see Pesticide application. Of change in farming practices, see Agricultural intensification.'' The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by argu ...
. In the 2010s, AI applications were at the heart of the most commercially successful areas of computing, and have become a ubiquitous feature of daily life. AI is used in search engines (such as Google Search), targeting online advertisements, recommendation systems (offered by
Netflix Netflix, Inc. is an American subscription video on-demand over-the-top streaming service and production company based in Los Gatos, California. Founded in 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California, it offers a fi ...
,
YouTube YouTube is a global online video sharing and social media platform headquartered in San Bruno, California. It was launched on February 14, 2005, by Steve Chen, Chad Hurley, and Jawed Karim. It is owned by Google, and is the second mo ...
or Amazon), driving
internet traffic Internet traffic is the flow of data within the entire Internet, or in certain network links of its constituent networks. Common traffic measurements are total volume, in units of multiples of the byte, or as transmission rates in bytes per cert ...
, targeted advertising (
AdSense Google AdSense is a program run by Google through which website publishers in the Google Network of content sites serve text, images, video, or interactive media advertisements that are targeted to the site content and audience. These advert ...
,
Facebook Facebook is an online social media and social networking service owned by American company Meta Platforms. Founded in 2004 by Mark Zuckerberg with fellow Harvard College students and roommates Eduardo Saverin, Andrew McCollum, Dustin Mosk ...
), virtual assistants (such as
Siri Siri ( ) is a virtual assistant that is part of Apple Inc.'s iOS, iPadOS, watchOS, macOS, tvOS, and audioOS operating systems. It uses voice queries, gesture based control, focus-tracking and a natural-language user interface to answer qu ...
or
Alexa Alexa may refer to: Technology *Amazon Alexa, a virtual assistant developed by Amazon * Alexa Internet, a defunct website ranking and traffic analysis service * Arri Alexa, a digital motion picture camera People * Alexa (name), a given name a ...
),
autonomous vehicles Vehicular automation involves the use of mechatronics, artificial intelligence, and multi-agent systems to assist the operator of a vehicle (car, aircraft, watercraft, or otherwise).Hu, J.; Bhowmick, P.; Lanzon, A.,Group Coordinated Control o ...
(including drones and
self-driving cars A self-driving car, also known as an autonomous car, driver-less car, or robotic car (robo-car), is a car that is capable of traveling without human input.Xie, S.; Hu, J.; Bhowmick, P.; Ding, Z.; Arvin, F.,Distributed Motion Planning for S ...
), automatic language translation ( Microsoft Translator,
Google Translate Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, and an API ...
), facial recognition ( Apple's
Face ID Face ID is a facial recognition system designed and developed by Apple Inc. for the iPhone and iPad Pro. The system allows biometric authentication for unlocking a device, making payments, accessing sensitive data, providing detailed facial ex ...
or Microsoft's DeepFace), image labeling (used by
Facebook Facebook is an online social media and social networking service owned by American company Meta Platforms. Founded in 2004 by Mark Zuckerberg with fellow Harvard College students and roommates Eduardo Saverin, Andrew McCollum, Dustin Mosk ...
, Apple's
iPhoto iPhoto is a discontinued digital photograph manipulation software application developed by Apple Inc. It was included with every Macintosh personal computer from 2002 to 2015, when it was replaced with Apple's Photos application. Originally so ...
and
TikTok TikTok, known in China as Douyin (), is a short-form video hosting service owned by the Chinese company ByteDance. It hosts user-submitted videos, which can range in duration from 15 seconds to 10 minutes. TikTok is an international version o ...
) and
spam filtering Various anti-spam techniques are used to prevent email spam (unsolicited bulk email). No technique is a complete solution to the spam problem, and each has trade-offs between incorrectly rejecting legitimate email (false positives) as opposed to ...
. There are also thousands of successful AI applications used to solve problems for specific industries or institutions. A few examples are energy storage, deepfakes, medical diagnosis, military logistics, or supply chain management. Game playing has been a test of AI's strength since the 1950s. Deep Blue became the first computer chess-playing system to beat a reigning world chess champion,
Garry Kasparov Garry Kimovich Kasparov (born 13 April 1963) is a Russian chess grandmaster, former World Chess Champion, writer, political activist and commentator. His peak rating of 2851, achieved in 1999, was the highest recorded until being surpassed by ...
, on 11 May 1997. In 2011, in a '' Jeopardy!'' quiz show exhibition match, IBM's question answering system, Watson, defeated the two greatest ''Jeopardy!'' champions, Brad Rutter and
Ken Jennings Kenneth Wayne Jennings III (born May 23, 1974) is an American game show host, author, and former game show contestant. He is the highest-earning American game show contestant, having won money on five different game shows, including $4,522,70 ...
, by a significant margin. In March 2016,
AlphaGo AlphaGo is a computer program that plays the board game Go. It was developed by DeepMind Technologies a subsidiary of Google (now Alphabet Inc.). Subsequent versions of AlphaGo became increasingly powerful, including a version that competed u ...
won 4 out of 5 games of Go in a match with Go champion Lee Sedol, becoming the first computer Go-playing system to beat a professional Go player without handicaps. Other programs handle imperfect-information games; such as for poker at a superhuman level, Pluribus and Cepheus. DeepMind in the 2010s developed a "generalized artificial intelligence" that could learn many diverse Atari games on its own. By 2020, Natural Language Processing systems such as the enormous GPT-3 (then by far the largest artificial neural network) were matching human performance on pre-existing benchmarks, albeit without the system attaining a commonsense understanding of the contents of the benchmarks. DeepMind's AlphaFold 2 (2020) demonstrated the ability to approximate, in hours rather than months, the 3D structure of a protein. Other applications predict the result of judicial decisions, create art (such as poetry or painting) and prove mathematical theorems.


Intellectual Property

In 2019,
WIPO The World Intellectual Property Organization (WIPO; french: link=no, Organisation mondiale de la propriété intellectuelle (OMPI)) is one of the 15 specialized agencies of the United Nations (UN). Pursuant to the 1967 Convention Establishin ...
reported that AI was the most prolific
emerging technology Emerging technologies are technologies whose development, practical applications, or both are still largely unrealized. These technologies are generally new but also include older technologies finding new applications. Emerging technologies ar ...
in terms of number of
patent A patent is a type of intellectual property that gives its owner the legal right to exclude others from making, using, or selling an invention for a limited period of time in exchange for publishing an enabling disclosure of the invention."A ...
applications and granted patents, the Internet of things was estimated to be the largest in terms of market size. It was followed, again in market size, by big data technologies, robotics, AI, 3D printing and the fifth generation of mobile services (5G). Since AI emerged in the 1950s, 340,000 AI-related patent applications were filed by innovators and 1.6 million scientific papers have been published by researchers, with the majority of all AI-related patent filings published since 2013. Companies represent 26 out of the top 30 AI patent applicants, with universities or public research organizations accounting for the remaining four. The ratio of scientific papers to inventions has significantly decreased from 8:1 in 2010 to 3:1 in 2016, which is attributed to be indicative of a shift from theoretical research to the use of AI technologies in commercial products and services.
Machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
is the dominant AI technique disclosed in patents and is included in more than one-third of all identified inventions (134,777 machine learning patents filed for a total of 167,038 AI patents filed in 2016), with computer vision being the most popular functional application. AI-related patents not only disclose AI techniques and applications, they often also refer to an application field or industry. Twenty application fields were identified in 2016 and included, in order of magnitude: telecommunications (15 percent), transportation (15 percent), life and medical sciences (12 percent), and personal devices, computing and human–computer interaction (11 percent). Other sectors included banking, entertainment, security, industry and manufacturing, agriculture, and networks (including social networks, smart cities and the Internet of things). IBM has the largest portfolio of AI patents with 8,290 patent applications, followed by Microsoft with 5,930 patent applications.


Philosophy


Defining artificial intelligence

Alan Turing wrote in 1950 "I propose to consider the question 'can machines think'?" He advised changing the question from whether a machine "thinks", to "whether or not it is possible for machinery to show intelligent behaviour". He devised the Turing test, which measures the ability of a machine to simulate human conversation. Turing's original publication of the Turing test in "
Computing machinery and intelligence "Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in ''Mind'', was the first to introduce his concept of what is now known as the Turing test to ...
": * Historical influence and philosophical implications: * * * *
Since we can only observe the behavior of the machine, it does not matter if it is "actually" thinking or literally has a "mind". Turing notes that we can not determine these things about other people but "it is usual to have a polite convention that everyone thinks" Russell and Norvig agree with Turing that AI must be defined in terms of "acting" and not "thinking". However, they are critical that the test compares machines to ''people''. "
Aeronautical engineering Aerospace engineering is the primary field of engineering concerned with the development of aircraft and spacecraft. It has two major and overlapping branches: aeronautical engineering and astronautical engineering. Avionics engineering is sim ...
texts," they wrote, "do not define the goal of their field as making 'machines that fly so exactly like
pigeon Columbidae () is a bird family consisting of doves and pigeons. It is the only family in the order Columbiformes. These are stout-bodied birds with short necks and short slender bills that in some species feature fleshy ceres. They primarily ...
s that they can fool other pigeons. AI founder John McCarthy agreed, writing that "Artificial intelligence is not, by definition, simulation of human intelligence". McCarthy defines intelligence as "the computational part of the ability to achieve goals in the world." Another AI founder, Marvin Minsky similarly defines it as "the ability to solve hard problems". These definitions view intelligence in terms of well-defined problems with well-defined solutions, where both the difficulty of the problem and the performance of the program are direct measures of the "intelligence" of the machine -- and no other philosophical discussion is required, or may not even be possible. A definition that has also been adopted by Google - major practitionary in the field of AI. This definition stipulated the ability of systems to synthesize information as the manifestation of intelligence, similar to the way it is defined in biological intelligence.


Evaluating approaches to AI

No established unifying theory or paradigm has guided AI research for most of its history. The unprecedented success of statistical machine learning in the 2010s eclipsed all other approaches (so much so that some sources, especially in the business world, use the term "artificial intelligence" to mean "machine learning with neural networks"). This approach is mostly
sub-symbolic In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Sy ...
, neat, soft and narrow (see below). Critics argue that these questions may have to be revisited by future generations of AI researchers.


Symbolic AI and its limits

Symbolic AI (or "
GOFAI GOFAI is an acronym for "Good Old-Fashioned Artificial Intelligence" invented by the philosopher John Haugeland in his 1985 book, ''Artificial Intelligence: The Very Idea''. Technically, GOFAI refers only to a restricted kind of symbolic AI, name ...
") simulated the high-level conscious reasoning that people use when they solve puzzles, express legal reasoning and do mathematics. They were highly successful at "intelligent" tasks such as algebra or IQ tests. In the 1960s, Newell and Simon proposed the physical symbol systems hypothesis: "A physical symbol system has the necessary and sufficient means of general intelligent action." Physical symbol system hypothesis: * Historical significance: * * However, the symbolic approach failed on many tasks that humans solve easily, such as learning, recognizing an object or commonsense reasoning. Moravec's paradox is the discovery that high-level "intelligent" tasks were easy for AI, but low level "instinctive" tasks were extremely difficult. Philosopher Hubert Dreyfus had argued since the 1960s that human expertise depends on unconscious instinct rather than conscious symbol manipulation, and on having a "feel" for the situation, rather than explicit symbolic knowledge. Dreyfus' critique of AI: * * Historical significance and philosophical implications: * * * * Although his arguments had been ridiculed and ignored when they were first presented, eventually, AI research came to agree. The issue is not resolved:
sub-symbolic In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Sy ...
reasoning can make many of the same inscrutable mistakes that human intuition does, such as
algorithmic bias Algorithmic bias describes systematic and repeatable errors in a computer system that create " unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm. Bias can emerge from ...
. Critics such as Noam Chomsky argue continuing research into symbolic AI will still be necessary to attain general intelligence, in part because sub-symbolic AI is a move away from
explainable AI Explainable AI (XAI), or Interpretable AI, or Explainable Machine Learning (XML), is artificial intelligence (AI) in which humans can understand the decisions or predictions made by the AI. It contrasts with the "black box" concept in machine lear ...
: it can be difficult or impossible to understand why a modern statistical AI program made a particular decision. The emerging field of neurosymbolic artificial intelligence attempts to bridge the two approaches.


Neat vs. scruffy

"Neats" hope that intelligent behavior is described using simple, elegant principles (such as logic,
optimization Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfi ...
, or neural networks). "Scruffies" expect that it necessarily requires solving a large number of unrelated problems (especially in areas like common sense reasoning). This issue was actively discussed in the 70s and 80s, Neats vs. scruffies, the historic debate: * * * A classic example of the "scruffy" approach to intelligence: * A modern example of neat AI and its aspirations: * but in the 1990s mathematical methods and solid scientific standards became the norm, a transition that Russell and Norvig termed "the victory of the neats".


Soft vs. hard computing

Finding a provably correct or optimal solution is intractable for many important problems. Soft computing is a set of techniques, including
genetic algorithms In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to gene ...
, fuzzy logic and neural networks, that are tolerant of imprecision, uncertainty, partial truth and approximation. Soft computing was introduced in the late 80s and most successful AI programs in the 21st century are examples of soft computing with neural networks.


Narrow vs. general AI

AI researchers are divided as to whether to pursue the goals of artificial general intelligence and
superintelligence A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. "Superintelligence" may also refer to a property of problem-solving systems (e.g., superintelligent languag ...
(general AI) directly or to solve as many specific problems as possible ( narrow AI) in hopes these solutions will lead indirectly to the field's long-term goals. General intelligence is difficult to define and difficult to measure, and modern AI has had more verifiable successes by focusing on specific problems with specific solutions. The experimental sub-field of artificial general intelligence studies this area exclusively.


Machine consciousness, sentience and mind

The philosophy of mind does not know whether a machine can have a mind,
consciousness Consciousness, at its simplest, is sentience and awareness of internal and external existence. However, the lack of definitions has led to millennia of analyses, explanations and debates by philosophers, theologians, linguisticians, and scien ...
and mental states, in the same sense that human beings do. This issue considers the internal experiences of the machine, rather than its external behavior. Mainstream AI research considers this issue irrelevant because it does not affect the goals of the field. Stuart Russell and
Peter Norvig Peter Norvig (born December 14, 1956) is an American computer scientist and Distinguished Education Fellow at the Stanford Institute for Human-Centered AI. He previously served as a director of research and search quality at Google. Norvig is t ...
observe that most AI researchers "don't care about the hilosophy of AI– as long as the program works, they don't care whether you call it a simulation of intelligence or real intelligence." However, the question has become central to the philosophy of mind. It is also typically the central question at issue in artificial intelligence in fiction.


Consciousness

David Chalmers David John Chalmers (; born 20 April 1966) is an Australian philosopher and cognitive scientist specializing in the areas of philosophy of mind and philosophy of language. He is a professor of philosophy and neural science at New York Univers ...
identified two problems in understanding the mind, which he named the "hard" and "easy" problems of consciousness. The easy problem is understanding how the brain processes signals, makes plans and controls behavior. The hard problem is explaining how this ''feels'' or why it should feel like anything at all. Human information processing is easy to explain, however, human subjective experience is difficult to explain. For example, it is easy to imagine a color-blind person who has learned to identify which objects in their field of view are red, but it is not clear what would be required for the person to ''know what red looks like''.


Computationalism and functionalism

Computationalism is the position in the philosophy of mind that the human mind is an information processing system and that thinking is a form of computing. Computationalism argues that the relationship between mind and body is similar or identical to the relationship between software and hardware and thus may be a solution to the mind-body problem. This philosophical position was inspired by the work of AI researchers and cognitive scientists in the 1960s and was originally proposed by philosophers
Jerry Fodor Jerry Alan Fodor (; April 22, 1935 – November 29, 2017) was an American philosopher and the author of many crucial works in the fields of philosophy of mind and cognitive science. His writings in these fields laid the groundwork for the modul ...
and Hilary Putnam. Philosopher John Searle characterized this position as "strong AI": "The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds." Searle counters this assertion with his Chinese room argument, which attempts to show that, even if a machine perfectly simulates human behavior, there is still no reason to suppose it also has a mind. Searle's Chinese room argument: * . Searle's original presentation of the thought experiment. * . Discussion: * * *


Robot rights

If a machine has a mind and subjective experience, then it may also have sentience (the ability to feel), and if so, then it could also ''suffer'', and thus it would be entitled to certain rights. Any hypothetical robot rights would lie on a spectrum with
animal rights Animal rights is the philosophy according to which many or all Animal consciousness, sentient animals have moral worth that is independent of their Utilitarianism, utility for humans, and that their most basic interests—such as avoiding s ...
and human rights. This issue has been considered in fiction for centuries, and is now being considered by, for example, California's
Institute for the Future The Institute for the Future (IFTF) is a Palo Alto, California, US–based not-for-profit think tank. It was established, in 1968, as a spin-off from the RAND Corporation to help organizations plan for the long-term future, a subject known as ...
; however, critics argue that the discussion is premature.


Future


Superintelligence

A superintelligence, hyperintelligence, or superhuman intelligence, is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind. ''Superintelligence'' may also refer to the form or degree of intelligence possessed by such an agent. If research into
artificial general intelligence Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fictio ...
produced sufficiently intelligent software, it might be able to reprogram and improve itself. The improved software would be even better at improving itself, leading to
recursive self-improvement The technological singularity—or simply the singularity—is a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization. According to the m ...
. Its intelligence would increase exponentially in an intelligence explosion and could dramatically surpass humans. Science fiction writer
Vernor Vinge Vernor Steffen Vinge (; born October 2, 1944) is an American science fiction author and retired professor. He taught mathematics and computer science at San Diego State University. He is the first wide-scale popularizer of the technological singu ...
named this scenario the "singularity". Because it is difficult or impossible to know the limits of intelligence or the capabilities of superintelligent machines, the technological singularity is an occurrence beyond which events are unpredictable or even unfathomable. Robot designer
Hans Moravec Hans Peter Moravec (born November 30, 1948, Kautzen, Austria) is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University in Pittsburgh, USA. He is known for his work on robotics, artificial intelligence, and writings ...
, cyberneticist Kevin Warwick, and inventor
Ray Kurzweil Raymond Kurzweil ( ; born February 12, 1948) is an American computer scientist, author, inventor, and futurist. He is involved in fields such as optical character recognition (OCR), text-to-speech synthesis, speech recognition technology, and e ...
have predicted that humans and machines will merge in the future into
cyborg A cyborg ()—a portmanteau of ''cybernetic'' and ''organism''—is a being with both organic and biomechatronic body parts. The term was coined in 1960 by Manfred Clynes and Nathan S. Kline.
s that are more capable and powerful than either. This idea, called transhumanism, has roots in
Aldous Huxley Aldous Leonard Huxley (26 July 1894 – 22 November 1963) was an English writer and philosopher. He wrote nearly 50 books, both novels and non-fiction works, as well as wide-ranging essays, narratives, and poems. Born into the prominent Huxle ...
and
Robert Ettinger Robert Chester Wilson Ettinger (December 4, 1918 – July 23, 2011) was an American academic, known as "the father of cryonics" because of the impact of his 1962 book ''The Prospect of Immortality''. Ettinger founded the Cryonics Institute ...
.
Edward Fredkin Edward Fredkin (born October 2, 1934) is a distinguished career professor at Carnegie Mellon University (CMU), and an early pioneer of digital physics. Fredkin's primary contributions include work on reversible computing and cellular automata. ...
argues that "artificial intelligence is the next stage in evolution", an idea first proposed by Samuel Butler's " Darwin among the Machines" as far back as 1863, and expanded upon by George Dyson in his book of the same name in 1998.


Risks


Technological unemployment

In the past, technology has tended to increase rather than reduce total employment, but economists acknowledge that "we're in uncharted territory" with AI. A survey of economists showed disagreement about whether the increasing use of robots and AI will cause a substantial increase in long-term unemployment, but they generally agree that it could be a net benefit if
productivity Productivity is the efficiency of production of goods or services expressed by some measure. Measurements of productivity are often expressed as a ratio of an aggregate output to a single input or an aggregate input used in a production proces ...
gains are redistributed. Subjective estimates of the risk vary widely; for example, Michael Osborne and
Carl Benedikt Frey Carl Benedikt Frey is a Swedish-German economist and economic historian. He is Oxford Martin Citi Fellow at Oxford University where he directs the programme on the Future of Work at the Oxford Martin School. Career After studying economics, his ...
estimate 47% of U.S. jobs are at "high risk" of potential automation, while an OECD report classifies only 9% of U.S. jobs as "high risk". Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; ''
The Economist ''The Economist'' is a British weekly newspaper printed in demitab format and published digitally. It focuses on current affairs, international business, politics, technology, and culture. Based in London, the newspaper is owned by The Eco ...
'' states that "the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution" is "worth taking seriously". Jobs at extreme risk range from paralegals to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy.


Bad actors and weaponized AI

AI provides a number of tools that are particularly useful for authoritarian governments: smart spyware, face recognition and voice recognition allow widespread surveillance; such surveillance allows
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
to classify potential enemies of the state and can prevent them from hiding; recommendation systems can precisely target propaganda and
misinformation Misinformation is incorrect or misleading information. It differs from disinformation, which is ''deliberately'' deceptive. Rumors are information not attributed to any particular source, and so are unreliable and often unverified, but can turn ...
for maximum effect; deepfakes aid in producing misinformation; advanced AI can make centralized decision making more competitive with liberal and decentralized systems such as markets. Terrorists, criminals and rogue states may use other forms of weaponized AI such as advanced digital warfare and
lethal autonomous weapon Lethal autonomous weapons (LAWs) are a type of autonomous military system that can independently search for and engage targets based on programmed constraints and descriptions. LAWs are also known as lethal autonomous weapon systems (LAWS), auto ...
s. By 2015, over fifty countries were reported to be researching battlefield robots. Machine-learning AI is also able to design tens of thousands of toxic molecules in a matter of hours.


Algorithmic bias

AI programs can become biased after learning from real-world data. It is not typically introduced by the system designers but is learned by the program, and thus the programmers are often unaware that the bias exists. Bias can be inadvertently introduced by the way
training data In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from ...
is selected. It can also emerge from
correlations In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics ...
: AI is used to classify individuals into groups and then make predictions assuming that the individual will resemble other members of the group. In some cases, this assumption may be unfair. An example of this is COMPAS, a commercial program widely used by U.S. courts to assess the likelihood of a defendant becoming a recidivist.
ProPublica ProPublica (), legally Pro Publica, Inc., is a nonprofit organization based in New York City. In 2010, it became the first online news source to win a Pulitzer Prize, for a piece written by one of its journalists''The Guardian'', April 13, 2010P ...
claims that the COMPAS-assigned recidivism risk level of black defendants is far more likely to be overestimated than that of white defendants, despite the fact that the program was not told the races of the defendants. Other examples where algorithmic bias can lead to unfair outcomes are when AI is used for
credit rating A credit rating is an evaluation of the credit risk of a prospective debtor (an individual, a business, company or a government), predicting their ability to pay back the debt, and an implicit forecast of the likelihood of the debtor defaulting. ...
or hiring. At its 2022 Conference on Fairness, Accountability, and Transparency (ACM FAccT 2022) the Association for Computing Machinery, in Seoul, South Korea, presented and published findings recommending that until AI and robotics systems are demonstrated to be free of bias mistakes, they are unsafe and the use of self-learning neural networks trained on vast, unregulated sources of flawed internet data should be curtailed.


Existential risk

Superintelligent AI may be able to improve itself to the point that humans could not control it. This could, as physicist Stephen Hawking puts it, " spell the end of the human race". Philosopher Nick Bostrom argues that sufficiently intelligent AI, if it chooses actions based on achieving some goal, will exhibit convergent behavior such as acquiring resources or protecting itself from being shut down. If this AI's goals do not fully reflect humanity's, it might need to harm humanity to acquire more resources or prevent itself from being shut down, ultimately to better achieve its goal. He concludes that AI poses a risk to mankind, however humble or " friendly" its stated goals might be. Political scientist Charles T. Rubin argues that "any sufficiently advanced benevolence may be indistinguishable from malevolence." Humans should not assume machines or robots would treat us favorably because there is no ''a priori'' reason to believe that they would share our system of morality. The opinion of experts and industry insiders is mixed, with sizable fractions both concerned and unconcerned by risk from eventual superhumanly-capable AI. Stephen Hawking, Microsoft founder Bill Gates, history professor Yuval Noah Harari, and SpaceX founder Elon Musk have all expressed serious misgivings about the future of AI. Prominent tech titans including
Peter Thiel Peter Andreas Thiel (; born 11 October 1967) is a German-American billionaire entrepreneur, venture capitalist, and political activist. A co-founder of PayPal, Palantir Technologies, and Founders Fund, he was the first outside investor in F ...
(
Amazon Web Services Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide d ...
) and Musk have committed more than $1 billion to nonprofit companies that champion responsible AI development, such as
OpenAI OpenAI is an artificial intelligence (AI) research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company conducts research in the field of AI with the stated goal of promo ...
and the Future of Life Institute. Mark Zuckerberg (CEO, Facebook) has said that artificial intelligence is helpful in its current form and will continue to assist humans. Other experts argue is that the risks are far enough in the future to not be worth researching, or that humans will be valuable from the perspective of a superintelligent machine.
Rodney Brooks Rodney Allen Brooks (born 30 December 1954) is an Australian roboticist, Fellow of the Australian Academy of Science, author, and robotics entrepreneur, most known for popularizing the actionist approach to robotics. He was a Panasonic Profes ...
, in particular, has said that "malevolent" AI is still centuries away.


Copyright

AI's decisions making abilities raises the questions of legal responsibility and copyright status of created works. This issues are being refined in various jurisdictions.


Ethical machines

Friendly AI are machines that have been designed from the beginning to minimize risks and to make choices that benefit humans.
Eliezer Yudkowsky Eliezer Shlomo Yudkowsky (born September 11, 1979) is an American decision theory and artificial intelligence (AI) researcher and writer, best known for popularizing the idea of friendly artificial intelligence. He is a co-founder and research ...
, who coined the term, argues that developing friendly AI should be a higher research priority: it may require a large investment and it must be completed before AI becomes an existential risk. Machines with intelligence have the potential to use their intelligence to make ethical decisions. The field of machine ethics provides machines with ethical principles and procedures for resolving ethical dilemmas. Machine ethics is also called machine morality, computational ethics or computational morality, and was founded at an
AAAI The Association for the Advancement of Artificial Intelligence (AAAI) is an international scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artif ...
symposium in 2005. Other approaches include Wendell Wallach's "artificial moral agents" and
Stuart J. Russell Stuart Jonathan Russell (born 1962) is a British computer scientist known for his contributions to artificial intelligence (AI). He is a professor of computer science at the University of California, Berkeley and was from 2008 to 2011 an adjunct ...
's three principles for developing provably beneficial machines.


Regulation

The regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI); it is therefore related to the broader regulation of algorithms. The regulatory and policy landscape for AI is an emerging issue in jurisdictions globally. Between 2016 and 2020, more than 30 countries adopted dedicated strategies for AI. Most EU member states had released national AI strategies, as had Canada, China, India, Japan, Mauritius, the Russian Federation, Saudi Arabia, United Arab Emirates, US and Vietnam. Others were in the process of elaborating their own AI strategy, including Bangladesh, Malaysia and Tunisia. The
Global Partnership on Artificial Intelligence The Global Partnership on Artificial Intelligence (GPAI, or "''gee-pay"'') is an international and multi-stakeholder initiative that aims to advance the responsible and human-centric development and use of artificial intelligence. Specifically, G ...
was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology.
Henry Kissinger Henry Alfred Kissinger (; ; born Heinz Alfred Kissinger, May 27, 1923) is a German-born American politician, diplomat, and geopolitical consultant who served as United States Secretary of State and National Security Advisor under the presid ...
, Eric Schmidt, and Daniel Huttenlocher published a joint statement in November 2021 calling for a government commission to regulate AI.


In fiction

Thought-capable artificial beings have appeared as storytelling devices since antiquity, and have been a persistent theme in
science fiction Science fiction (sometimes shortened to Sci-Fi or SF) is a genre of speculative fiction which typically deals with imaginative and futuristic concepts such as advanced science and technology, space exploration, time travel, parallel uni ...
. A common trope in these works began with
Mary Shelley Mary Wollstonecraft Shelley (; ; 30 August 1797 – 1 February 1851) was an English novelist who wrote the Gothic novel '' Frankenstein; or, The Modern Prometheus'' (1818), which is considered an early example of science fiction. She also ...
's '' Frankenstein'', where a human creation becomes a threat to its masters. This includes such works as Arthur C. Clarke's and Stanley Kubrick's '' 2001: A Space Odyssey'' (both 1968), with HAL 9000, the murderous computer in charge of the ''
Discovery One The United States Spacecraft ''Discovery One'' is a fictional spaceship featured in the first two novels of the ''Space Odyssey'' series by Arthur C. Clarke and in the films '' 2001: A Space Odyssey'' (1968) directed by Stanley Kubrick and '' 20 ...
'' spaceship, as well as '' The Terminator'' (1984) and ''
The Matrix ''The Matrix'' is a 1999 science fiction action film written and directed by the Wachowskis. It is the first installment in ''The Matrix'' film series, starring Keanu Reeves, Laurence Fishburne, Carrie-Anne Moss, Hugo Weaving, and Joe Pantolia ...
'' (1999). In contrast, the rare loyal robots such as Gort from '' The Day the Earth Stood Still'' (1951) and Bishop from '' Aliens'' (1986) are less prominent in popular culture. Isaac Asimov introduced the
Three Laws of Robotics The Three Laws of Robotics (often shortened to The Three Laws or known as Asimov's Laws) are a set of rules devised by science fiction author Isaac Asimov. The rules were introduced in his 1942 short story " Runaround" (included in the 1950 colle ...
in many books and stories, most notably the "Multivac" series about a super-intelligent computer of the same name. Asimov's laws are often brought up during lay discussions of machine ethics; while almost all artificial intelligence researchers are familiar with Asimov's laws through popular culture, they generally consider the laws useless for many reasons, one of which is their ambiguity. Transhumanism (the merging of humans and machines) is explored in the manga ''
Ghost in the Shell ''Ghost in the Shell'' is a Japanese cyberpunk media franchise based on the seinen manga series of the same name written and illustrated by Masamune Shirow. The manga, first serialized in 1989 under the subtitle of ''The Ghost in the Shell'' ...
'' and the science-fiction series '' Dune''. Several works use AI to force us to confront the fundamental question of what makes us human, showing us artificial beings that have the ability to feel, and thus to suffer. This appears in
Karel Čapek Karel Čapek (; 9 January 1890 – 25 December 1938) was a Czech writer, playwright and critic. He has become best known for his science fiction, including his novel '' War with the Newts'' (1936) and play '' R.U.R.'' (''Rossum's Universal ...
's '' R.U.R.'', the films ''
A.I. Artificial Intelligence ''A.I. Artificial Intelligence'' (also known as ''A.I.'') is a 2001 American science fiction film directed by Steven Spielberg. The screenplay by Spielberg and screen story by Ian Watson were based on the 1969 short story "Supertoys Last All ...
'' and '' Ex Machina'', as well as the novel ''
Do Androids Dream of Electric Sheep? ''Do Androids Dream of Electric Sheep?'' (retroactively retitled ''Blade Runner: Do Androids Dream of Electric Sheep?'' in some later printings) is a dystopian science fiction novel by American writer Philip K. Dick, first published in 1968. Th ...
'', by Philip K. Dick. Dick considers the idea that our understanding of human subjectivity is altered by technology created with artificial intelligence.


Scientific diplomacy


Warfare

As technology and research evolve and the world enters the third revolution of warfare following gunpowder and nuclear weapons, the artificial intelligence arms race ensues between the United States, China, and Russia, three countries with the world's top five highest military budgets. Intentions of being a world leader in AI research by 2030 have been declared by China's leader Xi Jinping, and President Putin of Russia has stated that "Whoever becomes the leader in this sphere will become the ruler of the world". If Russia were to become the leader in AI research, President Putin has stated Russia's intent to share some of their research with the world so as to not monopolize the field, similar to their current sharing of nuclear technologies, maintaining science diplomacy relations. The United States, China, and Russia, are some examples of countries that have taken their stances toward military artificial intelligence since as early as 2014, having established military programs to develop cyber weapons, control lethal autonomous weapons, and drones that can be used for surveillance.


Russo-Ukrainian War

President Putin announced that artificial intelligence is the future for all mankind and recognizes the power and opportunities that the development and deployment of lethal autonomous weapons AI technology can hold in warfare and homeland security, as well as its threats. President Putin's prediction that future wars will be fought using AI has started to come to fruition to an extent after Russia invaded Ukraine on 24 February 2022.  The Ukrainian military is making use of the Turkish Bayraktar TB2-drones that still require human operation to deploy laser-guided bombs but can take off, land, and cruise autonomously. Ukraine has also been using Switchblade drones supplied by the US and receiving information gathering by the United States's own surveillance operations regarding battlefield intelligence and national security about Russia. Similarly, Russia can use AI to help analyze battlefield data from surveillance footage taken by drones. Reports and images show that Russia's military has deployed KUB- BLA suicide drones into Ukraine, with speculations of intentions to assassinate Ukrainian President Volodymyr Zelenskyy.


Warfare regulations

As research in the AI realm progresses, there is pushback about the use of AI from the
Campaign to Stop Killer Robots The Campaign to Stop Killer Robots is a coalition of non-governmental organizations who seek to pre-emptively ban lethal autonomous weapons. History First launched in April 2013, the Campaign to Stop Killer Robots has urged governments and the Un ...
and world technology leaders have sent a petition to the United Nations calling for new regulations on the development and use of AI technologies in 2017, including a ban on the use of
lethal autonomous weapon Lethal autonomous weapons (LAWs) are a type of autonomous military system that can independently search for and engage targets based on programmed constraints and descriptions. LAWs are also known as lethal autonomous weapon systems (LAWS), auto ...
s due to ethical concerns for innocent civilian populations.


Cybersecurity

With the ever evolving cyber-attacks and generation of devices, AI can be used for threat detection and more effective response by risk prioritization. With this tool, some challenges are also presented such as privacy, informed consent, and responsible use. According to CISA, the cyberspace is difficult to secure for the following factors: the ability of malicious actors to operate from anywhere in the world, the linkages between cyberspace and physical systems, and the difficulty of reducing vulnerabilities and consequences in complex cyber networks. With the increased technological advances of the world, the risk for wide scale consequential events rises. Paradoxically, the ability to protect information and create a line of communication between the scientific and diplomatic community thrives. The role of cybersecurity in diplomacy has become increasingly relevant, creating the term of cyber diplomacy – which is not uniformly defined and not synonymous with cyber defence. Many nations have developed unique approaches to scientific diplomacy in cyberspace.


Czech Republic's approach

Dating back to 2011, when the Czech National Security Authority (NSA) was appointed as the national authority for the cyber agenda. The role of cyber diplomacy strengthened in 2017 when the Czech Ministry of Foreign Affairs (MFA) detected a serious cyber campaign directed against its own computer networks. In 2016, three cyber diplomats were deployed to Washington, D.C., Brussels and Tel Aviv, with the goal of establishing active international cooperation focused on engagement with the EU and
NATO The North Atlantic Treaty Organization (NATO, ; french: Organisation du traité de l'Atlantique nord, ), also called the North Atlantic Alliance, is an intergovernmental military alliance between 30 member states – 28 European and two No ...
. The main agenda for these scientific diplomacy efforts is to bolster research on artificial intelligence and how it can be used in cybersecurity research, development, and overall consumer trust. CzechInvest is a key stakeholder in scientific diplomacy and cybersecurity. For example, in September 2018, they organized a mission to Canada in September 2018 with a special focus on artificial intelligence. The main goal of this particular mission was a promotional effort on behalf of Prague, attempting to establish it as a future knowledge hub for the industry for interested Canadian firms.


Germany's approach

Cybersecurity is recognized as a governmental task, dividing into three ministries of responsibility: the Federal Ministry of the Interior, the Federal Ministry of Defence, and the Federal Foreign Office. These distinctions promoted the creation of various institutions, such as The German National Office for Information Security, The National Cyberdefence Centre, The German National Cyber Security Council, and The Cyber and Information Domain Service. In 2018, a new strategy for artificial intelligence was established by the German government, with the creation of a German-French virtual research and innovation network, holding opportunity for research expansion into cybersecurity.


European Union's approach

The adoption of ''The Cybersecurity Strategy of the European Union – An Open, Safe and Secure Cyberspace'' document in 2013 by the European commission pushed forth cybersecurity efforts integrated with scientific diplomacy and artificial intelligence. Efforts are strong, as the EU funds various programs and institutions in the effort to bring science to diplomacy and bring diplomacy to science. Some examples are the cyber security programme Competence Research Innovation (CONCORDIA), which brings together 14 member states, and Cybersecurity for Europe (CSE), which brings together 43 partners involving 20 member states. In addition, The European Network of Cybersecurity Centres and Competence Hub for Innovation and Operations (ECHO) gathers 30 partners with 15 member states and SPARTA gathers 44 partners involving 14 member states. These efforts reflect the overall goals of the EU, to innovate cybersecurity for defense and protection, establish a highly integrated cyberspace among many nations, and further contribute to the security of artificial intelligence.


Russo-Ukrainian War

With the 2022 invasion of Ukraine, there has been a rise in malicious cyber activity against the United States, Ukraine, and Russia. A prominent and rare documented use of artificial intelligence in conflict is on behalf of Ukraine, using facial recognition software to uncover Russian assailants and identify Ukrainians killed in the ongoing war. Though these governmental figures are not primarily focused on scientific and cyber diplomacy, other institutions are commenting on the use of artificial intelligence in cybersecurity with that focus. For example, Georgetown University's Center for Security and Emerging Technology (CSET) has the Cyber-AI Project, with one goal being to attract policymakers' attention to the growing body of academic research, which exposes the exploitive consequences of AI and machine-learning (ML) algorithms. This vulnerability can be a plausible explanation as to why Russia is not engaging in the use of AI in conflict per, Andrew Lohn, a senior fellow at CSET. In addition to use on the battlefield, AI is being used by the Pentagon to analyze data from the war, analyzing to strengthen cybersecurity and warfare intelligence for the United States.


Election security

As artificial intelligence grows and the overwhelming amount of news portrayed through cyberspace expands, it is becoming extremely overwhelming for a voter to know what to believe. There are many intelligent codes, referred to as bots, written to portray people on social media with the goal of spreading misinformation. The 2016 US election is a victim of such actions. During the
Hillary Clinton Hillary Diane Rodham Clinton ( Rodham; born October 26, 1947) is an American politician, diplomat, and former lawyer who served as the 67th United States Secretary of State for President Barack Obama from 2009 to 2013, as a United States sen ...
and
Donald Trump Donald John Trump (born June 14, 1946) is an American politician, media personality, and businessman who served as the 45th president of the United States from 2017 to 2021. Trump graduated from the Wharton School of the University of P ...
campaign, artificial intelligent bots from Russia were spreading misinformation about the candidates in order to help the Trump campaign. Analysts concluded that approximately 19% of
Twitter Twitter is an online social media and social networking service owned and operated by American company Twitter, Inc., on which users post and interact with 280-character-long messages known as "tweets". Registered users can post, like, and ...
tweets centered around the 2016 election were detected to come from bots.
YouTube YouTube is a global online video sharing and social media platform headquartered in San Bruno, California. It was launched on February 14, 2005, by Steve Chen, Chad Hurley, and Jawed Karim. It is owned by Google, and is the second mo ...
in recent years has been used to spread political information as well. Although there is no proof that the platform attempts to manipulate its viewers opinions, Youtubes AI algorithm recommends videos of similar variety. If a person begins to research
right wing Right-wing politics describes the range of Ideology#Political ideologies, political ideologies that view certain social orders and Social stratification, hierarchies as inevitable, natural, normal, or desirable, typically supporting this pos ...
political podcasts, then YouTube's algorithm will recommend more right wing videos. The uprising in a program called Deepfake, a software used to replicate someone's face and words, has also shown its potential threat. In 2018 a Deepfake video of
Barack Obama Barack Hussein Obama II ( ; born August 4, 1961) is an American politician who served as the 44th president of the United States from 2009 to 2017. A member of the Democratic Party, Obama was the first African-American president of the ...
was released saying words he claims to have never said. While in a national election a Deepfake will quickly be debunked, the software has the capability to heavily sway a smaller local election. This tool holds a lot of potential for spreading misinformation and is monitored with great attention. Although it may be seen as a tool used for harm, AI can help enhance election campaigns as well. AI bots can be programed to target articles with known misinformation. The bots can then indicate what is being misinformed to help shine light on the truth. AI can also be used to inform a person where each parts stands on a certain topic such as healthcare or
climate change In common usage, climate change describes global warming—the ongoing increase in global average temperature—and its effects on Earth's climate system. Climate change in a broader sense also includes previous long-term changes to ...
. The political leaders of a nation have heavy sway on international affairs. Thus, a political leader with a lack of interest for international collaborative scientific advancement can have a negative impact in the scientific diplomacy of that nation


Future of work


Facial recognition

The use of artificial intelligence (AI) has subtly grown to become part of everyday life. It is used every day in facial recognition software. It is the first measure of security for many companies in the form of a biometric authentication. This means of authentication allows even the most official organizations such as the United States Internal Revenue Service to verify a person's identity via a database generated from machine learning. As of the year 2022, the United States IRS requires those who do not undergo a live interview with an agent to complete a biometric verification of their identity via ID.me's facial recognition tool.


AI and school

In Japan and South Korea, artificial intelligence software is used in the instruction of English language via the company Riiid. Riiid is a Korean education company working alongside Japan to give students the means to learn and use their English communication skills via engaging with artificial intelligence in a live chat. Riid is not the only company to do this. American company Duolingo is well known for their automated teaching of 41 languages. Babbel, a German language learning program, also uses artificial intelligence in its teaching automation, allowing for European students to learn vital communication skills needed in social, economic, and diplomatic settings. Artificial intelligence will also automate the routine tasks that teachers need to do such as grading, taking attendance, and handling routine student inquiries. This enables the teacher to carry on with the complexities of teaching that an automated machine cannot handle. These include creating exams, explaining complex material in a way that will benefit students individually and handling unique questions from students.


AI and medicine

Unlike the human brain, which possess generalized intelligence, the specialized intelligence of AI can serve as a means of support to physicians internationally. The medical field has a diverse and profound amount of data in which AI can employ to generate a predictive diagnosis. Researchers at an Oxford hospital have developed artificial intelligence that can diagnose heart scans for heart disease and cancer. This artificial intelligence can pick up diminutive details in the scans that doctors may miss. As such, artificial intelligence in medicine will better the industry, giving doctors the means to precisely diagnose their patients using the tools available. The artificial intelligence algorithms will also be used to further improve diagnosis over time, via an application of machine learning called precision medicine. Furthermore, the narrow application of artificial intelligence can use " deep learning" in order to improve medical image analysis. In radiology imaging, AI uses deep learning algorithms to identify potentially cancerous lesions which is an important process assisting in early diagnosis.


AI in business

Data analysis is a fundamental property of artificial intelligence that enables it to be used in every facet of life from search results to the way people buy product. According to NewVantage Partners, over 90% of top businesses have ongoing investments in artificial intelligence. According to IBM, one of the world's leaders in technology, 45% of respondents from companies with over 1,000 employees have adopted AI. Recent data shows that the business market for artificial intelligence during the year 2020 was valued at $51.08 billion. The business market for artificial intelligence is projected to be over $640.3 billion by the year 2028. To prevent harm, AI-deploying organizations need to play a central role in creating and deploying trustworthy AI in line with the principles of trustworthy AI, and take accountability to mitigate the risks.


Business and diplomacy

With the exponential surge of artificial technology and communication, the distribution of one's ideals and values has been evident in daily life. Digital information is spread via communication apps such as Whatsapp, Facebook/Meta, Snapchat, Instagram and Twitter. However, it is known that these sites relay specific information corresponding to data analysis. If a right-winged individual were to do a google search, Google's algorithms would target that individual and relay data pertinent to that target audience. US President Bill Clinton noted in 2000:"In the new century, liberty will spread by cell phone and cable modem. ..We know how much the Internet has changed America, and we are already an open society. However, when the private sector uses artificial intelligence to gather data, a shift in power from the state to the private sector may be seen. This shift in power, specifically in large technological corporations, could profoundly change how diplomacy functions in society. The rise in digital technology and usage of artificial technology enabled the private sector to gather immense data on the public, which is then further categorized by race, location, age, gender, etc. ''The New York Times'' calculates that "the ten largest tech firms, which have become gatekeepers in commerce, finance, entertainment and communications, now have a combined market capitalization of more than $10 trillion. In gross domestic product terms, that would rank them as the world's third-largest economy." Beyond the general lobbying of congressmen/congresswomen, companies such as Facebook/Meta or Google use collected data in order to reach their intended audiences with targeted information.


AI and foreign policy

Multiple nations around the globe employ artificial intelligence to assist with their foreign policy decisions. The Chinese Department of External Security Affairs – under the Ministry of Foreign Affairs – uses AI to review almost all its foreign investment projects for risk mitigation. The government of China plans to use artificial intelligence in its $900 billion global infrastructure development plan, called the "Belt and Road Initiative" for political, economic, and environmental risk alleviation. Over 200 applications of artificial intelligence are being used by over 46 United Nations agencies, in sectors ranging from health care dealing with issues such as combating COVID-19 to smart agriculture, to assist the UN in political and diplomatic relations. One example is the use of AI by the UN Global Pulse program to model the effect of the spread of COVID-19 on internally displaced people (IDP) and refugee settlements to assist them in creating an appropriate global health policy. Novel AI tools such as remote sensing can also be employed by diplomats for collecting and analyzing data and near-real-time tracking of objects such as troop or refugee movements along borders in violent conflict zones. Artificial intelligence can be used to mitigate vital cross-national diplomatic talks to prevent translation errors caused by human translators. A major example is the 2021 Anchorage meetings held between US and China aimed at stabilizing foreign relations, only for it to have the opposite effect, increasing tension and aggressiveness between the two nations, due to translation errors caused by human translators. In the meeting, when United States National Security Advisor to President Joe Biden, Jacob Jeremiah Sullivan stated, "We do not seek conflict, but we welcome stiff competition and we will always stand up for our principles, for our people, and for our friends", it was mistranslated into Chinese as "we will face competition between us, and will present our stance in a very clear manner", adding an aggressive tone to the speech. AI's ability for fast and efficient natural language processing and real-time translation and transliteration makes it an important tool for foreign-policy communication between nations and prevents unintended mistranslation.


See also

* '' A.I. Rising'' * AI alignment * Artificial intelligence arms race * Artificial philosophy * Behavior selection algorithm * Business process automation *
Case-based reasoning In artificial intelligence and philosophy, case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. In everyday life, an auto mechanic who fixes an engine by recallin ...
* Emergent algorithm * Female gendering of AI technologies * Glossary of artificial intelligence * Robotic process automation * Synthetic intelligence * Universal basic income * Weak artificial intelligence * Operations research


Explanatory notes


References


AI textbooks

These were the four the most widely used AI textbooks in 2008: * * * . * Later editions. * . * The two most widely used textbooks in 202
Open Syllabus: Explorer
* *


History of AI

* . * . * *


Other sources

* * * * * * was introduced by
Kunihiko Fukushima Kunihiko Fukushima ( Japanese: 福島 邦彦, born 16 March 1936) is a Japanese computer scientist, most noted for his work on artificial neural networks and deep learning. He is currently working part-time as a Senior Research Scientist at the F ...
in 1980. * * * * * * * * * * * * * * * * * * * * * * * , * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * . * Presidential Address to the
Association for the Advancement of Artificial Intelligence The Association for the Advancement of Artificial Intelligence (AAAI) is an international scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artif ...
. * * * * * * Later published as
* * * * * . * * * *


Further reading

* Autor, David H., "Why Are There Still So Many Jobs? The History and Future of Workplace Automation" (2015) 29(3) ''Journal of Economic Perspectives'' 3. * Boden, Margaret, ''Mind As Machine'',
Oxford University Press Oxford University Press (OUP) is the university press of the University of Oxford. It is the largest university press in the world, and its printing history dates back to the 1480s. Having been officially granted the legal right to print books ...
, 2006. * Cukier, Kenneth, "Ready for Robots? How to Think about the Future of AI", '' Foreign Affairs'', vol. 98, no. 4 (July/August 2019), pp. 192–98. George Dyson, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist Alex Pentland writes: "Current AI machine-learning
algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...
s are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.) * Domingos, Pedro, "Our Digital Doubles: AI will serve our species, not control it", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 319, no. 3 (September 2018), pp. 88–93. * Gopnik, Alison, "Making AI More Human: Artificial intelligence has staged a revival by starting to incorporate what we know about how children learn", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 316, no. 6 (June 2017), pp. 60–65. * Halpern, Sue, "The Human Costs of AI" (review of Kate Crawford, ''Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence'', Yale University Press, 2021, 327 pp.;
Simon Chesterman Simon Chesterman is an Australian legal academic and writer who is currently vice-provost at the National University of Singapore (NUS) and dean of the NUS's Faculty of Law and NUS College. He is also a senior director for AI Governance at AI Si ...
, ''We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law'', Cambridge University Press, 2021, 289 pp.; Keven Roose, ''Futureproof: 9 Rules for Humans in the Age of Automation'', Random House, 217 pp.; Erik J. Larson, ''The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do'', Belknap Press / Harvard University Press, 312 pp.), ''
The New York Review of Books ''The New York Review of Books'' (or ''NYREV'' or ''NYRB'') is a semi-monthly magazine with articles on literature, culture, economics, science and current affairs. Published in New York City, it is inspired by the idea that the discussion of i ...
'', vol. LXVIII, no. 16 (21 October 2021), pp. 29–31. "AI training models can replicate entrenched social and cultural biases. ..Machines only know what they know from the
data In the pursuit of knowledge, data (; ) is a collection of discrete Value_(semiotics), values that convey information, describing quantity, qualitative property, quality, fact, statistics, other basic units of meaning, or simply sequences of sy ...
they have been given. . 30. tificial general intelligence–machine-based intelligence that matches our own–is beyond the capacity of
algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...
ic machine learning... 'Your brain is one piece in a broader system which includes your body, your environment, other humans, and culture as a whole.' en machines that master the tasks they are trained to perform can't jump domains. AIVA, for example, can't drive a car even though it can write music (and wouldn't even be able to do that without
Bach Johann Sebastian Bach (28 July 1750) was a German composer and musician of the late Baroque period. He is known for his orchestral music such as the ''Brandenburg Concertos''; instrumental compositions such as the Cello Suites; keyboard wor ...
and Beethoven nd other composers on which AIVA is trained." (p. 31.) * Johnston, John (2008) ''The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI'', MIT Press. * Koch, Christof, "Proust among the Machines", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 321, no. 6 (December 2019), pp. 46–49.
Christof Koch Christof Koch ( ; born November 13, 1956) is a German-American neurophysiologist and computational neuroscientist best known for his work on the neural basis of consciousness. He is the president and chief scientist of the Allen Institute for B ...
doubts the possibility of "intelligent" machines attaining
consciousness Consciousness, at its simplest, is sentience and awareness of internal and external existence. However, the lack of definitions has led to millennia of analyses, explanations and debates by philosophers, theologians, linguisticians, and scien ...
, because " en the most sophisticated brain simulations are unlikely to produce conscious feelings." (p. 48.) According to Koch, "Whether machines can become sentient s importantfor
ethical Ethics or moral philosophy is a branch of philosophy that "involves systematizing, defending, and recommending concepts of right and wrong behavior".''Internet Encyclopedia of Philosophy'' The field of ethics, along with aesthetics, concerns ma ...
reasons. If computers experience life through their own senses, they cease to be purely a means to an end determined by their usefulness to... humans. Per GNW Global_Neuronal_Workspace_theory.html" ;"title="Global Workspace Theory#Global neuronal workspace">Global Neuronal Workspace theory">Global Workspace Theory#Global neuronal workspace">Global Neuronal Workspace theory they turn from mere objects into subjects... with a point of view.... Once computers' cognitive abilities rival those of humanity, their impulse to push for legal and political rights will become irresistible—the right not to be deleted, not to have their memories wiped clean, not to suffer pain and degradation. The alternative, embodied by IIT ntegrated Information Theory is that computers will remain only supersophisticated machinery, ghostlike empty shells, devoid of what we value most: the feeling of life itself." (p. 49.) * Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 316, no. 3 (March 2017), pp. 58–63. A stumbling block to AI has been an incapacity for reliable
disambiguation Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to consc ...
. An example is the "pronoun disambiguation problem": a machine has no way of determining to whom or what a pronoun in a sentence refers. (p. 61.) * Gary Marcus, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 327, no. 4 (October 2022), pp. 42–45. * E McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2018
SSRN, part 2(3)
. * George Musser, " Artificial Imagination: How machines could learn creativity and common sense, among other human qualities", ''
Scientific American ''Scientific American'', informally abbreviated ''SciAm'' or sometimes ''SA'', is an American popular science magazine. Many famous scientists, including Albert Einstein and Nikola Tesla, have contributed articles to it. In print since 1845, it ...
'', vol. 320, no. 5 (May 2019), pp. 58–63. * Myers, Courtney Boyd ed. (2009)
"The AI Report"
. ''Forbes'' June 2009 * * Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race", '' Foreign Affairs'', vol. 98, no. 3 (May/June 2019), pp. 135–44. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.) * * * * Sun, R. & Bookman, L. (eds.), ''Computational Architectures: Integrating Neural and Symbolic Processes''. Kluwer Academic Publishers, Needham, MA. 1994. * Taylor, Paul, "Insanely Complicated, Hopelessly Inadequate" (review of Brian Cantwell Smith, ''The Promise of Artificial Intelligence: Reckoning and Judgment'', MIT, 2019, , 157 pp.; Gary Marcus and Ernest Davis, ''Rebooting AI: Building Artificial Intelligence We Can Trust'', Ballantine, 2019, , 304 pp.; Judea Pearl and Dana Mackenzie, ''The Book of Why: The New Science of Cause and Effect'', Penguin, 2019, , 418 pp.), '' London Review of Books'', vol. 43, no. 2 (21 January 2021), pp. 37–39. Paul Taylor writes (p. 39): "Perhaps there is a limit to what a computer can do without knowing that it is manipulating imperfect representations of an external reality." * Tooze, Adam, "Democracy and Its Discontents", ''
The New York Review of Books ''The New York Review of Books'' (or ''NYREV'' or ''NYRB'') is a semi-monthly magazine with articles on literature, culture, economics, science and current affairs. Published in New York City, it is inspired by the idea that the discussion of i ...
'', vol. LXVI, no. 10 (6 June 2019), pp. 52–53, 56–57. "Democracy has no clear answer for the mindless operation of
bureaucratic The term bureaucracy () refers to a body of non-elected governing officials as well as to an administrative policy-making group. Historically, a bureaucracy was a government administration managed by departments staffed with non-elected offi ...
and technological power. We may indeed be witnessing its extension in the form of artificial intelligence and robotics. Likewise, after decades of dire warning, the environmental problem remains fundamentally unaddressed.... Bureaucratic overreach and environmental catastrophe are precisely the kinds of slow-moving existential challenges that democracies deal with very badly.... Finally, there is the threat du jour:
corporation A corporation is an organization—usually a group of people or a company—authorized by the state to act as a single entity (a legal entity recognized by private and public law "born out of statute"; a legal person in legal context) and ...
s and the technologies they promote." (pp. 56–57.)


External links

* *
Artificial Intelligence
BBC Radio 4 discussion with John Agar, Alison Adam & Igor Aleksander (''In Our Time'', 8 December 2005). {{Authority control Cybernetics Formal sciences Data science Computational neuroscience Emerging technologies Unsolved problems in computer science Computational fields of study