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Artificial general intelligence (AGI) is the ability of an
intelligent agent In artificial intelligence, an intelligent agent (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledge. They may be simple or c ...
to understand or learn any intellectual task that a
human being Humans (''Homo sapiens'') are the most abundant and widespread species of primate, characterized by bipedality, bipedalism and exceptional cognitive skills due to a large and complex Human brain, brain. This has enabled the development of ad ...
can. It is a primary goal of some
artificial intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech re ...
research and a common topic 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 unive ...
and
futures studies Futures studies, futures research, futurism or futurology is the systematic, interdisciplinary and holistic study of social and technological advancement, and other environmental trends, often for the purpose of exploring how people will li ...
. AGI is also called strong AI,: Kurzweil describes strong AI as "machine intelligence with the full range of human intelligence." full AI, or general intelligent action, although some academic sources reserve the term "strong AI" for computer programs that experience
sentience Sentience is the capacity to experience feelings and sensations. The word was first coined by philosophers in the 1630s for the concept of an ability to feel, derived from Latin '':wikt:sentientem, sentientem'' (a feeling), to distinguish it fro ...
or
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 ...
. Strong AI contrasts with ''
weak AI Weak artificial intelligence (weak AI) is artificial intelligence that implements a limited part of mind, or, as narrow AI, is focused on one narrow task. In John Searle, John Searle's terms it “would be useful for testing hypotheses about minds ...
'' (or ''narrow AI''), which is not intended to have general
cognitive Cognition refers to "the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, ...
abilities; rather, weak AI is any program that is designed to solve exactly one problem. (Academic sources reserve "weak AI" for programs that do not experience
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 ...
or do not have a
mind The mind is the set of faculties responsible for all mental phenomena. Often the term is also identified with the phenomena themselves. These faculties include thought, imagination, memory, will, and sensation. They are responsible for various m ...
in the same sense people do.) A 2020 survey identified 72 active AGI R&D projects spread across 37 countries.


Characteristics

Various criteria for
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 b ...
have been proposed (most famously the
Turing test The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to artificial intelligence, exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing propos ...
) but to date, there is no definition that satisfies everyone.


Intelligence traits

However, there ''is'' wide agreement among artificial intelligence researchers that intelligence is required to do the following: *
reason Reason is the capacity of consciously applying logic by drawing conclusions from new or existing information, with the aim of seeking the truth. It is closely associated with such characteristically human activities as philosophy, science, ...
, use strategy, solve puzzles, and make judgments under
uncertainty Uncertainty refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable or ...
; * represent knowledge, including
common sense knowledge In artificial intelligence research, commonsense knowledge consists of facts about the everyday world, such as "Lemons are sour", that all humans are expected to know. It is currently an unsolved problem in Artificial General Intelligence. The f ...
; *
plan A plan is typically any diagram or list of steps with details of timing and resources, used to achieve an objective to do something. It is commonly understood as a temporal set of intended actions through which one expects to achieve a goal. F ...
; *
learn Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, animals, and some machines; there is also evidence for some kind of learn ...
; * communicate in
natural language In neuropsychology, linguistics, and philosophy of language, a natural language or ordinary language is any language that has evolved naturally in humans through use and repetition without conscious planning or premeditation. Natural languages ...
; and integrate all these skills towards common goals. Other important capabilities include: * input as the ability to
sense A sense is a biological system used by an organism for sensation, the process of gathering information about the world through the detection of Stimulus (physiology), stimuli. (For example, in the human body, the brain which is part of the cen ...
(e.g.
see See or SEE may refer to: * Sight - seeing Arts, entertainment, and media * Music: ** ''See'' (album), studio album by rock band The Rascals *** "See", song by The Rascals, on the album ''See'' ** "See" (Tycho song), song by Tycho * Television * ...
, hear, etc.), and * output as the ability to act (e.g. move and manipulate objects, change own location to explore, etc.) in this world where intelligent behaviour is to be observed. This would include an ability to detect and respond to
hazard A hazard is a potential source of harm Harm is a moral and legal concept. Bernard Gert construes harm as any of the following: * pain * death * disability * mortality * loss of abil ity or freedom * loss of pleasure. Joel Feinberg giv ...
. Many
interdisciplinary Interdisciplinarity or interdisciplinary studies involves the combination of multiple academic disciplines into one activity (e.g., a research project). It draws knowledge from several other fields like sociology, anthropology, psychology, ec ...
approaches to intelligence (e.g. cognitive science,
computational intelligence The expression computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no c ...
and
decision making In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rati ...
) tend to emphasise the need to consider additional traits such as
imagination Imagination is the production or simulation of novel objects, sensations, and ideas in the mind without any immediate input of the senses. Stefan Szczelkun characterises it as the forming of experiences in one's mind, which can be re-creations ...
(taken as the ability to form mental images and concepts that were not programmed in) and
autonomy In developmental psychology and moral, political, and bioethical philosophy, autonomy, from , ''autonomos'', from αὐτο- ''auto-'' "self" and νόμος ''nomos'', "law", hence when combined understood to mean "one who gives oneself one's ...
. Computer based systems that exhibit many of these capabilities do exist (e.g. see
computational creativity Computational creativity (also known as artificial creativity, mechanical creativity, creative computing or creative computation) is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence, cogn ...
,
automated reasoning In computer science, in particular in knowledge representation and reasoning and metalogic, the area of automated reasoning is dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer progra ...
,
decision support system A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and h ...
,
robot A robot is a machine—especially one programmable by a computer—capable of carrying out a complex series of actions automatically. A robot can be guided by an external control device, or the control may be embedded within. Robots may be c ...
,
evolutionary computation In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms, they ...
,
intelligent agent In artificial intelligence, an intelligent agent (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledge. They may be simple or c ...
), but no one has created an integrated system that excels at all these areas.


Tests for confirming human-level AGI

The following tests to confirm human-level AGI have been considered: ;
The Turing Test The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluato ...
( ''Turing'') : A machine and a human both converse unseen with a second human, who must evaluate which of the two is the machine, which passes the test if it can fool the evaluator a significant fraction of the time. Note: Turing does not prescribe what should qualify as intelligence, only that knowing that it is a machine should disqualify it. ;The Coffee Test ( ''Wozniak'') : A machine is required to enter an average American home and figure out how to make coffee: find the coffee machine, find the coffee, add water, find a mug, and brew the coffee by pushing the proper buttons. ;The Robot College Student Test ( ''Goertzel'') : A machine enrolls in a university, taking and passing the same classes that humans would, and obtaining a degree. ;The Employment Test ( ''Nilsson'') : A machine performs an economically important job at least as well as humans in the same job.


AI-complete problems

There are many individual problems that may require general intelligence, if machines are to solve the problems as well as people do. For example, even specific straightforward tasks, like
machine translation Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates t ...
, require that a machine read and write in both languages ( NLP), follow the author's argument (
reason Reason is the capacity of consciously applying logic by drawing conclusions from new or existing information, with the aim of seeking the truth. It is closely associated with such characteristically human activities as philosophy, science, ...
), know what is being talked about (
knowledge Knowledge can be defined as awareness of facts or as practical skills, and may also refer to familiarity with objects or situations. Knowledge of facts, also called propositional knowledge, is often defined as true belief that is distinc ...
), and faithfully reproduce the author's original intent (
social intelligence Social intelligence is the capacity to know oneself and to know others. Social intelligence is learned and develops from experience with people and learning from success and failures in social settings. Social intelligence is the ability to underst ...
). All of these problems need to be solved simultaneously in order to reach human-level machine performance. A problem is informally known as "AI-complete" or "AI-hard", if solving it is equivalent to the general aptitude of human intelligence, or strong AI, and is beyond the capabilities of a purpose-specific algorithm. (Section 4 is on "AI-Complete Tasks".) AI-complete problems are hypothesised to include general
computer vision Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the hum ...
,
natural language understanding Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an ...
, and dealing with unexpected circumstances while solving any real-world problem. AI-complete problems cannot be solved with current computer technology alone, and require
human computation Human-based computation (HBC), human-assisted computation, ubiquitous human computing or distributed thinking (by analogy to distributed computing) is a computer science technique in which a machine performs its function by outsourcing certain ste ...
. This property could be useful, for example, to test for the presence of humans, as
CAPTCHA A CAPTCHA ( , a contrived acronym for "Completely Automated Public Turing test to tell Computers and Humans Apart") is a type of challenge–response test used in computing to determine whether the user is human. The term was coined in 2003 ...
s aim to do; and for
computer security Computer security, cybersecurity (cyber security), or information technology security (IT security) is the protection of computer systems and networks from attack by malicious actors that may result in unauthorized information disclosure, the ...
to repel
brute-force attack In cryptography, a brute-force attack consists of an attacker submitting many passwords or passphrases with the hope of eventually guessing correctly. The attacker systematically checks all possible passwords and passphrases until the correct ...
s.


Mathematical formalisms

A mathematically precise definition of AGI was proposed by
Marcus Hutter Marcus Hutter (born April 14, 1967 in Munich) is DeepMind Senior Scientist researching the mathematical foundations of artificial general intelligence. He is on leave from his professorship at the ANU College of Engineering and Computer Scie ...
in 2000. Named
AIXI AIXI is a theoretical mathematical formalism for artificial general intelligence. It combines Solomonoff induction with sequential decision theory. AIXI was first proposed by Marcus Hutter in 2000 and several results regarding AIXI are proved ...
, the proposed agent maximises “the ability to satisfy goals in a wide range of environments”. This type of AGI, characterized by proof of the ability to maximise a mathematical definition of intelligence rather than exhibit human-like behavior, is called universal artificial intelligence. In 2015 Jan Lieke and
Marcus Hutter Marcus Hutter (born April 14, 1967 in Munich) is DeepMind Senior Scientist researching the mathematical foundations of artificial general intelligence. He is on leave from his professorship at the ANU College of Engineering and Computer Scie ...
showed that "Legg-Hutter intelligence is measured with respect to a fixed UTM. AIXI is the most intelligent policy if it uses the same UTM", a result which "undermines all existing optimality properties for AIXI". This problem stems from AIXI's use of compression as a proxy for intelligence, which requires that cognition take place in isolation from the environment in which goals are pursued. This formalises a philosophical position known as
Mind–body dualism In the philosophy of mind, mind–body dualism denotes either the view that mental phenomena are non-physical, Hart, W. D. 1996. "Dualism." pp. 265–267 in ''A Companion to the Philosophy of Mind'', edited by S. Guttenplan. Oxford: Blackwell. ...
. There is arguably more evidence in support of
enactivism Enactivism is a position in cognitive science that argues that cognition arises through a dynamic interaction between an acting organism and its environment. It claims that the environment of an organism is brought about, or enacted, by the active ...
-- the notion that cognition takes place within the environment in which goals are pursued. Subsequently, Michael Timothy Bennett formalised enactive cognition (see
enactivism Enactivism is a position in cognitive science that argues that cognition arises through a dynamic interaction between an acting organism and its environment. It claims that the environment of an organism is brought about, or enacted, by the active ...
) and identified an alternative proxy for intelligence called weakness . The accompanying experiments (comparing weakness and compression) and mathematical proofs showed that maximising weakness results in the optimal "ability to complete a wide range of tasks" or equivalently "ability to generalise" (thus maximising intelligence by either definition). This also showed that if
enactivism Enactivism is a position in cognitive science that argues that cognition arises through a dynamic interaction between an acting organism and its environment. It claims that the environment of an organism is brought about, or enacted, by the active ...
holds and
Mind–body dualism In the philosophy of mind, mind–body dualism denotes either the view that mental phenomena are non-physical, Hart, W. D. 1996. "Dualism." pp. 265–267 in ''A Companion to the Philosophy of Mind'', edited by S. Guttenplan. Oxford: Blackwell. ...
does not, then compression is not necessary or sufficient for intelligence, calling into question widely held views on intelligence (see also
Hutter Prize The Hutter Prize is a cash prize funded by Marcus Hutter which rewards data compression improvements on a specific 1 Gigabyte, GB English text file, with the goal of encouraging research in artificial intelligence (AI). Launched in 2006, the priz ...
). Regardless of the position taken with respect to cognition, whether this type of AGI exhibits human-like behavior (such as the use of natural language) would depend on many factors, for example the manner in which the agent is embodied, or whether it has a reward function that closely approximates human primitives of cognition like hunger, pain and so forth.


History


Classical AI

Modern AI research began in the mid-1950s. The first generation of AI researchers were convinced that artificial general intelligence was possible and that it would exist in just a few decades. AI pioneer
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 ...
wrote in 1965: "machines will be capable, within twenty years, of doing any work a man can do." Their predictions were the inspiration for
Stanley Kubrick Stanley Kubrick (; July 26, 1928 – March 7, 1999) was an American film director, producer, screenwriter, and photographer. Widely considered one of the greatest filmmakers of all time, his films, almost all of which are adaptations of nove ...
and Arthur C. Clarke's character
HAL 9000 HAL 9000 is a fictional artificial intelligence character and the main antagonist in Arthur C. Clarke's ''Space Odyssey'' series. First appearing in the 1968 film '' 2001: A Space Odyssey'', HAL ( Heuristically programmed ALgorithmic computer ...
, who embodied what AI researchers believed they could create by the year 2001. AI pioneer
Marvin Minsky Marvin Lee Minsky (August 9, 1927 – January 24, 2016) was an American cognitive and computer scientist concerned largely with research of artificial intelligence (AI), co-founder of the Massachusetts Institute of Technology's AI laboratory, an ...
was a consultant on the project of making HAL 9000 as realistic as possible according to the consensus predictions of the time; Crevier quotes him as having said on the subject in 1967, "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved". Several classical AI projects, such as
Doug Lenat Douglas Bruce Lenat (born 1950) is the CEO of Cycorp, Inc. of Austin, Texas, and has been a prominent researcher in artificial intelligence; he was awarded the biannual IJCAI Computers and Thought Award in 1976 for creating the machine learning p ...
's
Cyc Cyc (pronounced ) is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc f ...
project (that began in 1984), and
Allen Newell Allen Newell (March 19, 1927 – July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND Corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department ...
's Soar project, were specifically directed at AGI. However, in the early 1970s and then again in the early 90s, it became obvious that researchers had grossly underestimated the difficulty of the project. Funding agencies became skeptical of AGI and put researchers under increasing pressure to produce useful "applied AI". As the 1980s began, 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 revived interest in AGI, setting out a ten-year timeline that included AGI goals like "carry on a casual conversation". In response to this and the success of
expert systems In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if ...
, both industry and government pumped money back into the field. However, confidence in AI spectacularly collapsed in the late 1980s, and the goals of the Fifth Generation Computer Project were never fulfilled. For the second time in 20 years, AI researchers who had predicted the imminent achievement of AGI had been shown to be fundamentally mistaken. By the 1990s, AI researchers had gained a reputation for making vain promises. They became reluctant to make predictions at all and to avoid any mention of "human level" artificial intelligence for fear of being labeled "wild-eyed dreamer .


Narrow AI research

In the 1990s and early 21st century, mainstream AI achieved far greater commercial success and academic respectability by focusing on specific sub-problems where they can produce verifiable results and commercial applications, such as
artificial neural networks Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected unit ...
and 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 ...
. These "applied AI" systems are now used extensively throughout the technology industry, and research in this vein is very heavily funded in both academia and industry. Currently, development on this field is considered an emerging trend, and a mature stage is expected to happen in more than 10 years. Most mainstream AI researchers hope that strong AI can be developed by combining the programs that solve various sub-problems.
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 on ...
wrote in 1988:
I am confident that this bottom-up route to artificial intelligence will one day meet the traditional top-down route more than half way, ready to provide the real world competence and the
commonsense knowledge In artificial intelligence research, commonsense knowledge consists of facts about the everyday world, such as "Lemons are sour", that all humans are expected to know. It is currently an unsolved problem in Artificial General Intelligence. The f ...
that has been so frustratingly elusive in reasoning programs. Fully intelligent machines will result when the metaphorical
golden spike The golden spike (also known as The Last Spike) is the ceremonial 17.6-karat gold final spike driven by Leland Stanford to join the rails of the first transcontinental railroad across the United States connecting the Central Pacific Railroad ...
is driven uniting the two efforts.
However, even this fundamental philosophy has been disputed; for example, Stevan Harnad of Princeton concluded his 1990 paper on the Symbol Grounding Hypothesis by stating:
The expectation has often been voiced that "top-down" (symbolic) approaches to modeling cognition will somehow meet "bottom-up" (sensory) approaches somewhere in between. If the grounding considerations in this paper are valid, then this expectation is hopelessly modular and there is really only one viable route from sense to symbols: from the ground up. A free-floating symbolic level like the software level of a computer will never be reached by this route (or vice versa) – nor is it clear why we should even try to reach such a level, since it looks as if getting there would just amount to uprooting our symbols from their intrinsic meanings (thereby merely reducing ourselves to the functional equivalent of a programmable computer).


Modern artificial general intelligence research

The term "artificial general intelligence" was used as early as 1997, by Mark Gubrud in a discussion of the implications of fully automated military production and operations. The term was re-introduced and popularized by
Shane Legg Shane Legg is a machine learning research director and digital technology entrepreneur who did an AI-related postdoctoral fellowship at University College London's Gatsby Computational Neuroscience Unit, after doctoral work at the Istituto Da ...
and
Ben Goertzel Ben Goertzel is a cognitive scientist, artificial intelligence researcher, CEO and founder of SingularityNET, leader of the OpenCog Foundation, and the AGI Society, and chair of Humanity+. He helped popularize the term 'artificial general intell ...
around 2002. AGI research activity in 2006 was described by Pei Wang and Ben Goertzel as "producing publications and preliminary results". The first summer school in AGI was organized in Xiamen, China in 2009 by the Xiamen university's Artificial Brain Laboratory and OpenCog. The first university course was given in 2010 and 2011 at Plovdiv University, Bulgaria by Todor Arnaudov. MIT presented a course in AGI in 2018, organized by
Lex Fridman Lex Fridman ( /'lɛks 'friːdmæn/; , Russian: ) is a Russian-American computer scientist, podcaster, and an artificial intelligence researcher. He is a research scientist at the Massachusetts Institute of Technology, and he hosts the ''Lex Fr ...
and featuring a number of guest lecturers. However, as of yet, most AI researchers have devoted little attention to AGI, with some claiming that intelligence is too complex to be completely replicated in the near term. However, a small number of computer scientists are active in AGI research, and many of this group are contributing to a series of AGI conferences. The research is extremely diverse and often pioneering in nature. Timescales: In the introduction to his 2006 book, Goertzel says that estimates of the time needed before a truly flexible AGI is built vary from 10 years to over a century, but the 2007 consensus in the AGI research community seems to be that the timeline discussed by
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 ...
in '' The Singularity is Near'' or se
Advanced Human Intelligence
where he defines strong AI as "machine intelligence with the full range of human intelligence."
(i.e. between 2015 and 2045) is plausible. However, mainstream AI researchers have given a wide range of opinions on whether progress will be this rapid. A 2012 meta-analysis of 95 such opinions found a bias towards predicting that the onset of AGI would occur within 16–26 years for modern and historical predictions alike. It was later found that the dataset listed some experts as non-experts and vice versa. In 2017, researchers Feng Liu, Yong Shi and Ying Liu conducted intelligence tests on publicly available and freely accessible weak AI such as Google AI or Apple's Siri and others. At the maximum, these AI reached an IQ value of about 47, which corresponds approximately to a six-year-old child in first grade. An adult comes to about 100 on average. Similar tests had been carried out in 2014, with the IQ score reaching a maximum value of 27. In 2020,
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 ...
developed
GPT-3 Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text. Given an initial text as prompt, it will produce text that continues the prompt. The architecture is a standard ...
, a language model capable of performing many diverse tasks without specific training. According to
Gary Grossman Gary Grossman was the primary developer of ActionScript programming language. He currently works with Robert Tatsumi (creators of Adobe Flash) at Zendesk.https://www.linkedin.com/in/gagrossman/ In his previous position as a principal scientist ...
in a
VentureBeat ''VentureBeat'' is an American technology website headquartered in San Francisco, California. It publishes news, analysis, long-form features, interviews, and videos. History The ''VentureBeat'' company was founded in 2006 by Matt Marshall, a ...
article, while there is consensus that GPT-3 is not an example of AGI, it is considered by some to be too advanced to classify as a narrow AI system. In the same year Jason Rohrer used his GPT-3 account to develop a chatbot, and provided a chatbot-developing platform called "Project December". OpenAI asked for changes to the chatbot to comply with their safety guidelines; Rohrer disconnected Project December from the GPT-3 API. In 2022,
DeepMind DeepMind Technologies is a British artificial intelligence subsidiary of Alphabet Inc. and research laboratory founded in 2010. DeepMind was List of mergers and acquisitions by Google, acquired by Google in 2014 and became a wholly owned subsid ...
developed
Gato Gato (Spanish for cat) may refer to: People * Gato (given name) *Gato (surname) Places * Gato Island, in the Visayan Sea, Philippines * Gato Island, in the Mochima National Park on the northeastern coast of Venezuela * Gato, Orocovis, Puerto ...
, a "general-purpose" system capable of performing more than 600 different tasks.


Brain simulation


Whole brain emulation

A popular discussed approach to achieving general intelligent action is
whole brain emulation Mind uploading is a speculative process of whole brain emulation in which a brain scan is used to completely emulate the mental state of the individual in a digital computer. The computer would then run a simulation of the brain's information ...
. A low-level brain model is built by scanning and mapping a biological brain in detail and copying its state into a computer system or another computational device. The computer runs a
simulation A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of Conceptual model, models; the model represents the key characteristics or behaviors of the selected system or proc ...
model so faithful to the original that it will behave in essentially the same way as the original brain, or for all practical purposes, indistinguishably. . "The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain." Whole brain emulation is discussed in
computational neuroscience Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to u ...
and
neuroinformatics Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be ...
, in the context of
brain simulation Brain simulation is the concept of creating a functioning computer model of a brain or part of a brain. Brain simulation projects intend to contribute to a complete understanding of the brain, and eventually also assist the process of treating and ...
for medical research purposes. It is discussed in
artificial intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech re ...
research as an approach to strong AI.
Neuroimaging Neuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Incre ...
technologies that could deliver the necessary detailed understanding are improving rapidly, and
futurist Futurists (also known as futurologists, prospectivists, foresight practitioners and horizon scanners) are people whose specialty or interest is futurology or the attempt to systematically explore predictions and possibilities abou ...
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 ...
in the book ''The Singularity Is Near'' predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.


Early estimates

For low-level brain simulation, an extremely powerful computer would be required. The
human brain The human brain is the central organ of the human nervous system, and with the spinal cord makes up the central nervous system. The brain consists of the cerebrum, the brainstem and the cerebellum. It controls most of the activities of the ...
has a huge number of
synapses In the nervous system, a synapse is a structure that permits a neuron (or nerve cell) to pass an electrical or chemical signal to another neuron or to the target effector cell. Synapses are essential to the transmission of nervous impulses from ...
. Each of the 1011 (one hundred billion)
neurons A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. N ...
has on average 7,000 synaptic connections (synapses) to other neurons. It has been estimated that the brain of a three-year-old child has about 1015 synapses (1 quadrillion). This number declines with age, stabilizing by adulthood. Estimates vary for an adult, ranging from 1014 to 5×1014 synapses (100 to 500 trillion). An estimate of the brain's processing power, based on a simple switch model for neuron activity, is around 1014 (100 trillion) synaptic updates per second ( SUPS). In 1997, Kurzweil looked at various estimates for the hardware required to equal the human brain and adopted a figure of 1016 computations per second (cps). (For comparison, if a "computation" was equivalent to one " floating-point operation" – a measure used to rate current
supercomputer A supercomputer is a computer with a high level of performance as compared to a general-purpose computer. The performance of a supercomputer is commonly measured in floating-point operations per second ( FLOPS) instead of million instructions ...
s – then 1016 "computations" would be equivalent to 10
petaFLOPS In computing, floating point operations per second (FLOPS, flops or flop/s) is a measure of computer performance, useful in fields of scientific computations that require floating-point calculations. For such cases, it is a more accurate meas ...
, achieved in 2011, while 1018 was achieved in 2022.) He used this figure to predict the necessary hardware would be available sometime between 2015 and 2025, if the exponential growth in computer power at the time of writing continued.


Modelling the neurons in more detail

The
artificial neuron An artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing e ...
model assumed by Kurzweil and used in many current
artificial neural network Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected unit ...
implementations is simple compared with biological neurons. A brain simulation would likely have to capture the detailed cellular behaviour of biological
neurons A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. N ...
, presently understood only in the broadest of outlines. The overhead introduced by full modeling of the biological, chemical, and physical details of neural behaviour (especially on a molecular scale) would require computational powers several orders of magnitude larger than Kurzweil's estimate. In addition the estimates do not account for
glial cells Glia, also called glial cells (gliocytes) or neuroglia, are non-neuronal cells in the central nervous system (brain and spinal cord) and the peripheral nervous system that do not produce electrical impulses. They maintain homeostasis, form mye ...
, which are known to play a role in cognitive processes.


Current research

There are some research projects that are investigating brain simulation using more sophisticated neural models, implemented on conventional computing architectures. The
Artificial Intelligence System Artificial Intelligence System (AIS) was a volunteer computing project undertaken by Intelligence Realm, Inc. with the long-term goal of simulating the human brain in real time, complete with artificial consciousness and artificial general intell ...
project implemented non-real time simulations of a "brain" (with 1011 neurons) in 2005. It took 50 days on a cluster of 27 processors to simulate 1 second of a model. The Blue Brain project used one of the fastest supercomputer architectures in the world, IBM's
Blue Gene Blue Gene is an IBM project aimed at designing supercomputers that can reach operating speeds in the petaFLOPS (PFLOPS) range, with low power consumption. The project created three generations of supercomputers, Blue Gene/L, Blue Gene/P, ...
platform, to create a real time simulation of a single rat neocortical column consisting of approximately 10,000 neurons and 108 synapses in 2006. A longer-term goal is to build a detailed, functional simulation of the physiological processes in the human brain: "It is not impossible to build a human brain and we can do it in 10 years," Henry Markram, director of the Blue Brain Project said in 2009 at the
TED conference TED Conferences, LLC (Technology, Entertainment, Design) is an American-Canadian non-profit media organization that posts international talks online for free distribution under the slogan "ideas worth spreading". TED was founded by Richard Sau ...
in Oxford. There have also been controversial claims to have simulated a cat brain. Neuro-silicon interfaces have been proposed as an alternative implementation strategy that may scale better.
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 on ...
addressed the above arguments ("brains are more complicated", "neurons have to be modeled in more detail") in his 1997 paper "When will computer hardware match the human brain?". He measured the ability of existing software to simulate the functionality of neural tissue, specifically the retina. His results do not depend on the number of glial cells, nor on what kinds of processing neurons perform where. The actual complexity of modeling biological neurons has been explored in OpenWorm project that was aimed on complete simulation of a worm that has only 302 neurons in its neural network (among about 1000 cells in total). The animal's neural network has been well documented before the start of the project. However, although the task seemed simple at the beginning, the models based on a generic neural network did not work. Currently, the efforts are focused on precise emulation of biological neurons (partly on the molecular level), but the result cannot be called a total success yet.


Criticisms of simulation-based approaches

A fundamental criticism of the simulated brain approach derives from
embodied cognition Embodied cognition is the theory that many features of cognition, whether human or otherwise, are shaped by aspects of an organism's entire body. Sensory and motor systems are seen as fundamentally integrated with cognitive processing. The cognit ...
where human embodiment is taken as an essential aspect of human intelligence. Many researchers believe that embodiment is necessary to ground meaning. If this view is correct, any fully functional brain model will need to encompass more than just the neurons (i.e., a robotic body). Goertzel proposes virtual embodiment (like in ''
Second Life ''Second Life'' is an online multimedia platform that allows people to create an avatar for themselves and then interact with other users and user created content within a multi player online virtual world. Developed and owned by the San Fra ...
''), but it is not yet known whether this would be sufficient. Desktop computers using microprocessors capable of more than 109 cps (Kurzweil's non-standard unit "computations per second", see above) have been available since 2005. According to the brain power estimates used by Kurzweil (and Moravec), this computer should be capable of supporting a simulation of a bee brain, but despite some interest no such simulation exists. There are several reasons for this: #The neuron model seems to be oversimplified (see next section). #There is insufficient understanding of higher cognitive processes to establish accurately what the brain's neural activity (observed using techniques such as
functional magnetic resonance imaging Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area o ...
) correlates with. #Even if our understanding of cognition advances sufficiently, early simulation programs are likely to be very inefficient and will, therefore, need considerably more hardware. #The brain of an organism, while critical, may not be an appropriate boundary for a cognitive model. To simulate a bee brain, it may be necessary to simulate the body, and the environment.
The Extended Mind In philosophy of mind, the extended mind thesis (EMT) says that the mind does not exclusively reside in the brain or even the body, but extends into the physical world. The EMT proposes that some objects in the external environment can be part of ...
thesis formalizes the philosophical concept, and research into
cephalopods A cephalopod is any member of the molluscan class Cephalopoda (Greek plural , ; "head-feet") such as a squid, octopus, cuttlefish, or nautilus. These exclusively marine animals are characterized by bilateral body symmetry, a prominent head, an ...
has demonstrated clear examples of a decentralized system. In addition, the scale of the human brain is not currently well-constrained. One estimate puts the human brain at about 100 billion neurons and 100 trillion synapses. Another estimate is 86 billion neurons of which 16.3 billion are in the
cerebral cortex The cerebral cortex, also known as the cerebral mantle, is the outer layer of neural tissue of the cerebrum of the brain in humans and other mammals. The cerebral cortex mostly consists of the six-layered neocortex, with just 10% consisting of ...
and 69 billion in the
cerebellum The cerebellum (Latin for "little brain") is a major feature of the hindbrain of all vertebrates. Although usually smaller than the cerebrum, in some animals such as the mormyrid fishes it may be as large as or even larger. In humans, the cerebel ...
.
Glial cell Glia, also called glial cells (gliocytes) or neuroglia, are non-neuronal cells in the central nervous system (brain and spinal cord) and the peripheral nervous system that do not produce electrical impulses. They maintain homeostasis, form mye ...
synapses are currently unquantified but are known to be extremely numerous.


Philosophical perspective


"Strong AI" as defined in philosophy

In 1980, philosopher
John Searle John Rogers Searle (; born July 31, 1932) is an American philosopher widely noted for contributions to the philosophy of language, philosophy of mind, and social philosophy. He began teaching at UC Berkeley in 1959, and was Willis S. and Mario ...
coined the term "strong AI" as part of his
Chinese room The Chinese room argument holds that a digital computer executing a program cannot have a " mind," "understanding" or "consciousness," regardless of how intelligently or human-like the program may make the computer behave. The argument was pres ...
argument. He wanted to distinguish between two different hypotheses about artificial intelligence: * Strong AI hypothesis: An artificial intelligence system can "think", have "a mind" and "consciousness". * Weak AI hypothesis: An artificial intelligence system can (only) ''act like'' it thinks and has a mind and consciousness. The first one he called "strong" because it makes a ''stronger'' statement: it assumes something special has happened to the machine that goes beyond all its abilities that we can test – the behavior of a "weak AI" machine would be precisely identical to a "strong AI" machine, but the latter would also have subjective conscious experience. This usage is also common in academic AI research and textbooks. Mainstream AI is only interested in how a program ''behaves''. According to Russell and Norvig, "as long as the program works, they don't care if you call it real or a simulation." If the program can behave ''as if'' it has a mind, then there's no need to know if it ''actually'' has mind – indeed, there would be no way to tell. For AI research, Searle's "weak AI hypothesis" is equivalent to the statement "artificial general intelligence is possible". Thus, according to Russell and Norvig, "most AI researchers take the weak AI hypothesis for granted, and don't care about the strong AI hypothesis." Thus, for academic AI research, "Strong AI" and "AGI" are two very different things. In contrast to Searle and mainstream AI, some futurists such as
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 ...
use the term "strong AI" to mean "human level artificial general intelligence". This is not the same as Searle's strong AI, unless you assume that
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 ...
is necessary for human-level AGI. Academic philosophers such as Searle do not believe that is the case, and artificial intelligence researchers do not care.


Consciousness

There are other aspects of the human mind besides intelligence that are relevant to the concept of strong AI which play a major role 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 unive ...
and the
ethics of artificial intelligence The ethics of artificial intelligence is the branch of the ethics of technology specific to artificially intelligent systems. It is sometimes divided into a concern with the moral behavior of ''humans'' as they design, make, use and treat artific ...
: *
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 ...
: To have subjective experience and
thought In their most common sense, the terms thought and thinking refer to conscious cognitive processes that can happen independently of sensory stimulation. Their most paradigmatic forms are judging, reasoning, concept formation, problem solving, a ...
. *
self-awareness In philosophy of self, self-awareness is the experience of one's own personality or individuality. It is not to be confused with consciousness in the sense of qualia. While consciousness is being aware of one's environment and body and lifesty ...
: To be aware of oneself as a separate individual, especially to be aware of one's own thoughts. *
sentience Sentience is the capacity to experience feelings and sensations. The word was first coined by philosophers in the 1630s for the concept of an ability to feel, derived from Latin '':wikt:sentientem, sentientem'' (a feeling), to distinguish it fro ...
: The ability to "feel" perceptions or emotions subjectively. *
sapience Wisdom, sapience, or sagacity is the ability to contemplate and act using knowledge, experience, understanding, common sense and insight. Wisdom is associated with attributes such as unbiased judgment, compassion, experiential self-knowledge, ...
: The capacity for wisdom. These traits have a moral dimension, because a machine with this form of strong AI may have rights, analogous to the rights of non-human animals. As such, preliminary work has been conducted on approaches to integrating full ethical agents with existing legal and social frameworks. These approaches have focused on the legal position and rights of 'strong' AI.
Bill Joy William Nelson Joy (born November 8, 1954) is an American computer engineer and venture capitalist. He co-founded Sun Microsystems in 1982 along with Scott McNealy, Vinod Khosla, and Andy Bechtolsheim, and served as Chief Scientist and CTO at ...
, among others, argues a machine with these traits may be a threat to human life or dignity. It remains to be shown whether any of these traits are necessary for strong AI. The role of
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 ...
is not clear, and currently there is no agreed test for its presence. If a machine is built with a device that simulates the
neural correlates of consciousness The neural correlates of consciousness (NCC) refer to the relationships between mental states and neural states and constitute the minimal set of neuronal events and mechanisms sufficient for a specific conscious percept. Neuroscientists use empi ...
, would it automatically have self-awareness? It is also possible that some of these properties, such as sentience, naturally emerge from a fully intelligent machine. It's also possible that it will become natural to ''ascribe'' these properties to machines once they begin to act in a way that is clearly intelligent.


Artificial consciousness research

Although the role of consciousness in strong AI/AGI is debatable, many AGI researchers regard research that investigates possibilities for implementing consciousness as vital. In an early effort
Igor Aleksander Igor Aleksander FREng (born 26 January 1937) is an emeritus professor of Neural Systems Engineering in the Department of Electrical and Electronic Engineering at Imperial College London. He worked in artificial intelligence and neural networks a ...
argued that the principles for creating a conscious machine already existed but that it would take forty years to train such a machine to understand
language Language is a structured system of communication. The structure of a language is its grammar and the free components are its vocabulary. Languages are the primary means by which humans communicate, and may be conveyed through a variety of met ...
.


Possible explanations for the slow progress of strong AI research

Since the launch of AI research in 1956, progress in this field of creating machines skilled with intelligent action at the human level has slowed. One basic potential explanation for this delay is that computers lack a sufficient scope of memory, processing power, or chip flexibility to accommodate computer-science-oriented and/or neuroscience-oriented platforms. In addition, the level of complexity involved in AI research likely also limits the progress of strong AI research. Conceptual limitations are another possible reason for the slowness in AI research. AI researchers may need to modify the conceptual framework of their discipline in order to provide a stronger base and contribution to the quest of achieving strong AI. This means situating a strong AI in a sociocultural context where human-like AI derives from human-like experiences. As William Clocksin wrote in 2003: "the framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts". A fundamental paradox arising from this problem is that AI researchers have only been able to create computers that can perform jobs that are complicated for people to do, such as mathematics, but conversely they have struggled to develop a computer that is capable of carrying out tasks that are simple for humans to do, such as walking (
Moravec's paradox Moravec's paradox is the observation by artificial intelligence and robotics researchers that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational ...
). The problem as described by David Gelernter is that some people assume thinking and reasoning are equivalent. The idea of whether thoughts and the creator of those thoughts are isolated individually or must be socially situated has intrigued AI researchers. The problems encountered in AI research over the past decades have further impeded the progress of AGI research and development through generating a degree of distrust in the field. The failed predictions of success promised by AI researchers and the lack of a complete understanding of human behaviors have helped diminish optimism in the primary idea of creating human-level AI. Although the waxing and waning progress of AI research has brought both improvement and disappointment, most investigators are optimistic about achieving the goal of AGI in the 21st century. Other possible reasons have been proposed for the slow progress towards strong AI. The intricacy of scientific problems and the need to fully understand the human brain through psychology and neurophysiology have limited many researchers in the task of emulating the function of the human brain in computer hardware through initiatives like the
Human Brain Project The Human Brain Project (HBP) is a large ten-year scientific research project, based on exascale supercomputers, that aims to build a collaborative ICT-based scientific research infrastructure to allow researchers across Europe to advance knowl ...
. Many researchers tend to underestimate any doubt that is involved with future predictions of AI, but without taking issues like human brain modelling seriously, AGI researchers then overlook solutions to problematic questions. However, Clocksin states that a conceptual limitation that may impede the progress of AI research is that AI researchers may be using the wrong techniques for computer programs and for the implementation of equipment. When AI researchers first began to aim for AGI, a main interest was to emulate and investigate human reasoning. At the time, researchers hoped to establish computational models of human knowledge through reasoning and to find out how to design a computer with a specific cognitive task. In response, the practice of abstraction, which people tend to redefine when working with a particular context in research, provides AI researchers with the option to concentrate on just a few concepts. The most productive use of abstraction in AI research comes from planning and problem solving. Although the aim is to increase the speed of a computation, the role of abstraction operators has posed problems. Another possible reason for the slowness in strong AI progress relates to the acknowledgement by many AI researchers that human
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, ...
is still vastly superior to computer performance. Nonetheless, the specific functions that are programmed into increasingly powerful computers may be able to account for many of the requirements in heuristics that eventually allow AI to match human intelligence. Thus, while heuristics is not necessarily a fundamental barrier to achieving strong AI, it is widely agreed to be a challenge. Finally, many AI researchers have debated whether or not machines should be created with emotions. There are no emotions in typical models of AI, and some researchers say programming emotions into machines allows them to have a mind of their own. However, emotion sums up the experiences of humans because it allows them to remember those experiences. David Gelernter writes, "No computer will be creative unless it can simulate all the nuances of human emotion." Thus, just as this concern over emotion has posed problems for AI researchers, it is likely to continue to challenge the concept of strong AI as its research progresses.


Controversies and dangers


Feasibility

As of 2022, AGI remains speculativeitu.int: Beyond Mad?: The Race For Artificial General Intelligence
, "AGI represents a level of power that remains firmly in the realm of speculative fiction as on date." February 2, 2018, retrieved March 3, 2020
as no such system has yet been demonstrated. Opinions vary both on whether and when artificial general intelligence will arrive, if at all. At one extreme, AI pioneer
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 ...
speculated in 1965 that "machines will be capable, within twenty years, of doing any work a man can do". However, this prediction failed to come true. Microsoft co-founder
Paul Allen Paul Gardner Allen (January 21, 1953 – October 15, 2018) was an American business magnate, computer programmer, researcher, investor, and philanthropist. He co-founded Microsoft Corporation with childhood friend Bill Gates in 1975, which h ...
believed that such intelligence is unlikely in the 21st century because it would require "unforeseeable and fundamentally unpredictable breakthroughs" and a "scientifically deep understanding of cognition". Writing in ''
The Guardian ''The Guardian'' is a British daily newspaper. It was founded in 1821 as ''The Manchester Guardian'', and changed its name in 1959. Along with its sister papers ''The Observer'' and ''The Guardian Weekly'', ''The Guardian'' is part of the Gu ...
'', roboticist Alan Winfield claimed the gulf between modern computing and human-level artificial intelligence is as wide as the gulf between current space flight and practical faster-than-light spaceflight. As such, the basic concern is whether or not strong AI is fundamentally achievable, even after centuries of effort. While most AI researchers believe strong AI can be achieved in the future, some individuals, like
Hubert Dreyfus Hubert Lederer Dreyfus (; October 15, 1929 – April 22, 2017) was an American philosopher and professor of philosophy at the University of California, Berkeley. His main interests included phenomenology, existentialism and the philosophy of bo ...
and
Roger Penrose Sir Roger Penrose (born 8 August 1931) is an English mathematician, mathematical physicist, philosopher of science and Nobel Laureate in Physics. He is Emeritus Rouse Ball Professor of Mathematics in the University of Oxford, an emeritus fello ...
, deny the possibility of achieving strong AI. One fundamental problem is that while humans are complex, they are not general intelligences. Various computer scientists, like John McCarthy, believe human-level AI will be accomplished, but that the present level of progress is such that a date cannot accurately be predicted. AI experts' views on the feasibility of AGI wax and wane, and may have seen a resurgence in the 2010s. Four polls conducted in 2012 and 2013 suggested that the median guess among experts for when they would be 50% confident AGI would arrive was 2040 to 2050, depending on the poll, with the mean being 2081. Of the experts, 16.5% answered with "never" when asked the same question but with a 90% confidence instead. Further current AGI progress considerations can be found above ''Tests for confirming human-level AGI''. Yet it is worth noting that there is no scientific rigour in such predictions.
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 ...
notes the findings of a report by Stuart Armstrong and Kaj Sotala, of the Machine Intelligence Research Institute, that "over that 60 year time frame there is a strong bias towards predicting the arrival of human level AI as between 15 and 25 years from the time the prediction was made". They also analyzed 95 predictions made between 1950 and the present on when human level AI will come about. They show that there is no difference between predictions made by experts and non-experts.


Potential threat to human existence

The thesis that AI poses an existential risk for humans, and that this risk needs much more attention than it currently gets, has been endorsed by many public figures; perhaps the most famous are
Elon Musk Elon Reeve Musk ( ; born June 28, 1971) is a business magnate and investor. He is the founder, CEO and chief engineer of SpaceX; angel investor, CEO and product architect of Tesla, Inc.; owner and CEO of Twitter, Inc.; founder of The Bori ...
,
Bill Gates William Henry Gates III (born October 28, 1955) is an American business magnate and philanthropist. He is a co-founder of Microsoft, along with his late childhood friend Paul Allen. During his career at Microsoft, Gates held the positions ...
, and Stephen Hawking. The most notable AI researcher to endorse the thesis is
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 ...
, but many others, like
Roman Yampolskiy Roman Vladimirovich Yampolskiy (russian: link=no, Роман Владимирович Ямпольский; born 13 August 1979) is a Russian computer scientist at the University of Louisville, known for his work on behavioral biometrics, secu ...
and Alexey Turchin, also support the basic thesis of a potential threat to humanity. Endorsers of the thesis sometimes express bafflement at skeptics: Gates states he does not "understand why some people are not concerned", and Hawking criticized widespread indifference in his 2014 editorial: A 2021 systematic review of the risks associated with AGI conducted by researchers from the Centre for Human Factors and Sociotechnical Systems of the
University of the Sunshine Coast The University of the Sunshine Coast (UniSC) is a public university based on the Sunshine Coast, Queensland, Australia. After opening with 524 students in 1996 as the Sunshine Coast University College, it was later renamed the University of the ...
in Australia, while noting the paucity of data, found the following potential threats: "AGI removing itself from the control of human owners/managers, being given or developing unsafe goals, development of unsafe AGI, AGIs with poor ethics, morals and values; inadequate management of AGI, and existential risks. Many of the scholars who are concerned about existential risk believe that the best way forward would be to conduct (possibly massive) research into solving the difficult " control problem" to answer the question: what types of safeguards, algorithms, or architectures can programmers implement to maximize the probability that their recursively-improving AI would continue to behave in a friendly, rather than destructive, manner after it reaches superintelligence? Solving the control problem is complicated by the AI arms race, which will almost certainly see the militarization and weaponization of AGI by more than one nation-state, i.e., resulting in AGI-enabled warfare, and in the case of AI misalignment, AGI-directed warfare, potentially against all humanity. The thesis that AI can pose existential risk also has many strong detractors. Skeptics sometimes charge that the thesis is crypto-religious, with an irrational belief in the possibility of superintelligence replacing an irrational belief in an omnipotent God; at an extreme,
Jaron Lanier Jaron Zepel Lanier (, born May 3, 1960) is an American computer scientist, visual artist, computer philosophy writer, technologist, futurist, and composer of contemporary classical music. Considered a founder of the field of virtual reality, La ...
argues that the whole concept that current machines are in any way intelligent is "an illusion" and a "stupendous con" by the wealthy. Much of existing criticism argues that AGI is unlikely in the short term. Computer scientist
Gordon Bell Chester Gordon Bell (born August 19, 1934) is an American electrical engineer and manager. An early employee of Digital Equipment Corporation (DEC) 1960–1966, Bell designed several of their PDP machines and later became Vice President of Engi ...
argues that the human race will destroy itself before it reaches the
technological singularity 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 ...
.
Gordon Moore Gordon Earle Moore (born January 3, 1929) is an American businessman, engineer, and the co-founder and chairman emeritus of Intel Corporation. He is also the original proponent of Moore's law. As of March 2021, Moore's net worth is rep ...
, the original proponent of
Moore's Law Moore's law is the observation that the number of transistors in a dense integrated circuit (IC) doubles about every two years. Moore's law is an observation and projection of a historical trend. Rather than a law of physics, it is an empir ...
, declares that "I am a skeptic. I don't believe technological singularityis likely to happen, at least for a long time. And I don't know why I feel that way." Former
Baidu Baidu, Inc. ( ; , meaning "hundred times") is a Chinese multinational technology company specializing in Internet-related services and products and artificial intelligence (AI), headquartered in Beijing's Haidian District. It is one of the la ...
Vice President and Chief Scientist
Andrew Ng Andrew Yan-Tak Ng (; born 1976) is a British-born American computer scientist and technology entrepreneur focusing on machine learning and AI. Ng was a co-founder and head of Google Brain and was the former Chief Scientist at Baidu, building ...
states AI existential risk is "like worrying about overpopulation on Mars when we have not even set foot on the planet yet."


See also

* Artificial brain *
AI alignment In the field of artificial intelligence (AI), AI alignment research aims to steer AI systems towards their designers’ intended goals and interests. An ''aligned'' AI system advances the intended objective; a ''misaligned'' AI system is compete ...
* A.I. Rising *
Automated machine learning Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready ...
*
BRAIN Initiative The White House BRAIN Initiative (Brain Research through Advancing Innovative Neurotechnologies) is a collaborative, public-private research initiative announced by the Obama administration on April 2, 2013, with the goal of supporting the devel ...
* China Brain Project *
Future of Humanity Institute The Future of Humanity Institute (FHI) is an interdisciplinary research centre at the University of Oxford investigating big-picture questions about humanity and its prospects. It was founded in 2005 as part of the Faculty of Philosophy and the ...
*
General game playing General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. For many games like chess, computers are programmed to play these games using a specially designed algorithm, which ca ...
*
Human Brain Project The Human Brain Project (HBP) is a large ten-year scientific research project, based on exascale supercomputers, that aims to build a collaborative ICT-based scientific research infrastructure to allow researchers across Europe to advance knowl ...
*
Intelligence amplification Intelligence amplification (IA) (also referred to as cognitive augmentation, machine augmented intelligence and enhanced intelligence) refers to the effective use of information technology in augmenting human intelligence. The idea was first pr ...
(IA) *
Machine ethics Machine ethics (or machine morality, computational morality, or computational ethics) is a part of the ethics of artificial intelligence concerned with adding or ensuring moral behaviors of man-made machines that use artificial intelligence, otherw ...
*
Multi-task learning Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. This can result in improved learning efficiency and prediction ac ...
*
Outline of artificial intelligence The following outline is provided as an overview of and topical guide to artificial intelligence: Artificial intelligence (AI) – intelligence exhibited by machines or software. It is also the name of the scientific field which studies how to ...
*
Transhumanism Transhumanism is a philosophical and intellectual movement which advocates the enhancement of the human condition by developing and making widely available sophisticated technologies that can greatly enhance longevity and cognition. Transhuma ...
*
Synthetic intelligence Synthetic intelligence (SI) is an alternative/opposite term for artificial intelligence emphasizing that the intelligence of machines need not be an imitation or in any way artificial; it can be a genuine form of intelligence. John Haugeland propo ...
*
Transfer learning Transfer learning (TL) is a research problem in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize ...
*
Loebner Prize The Loebner Prize was an annual competition in artificial intelligence that awards prizes to the computer programs considered by the judges to be the most human-like. The prize is reported as defunct since 2020. The format of the competition was tha ...
* Hardware for artificial intelligence * Weak artificial intelligence


Notes


References


Sources

* * * * * * . * * . * . * * * * . * * * . * * * * * * . * * * * * . * * * * * * * * * * * . * . * * . * . * . * .


External links


The AGI portal maintained by Pei Wang


– Modern research on the computations that underlay human intelligence
OpenCog – open source project to develop a human-level AI

Simulating logical human thought

What Do We Know about AI Timelines?
– Literature review {{DEFAULTSORT:Artificial general intelligence Hypothetical technology Artificial intelligence Computational neuroscience fr:Intelligence artificielle#Intelligence artificielle forte