Strong AI
Encyclopedia
Strong AI is artificial intelligence
that matches or exceeds human intelligence
— the intelligence of a machine that can successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence
research and an important topic for science fiction
writers and futurists. Strong AI is also referred to as "artificial general intelligence" or as the ability to perform "general intelligent action". Science fiction
associates strong AI with such human traits as consciousness
, sentience
, sapience and self-awareness
.
Some references emphasize a distinction between strong AI and "applied AI
" (also called "narrow AI" or "weak AI"): the use of software to study or accomplish specific problem solving
or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
have been proposed (such as being able to pass the Turing test
) but there is to date no definition that satisfies everyone. However, there is wide agreement among artificial intelligence researchers that intelligence is required to do the following:
Other important capabilities include the ability to sense
(e.g. see
) and the ability to act (e.g. move and manipulate objects
) in the world where intelligent behaviour is to be observed. This would include an ability to detect and respond to hazard
. Some sources consider "salience
" (the capacity for recognising importance) as an important trait. Salience is thought to be part of how humans evaluate novelty so are likely to be important in some degree, but not necessarily at a human level. Many interdisciplinary approaches to intelligence (e.g. cognitive science
, computational intelligence
and decision making
) tend to emphasise the need to consider additional traits such as imagination
(taken as the ability to form mental images and concepts that were not programmed in) and autonomy
.
Computer based systems that exhibit many of these capabilities do exist (e.g. see computational creativity
, decision support system
, robot
, evolutionary computation
, intelligent agent
), but not yet at human levels.
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
and the ethics of artificial intelligence
:
These traits have a moral dimension, because a machine with this form of strong AI may have legal rights, analogous to the rights of animals
. Also, Bill Joy
, 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
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
, 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, or that it becomes natural to ascribe these properties to machines once they begin to act in a way that is clearly intelligent. For example, intelligent action may be sufficient for sentience, rather than the other way around.
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
and Arthur C. Clarke
's character HAL 9000
, who accurately embodied what AI researchers believed they could create by the year 2001. Of note is the fact that AI pioneer Marvin Minsky
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,", although Minsky states that he was misquoted.
However, in the early 1970s, it became obvious that researchers had grossly underestimated the difficulty of the project. The agencies that funded AI became skeptical of strong AI and put researchers under increasing pressure to produce useful technology, or "applied AI". As the 1980s began, Japan's fifth generation computer
project revived interest in strong AI, setting out a ten year timeline that included strong AI goals like "carry on a casual conversation". In response to this and the success of expert systems, both industry and government pumped money back into the field. However, the market for 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 arrival of strong AI had been shown to be fundamentally mistaken about what they could accomplish. By the 1990s, AI researchers had gained a reputation for making promises they could not keep. AI researchers became reluctant to make any kind of prediction at all and avoid any mention of "human level" artificial intelligence, for fear of being labeled a "wild-eyed dreamer."
or data mining
. These "applied AI" applications are now used extensively throughout the technology industry and research in this vein is very heavily funded in both academia and industry.
Most mainstream AI researchers hope that strong AI can be developed by combining the programs that solve various subproblems using an integrated agent architecture
, cognitive architecture
or subsumption architecture
. Hans Moravec
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 that has been so frustratingly elusive in reasoning programs. Fully intelligent machines will result when the metaphorical golden spike
is driven uniting the two efforts."
project (that began in 1984), and Allen Newell
's Soar
project are regarded as within the scope of AGI. AGI research activity in 2006 was described by Pei Wang and Ben Goertzel
as "producing publications and preliminary results". As 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. In the introduction to his 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 consensus in the AGI research community seems to be that the timeline discussed by Ray Kurzweil
in "The Singularity is Near
" (i.e. between 2015 and 2045) is plausible. Most mainstream AI researchers doubt that progress will be this rapid. Organizations actively pursuing AGI include Adaptive AI
, Artificial General Intelligence Research Institute (AGIRI)
, the Singularity Institute for Artificial Intelligence, Bitphase AI, and TexAI. One recent addition is Numenta
, a project based on the theories of Jeff Hawkins
, the creator of the Palm Pilot. While Numenta takes a computational approach to general intelligence, Hawkins is also the founder of the RedWood Neuroscience Institute, which explores conscious thought from a biological perspective. AND Corporation
has been active in this field since 1990, and has developed machine intelligence processes based on phase coherence principles, having strong similarities to digital holography and QM with respect to quantum collapse of the wave function. Ben Goertzel
is pursuing an embodied AGI through the open-source OpenCog
project. Current code includes embodied virtual pets capable of learning simple English-language commands, as well as integration with real-world robotics, being done at the robotics lab of Hugo de Garis
at Xiamen University
.
a biological brain in detail and copying its state into a computer system or another computational device. The computer runs a simulation
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. Whole brain emulation is discussed in computational neuroscience
and neuroinformatics
, in the context of brain simulation for medical research purposes. It is discussed in artificial intelligence
research as an approach to strong AI. Neuroimaging
technologies, that could deliver the necessary detailed understanding, are improving rapidly, and futurist Ray Kurzweil 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.
For low-level brain simulation, an extremely powerful computer would be required. The human brain
has a huge number of synapses. Each of the 1011 (one hundred billion) neurons has on average 7,000 synaptic connections 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 x 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) neuron updates per second. Kurzweil
looks at various estimates for the hardware required to equal the human brain and adopts a figure of 1016 computations per second (cps). He uses this figure to predict the necessary hardware will be available sometime between 2015 and 2025, if the current exponential growth in computer power continues.
A key fundamental criticism of the simulated brain approach derives from embodied cognition
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 Second Life
), but it is not yet known whether this would be sufficient.
Desktop computers using 2 GHz Intel Pentium microprocessors and capable of more than 109 cps 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 at least three reasons for this.
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
and 69 billion in the cerebellum
. Glial cell
synapses are currently unquantified but are known to be extremely numerous.
model assumed by Kurzweil
and used in many current artificial neural network
implementations is simple compared with biological neurons
. A brain simulation would likely have to capture the detailed cellular behaviour of biological neurons, presently only understood 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 a computer several orders of magnitude larger than Kurzweil
's estimate. In addition the estimates do not account for Glial cells which are at least as numerous as neurons, may outnumber neurons by as much as 10:1, and are now known to play a role in cognitive processes.
There are some research projects that are investigating brain simulation using more sophisticated neural models, implemented on conventional computing architectures. The Artificial Intelligence System
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
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
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.
Moravec
addressed the above arguments ("brains are more complicated", "neurons have to be modeled in more detail") in his 1997 paper. 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.
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
.
first identified by John Searle
as part of his Chinese room
argument in 1980. He wanted to distinguish between two different hypotheses about artificial intelligence:
The first one is called "the strong AI hypothesis" and the second is "the weak AI hypothesis" because the first one makes the stronger statement: it assumes something special has happened to the machine that goes beyond all its abilities that we can test. Searle referred to the "strong AI hypothesis" as "strong AI". This usage, which is fundamentally different than the subject of this article, is common in academic AI research and textbooks.
The term "strong AI" is now used to describe any artificial intelligence system that acts like it has a mind, regardless of whether a philosopher would be able to determine if it actually has a mind or not. As Russell
and Norvig
write: "Most AI researchers take the weak AI hypothesis for granted, and don't care about the strong AI hypothesis." AI researchers are interested in a related statement:
This assertion, which hinges on the breadth and power of machine intelligence, is the subject of this article.
Since the launch of AI research in 1956, the growth of this field has slowed down over time and has stalled the aims of creating machines skilled with intelligent action at the human level. A possible explanation for this delay is that computers lack a sufficient scope of memory or processing power. In addition, the level of complexity that connects to the process of AI research may also limit the progress of AI research.
While most AI researchers believe that strong AI can be achieved in the future, there are some individuals like Hubert Dreyfus
and Roger Penrose
that deny the possibility of achieving AI. John McCarthy
was one of various computer scientists who believe human-level AI will be accomplished, but a date cannot accurately be predicted.
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. 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".
Furthermore, AI researchers have been able to create computers that can perform jobs that are complicated for people to do, but conversely they have struggled to develop a computer that is capable of carrying out tasks that are simple for humans to do. A problem that is described by David Galernter is that some people assume that thinking and reasoning mean the same definition. However, the idea of whether thoughts and the creator of those thoughts are isolated individually has intrigued AI researchers.
The problems that have been encountered in AI research over the past decades have further impeded the progress of AI. The failed predictions that have been promised by AI researchers and the lack of a complete understanding of human behaviors have helped diminish the primary idea of human-level AI. Although the progress of AI research has brought both improvement and disappointment, most investigators have established optimism about potentially achieving the goal of AI in the 21st century.
Other possible reasons have been proposed for the lengthy research in the progress of strong AI. The intricacy of scientific problems and the need to fully understand the human brain through psychology and neurophysiology have limited many researchers from emulating the function of the human brain into a computer hardware. Many researchers tend to underestimate any doubt that is involved with future predictions of AI, but without taking those issues seriously can people then overlook solutions to problematic questions.
Clocksin says that a conceptual limitation that may impede the progress of AI research is that people may be using the wrong techniques for computer programs and implementation of equipment. When AI researchers first began to aim for the goal of artificial intelligence, a main interest was human reasoning. 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.
The practice of abstraction, which people tend to redefine when working with a particular context in research, provides researchers with a concentration 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 has posed questions about the involvement of abstraction operators.
A possible reason for the slowness in AI relates to the acknowledgement by many AI researchers that heuristics is a section that contains a significant breach between computer performance and human performance. The specific functions that are programmed to a computer may be able to account for many of the requirements that allow it to match human intelligence. These explanations are not necessarily guaranteed to be the fundamental causes for the delay in achieving strong AI, but they are widely agreed by numerous researchers.
There have been many AI researchers that debate over the idea whether 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. Emotion sums up the experiences of humans because it allows them to remember those experiences.
As David Gelernter writes, “No computer will be creative unless it can simulate all the nuances of human emotion.” This concern about emotion has posed problems for AI researchers and it connects to the concept of strong AI as its research progresses into the future.
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
that matches or exceeds human intelligence
Intelligence
Intelligence has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, planning, emotional intelligence and problem solving....
— the intelligence of a machine that can successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
research and an important topic for science fiction
Science fiction
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...
writers and futurists. Strong AI is also referred to as "artificial general intelligence" or as the ability to perform "general intelligent action". Science fiction
Science fiction
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...
associates strong AI with such human traits as consciousness
Consciousness
Consciousness is a term that refers to the relationship between the mind and the world with which it interacts. It has been defined as: subjectivity, awareness, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind...
, sentience
Sentience
Sentience is the ability to feel, perceive or be conscious, or to have subjective experiences. Eighteenth century philosophers used the concept to distinguish the ability to think from the ability to feel . In modern western philosophy, sentience is the ability to have sensations or experiences...
, sapience and self-awareness
Self-awareness
Self-awareness is the capacity for introspection and the ability to reconcile oneself as an individual separate from the environment and other individuals...
.
Some references emphasize a distinction between strong AI and "applied AI
Weak AI
Weak AI is used to refer to:* An artificial intelligence system which is not intended to match or exceed the capabilities of human beings, as opposed to strong AI, which is. Also known as applied AI or narrow AI...
" (also called "narrow AI" or "weak AI"): the use of software to study or accomplish specific problem solving
Problem solving
Problem solving is a mental process and is part of the larger problem process that includes problem finding and problem shaping. Consideredthe most complex of all intellectual functions, problem solving has been defined as higher-order cognitive process that requires the modulation and control of...
or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
Requirements
Many different definitions of intelligenceIntelligence
Intelligence has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, planning, emotional intelligence and problem solving....
have been proposed (such as being able to pass the Turing test
Turing test
The Turing test is a test of a machine's ability to exhibit intelligent behaviour. In Turing's original illustrative example, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All...
) but there is to date no definition that satisfies everyone. However, there is wide agreement among artificial intelligence researchers that intelligence is required to do the following:
- reasonAutomated reasoningAutomated reasoning is an area of computer science dedicated to understand different aspects of reasoning. The study in automated reasoning helps produce software which allows computers to reason completely, or nearly completely, automatically...
, use strategy, solve puzzles, and make judgments under uncertaintyUncertaintyUncertainty is a term used in subtly different ways in a number of fields, including physics, philosophy, statistics, economics, finance, insurance, psychology, sociology, engineering, and information science...
; - represent knowledgeKnowledge representationKnowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...
, including commonsense knowledge; - planAutomated planning and schedulingAutomated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are...
; - learnMachine learningMachine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...
; - communicate in natural languageNatural language processingNatural language processing is a field of computer science and linguistics concerned with the interactions between computers and human languages; it began as a branch of artificial intelligence....
; - and integrate all these skills towards common goals.
Other important capabilities include the ability to sense
Machine perception
In computing, machine perception is the ability of computing machines to sense and interpret images, sounds, or other contents of their environments, or of the contents of stored media....
(e.g. see
Computer vision
Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions...
) and the ability to act (e.g. move and manipulate objects
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...
) in the world where intelligent behaviour is to be observed. This would include an ability to detect and respond to hazard
Hazard
A hazard is a situation that poses a level of threat to life, health, property, or environment. Most hazards are dormant or potential, with only a theoretical risk of harm; however, once a hazard becomes "active", it can create an emergency situation. A hazard does not exist when it is not...
. Some sources consider "salience
Salience
Salience or saliency may refer to:* Salience , the state or quality of an item that stands out relative to neighboring items* Salience , relative importance or prominence of a piece of a sign...
" (the capacity for recognising importance) as an important trait. Salience is thought to be part of how humans evaluate novelty so are likely to be important in some degree, but not necessarily at a human level. Many interdisciplinary approaches to intelligence (e.g. cognitive science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
, computational intelligence
Computational intelligence
Computational intelligence is a set of Nature-inspired computational methodologies and approaches to address complex problems of the real world applications to which traditional methodologies and approaches are ineffective or infeasible. It primarily includes Fuzzy logic systems, Neural Networks...
and decision making
Decision making
Decision making can be regarded as the mental processes resulting in the selection of a course of action among several alternative scenarios. Every decision making process produces a final choice. The output can be an action or an opinion of choice.- Overview :Human performance in decision terms...
) tend to emphasise the need to consider additional traits such as imagination
Imagination
Imagination, also called the faculty of imagining, is the ability of forming mental images, sensations and concepts, in a moment when they are not perceived through sight, hearing or other senses...
(taken as the ability to form mental images and concepts that were not programmed in) and autonomy
Self-Determination Theory
Self-determination theory is a macro theory of human motivation and personality, concerning people's inherent growth tendencies and their innate psychological needs. It is concerned with the motivation behind the choices that people make without any external influence and interference...
.
Computer based systems that exhibit many of these capabilities do exist (e.g. see computational creativity
Computational creativity
Computational creativity is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence, cognitive psychology, philosophy, and the arts.The goal of computational creativity is to model, simulate or replicate creativity using a computer, to...
, decision support system
Decision support system
A decision support system is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in...
, robot
Robot
A robot is a mechanical or virtual intelligent agent that can perform tasks automatically or with guidance, typically by remote control. In practice a robot is usually an electro-mechanical machine that is guided by computer and electronic programming. Robots can be autonomous, semi-autonomous or...
, evolutionary computation
Evolutionary computation
In computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems....
, intelligent agent
Intelligent agent
In artificial intelligence, an intelligent agent is an autonomous entity which observes through sensors and acts upon an environment using actuators and directs its activity towards achieving goals . Intelligent agents may also learn or use knowledge to achieve their goals...
), but not yet at human levels.
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
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...
and the ethics of artificial intelligence
Ethics of artificial intelligence
The ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings. It is typically divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings,...
:
- consciousnessConsciousnessConsciousness is a term that refers to the relationship between the mind and the world with which it interacts. It has been defined as: subjectivity, awareness, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind...
: To have subjective experienceQualiaQualia , singular "quale" , from a Latin word meaning for "what sort" or "what kind," is a term used in philosophy to refer to subjective conscious experiences as 'raw feels'. Examples of qualia are the pain of a headache, the taste of wine, the experience of taking a recreational drug, or the...
and thoughtThought"Thought" generally refers to any mental or intellectual activity involving an individual's subjective consciousness. It can refer either to the act of thinking or the resulting ideas or arrangements of ideas. Similar concepts include cognition, sentience, consciousness, and imagination...
. - self-awarenessSelf-awarenessSelf-awareness is the capacity for introspection and the ability to reconcile oneself as an individual separate from the environment and other individuals...
: To be aware of oneself as a separate individual, especially to be aware of one's own thoughts. - sentienceSentienceSentience is the ability to feel, perceive or be conscious, or to have subjective experiences. Eighteenth century philosophers used the concept to distinguish the ability to think from the ability to feel . In modern western philosophy, sentience is the ability to have sensations or experiences...
: The ability to "feel" perceptions or emotions subjectively. - sapience: The capacity for wisdom.
These traits have a moral dimension, because a machine with this form of strong AI may have legal rights, analogous to the rights of animals
Animal rights
Animal rights, also known as animal liberation, is the idea that the most basic interests of non-human animals should be afforded the same consideration as the similar interests of human beings...
. Also, Bill Joy
Bill Joy
William Nelson Joy , commonly known as Bill Joy, is an American computer scientist. Joy co-founded Sun Microsystems in 1982 along with Vinod Khosla, Scott McNealy and Andy Bechtolsheim, and served as chief scientist at the company until 2003...
, 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
Consciousness is a term that refers to the relationship between the mind and the world with which it interacts. It has been defined as: subjectivity, awareness, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind...
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
Neural correlates of consciousness
The neural correlates of consciousness constitute the minimal set of neuronal events and mechanisms sufficient for a specific conscious percept. Neuroscientists use empirical approaches to discover neural correlates of subjective phenomena...
, would it automatically have self-awareness? It is also possible that some of these properties, such as sentience, naturally emerge
Emergence
In philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. Emergence is central to the theories of integrative levels and of complex systems....
from a fully intelligent machine, or that it becomes natural to ascribe these properties to machines once they begin to act in a way that is clearly intelligent. For example, intelligent action may be sufficient for sentience, rather than the other way around.
History of mainstream research into strong AI
Modern AI research began in the mid 1950s. The first generation of AI researchers were convinced that strong AI was possible and that it would exist in just a few decades. As AI pioneer Herbert SimonHerbert Simon
Herbert Alexander Simon was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics,...
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
Stanley Kubrick was an American film director, writer, producer, and photographer who lived in England during most of the last four decades of his career...
and Arthur C. Clarke
Arthur C. Clarke
Sir Arthur Charles Clarke, CBE, FRAS was a British science fiction author, inventor, and futurist, famous for his short stories and novels, among them 2001: A Space Odyssey, and as a host and commentator in the British television series Mysterious World. For many years, Robert A. Heinlein,...
's character HAL 9000
HAL 9000
HAL 9000 is the antagonist in Arthur C. Clarke's science fiction Space Odyssey saga. HAL is an artificial intelligence that interacts with the astronaut crew of the Discovery One spacecraft, usually represented as a red television-camera eye found throughout the ship...
, who accurately embodied what AI researchers believed they could create by the year 2001. Of note is the fact that AI pioneer Marvin Minsky
Marvin Minsky
Marvin Lee Minsky is an American cognitive scientist in the field of artificial intelligence , co-founder of Massachusetts Institute of Technology's AI laboratory, and author of several texts on AI and philosophy.-Biography:...
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,", although Minsky states that he was misquoted.
However, in the early 1970s, it became obvious that researchers had grossly underestimated the difficulty of the project. The agencies that funded AI became skeptical of strong AI and put researchers under increasing pressure to produce useful technology, or "applied AI". As the 1980s began, Japan's fifth generation computer
Fifth generation computer
The Fifth Generation Computer Systems project was an initiative by Japan'sMinistry of International Trade and Industry, begun in 1982, to create a "fifth generation computer" which was supposed to perform much calculation using massive parallel processing...
project revived interest in strong AI, setting out a ten year timeline that included strong AI goals like "carry on a casual conversation". In response to this and the success of expert systems, both industry and government pumped money back into the field. However, the market for 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 arrival of strong AI had been shown to be fundamentally mistaken about what they could accomplish. By the 1990s, AI researchers had gained a reputation for making promises they could not keep. AI researchers became reluctant to make any kind of prediction at all and avoid any mention of "human level" artificial intelligence, for fear of being labeled a "wild-eyed dreamer."
Current mainstream AI research
In the 1990s and early 21st century, mainstream AI has achieved a far higher degree of commercial success and academic respectability by focusing on specific sub-problems where they can produce verifiable results and commercial applications, such as neural nets, computer visionComputer vision
Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions...
or data mining
Data mining
Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...
. These "applied AI" applications are now used extensively throughout the technology industry and research in this vein is very heavily funded in both academia and industry.
Most mainstream AI researchers hope that strong AI can be developed by combining the programs that solve various subproblems using an integrated agent architecture
Agent architecture
Agent architecture in computer science is a blueprint for software agents and intelligent control systems, depicting the arrangement of components...
, cognitive architecture
Cognitive architecture
A cognitive architecture is a blueprint for intelligent agents. It proposes computational processes that act like certain cognitive systems, most often, like a person, or acts intelligent under some definition. Cognitive architectures form a subset of general agent architectures...
or subsumption architecture
Subsumption architecture
Subsumption architecture is a reactive robot architecture heavily associated with behavior-based robotics. The term was introduced by Rodney Brooks and colleagues in 1986...
. Hans Moravec
Hans Moravec
Hans Moravec is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University. He is known for his work on robotics, artificial intelligence, and writings on the impact of technology. Moravec also is a futurist with many of his publications and predictions focusing 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 that has been so frustratingly elusive in reasoning programs. Fully intelligent machines will result when the metaphorical golden spike
Golden spike
The "Golden Spike" is the ceremonial final spike driven by Leland Stanford to join the rails of the First Transcontinental Railroad across the United States connecting the Central Pacific and Union Pacific railroads on May 10, 1869, at Promontory Summit, Utah Territory...
is driven uniting the two efforts."
Artificial General Intelligence research
Artificial General Intelligence (AGI) describes research that aims to create machines capable of general intelligent action. The term was introduced by Mark Gubrud in 1997 in a discussion of the implications of fully automated military production and operations. The research objective is much older, for example Doug Lenat's CycCyc
Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning....
project (that began in 1984), and Allen Newell
Allen Newell
Allen Newell 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 of Psychology...
's Soar
Soar (cognitive architecture)
Soar is a symbolic cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University, now maintained by John Laird's research group at the University of Michigan. It is both a view of what cognition is and an implementation of that view through a...
project are regarded as within the scope of AGI. AGI research activity in 2006 was described by Pei Wang and Ben Goertzel
Ben Goertzel
Ben Goertzel , is an American author and researcher in the field of artificial intelligence. He currently leads Novamente LLC, a privately held software company that attempts to develop a form of strong AI, which he calls "Artificial General Intelligence"...
as "producing publications and preliminary results". As 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. In the introduction to his 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 consensus in the AGI research community seems to be that the timeline discussed by Ray Kurzweil
Raymond Kurzweil
Raymond "Ray" Kurzweil is an American author, inventor and futurist. He is involved in fields such as optical character recognition , text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments...
in "The Singularity is Near
The Singularity Is Near
The Singularity Is Near: When Humans Transcend Biology is a 2005 update of Raymond Kurzweil's 1999 book, The Age of Spiritual Machines and his 1990 book The Age of Intelligent Machines. In it, as in the two previous versions, Kurzweil attempts to give a glimpse of what awaits us in the near future...
" (i.e. between 2015 and 2045) is plausible. Most mainstream AI researchers doubt that progress will be this rapid. Organizations actively pursuing AGI include Adaptive AI
SmartAction
SmartAction is a company developing artificial intelligence technologies that was founded by inventor and entrepreneur Peter Voss.- History :The problem of developing artificial intelligence that learns the way humans do has challenged researchers since at least the 1940s...
, Artificial General Intelligence Research Institute (AGIRI)
Artificial General Intelligence Research Institute
Founded in 2001, the Artificial General Intelligence Research Institute's mission is to "foster the creation of powerful and ethically positive" Artificial General Intelligence. AGIRI hosts an online forum, publishes material on the development, application and implications for AGI, and hosts AGI...
, the Singularity Institute for Artificial Intelligence, Bitphase AI, and TexAI. One recent addition is Numenta
Numenta
Numenta is a company founded March 24, 2005, by Palm founder Jeff Hawkins with his longtime business partner Donna Dubinsky and Stanford graduate student Dileep George. It is headquartered in Redwood City, California.-Origin:...
, a project based on the theories of Jeff Hawkins
Jeff Hawkins
Jeffrey Hawkins is the founder of Palm Computing and Handspring...
, the creator of the Palm Pilot. While Numenta takes a computational approach to general intelligence, Hawkins is also the founder of the RedWood Neuroscience Institute, which explores conscious thought from a biological perspective. AND Corporation
AND Corporation
AND Corporation was incorporated in 1992. AND Corporation developed Holographic Neural Technology , the technology based upon complex-valued phase coherence/decoherence principles in the emulation of neurological learning and function. The company has been active primarily in the object recognition...
has been active in this field since 1990, and has developed machine intelligence processes based on phase coherence principles, having strong similarities to digital holography and QM with respect to quantum collapse of the wave function. Ben Goertzel
Ben Goertzel
Ben Goertzel , is an American author and researcher in the field of artificial intelligence. He currently leads Novamente LLC, a privately held software company that attempts to develop a form of strong AI, which he calls "Artificial General Intelligence"...
is pursuing an embodied AGI through the open-source OpenCog
OpenCog
OpenCog is a project that aims to build an open source artificial general intelligence framework. OpenCog Prime is a specific set of interacting components designed to give rise to human-equivalent artificial general intelligence...
project. Current code includes embodied virtual pets capable of learning simple English-language commands, as well as integration with real-world robotics, being done at the robotics lab of Hugo de Garis
Hugo de Garis
Hugo de Garis is a researcher in the sub-field of artificial intelligence known as evolvable hardware. He became known in the 1990s for his research on the use of genetic algorithms to evolve neural networks using three dimensional cellular automata inside field programmable gate arrays...
at Xiamen University
Xiamen University
Xiamen University , colloquially known as Xia Da , located in Xiamen, Fujian province, is the first university in China founded by overseas Chinese. Before 1949, it was originally known as the University of Amoy. The school motto is "Pursue Excellence, Strive for Perfection "...
.
Whole brain emulation
A popular approach discussed to achieving general intelligent action is whole brain emulation. A low-level brain model is built by scanning and mappingBrain mapping
Brain mapping is a set of neuroscience techniques predicated on the mapping of quantities or properties onto spatial representations of the brain resulting in maps.- Overview :...
a biological brain in detail and copying its state into a computer system or another computational device. The computer runs a simulation
Computer simulation
A computer simulation, a computer model, or a computational model is a computer program, or network of computers, that attempts to simulate an abstract model of a particular system...
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. Whole brain emulation is discussed in computational neuroscience
Computational neuroscience
Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system...
and neuroinformatics
Neuroinformatics
Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain...
, in the context of brain simulation for medical research purposes. It is discussed in artificial intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
research as an approach to strong AI. Neuroimaging
Neuroimaging
Neuroimaging includes the use of various techniques to either directly or indirectly image the structure, function/pharmacology of the brain...
technologies, that could deliver the necessary detailed understanding, are improving rapidly, and futurist Ray Kurzweil in the book "The Singularity Is Near
The Singularity Is Near
The Singularity Is Near: When Humans Transcend Biology is a 2005 update of Raymond Kurzweil's 1999 book, The Age of Spiritual Machines and his 1990 book The Age of Intelligent Machines. In it, as in the two previous versions, Kurzweil attempts to give a glimpse of what awaits us in the near future...
" predicts that a map of sufficient quality will become available on a similar timescale to the required computing power.
Processing requirements
Human brain
The human brain has the same general structure as the brains of other mammals, but is over three times larger than the brain of a typical mammal with an equivalent body size. Estimates for the number of neurons in the human brain range from 80 to 120 billion...
has a huge number of synapses. Each of the 1011 (one hundred billion) neurons has on average 7,000 synaptic connections 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 x 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) neuron updates per second. Kurzweil
Raymond Kurzweil
Raymond "Ray" Kurzweil is an American author, inventor and futurist. He is involved in fields such as optical character recognition , text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments...
looks at various estimates for the hardware required to equal the human brain and adopts a figure of 1016 computations per second (cps). He uses this figure to predict the necessary hardware will be available sometime between 2015 and 2025, if the current exponential growth in computer power continues.
Complications
The predictions outlined above are by no means guaranteed.A key fundamental criticism of the simulated brain approach derives from embodied cognition
Embodied cognition
Philosophers, psychologists, cognitive scientists and artificial intelligence researchers who study embodied cognition and the embodied mind believe that the nature of the human mind is largely determined by the form of the human body. They argue that all aspects of cognition, such as ideas,...
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 Second Life
Second Life
Second Life is an online virtual world developed by Linden Lab. It was launched on June 23, 2003. A number of free client programs, or Viewers, enable Second Life users, called Residents, to interact with each other through avatars...
), but it is not yet known whether this would be sufficient.
Desktop computers using 2 GHz Intel Pentium microprocessors and capable of more than 109 cps have been available since 2005. According to the brain power estimates used by Kurzweil
Raymond Kurzweil
Raymond "Ray" Kurzweil is an American author, inventor and futurist. He is involved in fields such as optical character recognition , text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments...
(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 at least three reasons for this.
- Firstly the neuron model seems to be oversimplified (see next section).
- Secondly there is insufficient understanding of higher cognitive processes to establish accurately what the neural activity observed using techniques such as functional magnetic resonance imaging correlates with.
- Thirdly, even if our understanding of cognition advances sufficiently, early simulation programs are likely to be very inefficient and will therefore need considerably more hardware.
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
Cerebral cortex
The cerebral cortex is a sheet of neural tissue that is outermost to the cerebrum of the mammalian brain. It plays a key role in memory, attention, perceptual awareness, thought, language, and consciousness. It is constituted of up to six horizontal layers, each of which has a different...
and 69 billion in the cerebellum
Cerebellum
The cerebellum is a region of the brain that plays an important role in motor control. It may also be involved in some cognitive functions such as attention and language, and in regulating fear and pleasure responses, but its movement-related functions are the most solidly established...
. Glial cell
Glial cell
Glial cells, sometimes called neuroglia or simply glia , are non-neuronal cells that maintain homeostasis, form myelin, and provide support and protection for neurons in the brain, and for neurons in other parts of the nervous system such as in the autonomous nervous system...
synapses are currently unquantified but are known to be extremely numerous.
Modelling the neurons in more detail
The artificial neuronArtificial neuron
An artificial neuron is a mathematical function conceived as a crude model, or abstraction of biological neurons. Artificial neurons are the constitutive units in an artificial neural network...
model assumed by Kurzweil
Raymond Kurzweil
Raymond "Ray" Kurzweil is an American author, inventor and futurist. He is involved in fields such as optical character recognition , text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments...
and used in many current artificial neural network
Artificial neural network
An artificial neural network , usually called neural network , is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes...
implementations is simple compared with biological neurons
Biological neuron model
A biological neuron model is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict biological processes...
. A brain simulation would likely have to capture the detailed cellular behaviour of biological neurons, presently only understood 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 a computer several orders of magnitude larger than Kurzweil
Raymond Kurzweil
Raymond "Ray" Kurzweil is an American author, inventor and futurist. He is involved in fields such as optical character recognition , text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments...
's estimate. In addition the estimates do not account for Glial cells which are at least as numerous as neurons, may outnumber neurons by as much as 10:1, and are now known to play a role in cognitive processes.
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
Artificial Intelligence System was a distributed 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 intelligence...
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
Blue Brain
The Blue Brain Project is an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level.The aim of the project, founded in May 2005 by the Brain and Mind Institute of the École Polytechnique Fédérale de Lausanne is to study the brain's architectural...
project used one of the fastest supercomputer architectures in the world, IBM
IBM
International Business Machines Corporation or IBM is an American multinational technology and consulting corporation headquartered in Armonk, New York, United States. IBM manufactures and sells computer hardware and software, and it offers infrastructure, hosting and consulting services in areas...
's Blue Gene
Blue Gene
Blue Gene is a computer architecture project to produce several supercomputers, designed to reach operating speeds in the PFLOPS range, and currently reaching sustained speeds of nearly 500 TFLOPS . It is a cooperative project among IBM Blue Gene is a computer architecture project to produce...
platform, to create a real time simulation of a single rat neocortical column
Neocortex
The neocortex , also called the neopallium and isocortex , is a part of the brain of mammals. It is the outer layer of the cerebral hemispheres, and made up of six layers, labelled I to VI...
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
Henry Markram
Henry Markram is Director of the Blue Brain Project at École Polytechnique Fédérale de Lausanne .He obtained his B.Sc. from Cape Town University, South Africa under the supervision of Rodney Douglas and his Ph.D. from the Weizmann Institute of Science, Israel, under the supervision of Menahem...
, director of the Blue Brain Project said in 2009 at the TED conference
TED (conference)
TED is a global set of conferences owned by the private non-profit Sapling Foundation, formed to disseminate "ideas worth spreading"....
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.
Moravec
Moravec
Moravec may refer to:* Moravec , a village in the Žďár nad Sázavou District of the Czech Republic* Moravec , a robot in the novel Ilium* Moravec , people with the surname Moravec...
addressed the above arguments ("brains are more complicated", "neurons have to be modeled in more detail") in his 1997 paper. 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.
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 AleksanderIgor Aleksander
Igor Aleksander FREng is an emeritus professor of Neural Systems Engineering in the Department of Electrical and Electronic Engineering at Imperial College London...
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
Language may refer either to the specifically human capacity for acquiring and using complex systems of communication, or to a specific instance of such a system of complex communication...
.
Origin of the term: John Searle's strong AI
The term "strong AI" was adopted from the name of a position in the philosophy of artificial intelligencePhilosophy of artificial intelligence
The philosophy of artificial intelligence attempts to answer such questions as:* Can a machine act intelligently? Can it solve any problem that a person would solve by thinking?...
first identified by John Searle
John Searle
John Rogers Searle is an American philosopher and currently the Slusser Professor of Philosophy at the University of California, Berkeley.-Biography:...
as part of his Chinese room
Chinese room
The Chinese room is a thought experiment by John Searle, which first appeared in his paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980...
argument in 1980. He wanted to distinguish between two different hypotheses about artificial intelligence:
- An artificial intelligence system can think and have a mind. (The word "mind" is has a specific meaning for philosophers, as used in "the mind body problem" or "the philosophy of mindPhilosophy of mindPhilosophy of mind is a branch of philosophy that studies the nature of the mind, mental events, mental functions, mental properties, consciousness and their relationship to the physical body, particularly the brain. The mind-body problem, i.e...
".) - An artificial intelligence system can (only) act like it thinks and has a mind.
The first one is called "the strong AI hypothesis" and the second is "the weak AI hypothesis" because the first one makes the stronger statement: it assumes something special has happened to the machine that goes beyond all its abilities that we can test. Searle referred to the "strong AI hypothesis" as "strong AI". This usage, which is fundamentally different than the subject of this article, is common in academic AI research and textbooks.
The term "strong AI" is now used to describe any artificial intelligence system that acts like it has a mind, regardless of whether a philosopher would be able to determine if it actually has a mind or not. As Russell
Stuart J. Russell
Stuart Russell is a computer scientist known for his contributions to artificial intelligence.Stuart Russell was born in Portsmouth, England. He received his Bachelor of Arts degree with first-class honours in Physics from Wadham College, Oxford in 1982, and his Ph.D. in Computer Science from...
and Norvig
Peter Norvig
Peter Norvig is an American computer scientist. He is currently the Director of Research at Google Inc.-Educational Background:...
write: "Most AI researchers take the weak AI hypothesis for granted, and don't care about the strong AI hypothesis." AI researchers are interested in a related statement:
- An artificial intelligence system can think (or act like it thinks) as well as or better than people do.
This assertion, which hinges on the breadth and power of machine intelligence, is the subject of this article.
Possible explanations for the slow progress of AI research
See alsoSince the launch of AI research in 1956, the growth of this field has slowed down over time and has stalled the aims of creating machines skilled with intelligent action at the human level. A possible explanation for this delay is that computers lack a sufficient scope of memory or processing power. In addition, the level of complexity that connects to the process of AI research may also limit the progress of AI research.
While most AI researchers believe that strong AI can be achieved in the future, there are some individuals like Hubert Dreyfus
Hubert Dreyfus
Hubert Lederer Dreyfus is an American philosopher. He is a professor of philosophy at the University of California, Berkeley....
and Roger Penrose
Roger Penrose
Sir Roger Penrose OM FRS is an English mathematical physicist and Emeritus Rouse Ball Professor of Mathematics at the Mathematical Institute, University of Oxford and Emeritus Fellow of Wadham College...
that deny the possibility of achieving AI. John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...
was one of various computer scientists who believe human-level AI will be accomplished, but a date cannot accurately be predicted.
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. 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".
Furthermore, AI researchers have been able to create computers that can perform jobs that are complicated for people to do, but conversely they have struggled to develop a computer that is capable of carrying out tasks that are simple for humans to do. A problem that is described by David Galernter is that some people assume that thinking and reasoning mean the same definition. However, the idea of whether thoughts and the creator of those thoughts are isolated individually has intrigued AI researchers.
The problems that have been encountered in AI research over the past decades have further impeded the progress of AI. The failed predictions that have been promised by AI researchers and the lack of a complete understanding of human behaviors have helped diminish the primary idea of human-level AI. Although the progress of AI research has brought both improvement and disappointment, most investigators have established optimism about potentially achieving the goal of AI in the 21st century.
Other possible reasons have been proposed for the lengthy research in the progress of strong AI. The intricacy of scientific problems and the need to fully understand the human brain through psychology and neurophysiology have limited many researchers from emulating the function of the human brain into a computer hardware. Many researchers tend to underestimate any doubt that is involved with future predictions of AI, but without taking those issues seriously can people then overlook solutions to problematic questions.
Clocksin says that a conceptual limitation that may impede the progress of AI research is that people may be using the wrong techniques for computer programs and implementation of equipment. When AI researchers first began to aim for the goal of artificial intelligence, a main interest was human reasoning. 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.
The practice of abstraction, which people tend to redefine when working with a particular context in research, provides researchers with a concentration 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 has posed questions about the involvement of abstraction operators.
A possible reason for the slowness in AI relates to the acknowledgement by many AI researchers that heuristics is a section that contains a significant breach between computer performance and human performance. The specific functions that are programmed to a computer may be able to account for many of the requirements that allow it to match human intelligence. These explanations are not necessarily guaranteed to be the fundamental causes for the delay in achieving strong AI, but they are widely agreed by numerous researchers.
There have been many AI researchers that debate over the idea whether 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. Emotion sums up the experiences of humans because it allows them to remember those experiences.
As David Gelernter writes, “No computer will be creative unless it can simulate all the nuances of human emotion.” This concern about emotion has posed problems for AI researchers and it connects to the concept of strong AI as its research progresses into the future.
See also
- History of artificial intelligenceHistory of artificial intelligenceThe history of artificial intelligence began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with "an ancient wish to forge the gods."...
- Marcus HutterMarcus HutterMarcus Hutter is a German computer scientist and professor at the Australian National University. Hutter was born and educated in Munich, where he studied physics and computer science...
's Universal Artificial Intelligence - Technological singularityTechnological singularityTechnological singularity refers to the hypothetical future emergence of greater-than-human intelligence through technological means. Since the capabilities of such an intelligence would be difficult for an unaided human mind to comprehend, the occurrence of a technological singularity is seen as...
aka "The Singularity" - Singularity Institute for Artificial Intelligence
- Artificial General Intelligence Research InstituteArtificial General Intelligence Research InstituteFounded in 2001, the Artificial General Intelligence Research Institute's mission is to "foster the creation of powerful and ethically positive" Artificial General Intelligence. AGIRI hosts an online forum, publishes material on the development, application and implications for AGI, and hosts AGI...
- Friendly AI
- Ethics of artificial intelligenceEthics of artificial intelligenceThe ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings. It is typically divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings,...
- Whole brain emulation (Mind uploading)
- Artificial Intelligence SystemArtificial Intelligence SystemArtificial Intelligence System was a distributed 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 intelligence...
A distributed computing attempt to simulate the brain via neural networking - AI-completeAI-completeIn the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to solving the central artificial intelligence problem—making computers as intelligent as people, or strong...
- Synthetic intelligenceSynthetic intelligenceSynthetic intelligence is an alternative term for artificial intelligence which emphasizes that the intelligence of machines need not be an imitation or any way artificial; it can be a genuine form of intelligence. John Haugeland proposes an analogy with artificial and synthetic diamonds—only the...
External links
- The AGI portal maintained by Pei Wang
- GPAI Project A Mass Collaboration for Strong AI
- AND Corporation - a neuromorphic model based on holographic neural processing
- Expanding Frontiers of Humanoid Robots
- AI lectures from Tokyo hosted by Rolf Pfeifer
- Artificial General Intelligence Research Institute
- The Genesis Group at MIT's CSAIL — Modern research on the computations that underlay human intelligence
- Essentials of general intelligence, article at Adaptive AI.
- OpenCog - open source project to develop a human-level AI
- Wiki of the Artificial General Intelligence Research Institute
- Problems with Thinking Robots
- www.eng.warwick.ac.uk
- Simulating logical human thought
- Texai, An open source project to create artificial intelligence
- The Game of Intelligent Design, An online game that promotes the development of artificial general intelligence
- The Practical Strong AI Project, A Practical approach and strategy for strong AI.