Q. What is artificial intelligence?
A. It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.
Q. Yes, but what is intelligence?
A. Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines.
Q. Isn’t there a solid definition of intelligence that doesn’t depend on relating it to human intelligence?
A. Not yet. The problem is that we cannot yet characterize in general what kinds of computational procedures we want to call intelligent. We understand some of the mechanisms of intelligence and not others.
Q. Is intelligence a single thing so that one can ask a yes or no question “Is this machine intelligent or not?”?
A. No. Intelligence involves mechanisms, and AI research has discovered how to make computers carry out some of them and not others. If doing a task requires only mechanisms that are well understood today, computer programs can give very impressive performances on these tasks. Such programs should be considered “somewhat intelligent”.
Q. Isn’t AI about simulating human intelligence?
A. Sometimes but not always or even usually. On the one hand, we can learn something about how to make machines solve problems by observing other people or just by observing our own methods. On the other hand, most work in AI involves studying the problems the world presents to intelligence rather than studying people or animals. AI researchers are free to use methods that are not observed in people or that involve much more computing than people can do.
Q. What about IQ? Do computer programs have IQs?
A. No. IQ is based on the rates at which intelligence develops in children. It is the ratio of the age at which a child normally makes a certain score to the child’s age. The scale is extended to adults in a suitable way. IQ correlates well with various measures of success or failure in life, but making computers that can score high on IQ tests would be weakly correlated with their usefulness. For example, the ability of a child to repeat back a long sequence of digits correlates well with other intellectual abilities, perhaps because it measures how much information the child can compute with at once. However, “digit span” is trivial for even extremely limited computers. However, some of the problems on IQ tests are useful challenges for AI.
Q. What about other comparisons between human and computer intelligence?
Arthur R. Jensen [Jen98], a leading researcher in human intelligence, suggests “as a heuristic hypothesis” that all normal humans have the same intellectual mechanisms and that differences in intelligence are related to “quantitative biochemical and physiological conditions”. I see them as speed, short term memory, and the ability to form accurate and retrievable long term memories. Whether or not Jensen is right about human intelligence, the situation in AI today is the reverse. Computer programs have plenty of speed and memory but their abilities correspond to the intellectual mechanisms that program designers understand well enough to put in programs. Some abilities that children normally don’t develop till they are teenagers may be in, and some abilities possessed by two year olds are still out. The matter is further complicated by the fact that the cognitive sciences still have not succeeded in determining exactly what the human abilities are. Very likely the organization of the intellectual mechanisms for AI can usefully be different from that in people. Whenever people do better than computers on some task or computers use a lot of computation to do as well as people, this demonstrates that the program designers lack understanding of the intellectual mechanisms required to do the task efficiently.
Q. When did AI research start?
A. After WWII, a number of people independently started to work on intelligent machines. The English mathematician Alan Turing may have been the first. He gave a lecture on it in 1947. He also may have been the first to decide that AI was best researched by programming computers rather than by building machines. By the late 1950s, there were many researchers on AI, and most of them were basing their work on programming computers.
Q. Does AI aim to put the human mind into the computer?
A. Some researchers say they have that objective, but maybe they are using the phrase metaphorically. The human mind has a lot of peculiarities, and I’m not sure anyone is serious about imitating all of them.
Q. What is the Turing test?
A. Alan Turing’s 1950 article Computing Machinery and Intelligence [Tur50] discussed conditions for considering a machine to be intelligent. He argued that if the machine could successfully pretend to be human to a knowledgeable observer then you certainly should consider it intelligent. This test would satisfy most people but not all philosophers. The observer could interact with the machine and a human by teletype (to avoid requiring that the machine imitate the appearance or voice of the person), and the human would try to persuade the observer that it was human and the machine would try to fool the observer. The Turing test is a one-sided test. A machine that passes the test should certainly be considered intelligent, but a machine could still be considered intelligent without knowing enough about humans to imitate a human. Daniel Dennett’s book Brainchildren [Den98] has an excellent discussion of the Turing test and the various partial Turing tests that have been implemented, i.e. with restrictions on the observer’s knowledge of AI and the subject matter of questioning. It turns out that some people are easily led into believing that a rather dumb program is intelligent.
Q. Does AI aim at human-level intelligence?
A. Yes. The ultimate effort is to make computer programs that can solve problems and achieve goals in the world as well as humans. However, many people involved in particular research areas are much less ambitious.
Q. How far is AI from reaching human-level intelligence? When will it happen?
A. A few people think that human-level intelligence can be achieved by writing large numbers of programs of the kind people are now writing and assembling vast knowledge bases of facts in the languages now used for expressing knowledge. However, most AI researchers believe that new fundamental ideas are required, and therefore it cannot be predicted when human-level intelligence will be achieved.
Q. Are computers the right kind of machine to be made intelligent?
A. Computers can be programmed to simulate any kind of machine. Many researchers invented non-computer machines, hoping that they would be intelligent in different ways than the computer programs could be. However, they usually simulate their invented machines on a computer and come to doubt that the new machine is worth building. Because many billions of dollars that have been spent in making computers faster and faster, another kind of machine would have to be very fast to perform better than a program on a computer simulating the machine.
Q. Are computers fast enough to be intelligent?
A. Some people think much faster computers are required as well as new ideas. My own opinion is that the computers of 30 years ago were fast enough if only we knew how to program them. Of course, quite apart from the ambitions of AI researchers, computers will keep getting faster.
Q. What about parallel machines?
A. Machines with many processors are much faster than single processors can be. Parallelism itself presents no advantages, and parallel machines are somewhat awkward to program. When extreme speed is required, it is necessary to face this awkwardness.
Q. What about making a “child machine” that could improve by reading and by learning from experience?
A. This idea has been proposed many times, starting in the 1940s. Eventually, it will be made to work. However, AI programs haven’t yet reached the level of being able to learn much of what a child learns from physical experience. Nor do present programs understand language well enough to learn much by reading.
Q. Might an AI system be able to bootstrap itself to higher and higher level intelligence by thinking about AI?
A. I think yes, but we aren’t yet at a level of AI at which this process can begin.
Q. What about chess?
A. Alexander Kronrod, a Russian AI researcher, said “Chess is the Drosophila of AI.” He was making an analogy with geneticists’ use of that fruit fly to study inheritance. Playing chess requires certain intellectual mechanisms and not others. Chess programs now play at grandmaster level, but they do it with limited intellectual mechanisms compared to those used by a human chess player, substituting large amounts of computation for understanding. Once we understand these mechanisms better, we can build human-level chess programs that do far less computation than do present programs. Unfortunately, the competitive and commercial aspects of making computers play chess have taken precedence over using chess as a scientific domain. It is as if the geneticists after 1910 had organized fruit fly races and concentrated their efforts on breeding fruit flies that could win these races. ChatGPT Created with AIPRM Prompt “Human-like Rewriter – V1.6”
Q. What constitutes artificial intelligence?
A. It signifies the craft and study of fabricating machines of sagacity, particularly sagacious computer programs. It’s akin to the endeavor of employing computers to grasp human intellect, albeit AI isn’t restricted to methods that are biologically discernible.
Q. Indeed, but could you delineate intelligence?
A. Intelligence embodies the computational facet of the aptitude to fulfill objectives in the cosmos. Varied manifestations and magnitudes of intelligence are observed among humans, numerous fauna, and a selection of machines.
Q. Is there not a definitive description of intelligence that eschews comparison to human intellect?
A. As of now, such a definition eludes us. The quandary lies in our inability to universally delineate what computational processes ought to be labeled as intelligent. We comprehend fragments of the mechanisms of intelligence, yet others remain enigmatic.
Q. Is intelligence a monolithic entity, allowing for a straightforward inquiry into whether a machine possesses intelligence or not?
A. Negative. Intelligence comprises mechanisms, and AI inquiry has unraveled methods to program computers to execute certain of these mechanisms but not others. If a task necessitates only mechanisms that are currently well-understood, computer programs can exhibit exceedingly adept performances at these tasks. Such programs ought to be deemed “somewhat intelligent.”
Q. Isn’t AI concerned with emulating human intelligence?
A. On occasion, yet not invariably or predominantly. On one side, observing others or introspecting on our own problem-solving methods can offer insights into crafting machines that solve puzzles. Conversely, the bulk of AI research is dedicated to tackling the challenges presented to intelligence by the external world, rather than studying humans or animals. AI researchers are at liberty to employ methods unobserved in humans or those that necessitate more computation than humans are capable of.
Q. What about IQ? Do computer programs possess IQs?
A. No. IQ gauges the pace at which intelligence evolves in children, comparing the age a child typically achieves a certain score to their chronological age. This metric correlates with various life outcomes, yet programming computers to excel on IQ tests would only weakly relate to their utility. For instance, a child’s ability to recite a lengthy sequence of digits correlates with other cognitive capabilities, possibly because it measures the volume of information the child can process simultaneously. However, this “digit span” is trivial for even the most basic computers. Nonetheless, certain challenges on IQ tests present useful conundrums for AI.
Q. How do other comparisons between human and computer intelligence fare?
Arthur R. Jensen, a preeminent scholar of human intelligence, posits “as a heuristic hypothesis” that all normal humans share identical intellectual mechanisms, with differences in intelligence linked to “quantitative biochemical and physiological conditions.” He identifies these as speed, short-term memory, and the capacity to forge accurate and retrievable long-term memories. Whether Jensen’s hypothesis holds for human intelligence, the current state of AI is the antithesis. Computer programs boast ample speed and memory, yet their capabilities mirror the intellectual mechanisms that their creators sufficiently comprehend to encode. Abilities that typically manifest in adolescents may be programmed, while some that emerge in toddlers remain elusive. This complexity is compounded by the cognitive sciences’ ongoing struggle to precisely identify human capabilities. Likely, the configuration of intellectual mechanisms for AI could beneficially diverge from human architecture. Whenever humans outperform computers at a task or when computers require significant computation to match human performance, it underscores the program designers’ incomplete grasp of the intellectual mechanisms essential for efficient task execution.
Q. When did AI research commence?
A. Post-WWII, several individuals independently embarked on crafting intelligent machines. The British mathematician Alan Turing might have been the pioneer, delivering a lecture on the subject in 1947. He possibly was also the first to deduce that AI research would prosper through computer programming rather than constructing physical machines. By the late 1950s, a burgeoning community of AI researchers had emerged, predominantly focusing on computer programming.
Q. Is the goal of AI to transplant the human mind into the computer?
A. Some researchers express this ambition, though perhaps metaphorically. The human mind is replete with peculiarities, and it’s dubious that anyone is earnestly endeavoring to replicate them all.
Q. What is the Turing test?
A. Alan Turing’s 1950 treatise “Computing Machinery and Intelligence” contemplates the criteria for a machine’s intelligence. He proposed that if a machine could convincingly masquerade as human to an informed observer, then it unequivocally merits the label of intelligent. This criterion might satisfy the majority, yet not all philosophers.
