Artificial intelligence and emulation of intelligent behavior

Summary

Artificial intelligence is a branch of current knowledge, linked to computer science that positively and negatively affects all members of society, from this topic the relationship between technology, science and society can be explained from various points of view. Fundamentally two aspects coexist for the same concept, the most widespread being "Branch of computer science dedicated to the development of non-living rational agents". Mainly due to its literal meaning and to the extensive science fiction literature and filmography related to the subject, where most of them address futuristic worlds dominated by intelligent robots.And a second, more scientific aspect, which is why most scholars on the subject define artificial intelligence as other methods and algorithms for solving problems that have no solution, become very complex or demand a considerable use of resources through conventional methods.

INTRODUCTION

Rapid technological advances have allowed man to perform in a more efficient way, and it is this efficiency that, to a great extent, has produced a profound transformation of the instrumentation of society, and consequently, leads to new models of production and of social transformation.

However, progress is more than technological innovation and industrialization; it is more linked to the development of fundamental human freedoms, such as social and economic freedoms, than to technological development. In highly technical societies, man loses the ability to choose his own lifestyle because the work environment is increasingly complex, due to technological changes and the uncertainty that this fact causes.

Technological changes, since ancient times, had generally tended to facilitate human work, replacing physical strength with the mental capacity and intelligence of the workers. At present, the development achieved by computer products tends to also replace the more routine and mechanical part of human mental activity by the work of computers.

In the present age, all aspects of culture are so tied to technology that it is technology that determines the future of humanity as never before. The new information technologies still have a potential for sociocultural change and transformation that today can only be glimpsed roughly.

Technological advancement can bring serious consequences such as unemployment, veneration and submission on the part of the human. It cannot be denied that Artificial Intelligence would bring great advantages to man; but you must also be aware of its negative implications.

The development of technology has been throughout history the modernizing element of the productive apparatus, of society. However, one should not fall into exaggerated optimism when thinking that the mere introduction of these technologies will automatically produce the miracle of transforming the quality of life.

Currently there is a mismatch between the organization of our societies and the expectations produced by the recognition of our own technological capabilities. We live in societies of the past with futuristic expectations, excessive, misunderstood, arcane and fed by a development that we cannot fully assimilate, since it occurs much faster than our own social evolution.

Only when it is possible to balance social transformations with scientific and technological advance will a healthy nature be achieved, which is not in permanent opposition to artificiality.

That is why the effects of science in society must be studied in depth not only in today's society, but also the effects on future society. In traditional societies there was a harmony between nature, society and man.

OBJECTIVES

GENERAL OBJECTIVES

Explain the relationship between technology, science and society that is included in the topic of Artificial intelligence in Computer Science.

Know and make known through written argumentation, the different criteria of the future of artificial intelligence in order to create reflection in the public.

SPECIFIC OBJECTIVES

Know and express all aspects of the selected topic in an argumentative way. Emphasize the relationship between technology, science and society. Know and translate the different criteria about artificial intelligence. Create a controversial essay that leads to reflection.

Chronological history of Artificial Intelligence

· The most basic ideas go back to the Greeks, before Christ. Aristotle (384-322 BC) was the first to describe a set of rules that describe a part of the mind's workings to obtain rational conclusions, and Ktesibios of Alexandria (250 BC) built the first self-controlled machine, a water flow regulator (rational but without reasoning).

· In 1290 Ramon Llull in his book Ars magna had the idea that reasoning could be carried out artificially.

· In 1936 Alan Turing formally designs a universal Machine that demonstrates the viability of a physical device to implement any formally defined computation.

· In 1943 Warren McCulloch and Walter Pitts presented their artificial neuron model, which is considered the first work in the field, even though the term did not yet exist. The first important advances began in the early 1950s with the work of, from which science has gone through various situations.

· In 1955 Herbert Simon, Allen Newell and JC Shaw, developed the first programming language oriented to solving problems, IPL-11. A year later they develop the Logic Theorist, which was able to prove mathematical theorems.

In 1956 the term artificial intelligence was invented by John McCarthy, Marvin Minsky and Claude Shannon at the Dartmouth Conference, a congress at which triumphalist ten-year forecasts were made that were never fulfilled, leading to the almost total abandonment of investigations for fifteen years..

· In 1957 Newell and Simon continued their work with the development of the General Problems Solver (GPS). GPS was a troubleshooting oriented system.

· In 1958 John McCarthy developed the LISP at the Massachusetts Institute of Technology (MIT). Its name is derived from LISt Processor. LISP was the first language for symbolic processing.

· In 1959 Rosenblatt introduces the Perceptron.

· In the late 50s and early 60s Robert K. Lindsay develops Sad Sam, a program for reading sentences in English and inference of conclusions from their interpretation.

· In 1963 Quillian developed semantic networks as a model for the representation of knowledge.

· In 1964 Bertrand Raphael built the SIR (Semantic Information Retrieval) system which was capable of inferring knowledge based on the information supplied to him. Bobrow develops STUDENT.

· Later, between 1968-1970, Terry Winograd developed the SHRDLU system, which made it possible to interrogate and give orders to a robot that moved within a world of blocks.

· In the mid-1960s, expert systems appear, which predict the probability of a solution under a set of conditions. For example DENDRAL, started in 1965 by Buchanan, Feigenbaum and Lederberg, the first Expert System, which assisted chemists in complex Euclidean chemical structures, MACSYMA, which assisted engineers and scientists in solving complex mathematical equations.

· In 1968 Minsky publishes Semantic Information Processing.

· In 1968 Seymour Papert, Danny Bobrow and Wally Feurzeig, developed the LOGO programming language.

In 1969 Alan Kay developed the Smalltalk language at Xerox PARC and was published in 1980.

· In 1973 Alain Colmenauer and his research team at the University of Marseilles created PROLOG (PROgramming in LOGic), a programming language widely used in AI.

· In 1973 Shank and Abelson developed the scripts, or scripts, pillars of many current techniques in Artificial Intelligence and computer science in general.

· In 1974 Edward Shortliffe wrote his thesis with MYCIN, one of the best known Expert Systems, which assisted physicians in the diagnosis and treatment of infections in the blood.

· In the 1970s and 1980s, the use of expert systems grew, such as MYCIN: R1 / XCON, ABRL, PIP, PUFF, CASNET, INTERNIST / CADUCEUS, etc. Some remain until today (shells) like EMYCIN, EXPERT, OPSS.

· In 1981 Kazuhiro Fuchi announced the Japanese project for the fifth generation of computers.

In 1986 McClelland and Rumelhart's published Parallel Distributed Processing (Neural Networks).

· In 1988 Object Oriented languages were established.

· In 2006 the anniversary was celebrated with the Congress in Spanish 50 years of Artificial Intelligence - Multidisciplinary Campus in Perception and Intelligence 2006 50 years of Artificial Intelligence - Multidisciplinary Campus in Perception and Intelligence 2006.

· In 2009, intelligent therapeutic systems are already under development that allow detecting emotions in order to interact with autistic children.

Applications of artificial intelligence

Computational linguistics Data Mining Industrial Medical Virtual worlds Natural Language Processing Robotics Decision support systems Video games Computer prototypes

Artificial Intelligence Relates to:

HeuristicsSmart SystemsArtificial VisionNatural Language ProcessingNeural NetworksRoboticsSearchPlanning

HEURISTICS Heuristics is the analysis and extrapolation of data based on past experiences and their consequences, this section is of vital importance for internal AI in computer games.

EXPERT SYSTEMS An expert system can be defined as a knowledge-based system that mimics the thinking of an expert to solve problems in a particular field of application. One of the main characteristics of expert systems is that they are rule-based, that is, they contain predefined knowledge that is used to make all decisions.

NEURONAL NETWORKS Neural networks are devices inspired by the functionality of biological neurons, applied to the recognition of patterns that make them suitable for modeling and making predictions in very complex systems. ROBOTICS They are machines controlled by computer and programmed to move, manipulate objects and enhance work while interacting with their environment. Robots are capable of performing repetitive tasks faster, cheaper, and more accurately than humans.

HOME AUTOMATION The Larousse encyclopedia defines the term Home Automation as: the concept of a home that integrates all automation in matters of security, energy management, communications, etc. The scientific term used to name the part of technology (electronics and computing), which integrates the control and supervision of the existing elements in an office building or one of houses or simply in any home. Also, a very familiar term for everyone is that of intelligent building that although it comes to refer to the same thing, normally we tend to apply it more to the field of large office blocks, banks, universities and industrial buildings.

What is Artificial Intelligence

The concept of AI is still too diffuse, contextualizing and controversial

Artificial Intelligence is a term that, in its broadest sense, would indicate the ability of an artifact to perform the same types of functions that characterize human thought. The possibility of developing such an artifact has aroused man's curiosity since ancient times; however, the workings of the human mind have yet to be fully understood, and consequently computer design will remain essentially incapable of reproducing these unknown and complex processes.

To explain the above definition, an agent is understood as anything capable of perceiving its environment (receiving inputs), processing such perceptions and acting on its environment (providing outputs). And rationality is understood as the characteristic that has a choice to be correct, more specifically, to tend to maximize an expected result. (This concept of rationality is more general and therefore more adequate than intelligence to define the nature of the objective of this discipline).

Obviously, this game restricts the definition of Artificial Intelligence to a mere imitation of human behavior, it does not matter if a machine is intelligent or not, as long as it seems so and this is possible with the appropriate algorithm. Artificial Intelligence is a very nice marketing name. “In reality it is a toolbox, of computational techniques that are not aimed at making the computer think like us, that the label is simply a metaphor. (IA Alberto Bugarín, member of the Spanish Association for Artificial Intelligence www.aepia.org); others believe that it is necessary to find acceptable definitions of intuition, creativity, learning ability, strategy and other essentially human characteristics, to try to translate them into a computer program.

Regarding the current definitions of artificial intelligence (AI), there are authors such as Rich & Knight, Stuart, who generally define AI as the ability of machines to perform tasks that are currently performed by human beings; other authors such as Nebendah, Delgado, provide more complete definitions and define them as the field of study that focuses on the explanation and emulation of intelligent behavior based on computational processes based on experience and continuous knowledge of the environment.

Both ways of facing the same problem coexist without conflict in the groups that investigate artificial intelligence.

One of the activities that has developed the most in the last fifty years is Technology. Currently, devices that are capable of self-regulation, that is, of modifying their operation according to certain variables in the environment, are trivially incorporated into almost all everyday appliances; for example, a thermostat that regulates the on or off of a heater, depending on the temperature of the room. Obviously, no reasonably reasonable person will ever say that a thermostat heater is intelligent, and yet the ability to observe the environment and act accordingly is one of the main traits of intelligence. Is it then possible to build a mechanical or electrical device that is really intelligent? The answer to this question is difficult. First,intelligence must be defined, as it is clear that it is more than the capacity for self-regulation. Or, it is possible to start building devices that are capable of logically performing complex tasks, according to certain operating parameters, without having to ask a question as philosophical as the one before us. Both lines of action have been in operation for several decades.

Thus, what has come to be called expert systems engineering was born: machines that make simple decisions from a wide range of possibilities stored in their memory. MYCIN, in 1974, was one of the first expert systems used successfully: using blood samples it diagnosed certain bacterial infections and suggested appropriate treatments, of course, under medical supervision.

At present, such systems, which occupy a very important part of the activity in artificial intelligence, are used in a variety of fields, ranging from the regulation of urban traffic to the routine operation of a space station. Therefore, without the need to consider what intelligence is, machines can be built that, although they cannot be properly called intelligent, at least it is possible to qualify them as very reasonable.

Why can't they be called smart?

Due to the very uncertainty of intelligence: it is a quality that we consider exclusively human - although there are those who believe that certain animals, and some of the machines that are currently being built, possess it, at least to some extent. This quality, in a very simplified way, is reflected in the so-called intellectual coefficient, a number that indicates the mental capacity of an individual, in relation to his biological age, through a series of psychological tests in which certain abilities that are They are acquiring, to a greater or lesser extent, throughout life; characteristics such as the capacity for abstraction, the resolution of numerical problems or the capacity for verbal comprehension. This test is, logically, inapplicable to machines: the simplest of computers can perform, in a few seconds,complicated mathematical calculations that only an army of experienced mathematics professors would be able to solve; although, on the other hand, this same machine would be incapable of understanding the meaning of the expression the apple is tasty, something that any four-year-old child masters. For all these reasons, it is difficult to know when a machine can be properly called intelligent. Alan Turing proposed, already in the 50s, an ingenious test to know if a machine was intelligent or not; In an article entitled Intelligence and computational machinery, he proposed a game: an observer interacts with a machine and a man, in such a way as to make it unnecessary for the machine to have to imitate the human voice or appearance. The observer asks both questions, whatever he wishes,and both man and machine must try to persuade the observer that they are human.

Obviously, this game restricts the definition of intelligence to a mere imitation of human behavior. However, a person can make mistakes in a mathematical calculation - something a computer would never do, unless it is programmed to deceive the observer - and still be intelligent; on the other hand, a machine that does not know enough about human beings to imitate them would not pass the test, and it would not have to be intelligent.

Although the imitation of human intelligence is one of the research areas of artificial intelligence, in many other cases better results are achieved using the enormous data processing capacity of computers, outside the reach of ordinary humans. Consider, for example, chess, a game that requires (in equal parts) great brainpower and high doses of creativity, and how the Russian champion Gary Kasparov was defeated by Deep Blue, a fantastic computer built by the American firm IBM, which used only a colossal memory and a calculation capacity of billions of variants for each position, several orders of magnitude greater than the mental capacity of the most brilliant of mortals.The world champion of a creative discipline was defeated by the brute force of algorithm outright. Thus, compared to those who believe that, even ignoring the exact type of mental process that a chess player performs, it is always possible to simulate it with a sufficient degree of approximation by means of the appropriate algorithm, in short, that it does not matter whether a machine is intelligent or not, as long as it seems.

Thus, it is not surprising that, together with teams of engineers that develop and perfect a large number of three-dimensional vision sensors, chemical sensors that mimic the smell and touch sensors that allow to dose the force used in the manipulation of objects, According to their weight and fragility, other teams work on the mechanisms of perception, trying to develop computer programs that allow a machine to recognize three-dimensional objects, in the development of learning programs that allow a machine to function according to its own experience. Fuzzy logic is also investigated, the one that underlies common speech, that is, the one that allows making statements as little demonstrable as that of the tasty apple,or others like this person is more attractive than this other or Juan is short, so that the interaction between a machine and a person can be carried out in the most natural way possible. Likewise, programs are developed that allow the use of symbolic language, which allows not to define, but to infer conclusions from incomplete data or based on the use of analogies. Another interesting field in which it is investigated is the use of so-called genetic algorithms, which use certain calculations to extract, from a set of premises and with insufficient data, the conclusion of higher statistical probability. It is also investigated in the development of neural networks, devices that try to interconnect a large number of chips,mimicking synaptic connections in the human brain, believing that intelligence can be better rebuilt in this way. And many other scientific disciplines collaborate in the construction of intelligent machines.

However, there will always be irreducible and fanatical spirits who believe that it is possible to achieve a truly intelligent machine, which will not be left with a human trait of intelligence that is difficult to convert into a series of algorithms, be it creativity or anything else.

Albert Einstein - who could well be chosen as the most intelligent person in history, in a hypothetical global consultation - affirmed it with a devastating aphorism, one of those that remains for later reflection: Machines can solve problems, but problems can never be raised.

Artificial Intelligence and Society

The Wachowski brothers opened the eyes of millions of viewers to the film “Matrix where computer programs manipulated human lives. The trilogy added to the 20th century cinephile tribute to Artificial Intelligence. For the scientific community, however, these films as well as Steven Spielberg's "Artificial Intelligence" have shown a distorted view of AI, by equating the intelligence of a machine to that of a human.

Today, reality is millions of light years distant from fiction. But in the future… Will there ever be machines whose intelligence equals that of human beings?

Almost all universities in the world have departments or research groups dedicated to various branches related to AI, a name that scientists prefer to replace with artificial neural networks or cognitive mechanisms. Or simply other troubleshooting methods. Its applications are multiple, predominantly engineering processes for ship sail design, submarine control, patient monitoring or semantic or medical work.

Technology has raised various paradigms that lead to the exhaustion of theories and practical experimentation, but there are exciting themes that despite defeats, develop an interest not only in scientists but also in the rest of society. At this level is artificial intelligence defined as "The science that focuses its study to achieve the understanding of intelligent entities." It is clear that computers that have intelligence at the human level, or higher that can reach our human capacity and even replace or dominate us, will have very important implications in our daily life and in society.

There are currently two trends in the development of AI systems: expert systems and neural networks. Expert systems try to reproduce human reasoning in a symbolic way, through formulas and logisms such as binary code. Neural networks do it from a more biological perspective (they recreate the structure of a human brain using genetic algorithms). Despite the complexity of both systems, the results are far from an authentic intelligent thought, since they only become the reproduction of specific functions and not the reasoning and complex thinking that characterizes man.

True artificial intelligence will be evident when we are not able to distinguish between a human being and a computer program in a blind conversation. It should be thought that when machines reach our mental capacity, they will have human characteristics such as learning, adaptation, reasoning, self-correction, implicit improvement, and model perception of the world. Thus, it is possible to speak not only of one objective, but of many depending on the point of view or utility that can be found to the so-called artificial intelligence.

It cannot be denied that artificial intelligence would bring great advantages to man and would mark a milestone in history; but you must also be aware of its negative implications. For example, unemployment, man would be totally replaced by machines that would produce even faster and with less complications, since they would not mix personal life with work life as man usually does, they would be excellent producers, and in an eminently capitalist world that is enough to survive and gain power.

At the moment, a reassuring fact is not knowing how the human brain works, this makes some AI emulations look like <>, put another way:

“It is as if we were blindfolded to see how we could create something that we do not even know well as it is and we began to test with some tiles of this huge puzzle of 100,000 million pieces of which I believe, we barely have 100… and we do not know if they fit each other… ”(Wilson. 2005) ³.

However, you have to think that even if the perfect imitation of human thought is not achieved, the fact of creating objects that can replace us in the sometimes banal situations of daily life already transforms society, the lifestyle and the organization that so much it has cost to maintain.

How intelligent systems will influence the life of humanity tomorrow, what role will these strange mechanisms, created by man himself almost in his image and likeness, play in a more or less distant future, who would say that one day a machine would be compared similar to the human was able to perform activities with such accuracy, and reliability and that it replaced his work, we do not know but it is a fact that will occur therefore there is nothing left but to prepare ourselves for future trends in humanity.

CONCLUSIONS

1. Two ways of interpreting artificial intelligence coexist.

· The definition of Artificial Intelligence is restricted to a mere imitation of human behavior, it does not matter if a machine is intelligent or not, as long as it seems so.

· Other methods of Problem Solving, which would not have a solution with conventional algorithms.

2. The ability of a machine to think and act like man in the technological field of Artificial Intelligence is one of the areas that causes the greatest expectation, even within society in general, due to the fact that the search to understand the mechanisms of intelligence has been the philosopher's stone in the work of many scientists for many years and still is.

3. Technological advancement can bring great changes to society. It cannot be denied that the use of artificial intelligence would bring great advantages for man, improving the quality of life; transforming society and the way in which man interacts with it, but one must also be aware of its negative implications such as the disappearance of jobs that involve both physical and mental efforts and the creation of others linked to new technologies.

4. We all know that technological evolution has been very important in recent years. Making a small visualization in the future, it becomes evident that the impact that the different telecommunication services, computing and especially artificial intelligence or intelligent systems will have are derived from that evolution, in the lives of citizens will be increasingly important.

5. Internet access will be faster and faster, television will become digital and interactive, the new operators will offer interesting alternatives to basic telephony, home automation will fully enter homes, and through the intelligent systems that some are already in place. gear in medicine, industry, agriculture.

6. Within society in general, Artificial Intelligence is one of the sciences that causes the greatest impact, machine learning, the process of performing intelligent behaviors being important, that a system can improve its behavior based on experience through process of repetitive tasks and that in addition to having a notion of what a mistake is and how to avoid it, it is very interesting.

BIBLIOGRAPHY

AEPIA “Ibero-American Magazine of Artificial Intelligence” in. Edited and published: Spanish Association for Artificial Intelligence (AEPIA) Spain, 1997

ALAVA, Jon. "Artificial intelligence" in. October 1998

LÓPEZ, Jhony C. “Artificial Intelligence” at https://es.wikipedia.org/wiki/Inteligencia_artificial. 2006

REYES, Gary "Artificial Intelligence Project" at. Guayaquil University. Ecuador, 2001

SERRANO AND SÁNCHEZ. "Artificial intelligence subportal" at http://ciberconta.unizar.es/docencia/intelig/. University of Zaragoza, 2004

WILSON, Daniel. How to survive a robot uprising. U.S. Carnegie University. 2005

ZACCAGNINI, JL, ALONSO, G. and CABALLERO, A.: Artificial intelligence from promising innovation to practical reality. In Double Game, n °. 29, December, 1992, pp. 22-30.

FILMS:

PROJAS, Alex. I robot. Twentieth century fox. United States, 2004

SPIELBERG, Steven. Artificial intelligence. United States, 2001

WEBGRAPHY.

www.eumed.net/eve/resum/07-febrero/egr.htm

html.rincondelvago.com/avances-tecnologicos.html

www.monografias.com/trabajos37/inteligencia-artificial/inteligencia-artificial2.shtml