The Impact of Artificial Intelligence Technology has advanced at an exponential rate. Computers were invented not too long ago and we can see how in just a few decades computers have a lot more capabilities, store more memory, perform more task, and in a less amount of time, come in smaller sizes, and are portable. Artificial Intelligence has brought much anticipation in society and scientists, researchers, and inventors are working hard to create such. There have been promises of many different inventions that will make life easier and better for humankind and at the rate they are going one can see that it will happen.
People’s life has changed dramatically and it has become dependent on the artificial intelligence that they have today, it is a wonder as to how much it will change society with the success of truly inventing artificial intelligence that can reason logically and master human language. Before we go any further, let’s take a look at the history behind artificial intelligence. Evidence of Artificial Intelligence folklore can be traced back to ancient Egypt, but with the development of the electronic computer in 1941, developed in both the U. S. and Germany, the technology finally became available to create machine intelligence.
The first computer required large, separate air-conditioned rooms, and involved the separate configuration of thousands of wires to get the program started. In 1949 a better version of the computer was invented, the stored program computer, it made the job of entering a program easier. With the advances in computer theory it led to computer science which eventually led to AI (Artificial Intelligence). Although the computer provided the technology necessary for AI, it was not until the early 1950’s that the link between human intelligence and machines was really observed.
A man named Norbert Wiener did research into feedback loops and was able to theorize that all intelligent behavior was the result of feedback mechanisms and they could possibly be simulated by machines. In late 1955, Newell and Simon developed the The Logic Theorist, considered by many to be the first AI program. In 1956 John McCarthy, regarded as the father of AI, organized a conference called “The Dartmouth Summer Research Project on Artificial Intelligence. ” It was held in Vermont and it drew the talent and expertise of others interested in machine intelligence for a onth of brainstorming. It was not a huge success but because of McCarthy the field is now known as Artificial Intelligence and it served to lay the groundwork for the future of AI research. In 1957, the first version of a new program The General Problem Solver (GPS) was tested. The program developed by the same pair which developed the Logic Theorist. The GPS was an extension of Weiner’s feedback principle, and was capable of solving a greater extent of common sense problems. A couple of years after the GPS, IBM contracted a team to research artificial intelligence.
Herbert Gelerneter spent 3 years working on a program for solving geometry theorems. In 1958 McCarthy announced his new development; the LISP language, which is still used today. LISP stands for LISt Processing, and was soon adopted as the language of choice among most AI developers. In 1968 the microworlds program created SHRDLU which consisted of research and programming in small worlds (such as with a limited number of geometric shapes). Another advancement in the 1970’s was the invention of the expert system.
Expert systems predict the probability of a solution under set conditions. In 1972 the PROLOGUE language was developed. During the 1980’s AI was moving at a faster pace, and further into the corporate sector. In 1986, US sales of AI-related hardware and software surged to $425 million. In 1991 the military put AI based hardware to the test of war during Desert Storm. AI-based technologies were used in missile systems, heads-up-displays, and other advancements. We have discussed the history behind artificial intelligence. But the question now is what exactly is artificial intelligence?
There are so many interpretations of what AI is and is not. Because of this, there is no “precise definition. ” The reason for not having a clear definition for AI is because those who are knowledgeable in AI are always trying to decide “where the boundary between AI and non-AI lies,” thus, they “do not always spell out their criteria” about artificial intelligence. So what are some of the definitions for artificial intelligence? The first one is defined by John McCarthy. He defines it as “the science and engineering of making intelligent machines. Boden defines artificial intelligence “as the study of how to build and/or program computers to enable them to do the sort of things that minds can do. ” Another similar definition is defined by Marvin Minsky in 1968. He defines AI as “the science of making machines do things that would require intelligence if done by men. ” This quote is widely known in the field of AI. This definition was then specified even more by Weizenbaum in 1976. Weizenbaum argued that “the overriding goal of AI is to create an artificial system which will equal or surpass a human-being intelligence. A year later, Winston and Boden pointed out that artificial intelligence is “the use of computer programs and programming techniques to cast light on the principle of intelligence in general and human thoughts in particular. ” And in 1981, Haugeland had a different interpretation of AI. He simply believes that “intelligent beings are semantic engines — in other words, automatic formal systems with interpretations under which they consistently make sense. ” To him and others like him, AI systems are merely “tools to perform specific tasks. However, if artificial intelligent systems have the minds to know when and how to “perform specific tasks,” then they have the minds to “diagnose, advise, infer, and understand. ” Thus, artificial intelligence systems cannot simply be just “tools. ” The modern definition is “the study and design of intelligent agents” where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success. One can see already, the contrasting interpretations of AI. Therefore, there is no straightforward definition.
One can literally go on trying to define this term. AI uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization, and logic. AI research also overlaps with tasks such as knowledge representation and reasoning, problem solving and problems, speech and natural language processing, machine learning, computer vision, and robotics. Knowledge representation and reasoning are two core challenges in AI.
There are many ways to handle them; one way is through the logical approach where knowledge is represented by precise logical rules. In this approach, reasoning involves computing the consequences implied by such rules. Another approach is the probabilistic approach; knowledge is represented using numerical probabilities. Reasoning involves computing the probability of various conclusions given specific evidence. And there is the neural network approach; knowledge is represented as a network of interconnected units that perform certain task by exchanging information. This approach mimics the behavior of neurons in the brain.
Planning and problem solving require programs to identify sequences of action that accomplish specified goals. A common type of problem solving involves playing board games. AI programs can play many games at the level of the best human players. In 1997, Deep Blue, a chess-playing computer developed by International Business Machines Corporation, won a match against Garry Kasparov, the reigning world chess champion. Speech and natural language processing involves developing computer programs that communicate in a human language instead of a specialized programming language.
Scientist has developed logical, probabilistic, and neural network systems for processing natural language. Modern systems can carry on a conversation about a narrow topic but some think that real artificial intelligence systems will need to be successful with natural-language communication. Machine Learning involves computer programs that learn from examples and from experience. The 1956 Dartmouth workshop presented the first program that learned to play checkers by competing against a copy of itself. Other programs have learned to play backgammon and to recognize human speech and writing.
Computer Vision attempts to build computers that recognize patterns and objects in visual images. Pattern recognition applications represent half of the AI industry. Applications include face identification, fingerprint identification, handwriting recognition, scientific data analysis, weather forecasting, biological slide analysis, surveillance satellite data analysis, robot vision, optical character recognition, automatic voice recognition, and expert systems. Robotics studies the control of mechanical robots.
Robotics enables machines to perform complicated tasks by combining motion planning, interpretation of visual and sound information, and artificial speech. AI robots developed to operate without human supervision could be used in space exploration or in driverless military vehicles. Earlier on we have discussed the history of artificial intelligence, defined what artificial intelligence is, and explained the research that is being done in artificial intelligence. We can now see what artificial intelligence is used for today. The technological field has been unbelievable and it has impacted many areas of our society.
Artificial intelligence is used in many areas of the medical device industry, including cardiac monitoring, medical imaging, clinical laboratory analysis, respiratory monitoring, EKG and anesthesia. Medical artificial intelligence is also employed in products ranging from hearing aids to polarized video screens that display 3-dimensional anatomical images. In the video game industry games like Madden Football, Earl Weaver Baseball and Tony La Russa Baseball all based their AI on an attempt to duplicate on the computer the coaching or managerial style of the selected celebrity. Artificial Intelligence has changed the stock trading industry. Five years ago it would have taken $500,000 and 12 people to do what today takes only a few computers and co-workers,” said Louis Morgan, managing director of HG Trading, a three-person hedge fund in Wisconsin. “I’m executing 1,500 to 2,000 trades a day and monitoring 1,500 pairs of stocks. My software can automatically execute a trade within 20 milliseconds – five times faster than it would take for my finger to hit the buy button. ” Studies estimate that a third of all stock trades in the United States were driven by automatic algorithms last year, contributing to an explosion in stock market activity.
Between 1995 and 2005, the average daily volume of shares traded on the New York Stock Exchange increased to 1. 6 billion from 346 million. Not all uses of Artificial Intelligence are specifically designed to advance the interests of the science or technology communities. Some are just plain fun. Many toys implement AI, and more will be developed as the technology grows and matures. Here is a couple that is thought to be the most notable. The 20Q which can guess with an uncanny certainty nearly any object you think of and The Sony robotic dog, Abio, is probably the fanciest and most famous AI toy.
Running at about $2000 US, the latest version of the pup could speak 1,000 words, react to its owner’s motions and commands, keep blogs, take pictures with its eyes, and play music. To pull together the results of web search engines, Clusty uses metasearch technology, which means it searches the results of other search engines and indexes. Then it applies the artificial intelligence to pick out the major themes found within the results for each search and organizes them into folders. In law enforcement they use an AI system called Capturing and Using Patterns for Evidence Detection.
Pattern-based analysis of data plays an increasing role in several important applications. In crime prevention (including securities trading, tax fraud, and homeland security) it is being used both to detect evidence of criminal events and to predict threatening activities before they completely mature. It’s hard to say how far or how much artificial intelligence will achieve but there are many predictions out there. AI has progressed at an exponential rate and it is only expected to increase. Artificial intelligence in the 90’s is centered on improving conditions for humans. But is that the only goal in the future?
Research is focusing on building human-like robots. This is because scientists are interested in human intelligence and are fascinated by trying to copy it. If A. I. machines can be capable of doing tasks originally done by humans, then the role of humans will change. Robots have already begun to replace factory workers. They are acting as surgeons, pilots, astronauts, etc. According to Crevier, a computer scientist, robots will take over clerical workers, the middle managers and on up. Eventually what society will be left with are machines working at every store and humans on every beach.
As Moravec puts it, we’ll all be living as millionaires. Ray Kurzweil, The creator of the Kurzweil Reading Machine, the Kurzweil synthesizer, and the Windows 95 voice recognition program, believes people will eventually live forever and that in 2045 man and machine would achieve “singularity,” and that humans would hold their breath for hours, thanks to nano-machines in our bloodstreams. Google is predicting that they will have a search engine that knows exactly what you are looking for, that can understand the question you are asking even better than you do, and find exactly the right information for you, instantly.
It has been said that machines will be both self-aware and superhuman in their intelligence, and capable of designing better computers and robots faster than humans can today. Over the next thirty years we will see new types of animal-inspired machines that are more `messy’ and unpredictable than any we have seen before. Family robots may be permanently connected to wireless family intranets, sharing information with those who you want to know where you are. The intelligence of the horse will be put back into the automobile, and cars will become nervous of their drunken owners, and refuse to get into positions where they would crash at igh speed. Cars will become (wireless) networked, and humans will stop driving altogether. Robots in the surgical rooms will be equipped with compact X-rays, MRI machines, lasers, scalpels and other equipment. No longer will you need to wait for a donor to expire, but artificial eyes will be available at your own pharmacy. The technological advances are incredible; one should take advantage of this and not take it for granted. We have discussed and seen the impact of artificial intelligence and we can only wait and see how much more of an impact it will make. References Carlos III University of Madrid (2020, July 13).
Artificial Intelligence for improving team sports. Sciencedaily. Retrieved July 28, 2010, from http://www. sciencedaily. com/release/2010/07/100712103333. htm Dr. Mark Humphreys. The Future of Artificial Intelligence. New Scientist Magazine. Retrieved July 28, 2010, from http://www. robotbooks. com/artificial-intelligence- future. htm John McCarthy (2007, November 12). What is Artificial Intelligence? Retrieved July 28, 2010 from http://www-formal. stanford. edu/jmc/whatisai/ The History of Artificial Intelligence. Retrieved July 28, 2010, from http://library. thinkquest. org/2705/
