Artificial Intelligence in Today’s Society

Last Updated: 27 May 2020
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Artificial Intelligence in Today’s Society Larry Anderson INF103 Instructor Geathers November 21, 2011 “The goal of many computer scientists since the mid-20th century has been to create a computer that could perform logical operations. ”(Bowles, 2010, 9. 2). The journey to achieving this is called Artificial Intelligence, which is considered to be the branch of computer science that is focused on creating machines that engage in human behavior, and intelligence. “The term Artificial Intelligence was first coined at the Dartmouth Conference in 1956 by John McCarthy. ” (McCorduck, 2004, 2. ). “The Dartmouth conference paved the way for examining the use of computers to process symbols, the need for new languages and the role of computers for theorem proving instead of focusing on hardware that simulated intelligence. ”(Krishnamoorthy & Rajeev, 1996, 9. 1). Even though this name was coined in 1956, we saw artificial intelligence 15 years earlier when the electronic computer was created in 1941. Artificial Intelligence is an exciting subject that will only get better with time, allowing humans to do things that were never thought to be reality, until the last few decades.

In this paper, I will be telling you about the four main studies of artificial intelligence and their importance to our society, as well as how they are affecting our everyday lives. These four studies are expert systems, natural language, neural networks, and robotics. Mostly all artificial intelligences can be categorized under these four studies. Not only are these technologies making life easier, they are making life more enjoyable for all societies. The first study of artificial intelligence I will talk about is expert systems. Expert systems are computer programs that contain large amounts of information in a certain field.

These programs use this large amount of information to solve problems that normally would require human intelligence. The great thing about expert systems is that they can process information, in seconds, which would take humans days. Every expert system is made up of two parts: knowledge, and reasoning. “The knowledge base of the expert systems contains both factual and heuristic knowledge. ”(Engelmore & Feigenbaum, 1993, 1. 2). The knowledge is the information, while the reasoning is the problem solving aspect of the expert system. One common, but powerful paradigm involves chaining of if-then rules to form a line of reasoning. ”(Engelmore & Feigenbaum, 1993, 1. 2). For example, if you have these symptoms, then you must have a head cold. Expert systems are affecting our everyday lives by diagnosing illnesses, and predicting the weather. “One of the first systems was a computer that could perform a medical diagnosis. ” (Bowles, 2010, 9. 2). A doctor can enter symptoms into a computer, and then process a few questions for the doctor; after answering the questions the computer will make a diagnosis of the patient.

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This is very useful to doctors because now they can see more patients, and give promising diagnosis efficiently. The second way expert systems are affecting our lives is by predicting the weather. Meteorologists are using these systems to help predict hurricanes and tornadoes. This is very helpful to society, giving people more evacuation time during major storms. The second study of artificial intelligence is Natural Language, which is considered human language. “Natural language processing programs use artificial intelligence to allow a user to communicate with a computer in the user’s natural language. (Poole & Mackworth, 2010, 12. 6). The computer can both understand and respond to commands given in human language. The two biggest hurdles in this study are phonetic knowledge, and pragmatic knowledge. Phonetic knowledge concerns how words are realized, and how words are realized as sounds. Pragmatic Knowledge has to do with how sentences are used in different contexts and how that affects sentence interpretation. Even with the tough barriers of language, and the meaning of words computer specialists are producing helpful natural language processing programs to better society. When was the last time you made a customer service call?

Natural language is affecting you when you call a customer service number, and an automated voice tells you to say a command. “Voice-recognition systems are now handling night and weekend toll-free directory assistance calls for big corporations. ” (Poole & Mackworth, 2010, 12. 6). For example if you need to check your balance for a cell phone bill, a voice-recognition system can assist, without the need of a human. This allows the human customer service representatives to help customers with more complex questions. Another way natural language is being used is with Google’s real time translation application.

With this application you can take snapshots of things in a different language with your phone and it will translate the words into your language in seconds. This can be useful when you are traveling in different countries, needing directions, or when you are selecting from a menu in a different language. “A neural network is, in essence, an attempt to simulate the brain. Neural network theory revolves around the idea that certain key properties of biological neurons can be extracted and applied to simulations, thus creating a simulated, and very much simplified brain. ”(Reingold & Nightingale, 4. 1).

The first important thing to understand is that artificial neural networks are an attempt to recreate the computing potential of the brain. However, no one has ever simulated anything as complex as an actual brain which makes it very difficult to finish the whole project. Credit card fraud is very big in the present day, because many people are not using cash; instead they are using credit cards and debit cards to make transactions. “Nearly 400,000 transactions per day are of fraudulent charges. ” (Brause & Langsdorf, 1). Neural Networks are being used to detect fraud transactions with the principal of pattern recognition.

Every time a credit card user uses their card there is a pattern of transaction. Neural network software uses information such as how much money a person makes, type of transactions made, and how frequent certain transactions are made to predict fraud. “Neural network based fraud detection is based totally on the human brain working principal. As the human brain learns through past experience and uses its knowledge or experience in making the decision in daily life problem the same technique is applied with the credit card fraud detection technology. ” (Patidar & Sharma 2. ). The last study of artificial intelligence I will be talking about is robotics. Robots are physical agents that perform tasks by manipulating the physical world. “They perform tasks which are idealizations or extensions of human capabilities. ”(Selig, 1992, 1. 1). Robots have four characteristics; sensing, movement, energy, and intelligence. First off, a robot must sense its surroundings using light, touch, and pressure sensors. Secondly a robot must have movement; a robot needs to move around in its in environment, whether or not the whole robot moves, or just parts.

Thirdly, a robot needs power to function properly, this energy could be solar, electrical, or battery powered. Last, it must have some kind of intelligence, such as software from a programmer in order to operate. Actual robots might seem like far off science fiction, but that is not the case robots have been affecting our everyday life for years. One of the biggest uses for robots today is in the automotive industry. Over the past few decades robots have completely changed the automobile industry in many ways.

Even though the use of robots has also led to many workers losing their jobs, it is very cost effective. The robots are used for welding, painting, drilling, sanding, cutting, and moving tasks in manufacturing plants. The robots have improved this industry with a job efficiency that couldn’t be duplicated by humans. These robots have made assembly lines and factories safer by handling jobs that are too dangerous and too difficult for workers to perform. Another great way that robots are working in society’s favor is by cleaning up toxic and contaminated areas that would otherwise be harmful to humans.

The biggest reason that robots are able to do these jobs is that they can be easily shielded against hazardous environments and are easily replaceable, unlike humans. Robots are used to clean up nuclear waste or clean ammunition, and landmines all over the world. Robots are also an asset to the military because they can detect and diffuse bombs in a combat zone. These robots are saving lives every day because they are able to go into situations that are life threating to humans and get the job done.

The studies of expert systems, natural language, neural networks, and robotics are just in their early stages of advancements, but are already showing important promising characteristics for the future of mankind. We already see these advancements being put to the test by making medical diagnosis, predicting weather, voice automated services, catching transaction fraud, building automobiles, and cleaning up hazardous wastes. There is no doubt that Artificial Intelligence is already affecting society in ways that were never imagined decades ago.

Technology will continue to explode into the next few decades, excelling in Artificial Intelligence, how we embrace the advances, will define us as a society. Resources: Bowles, Mark, D. (2010). Introduction to Computer Literacy. San Diego, CA: Bridgepoint Education. McCorduck, P. (2004). Machines Who Think. Natick, MA. AK Peters, Ltd. Krishnamoorthy, C. , Rajeev, S. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press. Englemore, R. & Feigenbaum, E. (1993). Expert Systems and Artificial Intelligence. WTEC Hyper-Librarian. Poole, D. & Mackworth, A. 2010). Artificial Intelligence Foundations of Computational Agents. Cambridge University Press. Reingold, E. & Nightingale, J. Artificial Intelligence Tutorial Review. http://www. psych. utoronto. ca/users/reingold/courses/ai/ai. html Brause, R. & Langsdorf. Neural Data Mining for Credit Card Fraud Detection. J. W. Goethe-University. Frankfurt, Germany. Patidar, R. & Sharma, L. (2011). International Journal of Soft Computing and Engineering. Jaipur, India. Selig, J. (1992). Introductory Robotics. Englewood Cliffs, NJ: Prentice Hall International.

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