AI

=2.4.2 Artificial Intelligence and Expert Systems=

 ** **Introduction**
 * Artificial Intelligence

Watch the opening 10 mins of AI film

**What is AI?** AI - artificial intelligence: the branch of computer science that deal with writing computer programs that can solve problems creatively; "workers in AI hope to imitate or duplicate intelligence in computers and robots". CC p 586 - read and discuss the different definitions: It is the study of ideas which enable computers to do the things that make people seem intelligent. It is the study of how to make computers do things at which at the moment people are better. It is the study of the computations that make it possible to perceive, reason and act.

The aim is to try and simulate the human mental process. This has some problems: • Most people cannot describe how they do things • There is a difference between the structure and capabilities of the human brain compared to the computer. • The best way for a machine is often different to a human.

  Give 3 examples of how AI is used. • Gaming:.e.g. Playing the computer in Chess. • Language translations e.g Babel Fish • OCR used to recognise text on envelopes to automatically sort mail. • Handwriting recognition software e.g. IWB, palms and tablet pcs • Speech to text converters e.g. help for deaf people in mobile phones
 * Know key terminology** – A1, Turing test, parallel processing, machine learning, natural language, common-sense knowledge, agent, pattern recognition, Expert system, knowledge base, inference engine, heuristics, fuzzy logic
 * Parallel Processing** - is the breaking a complex job into smaller, simpler tasks and completing these simultaneously. A human can do this but a computer cant.
 * Turing Test** - is a classic test of machine intelligence where the computer is considered intelligent if it can successfully pose as a person in a typed conversation. See page 585
 * Machine Learning** - are programs as they learn from mistakes
 * Natural Language** - is the ability for a computer to communicate in a natural language. There have been developments e.g. parsing programs where sentence structure is analysed and words identified to be verb, subject or other and words are looked up in the dictionary and then appropriate words substituted. This did not work, as meaning was often lost. So programs now are built in with positive and negative examples of well translated sentences so the program can learn.
 * Common Sense Knowledge** - computers lack common sense which is the wealth of knowledge and understanding about the world that people share. This is especially important when words have more than one meaning. Common sense is necessary to give meaning to things that are said. A computer does not have this.
 * Pattern Recognition** - involves identifying recurring patterns in input data with the goal of understanding or categorizing that input. It is used in biometric applications e.g. finger print recognition, handwriting recognition, scientific data analysis, surveillance satellite data analysis, robot vision, OCR, automatic voice recognition and expert systems.

AI has been successful where tasks are sequential and follow logical rules and have orderly relationships. They are unsuccessful when competing with human intelligence. Latest developments have been in neural networks which are parallel computer systems similar to the human brain so that it can parallel process and learn by trial and error and can develop habits

What are the social and ethical issues associated with AI? • People have become emotionally attached to machines • Smart computing - where will it lead to • Will it be a political battle • What will our life be like in the future? • Where will responsibilities lie?

Link with smart weapons, creative productions e.g. visual art and smart machines in everyday life. 

**Expert Systems** (see previous work in Health)

back