Example For High School about Artificial Intelligence

It is the science and engineering of making intelligent machines, especially intelligent computer programs. Artificial Intelligence is the study of the computations that make it possible to perceive, reason and act.

Artificial Intelligence becomes a formal branch of Computer Science around 1956.

AI has its own computer programming languages LISP, which developed in 1957, is STILL in use today, along with others. Every major computer technology company has a considerable investment in AI research.

The major philosophical issue related to AI in computer science is the mind-body problem -- how the mind relates to the body as espoused by Rene Descartes. A closely related problem is "can computers think?"

People (and presumably some animals) have a mental life.

Consider the question "what would it be like to be a bat?" Mental life is made up of sensations (color, pain, etc.), emotions and thoughts etc..

1) Bodies are physical.2) Minds are not physical.

3) Minds and bodies interact. 4) The physical and non-physical can't interact. Any three of this propositions are compatible but all four together are not..

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Cartesian dualism as espoused by Rene Descartes claims that mental activity is governed by different laws, and is made up of different stuff than purely physical activity. The major problem with this theory for science is that nobody has every seen such stuff, or observed such laws.

Physicalism contends that mental activity and physical brain activity are the same thing.

Computers today to some degree make physicalism seem less plausible.

"What is it like to be an IBM ThinkPad?" Presumably our answer would be "not much". Would our answer change if the computer were talking to us?

Not yet...but who knows what the future holds in store? Either way there are important philosophical ramifications.

Imagine a person sitting in a room, and who does not understand Chinese.

This person is given a manual on how to respond to all possible sequences of Chinese symbols. To the outside world, the person in the room seems to understand Chinese, but does not. The same should be said about computers.

Robots, expert systems, automation, natural language processors.

Software that analyzes other systems and software. Software that "learns" and never forgets.

Very reliable robotic systems at decreasing cost. Problem solvers (computer chess).

Artificial intelligence is concerned with understanding the nature of intelligence through the creation of computer programs which control machines. It is normally divided up into various sub-disciplines such as vision, language, planning, etc.

Game theory, speech and language recognition, machine vision, expert systems (learning), robotics, heuristic classification (what should I do?).

Computer vision is concerned with reconstructing the objects and their placement in a scene from one or more arrays of light intensities generated by these objects.

It is a very complicated problem. That we and other animals do it so effortlessly speaks highly of evolution.

The greater the disparity between where an object appears to the right and left eyes, the closer it is.

Early vision (things that are done early in the vision process) is generally concerned with line detection.Lines are places where there is a sharp change in light intensities.

Noise often complicates things, so it is necessary to smooth the observed light intensities.

Line caused by reflectance change. Line caused by object boundary. Line caused by object orientation change.

So far we have been talking about early vision: line detection, stereo, texture. Some tasks require not much more than this, e.

g. driving a car on a highway.

More advanced machine vision is concerned with object recognition. Problem involve how to represent object shapes and sizes, how to map such representations when an object is seen at different angles.

Manufacturing quality control, medical research, navigation over terrain (Guidance systems), facial analysis (Security Systems).

Machine learning is the creation of new hypotheses by computers (or at least hypotheses new to the computer).

Today most machine learning programs use statistical techniques, and there is, in general, a great cross fertilization between Statistics and Artificial Intelligence.

Planning is deciding what action to take next. Within AI planning problems are generally thought of as coming in two varieties: planning with and without complete information.

One standard planning problem is game playing. Games like chess are examples of planning with complete information since one knows the exact state of the game board, and nothing else affects the play of the game.

In principle one can decide on a move by considering all possible responses to responses. In practice one cannot carry this out to the end of the game. So one carries it out as far as one can.

Many of the worlds best chess players are computers. A computer (IBM's Deep Blue) beat the Gary Kasparov, the world champion in 1997 in a one on one tournament using the tree technique

A standard tool for reasoning in such situations as uncertainty or imperfect information is utility theory.

Actions have costs, and possible outcomes with certain probabilities. Do the action for which the sum of P(outcome) × Utility of outcome - cost is the greatest.

Very difficult problem. Recognizing words and simple phrases vs.

complex thoughts and syntax. Cultural nuance and Context Pattern recognition on different speech patterns and accents. Used by the "Turing test" as the ultimate test of computer intelligence.

Awarded each year to the computer program that best responds to a team of human questioners and best mimics another human being in what is called the "Turing Test". Turing asked the question, " If a computer could be made to think, how would we tell?"...have a conversation with it.

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A Chatterbot is a program that attempts to simulate typed conversation, with the aim of at least temporarily fooling a human into thinking they were talking to another person. Chatterbots are lightweight Natural Language Programs.

For a given set of circumstances, what should be done? What information can be used as input into the decision process? What weight should be given to different pieces of data (example: approving a credit card purchase)?

The ultimate exercise in planning and action is in the area of robotics. The current state of robotics is fairly primitive. Our sensors typically do not tell us much about the environment with much certainty, and our effectors do not work all that well either.

Infrared, lasers, temperature, humidity, liquid, micro switches.

Can machines be made Self-Aware? Implies that at some point they might not need further programming....

they do it themselves....just like a new born infant does from the time it is born! The machines could then decide whether or not they like us..

.and if they should keep us around!

Over-riding Law: A robot may not injure humanity, or, through inaction, allow humanity to come to harm. Law One: A robot may not injure a human being, or, through inaction, allow a human being to come to harm, unless this would violate a higher order law.Law Two: A robot must obey orders given it by human beings, except where such orders would conflict with a higher order law. Law Three: A robot must protect its own existence as long as such protection does not conflict with a higher order law.