Artificial Intelligence

Positive Outcomes
Many positive outcomes in our society can result with the use of artificial intelligence.  Increased production and indirectly lowered costs have already been witnessed in factories and production lines.  Jobs better suited for computers have decreased errors and increased efficiency.  One example of this is with detecting credit card fraud.  American Express has developed an "Authorization Assistant" that uses artificial intelligence to determine whether a purchase is out of character for a card member.  This system is more accurate than when done by a human and it saves time.  This and many infinite other possibilities exist for using artificial intelligence to increase efficiency.
Artificial intelligence is also being pursued to replace humans in dangerous situations.  Not only can they withstand radioactive elements but they also work better in places where there is confined space and little oxygen to breathe.  This replacement will eliminate unwarranted deaths due to potential accidents and unsafe conditions.
Another important area that artificial intelligence is projected to improve concerns the lives of the elderly.  Because of the demand for adults to be fully involved in their work, the care for the elderly at home has diminished.  Now the numbers needing nursing care has risen.  The desire for these individuals to be independent can no longer be met and the elderly will have to live in a nursing home.  Artificially intelligent robots are an attempt to rectify this problem.  If a spouse passes away, the widowed spouse, while perhaps not fully independent, may no longer have to seek help in a nursing home.  Now a robot can oversee the individual and help with tasks too difficult for the person on their own.  As a whole, society will begin to change.  Menial tasks done by humans will no longer need attention and time can be spent doing more constructive things.  The systems run by artificial intelligence will be more accurate then ever, thereby increasing the level of trust in making certain decisions.  Lives can be lived more fully.  Perhaps years from now people will look back, much like individuals today look back at progress, and ponder how unnecessarily difficult their lives used to be.


Negative Outcomes
Along with any progress in technology are negative outcomes as well.  Because computers are more capable of producing accurate results, they will potentially replace humans in jobs that are better suited for them.  This could mean that the workplace will no longer be man's domain.  Unemployment rates could go up.  Humans could soon lose their ground as dominant creature.  Most drastic of possibilities is complete destruction of the human race.  If artificial intelligence at the level of Moravec's Fourth Generation Robots is created, these machines will have a "mind" of their own and could potentially annihilate humanity.
At a more basic level, the use of artificial intelligence in everyday tasks might produce laziness on the part of humans.  Mentality might become; "if the computer can do it why should I waste my time trying it myself?"  Humans have an extraordinary ability to think, analyze, and use judgment.  If artificial intelligence is used for interpreting, then the human mind and its capabilities might go to waste.

game playing

You can buy machines that can play master level chess for a few hundred dollars. There is some AI in them, but they play well against people mainly through brute force computation--looking at hundreds of thousands of positions. To beat a world champion by brute force and known reliable heuristics requires being able to look at 200 million positions per second.

speech recognition

In the 1990s, computer speech recognition reached a practical level for limited purposes. Thus United Airlines has replaced its keyboard tree for flight information by a system using speech recognition of flight numbers and city names. It is quite convenient. On the the other hand, while it is possible to instruct some computers using speech, most users have gone back to the keyboard and the mouse as still more convenient.

understanding natural language

Just getting a sequence of words into a computer is not enough. Parsing sentences is not enough either. The computer has to be provided with an understanding of the domain the text is about, and this is presently possible only for very limited domains.

computer vision

The world is composed of three-dimensional objects, but the inputs to the human eye and computers' TV cameras are two dimensional. Some useful programs can work solely in two dimensions, but full computer vision requires partial three-dimensional information that is not just a set of two-dimensional views. At present there are only limited ways of representing three-dimensional information directly, and they are not as good as what humans evidently use.

expert systems

A ``knowledge engineer'' interviews experts in a certain domain and tries to embody their knowledge in a computer program for carrying out some task. How well this works depends on whether the intellectual mechanisms required for the task are within the present state of AI. When this turned out not to be so, there were many disappointing results. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. It did better than medical students or practicing doctors, provided its limitations were observed. Namely, its ontology included bacteria, symptoms, and treatments and did not include patients, doctors, hospitals, death, recovery, and events occurring in time. Its interactions depended on a single patient being considered. Since the experts consulted by the knowledge engineers knew about patients, doctors, death, recovery, etc., it is clear that the knowledge engineers forced what the experts told them into a predetermined framework. In the present state of AI, this has to be true. The usefulness of current expert systems depends on their users having common sense.

heuristic classification

One of the most feasible kinds of expert system given the present knowledge of AI is to put some information in one of a fixed set of categories using several sources of information. An example is advising whether to accept a proposed credit card purchase. Information is available about the owner of the credit card, his record of payment and also about the item he is buying and about the establishment from which he is buying it (e.g., about whether there have been previous credit card frauds at this establishment).

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. Norbert Wiener was one of the first Americans to make observations on the principle of feedback theory feedback theory. The most familiar example of feedback theory is the thermostat: It controls the temperature of an environment by gathering the actual temperature of the house, comparing it to the desired temperature, and responding by turning the heat up or down. What was so important about his research into feedback loops was that Wiener theorized that all intelligent behavior was the result of feedback mechanisms. Mechanisms that could possibly be simulated by machines. This discovery influenced much of early development of AI.
In late 1955, Newell and Simon developed The Logic Theorist, considered by many to be the first AI program. The program, representing each problem as a tree model, would attempt to solve it by selecting the branch that would most likely result in the correct conclusion. The impact that the logic theorist made on both the public and the field of AI has made it a crucial stepping stone in developing the AI field.