Herbert Simon research and concepts increased computer scientist understanding of reasoning and increased the computer’s ability too solve problems and proof theorems. Herbert Simon, Al Newell, Clifford Shaw proposals were radical and affect computer scientist today. In Simon’s book, “Models of my life”, Simon demonstrated the Logical Theorem algorithm could prove certain mathematical theorems. Simon said, “This was the task to get a system to discover proof for a theorem, not simply to test the proof. We picked logic just because I happened to have Principia Mathematica sitting on my shelf and I was using it to see what was involved in finding a proof of anything.” Alfred North Whitehead and Bertrand Russell book Principia Mathematica contained theorems considered to form the foundation of mathematical logic. Simeon evolved Logic theorem into General problem solver. GPS is currently used in robotics and gives the robot amazing problem solving capabilities. Many mathematicians considered some of LTs proofs superior to those previously published.

In the past when a person mentioned AI it meant “all characteristic and capabilities that a excellent software programmer couldn’t do. In other words, AI was a symbolized a cynical jest by computer scientist writing commercial code that sold.” GPS can expert systems could bring power too the people and make available intelligent application and new found parallelism for existing computing barriers. Parallelism computing architecture would allow the computer to do things in real time in architecture not possible to do at all. GPS, CAs, neural nets, and expert systems would penetrate all areas and no area would be immune from eventual exploration; information projects will be done on multiple fronts at once; and most of the work would not be done by computer scientists or Knowledge based people but most likely by those in end-use fields, who see a need and have a more-or-less direct contact with these more theoretical sources of ideas. GPS, neural nets, CAs, Gas, and expert systems are a commodity for everyone to use. Natural language semantic networks will become more available. Simon seems optimistic that semantic networks accuracy will improve, as a he says, “I think our main bottlenecks there today are not in natural language, but in our ability to mount projects big enough to grow the data bases that would be necessary to do a job on the full language with all of its possibilities for metaphor.”

Expert system holds amazing promise. Dr Jack Myers Internist 1 database was made up of 100,000 numbers and facts about the patient for more than 500 diseases. Internist 1 used the numbers to generate a score, the score was used to make diagnoses or ask the doctor for more information. Internist 1 was a as good as many physicians but not as good as Myers. Other criticized Internist 1 as a Jack-in-The-box mimic of Myers. Myers countered the comment saying “computer scientist can not write programs to organize and use information as well as humans”. At the same time MYCIN was being developed by a group from Stanford University led by Edward Feigenbaum. The group began developing a computer technique to diagnose infectious disease. The research team took 10 meningitis patients and distributed the patient information too MYCIN, a Stanford facility member specializing in infectious disease treatment, a resident, and a medical student. The research team compared diagnoses and actual treatment recommendations and concluded that Mycin recommendations and diagnosis were at least as good as the three humans. Mycin type application could have lower cost introduction too emergency waiting rooms and improve accuracy and recommendation speed for a doctor, who must hand increasing numbers of patients on demand. Suppose, in the future, a person has an injury, drives to the hospital, and walks into the waiting area. The individual is greeted by one or many verbally interactive robot reception machine like Kismet and this cog begins extracting and storing information about the patient include all the billing information using voice recognition and synthesis. After the basic billing information is gather the Mycin algoritm starts collecting information about individual’s injury or disease and uses this information to make a preliminary diagnosis and make decisions to escalate attention. Once the doctor meets with the patient, the cog reviews the medical chart with the doctor and provides recommendations along the way assisting the doctor in decision making. As new information is added too the medical chart, the cog may ask for additional clarification questions and change recommendations. The patient information recommendations by the cog can be reviewed by a central computer with collective knowledge. The central computer can be polled too determine consensus on diagnosis and recommendation. The doctor concurrence statistics could be weighted against the cog advice. The more times the cog is concurred with the doctor, the higher the cogs rating. If a doctor habitually ignores the recommendations and disagrees, this information is passed too the central system for evaluation and assessment of cogs ability. Poor performing cogs are discontinued or replaced. As the cog abilities improves, the doctor will be more inclined to trust the cogs recommendations and malpractice suites could receive the reasoning of both the cog and the doctor in determine possible negligence. Eventually, the cog will become a valued assistant to reduce time, improve quality of medical treatment, and provide universal medical recommendations, at lower costs too the people.