Revision   Expert Systems (Claudia, Federico, Natalia)
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Transcript

  • 1. expert systems
    • Federico Zablah
    • Natalia Quiñonez
    • Claudia Mendoza
  • 2.
    • What is an expert system?
  • 3.
    • Software that attempts to reproduce the performance of one or more human experts.
    • A traditional application of artificial intelligence.
  • 4. steps to the creation of an expert system
  • 5. 1. programming Informant (Expert) Knowledge Engineer Knowledge Base
  • 6. 2. Querying User interface Inference Engine Knowledge base user
  • 7. Problems of using a medical expert system
    • If the knowledge is not on the base, a decision cannot be made.
      • Risk: Display the wrong diagnosis or no decision.
    • Inaccurate diagnosis
      • There are symptoms that some illnesses will have in common, meaning that the wrong diagnosis can be displayed.
  • 8.
    • GIGO – garbage in, garbage out.
      • All expert systems will make decisions based on the knowledge they have on the knowledge base. If the knowledge in the base is incorrect, the decision made by the expert system will also be incorrect.
      • Patients may not have adequate medical knowledge to input the correct symptoms which would give a wrong diagnosis.
  • 9.
    • Knowledge reliability may compromised if the data in the base is not updated regularly
      • Might be updated in intervals as doctors do not have time to update the expert system with every new piece of medical knowledge which comes out.
    • Lack of patient’s knowledge
      • Patients might not have sufficient IT knowledge in order to correctly use the expert system
      • Patients may not have sufficient medical knowledge to correctly understand medical diagnosis and advice.
  • 10. Factors in failure of expert systems Programmers and users 2. Overconfidence Programmers 1. Lack of testing Experts 4. Missing information Experts and users 3. GIGO Stakeholders involved Factors in failure
  • 11. Factors in failure and stakeholders
    • Programmers…
      • They have full responsibility in terms that the expert system works correctly. They do this by testing the system to make sure it works and try to eliminate any bugs present.
      • This is to say that they are in charge that the expert system’s processes are carried out but or are not in charge of any misinformation provided as they do not provide the knowledge base for the expert system: experts do.
  • 12.
    • Experts…
      • Are the ones in charge of providing a knowledge base for the system. In the case of the medical expert system, the expert is a doctor.
      • If there is any misinformation provided by the system, it is the expert’s fault as they provided the knowledge base to be used in the system. This is in terms of symptoms providing the wrong disease.
      • Knowledge base will never be complete as experts will never have a complete knowledge of everything in his area.
  • 13.
    • Users…
      • Are the ones who make use of expert systems for their own benefit.
      • If they input wrong queries into the expert system, the answer will be not what they are looking for (GIGO).
      • If they don’t realize this, they may stick to a wrong diagnosis and may result fatally if they do not go to a real doctor. (Overconfidence).