Artificial%20Intelligence%20(AI)

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Artificial Intelligence (AI)

• Can Machines Think?

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Advantage computer

• Calculate
• Communicate
• Process information
• Storage and recall of facts
• Make decisions using established rules of logic
• Consistency

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Advantage human

• Perceive
• Reason
• Not all possibilities can be anticipated, and
  therefore programmed
• Recognize patterns
• Unless a specific pattern has been anticipated
  and programmed, a computer cant act on it
• Ambiguity
• Application of knowledge (child describing his
  toys)

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So, can they think??

• The Turing Test
• Developed by Alan Turing (1950)
• A person sits at a computer and types questions
  into a terminal.
• If a computer were truly intelligent, the
  questioner would not be able to determine whether
  the responder was a human or a computer
• To date, no computer has even come close
• Some still consider the Turing Test to be the
  best determinant of AI. Other researchers favor
  a more lenient definition.

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Defining AI

• Hard to define
• Many disagree
• ability to perceive, reason, and act
• do things which, at the moment, people are
  better
• etc

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Was Deep Blue intelligent?

• Deep Blue was a computer developed by IBM that
  defeated Kasparov in chess.
• Rules were clearly defined
• Objectives were unmistakable
• Searching Winning typically goes to the player
  who can sift through the greatest number of
  possibilities and outcomes
• Recall Pattern recognition of board patterns and
  best strategies to employ given a specific
  pattern
• Humans may have the edge here
• 25 chess programs can defeat the greatest
  players in the world

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Language Translation

• Still work to be done
• Shakespeare The spirit is willing, but the
  flesh is rotten
• Computer The wine is agreeable, but the meat
  is rotten
• Out of sight, out of mind
• Computer Invisible idiot

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Syntax vs Semantics

• Language rarely limits itself to a consistent set
  of rules and structure
• There are always exceptions
• Sometimes, understanding the true, underlying
  meaning of a single word can require a great deal
  of knowledge
• Syntax the rules of a language, definitions
  of words
• Semantics the underlying meanings
• Expressions
• Idioms
• Slang
• Visual cues
• Ambiguity e.g. All that glitters is not gold.
  
• Etc

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Practical applications of AI

• Knowledge bases
• Expert systems

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AI techniques

• Heuristics
• Pattern recognition
• Machine learning

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Knowledge vs Facts

• Facts are details that are typically quantifiable
  and reproducible
• Knowledge is the ability to form relationships by
  using facts
• Humans are considerably better at inferring
  things
• Computer require tremendous input of data to
  accomplish this same task, and even then, will
  inevitably fall short at some point

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Knowledge Base

• A computer KB will
• Incorporate a database of facts
• Incorporate a series of programmed rules
• Attempt to derive new facts by applying steps 1
  and 2

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Expert Systems

• A software program designed to replicate the
  decision making process of a human expert
• A collection of specialized knowledge where facts
  and appropriate actions are obtained from expert
  sources and programmed into a database
• Usually involves a series of If?Then question
  and answers.

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Algorithms

• An expert system will frequently use a series of
  algorithms to provide solutions to a given
  question
• Here are a couple of examples of well-established
  medical algorithms

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Difficult Airway Algorithm
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ACLS Algorithm Cardiac Arrest
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Pulmonary HTN Algorithm
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Fuzzy Logic

• Uncertainty is an inevitable part of the human
  experience
• Computers do not handle ambiguity well
• Computers use likelihood (e.g. percentages)
  derived from as much factual data as possible
  to come up with the best solution

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Expert Systems - examples

• Training
• Teaching difficult airway procedure to
  anesthesiology residents
• What do you do next?
• Routine / repetitive task work
• Monitoring millions of credit card accounts for
  unusual activity
• Expertise when human help is not available
• PDAs with medical databases
• Error reduction
• Checking for drug interactions in an EMR

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