Topic 11a
What is AI?

Learning Outcomes

By the end of this topic students should be able to:

  • Define and provide examples for foundational vocabulary terms including:
    • Agent
    • Sensor
    • Actuator
    • Procedural knowledge
    • Declarative knowledge
    • Strong AI
    • Weak AI
  • Identify examples of [procedural | declarative] knowledge.
  • Explain the Turing Test.
  • Discuss the connection between the Turing Test and the distinction between Strong AI and Weak AI

 

Learning Materials

  • Readings
    • Intelligence and Machines - pp 562-567
    • Strong AI versus Weak AI - pp 569
  • Videos
    • Crash Course Computer Science #34: Machine Learning & Artificial Intelligence (combines aspects of Ch9 and Ch11)
      • This video not only introduces AI, but actually starts to touch on several of the topics we will discuss in detail later in the unit.
    • Crash Course AI #1 - What is Artificial Intelligence?

     

Checking for Understanding

Answer the following questions from your textbook. The answers to all Q&E questions are in the back of your book in Appendix F.

  • p567, #1
  • p567, #2
  • p567, #3
  • p567, #4
  • p567, #5

 

Additional Guidance

  • NA

Further Information

  • Some people may find it interesting to read the original paper where Turing first explained "The Imitation Game" which has become known as "The Turing Test"
  • We do not consider the material on Vision/Image processing and Natural Language Processing to be part of the learning objectives of this course. Depending on your circumstances and interest you may want to read that material for your own knowledge