Chapter 11 - Artificial Intelligence
Outcomes
Learning Outcomes
- Artificial Intelligence challenges include obstacles such as processing images and language, or building autonomous agents and robots.
- Differentiate between the concepts of machine reasoning/behavior and human reasoning/behavior.
- Identify common vocabulary concerning artificial intelligence.
- Identify challenges with artificial intelligence concerning images and language processing.
- Security and ethical concerns exist concerning artificial intelligence.
- Discuss ethical and security concerns relating to artificial intelligence.
Activities
Reading Guide
In order to guide your reading we have designated each section into one of three categories:
- Essential - You should thoroughly read this material and be prepared to answer questions about this material on assessments.
- Important - You should thoroughly read this material and be prepared to participate in in-class discussions/activities about this material.
- Useful - We feel that this material is worth knowing and may supplement other material in the chapter. However, we do not plan on assessing or discussing (unless you ask questions).
Section | Essential | Important | Useful |
---|---|---|---|
11.1 Intelligence and Machines | |||
11.2 Perception | |||
11.3 Reasoning | |||
11.4 Additional Areas of Research | |||
Representing and Manipulating Knowledge | |||
Learning | |||
Genetic Algorithms | |||
11.5 Artificial Neural Networks | |||
11.6 Robotics | |||
11.7 Considering the Consequences |
Video Resources
- Crash Course CS: Machine Learning & Artificial Intelligence (combines aspects of Ch9 and Ch11)
- Crash Course CS: Computer Vision
- Crash Course CS: Natural Language Processing
- Crash Course CS: Robots
- Crash Course CS: The Singularity, Skynet, and the Future of Computing
- Neural Network Examples (From the Crash Course in Statistics)
- Neural Networks Explained (Goes in to the math/structure of the network in more detail)
Activities
This website uses an evolutionary technique called "simulated annealing" [Overly simplified - a one chromosome precursor to a genetic algorithm] to learn how to reproduce an image with a collection of polygons.
Articles
These discuss some interesting issues with AI that might help you frame some of what you read.- AI that predicts your face from your voice. [Uses Neural Networks. Includes a strong discussion on the ethics and privacy concerns of such a system.]
Study Guide
The competency demo for this chapter will consist of several questions from the following study guide. As you study this chapter we suggest you work through the materials in this study guide and ask questions if you need clarifications.
Study Questions
After you complete the readings for this unit/chapter you should arrange to meet with your groupmates and work on the following activities.
Based on these questions we will prepare additional materials to help clarify issues.
- Podcast response videos
- Podcast 11.1 - Weekly Introductions (5 minutes)
- Podcast 11.2 - SG#7 (34 minutes)
- Podcast 11.3 - SG#8 (8 minutes)
- Podcast 11.4 - SG#9 (8 minutes)
- Podcast 11.5 - SG#10 (7 minutes)
- Group Meetup Video
Additional Materials
The following materials are links to optional materials we think you might find helpful in understanding this chapter and/or when working with your own students.- Making AI safer
- The AI4ALL program which is currently developing AI resources for K-12.
- Should we tax robot labor?