Living and Working with
Artificial Intelligence 

Learning Objectives

• List some different types of reasoning computers can do

• Determine what kind of reasoning is involved in a given computer application

Quick Resources

1. View in Google Slides 

Learning Objectives

• Explain how to use a decision tree to classify an object.

• Demonstrate how to extend a decision tree to include a new class.

Mod 3.2 - Video Case Study

• Videos and Resources

Quick Resources

1. View in Google Slides 

2. Lesson Plan

Learning Objectives

• Explain how decision tree classifiers work. (They should have gotten this from Pasta Land but it’s reinforced here.)

• Show how training examples can be encoded as feature vectors.

• Use MachineLearningForKids to set up and solve a machine learning problem.

Quick Resources

1. View in Google Slides

Learning Objectives

• Explain how decision tree classifiers work. (They should have gotten this from Pasta Land but it’s reinforced here.)

• Show how training examples can be encoded as feature vectors.

• Use MachineLearningForKids to set up and solve a machine learning problem.

Quick Resources

1. View in Google Slides

Learning Objectives

• Use AI Lab to explore a dataset.

• Train a classifier or predictor using AI Lab.

• Measure the performance of a classifier or predictor on a test set.

• Explain why running the same experiment in AI Lab multiple times may produce different results.

Quick Resources

1. View in Google Slides

Learning Objectives

• Understand what tasks neural networks can be used for.

• Explain in basic terminology the operation of a single computing unit (neuron).

Mod 3.5 - Video Case Study

• Videos and Resources

Quick Resources

1. View in Google Slides

Learning Objectives

• Understand how a linear threshold neuron works

• Understand how to solve problems by adjusting a neuron's wieghts and threshold

Mod 3.5 - Video Case Study

• Videos and Resources

Quick Resources

1. View in Google Slides

2. Neuron Sandbox web site

Learning Objectives

• Identify current uses of AI to make decisions and how it has impacted society or people

• Evaluate the ways various stakeholders' values influence the design of an AI System 

• Identify and explain sources of bias in an AI system and decision making process 

• Explain how and why issues of bias, fairness, and transparency affect the design and use of AI systems and impacts on people

• Create example laws, policies, and procedures that regulate the design and use of AI Systems that make decisions about people.

Quick Resources

1. View in Google Slides

Learning Objectives

• Understand what makes an AI biased and how to limit bias. 

• Build AI models and systems that are fair, ethical, and, transparent.

• Consider the users of your AI system.

Quick Resources

1. View in Google Slides

2.  See Teacher resources for lesson plans for Teachable Machines, AI Lab, and Machine Learning for Kids