When to use ML
As AI and machine learning become more prevalent in our lives, students need opportunities to understand not only how these technologies work, but also when they are appropriate, and ethical, tools for the problem at hand. These activities invite students to critically assess the use of machine learning across different contexts, balancing technical feasibility with social and ethical considerations.
When to use ML?
In this lesson students collaboratively create a checklist for determining when machine learning is an appropriate tool. By considering scale, bias, and ethical implications, and exploring non-ML alternatives first, students learn to critically evaluate when ML should be used to solve a problem.
Create an ML Model Flowchart
This lesson invites students to use and create flowcharts to evaluate real-world scenarios and determine whether machine learning is an appropriate and ethical tool for the problem at hand.