Advancing AI Literacy Lessons


Deforestation and Machine Learning

Environmental Science | 9-12
Duration: 70 minutes
Author: Gary Leary, Science Department and Instructional Technology Chair

In this lesson, students explore how artificial intelligence (AI) and satellite imagery can be used to monitor deforestation. They begin by analyzing satellite images to identify forest loss over time and then train a simple machine learning model using Teachable Machine to classify land cover types. Through hands-on model building, testing, and evaluation, students gain insight into how AI systems learn from data and how human choices impact model accuracy. The lesson culminates in a whole-class discussion on the ethical and ecological implications of deforestation and the role of AI in supporting sustainable land management.

Lesson Objectives

  • Analyze satellite images to identify patterns of forest cover change over time.
  • Train and test a basic machine learning model to classify land cover types.
  • Evaluate the accuracy and limitations of AI models based on training data and design choices.
  • Interpret spatial patterns of deforestation and propose informed solutions for sustainable land management.
  • Reflect on the ethical implications of using AI for environmental monitoring and decision-making.

Essential Questions

  • How can satellite imagery and AI help us detect and understand patterns of deforestation?
  • What decisions do humans make when training AI models, and how do those choices affect model accuracy and reliability?
  • What are the ecological and societal consequences of deforestation, and how can technology support sustainable solutions?
  • What are the strengths and limitations of using AI compared to human observation in environmental monitoring?
  • How can students use AI tools responsibly to analyze environmental data and propose informed actions?