Artificial Intelligence is an activity developed by Learning Undefeated to help students explore the machine learning and the applications of artificial intelligence.
Artificial intelligence is a method of making a computer think like a human mind. This means that it studies data, finds patterns, and problem-solves. The key here is that a computer alone can follow directions very easily, but it often doesn’t have the capability to write and follow its own directions for a specific goal.
Artificial intelligence can be applied in a variety of fields including video games, banking, and health care. The Department of Defense uses AI for programs like unmanned vehicles and even augmented visual systems. The Integrated Visual Augmentation System (IVAS) is an augmented reality headset that uses sensors for low-light and thermal night vision to create a mixed-reality interface for a soldier. With enough image recognition, the system can help identify terrain and mark targets. These systems will most likely make their way to the commercial sphere in the field of VR/AR headsets. With more data to identify terrain or even hand positions, we might find that controllers for these headsets are no longer necessary.
In this activity, students will learn what it means for a computer to be intelligent and how AI software uses data to identify different things.
Students will be able to
- Students will understand and define what artificial intelligence is
- Students will collect data to understand how algorithmic bias can affect the capabilities of AI
- Students will implement AI in a coded game/tool
Computer Science Teachers Association Standards Connections
3A-AP-16: Design and iteratively develop computational artifacts for practical intent, personal expression, or to address a societal issue by using events to initiate instructions.
3A-IC-25: Test and refine computational artifacts to reduce bias and equity deficits.
3B-AP-08: Describe how artificial intelligence drives many software and physical systems.
Maryland Computer Science Standards Connections
12.AP.A.01: describe how artificial intelligence drives many software and physical systems (e.g., autonomous robots, computer vision, pattern recognition, test analysis).
10.IC.C.02: evaluate and refine computational artifacts to reduce bias and equity deficits
Texas Essential Knowledge and Skills Connections
AR.8A: use coding languages and proper syntax
AR.8E: create algorithms for evaluating a condition and performing an appropriate action using decisions
Virginia Computer Science Standards of Learning Connections
CSF.15: The student will design and implement algorithms using a. sequencing of instructions; b. conditional execution; and c. iteration.
CSF.25: The student will explain the privacy concerns related to the collection and generation of data through automated processes that are not always evident to users.
Activities to Gather Evidence
A middle school project-based curriculum about making interactive, movement-focused AI systems.
Through a series of lessons and activities, students learn technical concepts—such as how to train a simple classifier—and the ethical implications those technical concepts entail, such as algorithmic bias.
Explore how computer science is also about people, solving puzzles, creativity, changing the future and, especially having fun.
This two-lesson plan has students learn how to make sense of conflicting viewpoints from credible sources and how ethics relates to artificial intelligence.