Not About Us Without Us: Machine Learning in the Indigenous Elementary Classroom

Purpose & objective

Machine learning and AI are all around us, and we use them every day. Engaging our students in the creation of AI empowers them to make positive changes and improvements for their communities. It also opens doors for the jobs of the future, which will no doubt include machine learning and AI. The connection to design thinking allows for natural crosswalks with science and other core courses, creating multiple avenues for integration in the classroom.

This presentation will allow participants to think critically, apply the design thinking process, create a demonstration project, and brainstorm possible applications within their own settings.

All of the programs presented and utilized are free of charge and do not require students to create logins, making replication very easy.

Programs used for this project include:
-Google Slides
-Machine Learning for Kids
-Scratch3

Instructional strategies used for this project include:
-Whole group instruction
-Peer-to-peer discussion and work
-Individual work
-Design thinking

Objectives:
-Participants will have a working definition of machine learning.
-Participants will be introduced to the Guidelines for Indigenous-centred AI Design v.1
-Participants will understand how machine learning for kids and Scratch 3 can be used in the elementary classroom.
-Participants will train a machine to recognize text, an image, or a sound.
-Participants will use Scratch3 to code a project.
-Participants will leave with a list of further readings about AI and Indigenous Communities.

Evidence of Success:
Students in one of our second grade classrooms have successfully completed training and testing a machine learning bot to recognize the difference between maple leaves and other leaves that naturally appear on our grounds. They have also completed the process of training and coding a chatbot that responds appropriately to both positive and negative messages through a cross-curricular connection with our social emotional learning program.

Students who participated in the machine learning program showed active engagement in both the training and evaluation of their machines. Students were able to problem solve when the machine did not work as they expected, and make appropriate adjustments.

Outline

1. Presenter led presentation (backchannel included) 20 minutes
a. Introduction to the Five Big Ideas in Artificial Intelligence
b. Introduction to Machine Learning
c. Guidelines for Indigenous-centred AI Design v. 1
d. Make Me Smile project overview
e. Additional resources and programs
2. Attendee participation (device-based activity, peer-to-peer interaction) 35
minutes
a. Option 1: Train a machine using Machine Learning for Kids projects.
1. Use the trained machine in Scratch3 to complete the project.
b. Option 2: Train a machine using images, sounds, or text. Test the machine
without coding in Scratch3.
3. Discussion Wrap-up in Jamboard: What are some ways you can use
machine learning in your school or classroom? 5 minutes

Supporting research

LinkedIn's Fastest-Growing Jobs Today Are In Data Science And Machine Learning
https://www.forbes.com/sites/louiscolumbus/2017/12/11/linkedins-fastest-growing-jobs-today-are-in-data-science-machine-learning/?sh=2515500951bd

A Complete Guide to Generative AI in 2022
https://research.aimultiple.com/generative-ai/

AI4K12 (AI for K12)
https://github.com/touretzkyds/ai4k12/wiki

AI Beat Humans at Reading! Maybe Not
https://www.wired.com/story/ai-beat-humans-at-reading-maybe-not/

The Rise of Artificial Intelligence and the Threat to our Human Rights
https://rightsinfo.org/rise-artificial-intelligence-threat-human-rights/

How Native Americans Are Trying to Debug A.I.’s Biases
https://www.nytimes.com/2022/03/22/technology/ai-data-indigenous-ivow.html

Creating ethical AI from Indigenous perspectives
https://www.ualberta.ca/folio/2020/10/creating-ethical-ai-from-indigenous-perspectives.html

Indigenous Protocol and Artificial Intelligence
https://spectrum.library.concordia.ca/id/eprint/986506/7/Indigenous_Protocol_and_AI_2020.pdf