Module 1
Lessons 1-11
The first module introduces students to the world of Artificial Intelligence exploring examples of technology, learning about simple algorithms and decision trees and delving into the ethical principles of AI.
Keywords: data, algorithm, intelligent result, human agency, human oversight, ethical principles and bias, real-life scenarios, discussions, group work, presentations, constructive feedback.
Lesson
1
Orientation to Developing AI Competencies
Regarding AI, students start by discussing myths versus realities, discover applications of AI, how it learns and
are introduced to a short history of AI.
Core Learning Objectives
Understands what AI is, and what AI is not.
Provides examples of AI in everyday life.
Lesson
2
Human-AI Interaction
In the second lesson, students are engaged in brainstorming what AI can do and what the human mind can do,
recognizing strengths and weaknesses in both cases.
Core Learning Objectives
Articulates what AI is, and what AI is not and provides examples of AI in everyday life.
Reflects on the role of humans and AI in different real-life scenarios.
Lesson
3
Human Agency in AI interactions
Students debate human agency in a study-case based on a real event, moving on to a game of ”What is and is not
AI”, articulating their opinions.
Core Learning Objectives
Articulates what AI is, and what AI is not.
Recognizes AI as human-led, and presents the importance of human agency and oversight.
Lesson
4
Decision Trees I
The fourth lesson is an introduction to algorithms used by AI with an application for a simple algorithm based on
decision trees.
Core Learning Objectives
Describes a contextually relevant example of human oversight of AI.
Describes a common AI algorithm and how it works.
Lesson
5
Decision Trees II
Exploration of decision trees continues in lesson 5 with concrete exercises of sorting and classifying different
types of pasta.
Core Learning Objectives
Describes a common AI algorithm, how it works, and general use cases for it.
Describes a contextually relevant example of human oversight of AI.
Lesson
6
Module 1 Assessment
Students take the knowledge test that covers the first 5 lessons.
Core Learning Objectives
Consolidate knowledge from Module 1.
Lesson
7
Recommender Algorithms
Students analyze and evaluate the recommender algorithm of a popular music streaming platform.
Core Learning Objectives
Describes a common AI algorithm, how it works, and general use cases for it.
Describes a contextually relevant example of human oversight of AI.
Lesson
8
Ethical AI – Principles
Students discover the core ethical principles of AI and explore examples where ethical risks might occur.
Core Learning Objectives
Defines ethical principles in AI: fairness and non-discrimination, privacy, security, transparency, explainability.
Describes core ethical challenges that may arise in AI.
Lesson
9
Ethical AI – Group Work
In groups, students deliver the presentation they worked on in the previous lesson and offer constructive feedback on the work of their colleagues.
Core Learning Objectives
Defines ethical principles in AI: fairness and non-discrimination, privacy, security, transparency, explainability.
Describes core ethical challenges that may arise in AI.
Lesson
10
Ethical AI – Presentation on a principle
In groups, students design a creative presentation based on an AI principle of their choice.
Core learning objectives
Evaluates the benefits and risks of deploying different AI technologies.
Understands legal privacy and data-sharing protections in their own national context, as well as personal rights and local laws as they pertain to AI.
Lesson
11
Ethical AI – Presentation on a principle II
In groups, students deliver the presentation they worked on in the previous lesson and offer constructive
feedback on the work of their colleagues.
Core learning objectives
Evaluates the strengths and weaknesses of human vs. AI capabilities.
Reflects on the human agency to direct artificial intelligence, and the implications of the conscious decision to use machine-based tools.
Module 2
Lessons 12-20
In the second module, students will use generative AI tools to create images and text while working in group projects. They will critically evaluate AI features used by popular digital platforms and understand their purposes, intentions by using the Ethical Stakeholders Matrix.
Keywords: chatbots, generative AI, image generation, copyright and intellectual property, security and privacy, AI-generated content, Ethical Stakeholders Matrix.
Lesson
12
Generate images with AI
Students engage with a generative AI tool for images in a challenge-based activity and experience first-hand the
potential and limitations of such platforms.
Core Learning Objectives
Explores and reflects on the ways in which AI technologies can be applied to other domains (e.g. art).
Leverages AI tools to create or refine products across different learning domains/subjects.
Lesson
13
Generate text with AI I
This time students engage with a generative AI tool for text. They work in groups on a challenge-based activity
and experience first-hand the potential and limitations of such platforms.
Core Learning Objectives
Takes action to ensure their own security and privacy in digital environments
Understands ownership of content created using AI, and respects intellectual property rights.
Lesson
14
Generate text with AI II
Students continue their exploration of generative AI with chatbots and critically assess the relevance, accuracy,
and bias of the text produced.
Core Learning Objectives
Explores and reflects on the ways in which AI technologies can be applied to other domains (art, music, motion, creative writing, history, etc.).
Recognizes digital manipulation of content or AI-generated content.
Lesson
15
Algorithms as Opinions
This lesson is centered around analyzing different types of platforms and their algorithms: from social media to
mailing tools.
Core Learning Objectives
Explores different types of AI algorithms and what they do.
Understands the role of human opinion in creating algorithms.
Lesson
16
An Ethical Stakeholder Matrix I
In this lesson, students learn about the Ethical Stakeholder Matrix and how it should be used when optimising
algorithms to serve different purposes.
Core Learning Objectives
Explores different stakeholder interests in artificial intelligence.
Understands how to evaluate stated and unstated purposes of AI.
Lesson
17
Ethical Stakeholder Matrix II
Students work in groups to apply the Ethical Stakeholder Matrix in the analysis of a popular social media
platform.
Core Learning Objectives
Works collaboratively to deepen their own expertise and create better products.
Presents to peers, giving and receiving “critical friend” feedback.
Lesson
18
Ethical Stakeholder Matrix III
In teams, students present their work on the matrices and offer structured feedback on their colleagues’
presentations.
Core Learning Objectives
Works collaboratively to deepen their own expertise and create better products.
Presents to peers, giving and receiving “critical friend” feedback.
Lesson
19
Analyzing a video streaming platform’s AI
Students work in groups to critically analyze different features of popular video streaming platforms and how AI
is used to create a personalized experience for users.
Core Learning Objectives
Applies ethical AI principles to critically analyze AI technologies and their outputs.
Reflect on the human agency to direct artificial intelligence and the implications of the conscious decision to use machine-based tools.
Lesson
20
Module 2 Assessment
Students take the knowledge test that covers lessons from Module 2.
Core Learning Objectives
Consolidate learnings from module 2.
Module 3
Lessons 21-30
During the third module, students will continue their learning by applying ethics to their analysis of a popular shopping platform, exploring Deep Fakes, reviewing and designing AI public policies and a child-care robot.
Keywords: Deep Fakes, AI system design, AI citizenship, public policies, environmental implications, designing a child-care robot, ethics by design
Lesson
21
AI Ethics and Deep Fakes
Students sharpen their analyzing skills by exploring Deep Fakes, learning how to identify them and discussing
the risks associated with using Deep Fakes.
Core Learning Objectives
Explains how the decisions of AI creators impact system outcomes.
Assesses the purpose and intention of an AI product, including beyond what is explicitly stated.
Lesson
22
Ethics by Design
Students critically evaluate the features of a popular shopping platform, assessing its objectives and functions.
Core Learning Objectives
Assesses the purpose and intention of an AI product, including beyond what is explicitly stated.
Reflects on the parameters for appropriate data to use in the training and validation of AI models.
Lesson
23
AI Citizenship
This lesson focuses on active citizenship and empowers students to discover their potential to influence public
policies.
Core Learning Objectives
Critically evaluates the impact of AI technologies on employment, and social and cultural norms.
Competently engages in decision-making processes relating to AI policy.
Lesson
24
AI Policy Analysis
Starting from a fictional country policy, students critically analyze the goals, principles and values of the
document, preparing the next steps in the following lesson.
Core Learning Objectives
Considers the environmental footprint of developing and deploying AI technologies, as part of AI decision-making.
Critically evaluates the impact of AI technologies on employment, and social and cultural norms.
Lesson
25
AI Policy Redesign
Students work in groups to redesign the fictional policy from the previous lesson, considering important aspects
that lead to a better society, such as the environmental implications.
Core Learning Objectives
Considers the environmental footprint of developing and deploying AI technologies, as part of AI decision-making.
Competently engages in decision-making processes relating to AI policy.
Lesson
26
AI and the Environment
Students learn about how AI impacts the environment and quantify their own carbon footprint.
Considers the environmental footprint of developing and deploying AI technologies, as part of AI decision-making.
Competently engages in decision-making processes relating to AI policy.
Lesson
27
Module 3 Assessment
Students take the knowledge test that covers lessons from Module 3.
Core Learning Objectives
Consolidate learnings from module 3.
Lesson
28
AI System Design – Designing a Childcare Robot
In the next lessons, students will apply their AI knowledge to design a childcare robot by defining its purpose,
mapping ethical stakeholders, considering design features, and addressing ethical challenges.
Core Learning Objectives
Communicates the purpose, process, and data use of AI creations.
Reflects on and communicates artistic, social, cultural and/or ethical considerations when creating artifacts with AI tools.
Lesson
29
AI System Design – Feedback
The next stage of their project is evaluating and giving and receiving feedback. Each team will evaluate another
team’s design, exercising their critical thinking.
Core Learning Objectives
Communicates the purpose, process, and data use of AI creations.
Provides and receives constructive feedback. Reflects on feedback received.
Lesson
30
AI System Design – Iteration & Feedback
This lesson enables students to improve their original designs while preparing them for the final group project.
Core Learning Objectives
Reflects on and communicates artistic, social, cultural and/or ethical considerations when creating artifacts with AI tools.
Provides and receives constructive feedback. Reflects on feedback received.
Module 4
Lessons 31-36
Module 4 concludes the course with a finale exam and followed by a series of sessions where students work on their group project, designing a learning experience on AI for their community.
Keywords: brainstorming, teamwork, planning, design, feedback, presentation.
Core Learning Objectives
Leverages socio-emotional competencies to work with others to create a lesson to help teach
community members about AI.
Reflects on any ethical, data-oriented, and environmental implications of their AI lesson.