Course Modules

Module Topics, Questions Posed, and Learning Outcomes

1. AI Basics: Terms & Concepts: This module provides an overview of key terms and concepts, like AGI and Narrow AI, that are crucial for understanding AI. Learners will participate in activities and discussions that reinforce these concepts. 

Essential Question: What is the difference between Artificial General Intelligence (AGI) and Narrow AI? Why is it important to distinguish between the two?

By the end of this module, learners should be able to:

• Define key terms such as AI, AGI, and Narrow AI.

• Differentiate between AGI and Narrow AI.

• Understand the fundamental principles of AI and how it operates.

2. AI Applications & Benefits: Here, we explore the various applications of AI in today's world and the benefits these technologies offer. This includes hands-on activities using AI tools and software. 

Essential Question: What are some real-world applications of AI? How does AI add value in these scenarios?

By the end of this module, learners should be able to:

• Identify various real-world applications of AI.

• Understand the benefits of AI applications in different sectors.

• Reflect on the impact of AI technologies on everyday life.

3. AI Tools: Real-world Cases: In this module, learners will be introduced to real-world examples of how AI is being used. We will examine cases that highlight the practical utility of AI in various fields. 

Essential Question: Can you identify and explain a real-world case where AI was used? How did AI contribute to the outcome?

By the end of this module, learners should be able to:

• Describe real-world examples where AI has been applied.

• Understand the practical utility of AI across various fields.

• Reflect on the broader implications of AI's real-world applications.

4. Understanding AI Paradox: This module delves into the paradoxes inherent in AI, such as its potential to both solve complex problems and create new ones. 

Essential Question: What is the AI paradox? Can you provide examples of how AI can both solve and create problems?

By the end of this module, learners should be able to:

• Understand and explain the AI paradox.

• Provide examples of how AI can both solve and create problems.

• Reflect on the complexities and paradoxes inherent in AI technology.

5. Consequences of AI Misinterpretation: We will explore the potential negative consequences of misinterpreting AI outputs or misunderstanding AI's limitations. Activities will involve hands-on experimentation with AI tools and software to illustrate these points. 

Essential Question: What can be the potential negative outcomes of misinterpreting AI outputs? How can misunderstanding AI's limitations lead to issues?

By the end of this module, learners should be able to:

• Understand the potential negative consequences of misinterpreting AI outputs.

• Recognize the risks of misunderstanding AI's limitations.

• Reflect on the importance of correctly interpreting and understanding AI.

6. AI's Dark Side: Scams & Tactics: In this module, learners will learn about the ways AI can be used nefariously, such as in scams or misinformation campaigns. This knowledge is vital for understanding the broader ethical and societal implications of AI. 

Essential Question: What are some ways in which AI can be used for nefarious purposes? How does understanding these tactics contribute to our broader understanding of AI's societal implications?

By the end of this module, learners should be able to:

• Understand how AI can be used for nefarious purposes.

• Identify examples of AI-enabled scams or misinformation campaigns.

• Reflect on the ethical and societal implications of AI misuse.

7. Countering AI-enabled Scams: We'll look at ways individuals and societies can counter the misuse of AI, promoting a proactive, informed approach to these technologies. 

Essential Question: How can individuals and societies proactively counter the misuse of AI? What strategies or tools could be employed to this end?

By the end of this module, learners should be able to:

• Identify strategies to counter the misuse of AI.

• Understand the role of individuals and societies in countering AI misuse.

• Reflect on the need for proactive measures to combat AI misuse.

8. Countering AI-enabled Scams: We'll discuss the key ethical dilemmas posed by AI and how society should navigate these dilemmas. Essential Question: What are the key ethical dilemmas posed by AI? How should society navigate these dilemmas?

Essential Question: What are the key ethical dilemmas posed by AI? How should society navigate these dilemmas?

By the end of this module, learners should be able to:

• Understand the key ethical dilemmas posed by AI.

• Reflect on potential ways society can navigate these dilemmas.

• Contribute to discussions on the ethical implications of AI.

Assessment Plan:

The assessment in this course is designed to measure learners' understanding of the subject matter, and their ability to apply their knowledge and skills in a variety of contexts. The assessment plan consists of the following components:

1. Introductory Exam (0%): This is a diagnostic assessment designed to evaluate learners' existing knowledge and understanding of the subject matter. While this does not contribute to the final grade, it helps establish a baseline and identify areas where learners might need additional support.

2. Three Labs (5% each): These labs provide learners with the opportunity to apply their knowledge and skills in a practical setting. Learners will be given feedback on their performance to help them understand where they did well and where they need to improve.

3. Two Assignments (20% each): These assignments will require learners to engage more deeply with the subject matter, using critical thinking and problem-solving skills. Feedback will be provided on these assignments, focusing on the quality of the learners' analysis and understanding.

4. Lab Report (15%): This will involve a detailed write-up of a practical activity, requiring learners to explain their approach, their findings, and their interpretation of the results. Feedback will be given on the accuracy and depth of their analysis.

5. Final Exam (30%): This is a comprehensive examination that covers all aspects of the course. It will measure learners' understanding and retention of the course content.

There are no letter grades in this course to avoid the usual disputes about grade boundaries. Instead, learners' performance will be evaluated on a continuum of understanding. The passing grade is 50%, which means learners must demonstrate a good understanding of at least half of the course material.

The confidence in this determination is mostly high, since there are many paths the learners can take according to their strengths and interests. The final exam is meant to verify the knowledge they have gained throughout the course. The multiple modes of assessment and their alternative paths - labs, assignments, and exams - also help ensure a more holistic and reliable evaluation of learners' understanding and capabilities.