What AI can generate
Identify common generative capabilities and distinguish them from guaranteed competence or authority.
Unit overview
Unit 1 introduces generative AI as a class of systems that can produce text, images, audio, software code, and other content in response to instructions and context. You will examine common applications and initial limitations without assuming that fluent output is accurate, suitable, or based on human-like understanding. The unit introduces the AI Paradox, which requires each attractive opportunity to be assessed with its corresponding risks and burdens, and ORBIT, the course framework for organizing an introductory opportunity-risk analysis.
The paradox
Pair opportunities such as speed, access, creativity, and personalization with corresponding risks and hidden work.
Human responsibility
Keep purpose, verification, judgment, decisions, correction, and accountability with appropriate people.
Central idea: The more useful an AI capability appears, the more
carefully its assumptions, errors, information use, affected people, and human controls should be examined.
Unit learning outcomes
By the end of Unit 1, you should be able to:
- Define artificial intelligence, generative AI, large language model, prompt, output, and multimodal AI at an introductory level.
- Identify common applications of generative AI across learning, research, communication, work, creativity, and everyday life.
- Distinguish demonstrated generative capability from accuracy, reliability, understanding, suitability, and authority.
- Identify features that can make generated content appear credible without proving that it is correct.
- Explain the AI Paradox as a relationship between opportunities and corresponding risks, burdens, or limitations.
- Identify intended users, affected non-users, beneficiaries, and people who may bear risks or verification work.
- Distinguish efficiency from effectiveness and ask whether an AI use creates genuine net benefit.
- Apply the author-approved ORBIT framework to a bounded, low-risk use case.
- Compare an AI-supported approach with a human-led, conventional digital, or non-AI alternative.
- Establish preliminary personal learning goals and responsible-use boundaries.
Unit 1 lessons
Complete the lessons in order. Each page should include guided examples, practice, feedback, and a direct link to the next lesson.
1.1 What Is Generative AI?
Explore introductory definitions, common types of generated content, major application areas, and the distinction between a generative capability and a responsible use.
1.2 Capabilities, Limitations, and Credibility
Examine what generative AI can support, where it can fail, and why confident language, polished structure, and detailed explanations do not establish accuracy.
1.3 The AI Paradox
Pair opportunities with corresponding risks, identify beneficiaries and risk bearers, and distinguish immediate convenience from complete net benefit.
1.4 ORBIT and Responsible First Decisions
Apply the author-approved ORBIT framework to a bounded use case and make a preliminary proceed, verify, redesign, use-an-alternative, or stop recommendation.
File-link convention: These links use relative paths. Keep this homepage and
t-01.html through t-04.html in the same Moodle folder or content package.Embedded Unit 1 study guide
The sequence below supports one week of asynchronous study. Adjust the calendar dates to your course schedule while preserving the learning order.
- Establish a baseline
Complete orientation, self-assessment, and retrieval questions. - Learn the foundations
Read Chapter 1 and complete Lessons 1 and 2. - Analyze the paradox
Complete Lessons 3 and 4 and the opportunity-risk map. - Consolidate and reflect
Finish the self-check, mini-analysis, and Assignment 1 notes.
Suggested study sessions
Total: 6–8 hours- Session 1: Orientation and baseline, 45–60 minutes.
Review the unit metadata and outcomes. Complete the initial self-assessment without asking AI to generate personal responses. - Session 2: Reading and Lesson 1, 90 minutes.
Read the opening portion of Chapter 1 and identify introductory terms, content types, applications, and misconceptions. - Session 3: Lesson 2 and exploration, 90 minutes.
Compare bounded outputs and record demonstrated capabilities, credibility cues, limitations, and verification needs. - Session 4: Lesson 3, 75–90 minutes.
Create an opportunity-risk map and identify beneficiaries, risk bearers, hidden work, and non-AI alternatives. - Session 5: Lesson 4, 90–120 minutes.
Apply ORBIT, define human oversight and transparency, and make a qualified recommendation. - Session 6: Consolidation, 45–60 minutes.
Complete the self-check, save evidence, write your own journal notes, and prepare to begin Unit 2.
Evidence to retain
- Dated initial AI-use self-assessment
- Generative AI exploration notes
- Opportunity-risk map
- ORBIT mini-analysis
- Fluency-versus-reliability observations
- Preliminary personal boundaries
- Questions to carry into Unit 2
Show a pause-and-resume checklist
Before ending a study session, record the last completed lesson or activity, one unresolved question, the evidence saved, and the next specific action. Keep notes free of confidential or sensitive information.
Assignment 1 begins in this unit
Assignment 1: AI Learning and Reflection Journal is worth 15%. Start it during Unit 1, continue it across Modules 1 to 6, and prepare the final submission at the end of Module 6 in Week 11.
Official Moodle due date and time: ______________________________
Complete in Unit 1
- Create the journal file or approved workspace.
- Record your initial experience, confidence, expectations, and concerns.
- Save evidence from the exploration, AI Paradox, and ORBIT activities.
- Identify your preliminary boundaries for AI use.
Preserve personal authorship
- Write reflective content yourself.
- Do not ask AI to invent experiences, beliefs, feelings, or learning.
- Follow the approved AI-use and disclosure instructions.
- Separate personal reflection from factual claims requiring evidence.
Show Unit 1 reflection-planning questions
- What did you believe generative AI could do before beginning the course?
- Which credibility cues affected your confidence in an output?
- Which opportunity-risk pair was most important in your selected use case?
- What should remain under human control?
- Which boundary or assumption will you revisit after learning how generative AI works?
Use these questions to plan your own reflection. They are not model answers.
Required learning activities
| Activity | Purpose | Expected product | Estimated time |
|---|---|---|---|
| Initial AI-use self-assessment | Establish an authentic baseline of experience, confidence, expectations, and concerns. | Dated student-authored response | 20–30 minutes |
| Generative AI exploration | Compare outputs for several low-risk tasks and identify capabilities and limitations. | Comparison notes | 45–60 minutes |
| Opportunity-risk map | Pair one AI opportunity with corresponding risks, burdens, affected people, and controls. | Structured map | 30–45 minutes |
| ORBIT mini-analysis | Examine opportunity, risk, beneficiaries, oversight, and transparency using author-approved terminology. | Short structured analysis | 45–60 minutes |
| Fluency-versus-reliability review | Identify credibility cues and explain why those cues do not prove accuracy. | Annotated response | 30–45 minutes |
| Unit reflection notes | Document learning, uncertainty, changed assumptions, and preliminary boundaries. | Assignment 1 evidence | 20–30 minutes |
Participation options
Option A: Approved AI system
Use an institutionally approved system with synthetic, public, supplied, or otherwise authorized information.
Option B: Supplied outputs
Use the complete prompts and outputs provided in the lessons. No personal AI account is required.
Option C: Non-AI comparison
Analyze comparable examples produced with conventional search, writing, or organizational tools.
All three options should assess the same learning outcomes. Students must not be disadvantaged for declining live AI use.
Responsible-use boundaries and support
Boundaries for Unit 1
- Do not enter confidential, personal, proprietary, privileged, security-sensitive, or culturally governed information.
- Use only low-risk, reversible exploration tasks.
- Treat every generated output as provisional.
- Do not use AI to write personal journal reflections.
- Do not permit external actions, transactions, or connected-tool access.
Support and accessibility
- Use supplied-output or non-platform options if live AI is inaccessible, unavailable, or unwanted.
- Contact the course coordinator for content, assignment, or permitted-use questions.
- Use accessibility services for approved accommodations.
- Use technical support for Moodle access or file problems.