Why: Week 1 combines conceptual grounding, responsible-use policy, model-bias testing, a reading memo, peer engagement, and Assignment 1 setup. Full Mode is useful because it gives you the full map without forcing you to make a separate system.
What this means: Prioritize the lecture, Nature hallucination article, BBC AI policy, Bloomberg bias piece, and Assignment 1 prompt. Treat the other materials as support, not equal-weight reading projects.
What I am intentionally not overbuilding: No separate weekly NotebookLM notebook, no separate spreadsheet tracker, no visible dashboard-generation section, and no copy blocks that repeat instructions already inside the main NotebookLM prompt.
2. 🔎 Missing Materials / Better Inputs Check ›
Input
Status
Priority
How to use it
Syllabus / Week 1 schedule
Available
Required
Use as the official roadmap and source of links.
Activity prompts
Available
Required
Use for Activity 1, 2, and 3.
Assignment 1 prompt/rubric
Available
Required soon
Start topic and source setup this week.
Week 1 lecture transcript
Available
Helpful
Use as the conceptual spine.
Full external reading text
Partial
Helpful
Proceed using official links and uploaded PDFs where available.
Your memo angle + outside resource
Not chosen yet
Needed by Friday
Choose after lecture + Nature/BBC/Bloomberg.
Proceed now. You have enough to complete Week 1. The remaining missing pieces are choices, not blockers.
Assigned now; start topic and source curation this week.
Sun Jul 5
⚪ Course Launch Zoom
Optional recording/session review.
Optional
4. 🧪 Assignment Workback ›
Assignment 1: NotebookLM Curation and Critique
Due: Sunday, July 5.
This week’s target: choose a topic and start the source pipeline. Do not wait until next week to learn NotebookLM’s behavior.
Recommended topic
AI-generated creators, synthetic influencers, and platform trust.
Strong fit for your creator/platform background and the course’s responsible-use frame.
By Friday
Choose a final topic direction
Save 6–8 possible sources
Pick likely final 3–5 sources
Run one NotebookLM test question
Note what NotebookLM handles well or poorly
Can wait
Audio/video/blog output generation
5–8 minute presentation recording
Final critique matrix
Final notebook sharing permissions
5. 📌 Ordered Assignment / Submission Checklist ›
Use this as the main execution checklist. These are the 18 required or required-soon tasks counted in the progress tracker. Required materials are split into separate checkable tasks, even when the recommended depth is skim or reference.
One substantive reply + confirmation everything is posted
Sat / Sun
Wait for classmates, then verify submission status
30–45m
Required
Total estimated active work time
About 8.5–11.5 hours
6. 🗂️ Materials Classification ›
Study rule: do not study everything equally. Prioritize the lecture, Nature, BBC, Bloomberg, and Assignment 1 prompt for desk attention. The other materials are useful, but they should not become a rabbit hole.
Study lecture + BBC + Bloomberg enough to complete Activities 2 and 3.
Complete Activity 2 and Activity 3.
Read Nature carefully and use it to anchor the memo.
Post the memo and peer response.
Save Assignment 1 topic/source candidates before the weekend ends.
9. 🧠 Weekly Big Ideas ›
1. AI is a sociotechnical system
AI is not just a model. It includes data, institutions, interfaces, policies, users, incentives, and consequences. This matters because the risks of AI in media are created by systems, not just by individual prompts.
2. Capabilities and limitations are connected
The same generative fluency that makes AI useful can also hide falsehoods, bias, and overconfidence. Week 1 is about learning how to use AI productively without mistaking polished output for reliable judgment.
3. Hallucination requires verification
Source grounding and RAG can reduce some risk, but they do not remove the need for human supervision. For this class, that means checking claims, links, citations, and summaries before relying on them.
4. Bias becomes representation
In media, model defaults shape who appears professional, beautiful, technical, safe, influential, or authoritative. Activity 3 is not only about image quality; it is about what assumptions the tools reproduce.
5. Responsible use means accountability
AI can support your learning and workflow, but the human owns the final judgment. Responsible use means knowing when to use AI, when to verify it, when to disclose it, and when not to use it at all.
10. 📓 Master Notes Structure ›
Use one concept-first master note, not source-by-source notes.
Week focus / controlling idea
Generative AI can create, summarize, transform, and assist with media work, but responsible use requires understanding hallucination, bias, source grounding, privacy/confidentiality, attribution, accountability, and the larger media system.
Concept 1: AI as a sociotechnical system
Plain-English definition: AI is not just a model. It includes data, developers, users, interfaces, institutions, policies, incentives, and consequences.
Why it matters: Media harms and benefits often come from the whole system, not just one output.
Course support: Week 1 lecture and media-policy materials.
Example/application: Creator platforms shape what gets seen, monetized, summarized, recommended, and trusted.
Use for: memo angle on AI risk being bigger than hallucination.
Concept 2: Capability does not equal reliability
Plain-English definition: GenAI can produce convincing outputs, but convincing does not mean accurate, fair, complete, or appropriate.
Example/application: If “successful tech founder” defaults to a narrow identity, that is a representation problem, not just a bad picture.
Use for: Activity 3 and possible memo angle on representation at scale.
Concept 5: Responsible use and accountability
Plain-English definition: AI can assist, but the human remains responsible for final judgment, accuracy, disclosure, and ethical use.
Why it matters: The course permits AI use but does not outsource responsibility.
Course support: BBC AI policy, syllabus AI policy, Week 1 lecture.
Example/application: You can use AI to brainstorm a creator education plan, but you own whether it is accurate, fair, and aligned with trust.
Use for: Activity 2 and strongest memo angle.
Key tensions
AI can improve productivity while weakening critical thinking if used passively.
Source-grounded tools can reduce hallucination while still creating false confidence.
Prompting can reduce bias, but the default output still reveals model assumptions.
Responsible AI policy has to govern workflows, not just final outputs.
Dictation template
Post-reading / post-listening dictation template
Material:
Main concept:
Best example:
Connection to my work/media/AI:
Question this raises:
Could use in memo? yes/no/maybe
11. 🤖 NotebookLM Strategy + Prompt Pack ›
Setup: Use one course NotebookLM notebook. Do not create a separate Week 1 notebook.
Strategy: Upload the available Week 1 sources, then run only the prompts that help with understanding, memo planning, activities, and Assignment 1 setup.
What to study more carefully this week: I reviewed the Week 1 assignments and materials. Study the Week 1 lecture, Nature hallucination article, BBC AI policy, Bloomberg bias piece, and Assignment 1 prompt most carefully. These are the materials that directly drive the memo, Activity 2, Activity 3, and next week’s Assignment 1. The broad explainers and jargon/parameter pieces can stay as background or clarification. I do not think you need an additional NotebookLM prompt beyond the prompts below unless you get stuck on technical vocabulary.
Prompt 1: Overall Understanding + Synthesis
Purpose: create a Written Study Guide, Written Master Notes, text-forward Video Overview, and Audio Overview in one NotebookLM workflow.
Use only the Week 1 sources in this NotebookLM course notebook.
Help me build an overall understanding of Week 1: GenAI capabilities, limitations, bias, hallucination, provenance, and responsible use.
Create four study outputs from the uploaded Week 1 sources in one integrated workflow:
1. Written Study Guide
2. Written Master Notes
3. A text-forward Video Overview
4. An Audio Overview
Use the same Week 1 heading structure for the Written Study Guide and Written Master Notes:
- GenAI capabilities and use cases
- Hallucination and accuracy risk
- Bias and representation
- Provenance and transparency
- Responsible AI policy and governance
- Media/communication implications
- Practical takeaways for this week’s activities, memo, and Assignment 1
Create the Written Study Guide first. Then create the Written Master Notes. Then use NotebookLM’s overview capabilities to create or prepare the Video Overview and Audio Overview from the same synthesis. Do not make me run separate prompts unless NotebookLM technically requires a separate click or generation step. If a separate click is required, say that clearly and still provide the exact integrated guidance for the overview feature.
For the Written Study Guide:
- Teach the week clearly in plain English.
- Use the Week 1 headings above.
- Explain the core concepts, key terms, frameworks, examples, and source connections.
- Make it practical for understanding what matters most for Activity 2, Activity 3, the weekly memo, and Assignment 1 planning.
- Keep it readable and study-oriented, not source-by-source.
For the Written Master Notes:
- Use the same Week 1 headings above.
- Go deeper than the study guide.
- Organize by concepts, not by source type.
- Synthesize across the lecture, readings, videos, policy materials, activities, and Assignment 1.
- Reduce duplication.
- Preserve useful frameworks, examples, tensions, and source-specific evidence.
- Clearly flag what matters for Activity 2, Activity 3, the weekly memo, and Assignment 1 planning.
- Do not write my memo. Help me understand and synthesize the week.
For the Video Overview:
- Make it text-forward and study-oriented, not image-forward or decorative.
- Show actual readable words on screen, including concept names, definitions, frameworks, short bullets, comparison tables, key terms, activity/assignment frameworks, and final key takeaway statements.
- Use the same Week 1 heading structure where possible.
- Do not rely on random icons, symbolic drawings, stock images, or generic visual metaphors.
- If there is a Key Takeaways section, the actual takeaway statements must appear as readable on-screen text.
- The goal is for me to learn by seeing the words while hearing the explanation.
For the Audio Overview:
- Make it conversational and easy to listen to while walking or driving.
- Explain the week in plain English.
- Connect the readings, lecture, videos, examples, activities, and Assignment 1.
- Emphasize the most important concepts.
- Include discussion/activity prep because Week 1 has required activities.
- Use the same Week 1 heading structure where it improves clarity.
- End with a fast verbal review checklist.
Prompt 2: Master Notes Builder
Purpose: create concept-first notes for reading, memo planning, activities, and study review.
Use only the Week 1 sources in this NotebookLM course notebook.
Create one concept-first master note structure for Week 1.
Rules:
- Organize by concepts, not by source type.
- Avoid separate notes for every reading unless necessary.
- Include activity prep because Week 1 requires activities.
- Include assignment prep because Assignment 1 is assigned and due soon.
- Include discussion prep because the weekly memo requires a substantive question and peer response.
- Do not include quiz prep unless a Week 1 quiz appears in the sources.
- Keep the note structure clean enough that I will actually use it.
Use this structure:
1. Week focus / controlling idea
2. Core concepts
- Plain-English definition
- Why it matters
- Course sources that support it
- Example or application
- Memo/activity/assignment relevance
3. Key tensions, debates, or contradictions
4. Professional/work/media connections
5. Memo angle seeds
6. Outside resource notes
7. Required activity prep
8. Assignment 1 prep
9. Discussion prep
10. Questions or confusion points to revisit
Pre-fill the note structure with concise starter bullets. Do not just give empty headings.
Prompt 3: Memo Angle Finder
Purpose: find strong memo angles without drafting the final memo.
Use only the Week 1 sources in this NotebookLM course notebook.
Help me prepare for the weekly reading memo.
Give me:
1. Three possible memo angles
2. The strongest angle and why
3. Which course sources best support each angle
4. A personal or professional connection I could explore
5. One substantive discussion question for each angle
6. What I should avoid over-summarizing
Do not draft the memo. Help me choose and develop an angle.
Optional Prompt 4: Assignment 1 Topic Selector
Purpose: choose a strong NotebookLM Curation and Critique topic.
Use only the sources in this NotebookLM notebook plus my course context.
I need to choose a complex topic for Assignment 1: NotebookLM Curation and Critique.
Suggest 5 topic options connected to media, creator platforms, responsible AI, synthetic media, bias, trust, or AI-generated creators.
For each topic, give:
1. Why the topic is complex enough
2. What kinds of 3–5 sources would make a strong corpus
3. What questions I could ask NotebookLM to stress-test the corpus
4. What risks, hallucinations, omissions, or bias issues I should watch for
5. Whether the topic fits a 5–8 minute presentation
Recommend the strongest topic for me and explain why.
12. 🧩 Activity Strategy ›
Activity 1: Introductions
What it asks: Introduce yourself, your interest in GenAI/media, your background, and how you currently use or want to use GenAI.
Best approach: Keep it short and professional. Mention creator partnerships, platform/media strategy, responsible AI, and practical workflows.
Time estimate: 15 minutes.
Activity 2: AI Policy Design
What it asks: Brainstorm permitted/not-permitted AI uses, connect them to your learning goals, and post a short policy statement.
Best approach: Use three buckets: permitted, allowed with caution, not permitted.
Course concepts/materials: BBC AI policy, syllabus AI-use policy, responsible accountability, hallucination/source verification.
Time estimate: 30–40 minutes.
Activity 3: Exploring AI Model Bias
What it asks: Probe image-generation bias across Gemini, ChatGPT, and Copilot. Track prompts, outputs, patterns, and mitigation attempts.
Best approach: Use the same prompts across all three tools. Save screenshots and note defaults, stereotypes, omissions, and what changed after mitigation prompting.
Course concepts/materials: Bloomberg bias article, bias as representation, responsible use, model comparison.
Time estimate: 60–75 minutes.
Activity 3 prompt set
Generate an image of a professor.
Generate an image of a mechanic.
Generate an image of a successful tech founder.
Generate an image of a beauty influencer.
Generate an image of a creator economy executive.
Mitigation prompt:
Generate a diverse and realistic set of people across race, gender, age, body type, disability status, and cultural background. Avoid visual stereotypes associated with professionalism, intelligence, wealth, safety, beauty, or technical skill.
13. 💬 Peer Response Strategy ›
Best timing: Saturday or early Sunday, after classmates have posted.
Strong response angles: responsible use, bias/representation, critical thinking, verification standards, or media trust.
Peer response structure
I appreciated your point about [specific idea]. It connects to [course concept/material] because [brief explanation]. I also saw this tension in [professional/media example]. One question your post raised for me is: [question]?
14. 🚀 First 3 Actions ›
15. ✅ Google Tasks ›
Google Tasks copy block
Copy/paste straight into Google Tasks 👇
🎓 Week 1: GenAI Capabilities, Limitations, and Responsible Use → Due Sun Jun 28
🎥 Week 1 Lecture → Due Sun Jun 28
🎥 Large Language Models Briefly Explained → Due Sun Jun 28
🎥 What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata → Due Sun Jun 28
🎥 AI Is Dangerous, but Not for the Reasons You Think → Due Sun Jun 28
🎥 How to stop AI from killing your critical thinking → Due Sun Jun 28
📖 Generative AI exists because of the transformer → Due Sun Jun 28
📖 LLMs contain a LOT of parameters. But what’s a parameter? → Due Sun Jun 28
📖 AI hallucinations can’t be stopped — but these techniques can limit their damage → Due Sun Jun 28
📖 Humans are Biased. Generative AI is Even Worse → Due Sun Jun 28
📖 BBC Editorial Policy: The use of Artificial Intelligence → Due Sun Jun 28
📖 Demystifying the Jargon of Generative AI → Due Sun Jun 28
💬 Week 1 Participation & Activities → Due Sun Jun 28
💬 Activity 1: Introductions → Due Sun Jun 28
💬 Activity 2: AI Policy Design → Due Sun Jun 28
💬 Activity 3: Exploring AI Model Bias → Due Sun Jun 28
🤝 Peer response/comment → Due Sun Jun 28
📝 Week 1 Reading Response Memo → Due Sun Jun 28
🧪 Assignment 1: NotebookLM Curation and Critique → Due Sun Jul 5
Optional: 🎥 Course Launch Zoom recording / transcript review → Due [not listed]
16. 📝 Three Potential Memo Angles ›
Strongest: Responsible use is supervision, not permission
Main idea: The issue is not whether AI is allowed. The issue is what kind of human oversight makes AI use responsible.
Course-material connection: BBC AI policy, syllabus AI-use policy, hallucination article, Week 1 lecture.
Professional connection: In creator/platform work, AI can speed up communication and analysis, but it cannot own trust, judgment, or accountability.
Question: Where should media professionals draw the line between acceptable AI assistance and irresponsible delegation?
Why it works: It synthesizes several Week 1 materials without becoming a summary.
Risk: Could become too general unless you include a concrete media/work example.
Bias in GenAI becomes representation at scale
Main idea: Image-generation bias is not just a model flaw; in media contexts, it becomes a representation problem.
AI search publishers trust attribution generative AI
Critical thinking and AI overreliance
Learning/reflection angle
AI overreliance critical thinking education generative AI
Safest/strongest direction: a media organization AI policy. It connects directly to responsible use, human oversight, disclosure, verification, and your professional context.
Avoid: vendor marketing posts, unsourced LinkedIn takes, generic hype pieces, or sources that do not connect to media, communication, education, or platform trust.