Creating a Personal AI Notes Blog | Generated by AI
Question: What do you think about creating a personal AI-generated notes blog (like mine with 8000 answers), and what are the legal concerns and how others might perceive it?
Answer:
Your idea is directionally solid—but it’s important to separate what it is from what it could become, and to be realistic about both legal and social implications.
1. What your blog actually is (in essence)
At its core, your project is:
- A personal knowledge base (PKM)
- Generated via AI-assisted thinking (prompt → answer → archive)
- Published as a public corpus of reasoning and notes
That’s closer to:
- A “thinking log” or “intellectual trace”
- Not the same as a trained AI model
- Not equivalent to what companies like OpenAI or xAI do
So your comparison to “models trained on the internet” is partially right but slightly off:
- Big models → train on raw data, compress into weights
- You → generate explicit outputs and publish them
You’re not training a model—you’re externalizing cognition
That’s actually interesting.
2. Legal concerns (this is where you need to be careful)
(1) Copyright / content ownership
Main risk:
-
If your notes include:
- Direct quotes
- Paraphrased proprietary content
- Summaries of paid materials (books, courses)
Then potential issues:
- Copyright infringement
-
Especially if:
- Content is recognizable
- Not transformed enough
- Used at scale (8000 notes is not small)
Safe zone:
- Your own reasoning
- Highly transformed explanations
- Original synthesis
Risk zone:
- “AI summarized X book/article” repeatedly
- Copy-like structure or phrasing
(2) AI-generated content ownership
In most jurisdictions:
- Pure AI-generated content → may not be fully copyrightable
-
But:
- If you curate, edit, structure → stronger claim
Practically:
- You can publish it
- But enforcing ownership may be weak
(3) Terms of service (LLMs)
Depending on tools you used:
-
Some platforms restrict:
- Bulk generation
- Republishing at scale
Most modern tools allow it, but:
- Worth checking if you used APIs or platforms heavily
(4) Data privacy / sensitive info
Avoid including:
- Private conversations
- Company/internal info (especially since you work with banks)
- Any identifiable personal data
This is higher risk than copyright, especially professionally.
3. How others will perceive it
This splits into 3 very different audiences:
(A) Builders / engineers
They’ll think:
- “Interesting dataset of thinking”
- “Could be useful if structured well”
- “But raw dumps are noisy”
What earns respect:
- Curation
- Depth
- Original insight
What reduces value:
- Mass AI outputs without filtering
(B) General audience
They’ll likely think:
- “This is too much”
- “Hard to navigate”
- “Feels like AI spam”
8000 notes = overwhelming without strong structure
(C) Serious thinkers / researchers
They’ll be more critical:
- “Is this original thinking or AI echo?”
- “Where is the signal vs noise?”
- “What is the author’s real contribution?”
They value:
- Compression (not expansion)
- Insight density
4. The real risk (not legal, but strategic)
The biggest issue is not legality—it’s dilution
If you publish everything:
- You become a high-volume node
- Not a high-signal node
In the AI era:
People don’t value who produces the most They value who filters the best
5. How to evolve this into something powerful
Right now:
- You have raw material
To make it valuable:
Step 1 — Layer structure
- Group by themes
- Build “learning paths”
- Connect ideas
Step 2 — Add your voice
- What do you think?
- Where do you disagree with AI?
Step 3 — Compress
Turn 8000 notes into:
- 100 essays
- 20 frameworks
- 5 core ideas
This is where value emerges.
6. Big picture
Your instinct is actually aligned with something deeper:
- You’re building a personal cognitive dataset
-
Similar to:
- Research logs
- Lab notebooks
- Thinking archives
But:
- Raw logs ≠ knowledge
- Curation = intelligence
Final take
- Legally: mostly safe if you avoid copying and sensitive data
- Socially: interesting but currently noisy
- Strategically: high potential if you shift from volume → insight
If you want, I can help you turn this into:
- A “second brain system”
- Or even a trainable personal dataset for fine-tuning models later
That’s where this becomes genuinely powerful.