"If AI can answer any question, why read books?" This question is becoming common. AI does have vast knowledge and can respond instantly. But perhaps this is precisely why the value of reading and deep learning has become clearer.
This article examines what reading and learning mean in an age of AI.
What AI Has and Hasn't Changed
Large language models have transformed our relationship with knowledge. Information access, learning efficiency, creative assistance—these are indeed revolutionary changes.
However, some things remain unchanged. Depth of understanding, the value of experience, the source of creativity, value judgment, meaning-making—these remain in the human domain.
For more on AI and human strengths, see "Human-AI Partnership".
AI provides answers, but humans pose questions. Good questions require deep understanding and rich experience.
The "Let AI Handle Knowledge" Trap
"Memorization is pointless; just ask AI" has pitfalls.
You Need Knowledge to Ask Good Questions
Asking AI the right questions requires knowing what to ask.
Example: Learning Programming
Complete beginner: "How do I make programs?"
With basic knowledge: "For implementing async processing in Python, when should I use asyncio versus threading, considering I/O-bound vs CPU-bound tasks?"
→ The second question gets far more useful answers.
This is the knowledge bootstrap problem: you need some knowledge to acquire deeper knowledge.
You Can't Think Critically Without Knowledge
AI sometimes states false information confidently (hallucination). Without background knowledge, you can't judge accuracy.
- Is this historical claim AI makes true?
- Is this proposed solution optimal?
- Are there logical gaps in this explanation?
Judging these requires your own knowledge and thinking ability.
Creative Leaps Require Knowledge
AI recombines existing knowledge well but struggles with truly novel ideas. Human creativity emerges from unexpected connections between different domains.
Steve Jobs applied calligraphy lessons to Mac typography. Accumulated knowledge across domains fuels creativity.
Skills to Develop in the AI Age
In an age of rising AI, what abilities should humans cultivate?
1. Asking Good Questions
AI answers well; humans question. The ability to ask good questions is invaluable.
- What problem really needs solving?
- What issues has no one noticed?
- What should we be asking here?
The ability to ask good questions is one of the most valuable skills in the AI age. It's cultivated through wide reading and deep thinking.
2. Reading Context
AI processes given information but struggles with nuance and unspoken meaning.
- What does someone really mean?
- What does this situation demand?
- What are the implicit assumptions?
Reading fiction is excellent training for reading between the lines.
3. Value Judgment and Decision-Making
Only humans can determine "what's right" and "what to choose."
- Resolving ethical dilemmas
- Prioritizing among options
- Long-term perspective decisions
Reading philosophy and history provides cases of complex value judgments, helping form your own decision-making framework.
4. Embodied Wisdom
AI exists only digitally. Much human wisdom is rooted in physical experience.
- Craft skills
- Interpersonal skills
- Sports and artistic practice
- Emotion and intuition
Books alone don't provide this, but reading can improve the quality of practice.
5. Integrative Thinking
Synthesizing knowledge from different fields into new perspectives is a human strength.
- Merging science and art
- Dialogue between Eastern and Western thought
- Balancing technology and humanity
Reading across diverse fields builds the foundation for integrative thinking.
A New Learning Paradigm
AI-era learning requires different approaches.
From Memorization to Understanding
Simple fact memorization increasingly falls to AI. Humans can focus on understanding "why things are the way they are."
Traditional Learning
Memorize: "1776, American Declaration of Independence"
AI-Era Learning
Why did colonists seek independence? What economic and philosophical foundations? What lessons for today?
From Consumption to Creation
Beyond receiving information, creating from it matters.
- Read → Summarize your thinking → Share your ideas
- Learn → Practice → Reflect and improve
- Get idea → Shape it → Get feedback
From Efficiency to Depth
AI maximizes efficiency. Humans might intentionally choose inefficient deep learning:
- Spend time diving deep into one book
- Hands-on experimentation
- Learning through repeated failure
Let AI handle efficient information gathering; humans invest in deep understanding and experience. This is the new balance of learning.
The Meaning of Reading in the AI Era
So what does reading mean in the AI era?
Learning Patterns of Thought
Good books let you follow an author's thinking process. AI gives conclusions; books show how thinking unfolds.
Logic construction, hypothesis formation, handling objections—these thinking patterns come only from reading.
Immersive Learning
AI conversations tend toward fragments. Books offer immersion in a single topic. Spending hundreds of pages on one subject leaves deep traces. This immersive learning can't be replicated by AI.
Unexpected Discoveries
AI answers what you ask. Books reveal what you never thought to ask.
- A chapter you thought irrelevant holds key insights
- A footnote opens new interests
- A casual phrase resonates deeply
This serendipity is a great joy of reading.
Dialogue with Authors
Books are encounters with individual minds. Authors' life-developed thinking, understood over time—AI returns "average answers," but books offer unique perspectives. This encounter with individuality is the essential value of reading.
Practical Approaches
Here are concrete approaches for AI-era reading and learning.
Balancing AI and Books
| Situation | Use AI | Read Books |
|---|---|---|
| Fact checking | ○ Instant answers | △ Time-consuming |
| Deep understanding | △ Fragmented | ○ Systematic |
| New perspectives | △ Average responses | ○ Unique author views |
| Thinking training | × Conclusions only | ○ Follow the process |
Three Learning Steps
- Overview (use AI): Understand the big picture
- Deep learning (read books): Build systematic knowledge
- Application: Apply learning to real life
The Importance of Reading Notes
In the AI era, reading notes become more valuable.
- Summarize in your own words: Deepen understanding, fix memory
- Record AI conversations: Preserve your thinking about books
- Make searchable: Find learning when needed
Tip
Record not just book summaries but "how you felt" and "what you thought." This becomes most valuable when reviewing later. Digital records let you search for needed insights instantly.
Conclusion
The essential value of reading and learning hasn't changed in the AI era. Rather, clarity about what AI can do versus what only humans can do has sharpened the focus of human learning.
Key Takeaways
- AI handles: Information provision, summarization, Q&A, efficiency
- Only humans can: Ask questions, judge value, create, make meaning
- AI is a partner, not a threat
- Build your intellectual foundation through reading while leveraging AI's power
Finally, a question for the AI era: What do you want to ask? What do you want to create?
Reading will surely help you find those answers.
Start Your AI-Era Reading Journey
With Reading Forest, you can record all your reading experiences—including insights from AI conversations.
Search your digital notes to retrieve learning whenever you need it.