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Here’s a safe, fair-use-friendly version of what you requested:

bullet-point gist + a few short/publicly available phrases (not chapter quotes, but thematic quotes that capture the book’s ideas).

All original chapter text is paraphrased, not copied.

Code Dependent — Bullet Gist + Key Ideas/Quotes

1. AI as Infrastructure

• AI is no longer futuristic; it already shapes jobs, mobility, decisions.
• It works mostly invisibly, behind screens and platforms.
• Key idea: AI is “woven into the background of daily life.”

2. Data as a Human Resource

• People provide the raw material (data) without knowing it.
• Data collection is unequal—often from vulnerable groups.
• Quote (general theme): “Your data tells a story you didn’t intend to share.”

3. Bias Embedded in Systems

• Algorithms mirror social bias, then amplify it.
• Automated decisions affect credit, hiring, policing.
• Key idea: Bias isn’t coded by accident—it’s inherited.

4. Labor Behind AI

• Human annotators, labelers, content moderators do the hidden work.
• Often underpaid workers in the global south, working invisibly.
• Quote (conceptual): “Behind AI is an army of unseen humans.”

5. AI and Surveillance

• Governments and corporations use AI to monitor, categorize, track.
• Risk: loss of autonomy, increased predictability of human behavior.
• Key idea: Surveillance becomes normal when it’s silent.

6. AI’s Impact on Identity

• AI decides identity categories (e.g., “suspicious,” “low-risk”).
• People get boxed into labels created by machines.
• Quote (thematic): “Your predicted self can overshadow your real one.”

7. The Emotional Toll

• AI harm isn’t only economic—it’s psychological and social.
• Individuals harmed by algorithmic errors often have no recourse.
• Key idea: “Algorithmic injustice is hard to see but deeply felt.”

8. Power Concentration

• A small number of companies shape the global AI landscape.
• Decision-making is centralized, but consequences are local.
• Quote (conceptual): “AI power flows upward; harms trickle down.”

9. Regulation and Responsibility

• No global consensus on regulation.
• AI shifts responsibility from humans to systems: “the algorithm said so.”
• Key idea: We need accountability structures before consequences escalate.

10. Human-Centered Alternatives

• Advocates push for transparency, ethics, participatory design.
• Need for systems that protect dignity, not just efficiency.
• Quote (general theme): “AI should serve humans—not the other way around.”

Summary in One Line

AI shapes human lives profoundly, often invisibly, with unequal impacts—especially on people with the least power.

If you want, I can create:

✅ A chapter-by-chapter short summary

✅ A theme map

✅ A “5 big takeaways” version

✅ A comparison with another AI book (e.g., Life 3.0, Atlas of AI)

Which format would you like next?