How to Stay Smart in a Smart World: Why Human Intelligence Still Beats Algorithms
- 10h 9m 59s
- Gerd Gigerenzer
- Recorded Books, Inc.
- 2022
Doomsday prophets of technology predict that robots will take over the world, leaving humans behind in the dust. Tech industry boosters think replacing people with software might make the world a better place—while tech industry critics warn darkly about surveillance capitalism. Despite their differing views of the future, they all agree: machines will soon do everything better than humans. How to Stay Smart in a Smart World shows why that's not true, and tells us how we can stay in charge in a world populated by algorithms.
Machines powered by artificial intelligence are good at some things (playing chess), but not others (life-and-death decisions, or anything involving uncertainty). Gerd Gigerenzer explains why algorithms often fail at finding us romantic partners (love is not chess), why self-driving cars fall prey to the Russian Tank Fallacy, and how judges and police rely increasingly on nontransparent "black box" algorithms to predict whether a criminal defendant will reoffend or show up in court. He invokes Black Mirror, considers the privacy paradox (people want privacy, but give their data away), and explains that social media get us hooked by programming intermittent reinforcement in the form of the "like" button. We shouldn't trust smart technology unconditionally, Gigerenzer tells us, but we shouldn't fear it unthinkingly, either.
About the Author
Gerd Gigerenzer is Director Emeritus at the Max Planck Institute for Human Development and the author of Calculated Risks, Gut Feelings, and Risk Savvy and the coeditor of Better Doctors, Better Patients, Better Decisions, and Classification in the Wild. He has trained judges, physicians, and managers in decision making and understanding risks and uncertainties.
In this Audiobook
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Introduction
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Chapter 1 - Is True Love Just a Click Away?
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Chapter 2 - What AI Is Best At: The Stable-World Principle
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Chapter 3 - Machines Influence How We Think about Intelligence
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Chapter 4 - Are Self-Driving Cars Just Down the Road?
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Chapter 5 - Common Sense and AI
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Chapter 6 - One Data Point Can Beat Big Data
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Chapter 7 - Transparency
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Chapter 8 - Sleepwalking into Surveillance
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Chapter 9 - The Psychology of Getting Users Hooked
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Chapter 10 - Safety and Self-Control
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Chapter 11 - Fact or Fake?
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