The Book of WhyThe New Science of Cause and Effect
Judea Pearl, Dana Mackenzie
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Zusammenfassungen
If I could sum up the message of this book in one pithy phrase, it would be
that you are smarter than your data. Data do not understand causes and
effects; humans do. I hope that the new science of causal inference will enable
us to better understand how we do it, because there is no better way to
understand ourselves than by emulating ourselves. In the age of computers,
this new understanding also brings with it the prospect of amplifying our
innate abilities so that we can make better sense of data, be it big or small."Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality--the study of cause and effect--on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needsThe Book of Why.
Kapitel 
- Mind over Data
- 1. The Ladder of Causation
- 2. From Buccaneers to Guinea Pigs - The Genesis of Causal Inference
- 3. From Evidence to Causes - Reverend Bayes Meets Mr. Holmes
- 4. Confounding and Deconfounding - Or, Slaying the Lurking Variable
- 5. The Smoke-Filled Debate - Clearing the Air
- 6. Paradoxes Galore!
- 7. Beyond Adjustment - The Conquest of Mount Intervention
- 8. Counterfactuals - Mining Worlds That Could Have Been
- 9. Mediation - The Search for a Mechanism
- 10. Big Data, Artificial Intelligence, and the Big Questions
Dieses Buch erwähnt ...
 Personen KB IB clear | Pedro Domingos , Elon Musk | ||||||||||||||||||
 Aussagen KB IB clear | Korrelation bedeutet nicht Kausalität | ||||||||||||||||||
 Begriffe KB IB clear |  AlphaGo
, Bayes-Netz
, Berkson’s paradox
,  Cholera
, Gesetze der Robotik
, Kausalitätcausality
, Korrelation
,  Künstliche Intelligenz (KI / AI)artificial intelligence
,  Statistikstatistics
,  Wissenschaftscience
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Dieses Buch erwähnt vermutlich nicht ...
Nicht erwähnte Begriffe | Epidemie, Intelligenz |
Tagcloud
Zitationsgraph
4 Erwähnungen
- The Feeling of Life Itself - Why Consciousness Is Widespread but Can’t Be Computed (Christof Koch) (2020)
- Warum wir kein digital gestütztes Lernen brauchen - ein Bildungs-Puzzle (Axel Krommer) (2020)
- Framers - Human Advantage in an Age of Technology and Turmoil (Kenneth Cukier, Viktor Mayer-Schönberger, Francis de Véricourt) (2021)
- 3. causality
- Fairness and Machine Learning - Limitations and Opportunities (Solon Barocas, Moritz Hardt, Arvind Narayanan) (2023)
Volltext dieses Dokuments
| The Book of Why: Gesamtes Buch als Volltext (:  , 7442 kByte) |
Standorte
Bibliographisches
| Titel | Format | Bez. | Aufl. | Jahr | ISBN | ||||||
| The Book of Why | E | - | - | 0 | 046509760X |  |
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Beat und dieses Buch
Beat hat dieses Buch während seiner Zeit am Institut für Medien und Schule (IMS) ins Biblionetz aufgenommen. Beat besitzt ein physisches und ein digitales Exemplar. (das er aber aus Urheberrechtsgründen nicht einfach weitergeben darf). Es gibt bisher nur wenige Objekte im Biblionetz, die dieses Werk zitieren.
Biblionetz-History 