Zusammenfassungen
In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally―hiring, driving, paying bills, even choosing romantic partners―that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology―and issues a warning that we should never assume that computers always get things right.
Making a case against technochauvinism―the belief that technology is always the solution―Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding "the cyborg future is not coming any time soon"; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.
Von Klappentext im Buch Artificial Unintelligence (2018) Making a case against technochauvinism―the belief that technology is always the solution―Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding "the cyborg future is not coming any time soon"; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.
Bemerkungen zu diesem Buch
One recurrent idea in this book is that computers are good at
some things and very bad at others, and social problems arise from situations
in which people misjudge how suitable a computer is for performing
the task.
Von Meredith Broussard im Buch Artificial Unintelligence (2018) im Text Machine Learning: The DL on ML Kapitel
- 3. Hello AI (Seite 31 - 40)
- 5. Why Poor Schools Can’t Win at Standardized Tests (Seite 51 - 66)
- 7. Machine Learning: The DL on ML (Seite 87 - 119)
Dieses Buch erwähnt ...
Dieses Buch erwähnt vermutlich nicht ...
Nicht erwähnte Begriffe | Algorithmus, Bildung, blockbasierte Programmierumgebungen, Buch, Datenschutz, deep learning, Ein Notebook pro StudentIn (ENpS), facebook, Fehlvorstellungen beim Programmieren, Informatik-Didaktik, Informatik-Unterricht (Fachinformatik), Kinder, LehrerIn, Lernen, Notebooks an Schulen, Siri, Sprachassistenten, Unterricht, Verlage |
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Zeitleiste
13 Erwähnungen
- Handbook of Research on E-Learning Methodologies for Language Acquisition (Rita de Cássia Veiga Marriott, Patricia Lupion Torres) (2009)
- CALL as Action (Vilson J. Leffa)
- Artificial Unintelligence (Meredith Broussard) (2018)
- Algorithms (Panos Louridas) (2020)
- New Laws of Robotics (Frank Pasquale) (2020)
- The Atlas of AI (Kate Crawford) (2021)
- Digitalisierung der Schweizer Demokratie - Technologische Revolution trifft auf traditionelles Meinungsbildungssystem (Urs Bieri, Edward Weber, Nadja Braun Binder, Sébastien Salerno, Tobias Keller, Manuela Kälin) (2021)
- Education andTechnology - Key Issues and Debates (3rd edition) (Neil Selwyn) (2022)
- Digitaler Habitus - Zur Veränderung literaler Praktiken und Bildungskonzepte (Andreas Langenohl, Katrin Lehnen, Nicole Zillien) (2022)
- You Are Not a Parrot (Elizabeth Weil) (2023)
- KI-Realitäten (Richard Groß, Rita Jordan) (2023)
- Unmasking AI (Joy Buolamwini) (2023)
- Resisting Dehumanization in the Age of «AI» (Emily M. Bender) (2024)
Co-zitierte Bücher
Volltext dieses Dokuments
Artificial Unintelligence: Gesamtes Buch als Volltext (: 1942 kByte) | |
Artificial Unintelligence: Gesamtes Buch als Volltext (: , 3543 kByte) | |
Hello AI: Kapitel als Volltext (: , 59 kByte) | |
Machine Learning: The DL on ML: Kapitel als Volltext (: , 129 kByte) | |
Why Poor Schools Can’t Win at Standardized Tests: Kapitel als Volltext (: , 120 kByte) |
Bibliographisches
Beat und dieses Buch
Beat hat dieses Buch während seiner Zeit am Institut für Medien und Schule (IMS) ins Biblionetz aufgenommen. Beat besitzt kein physisches, aber ein digitales Exemplar. (das er aber aus Urheberrechtsgründen nicht einfach weitergeben darf). Aufgrund der vielen Verknüpfungen im Biblionetz scheint er sich intensiver damit befasst zu haben.