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Data science ethics : concepts, techniques and cautionary tales / / David Martens



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Titolo: Data science ethics : concepts, techniques and cautionary tales / / David Martens Visualizza cluster
Pubblicazione: Oxford, United Kingdom : , : Oxford University Press, , [2022]
Descrizione fisica: xii, 255 pages : illustrations (some color), color map ; ; 24 cm
Disciplina: 005.7
Soggetto topico: Big data - Moral and ethical aspects
Data mining - Moral and ethical aspects
Données volumineuses - Aspect moral
Exploration de données (Informatique) - Aspect moral
MATHEMATICS / General
Altri autori: Mertens  
Nota di bibliografia: Includes bibliographical references and index.
Sommario/riassunto: Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - Data Science Ethics addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data. --
Titolo abbreviato (Periodici): Oxford, United Kingdom
Titolo autorizzato: Data science ethics  Visualizza cluster
ISBN: 0192847260
9780192847263
0192847279
9780192847270
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910803896803321
Lo trovi qui: Univ. Federico II
Collocazione: SOC 188
005.74-MAR-1
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