Name: Data Science Ethics: Concepts, Techniques, and Cautionary Tales (en Inglés)
SKU: 54337495
Price: 371993.00 COP
Availability: InStock
Author: Martens, David
ISBN: 9780192847263

portada Data Science Ethics: Concepts, Techniques, and Cautionary Tales (en Inglés)

Data Science Ethics: Concepts, Techniques, and Cautionary Tales (en Inglés)

Formato

Libro Físico

Autor

David Martens

Editorial

Oxford University Press

Idioma

Inglés

N° páginas

272

Encuadernación

Tapa Dura

Dimensiones

24.1x16x2 cm

Peso

0.59 kg.

ISBN13

9780192847263

Categorías

Probabilidad y estadística
Inteligencia artificial

Data Science Ethics: Concepts, Techniques, and Cautionary Tales (en Inglés)

David Martens (Autor) · Oxford University Press · Tapa Dura

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Reseña del libro "Data Science Ethics: Concepts, Techniques, and Cautionary Tales (en Inglés)"

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 ofprivacy 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 aidunderstanding, 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 ethicaldilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.