Data science in context: foundations, challenges, opportunities
Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, r...
Gespeichert in:
| Beteiligte Personen: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2023
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| Schlagwörter: | |
| Links: | https://doi.org/10.1017/9781009272230 https://doi.org/10.1017/9781009272230 https://doi.org/10.1017/9781009272230 https://doi.org/10.1017/9781009272230 https://doi.org/10.1017/9781009272230 |
| Zusammenfassung: | Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 29 Sep 2022) |
| Umfang: | 1 Online-Ressource (xvi, 316 Seiten) |
| ISBN: | 9781009272230 |
| DOI: | 10.1017/9781009272230 |
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| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:47:52Z |
| institution | BVB |
| isbn | 9781009272230 |
| language | English |
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| physical | 1 Online-Ressource (xvi, 316 Seiten) |
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| spellingShingle | Spector, Alfred Z. ca. 20./21. Jh Norvig, Peter 1956- Wiggins, Chris ca. 20./21. Jh Wing, Jeannette M. 1956- Data science in context foundations, challenges, opportunities Data mining Big data Quantitative research |
| title | Data science in context foundations, challenges, opportunities |
| title_auth | Data science in context foundations, challenges, opportunities |
| title_exact_search | Data science in context foundations, challenges, opportunities |
| title_full | Data science in context foundations, challenges, opportunities Alfred Z. Spector [and three others] |
| title_fullStr | Data science in context foundations, challenges, opportunities Alfred Z. Spector [and three others] |
| title_full_unstemmed | Data science in context foundations, challenges, opportunities Alfred Z. Spector [and three others] |
| title_short | Data science in context |
| title_sort | data science in context foundations challenges opportunities |
| title_sub | foundations, challenges, opportunities |
| topic | Data mining Big data Quantitative research |
| topic_facet | Data mining Big data Quantitative research |
| url | https://doi.org/10.1017/9781009272230 |
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