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The Ethical Algorithm: The Science of Socially Aware Algorithm Design
89% of respondents would recommend this to a friend
€ 28
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What Stands Out
Produkto Aprašymas
| Publisher | Oxford University Press |
| Publication date | November 1, 2019 |
| Edition | Illustrated |
| Language | English |
| Print length | 230 pages |
| ISBN-10 | 0190948205 |
| ISBN-13 | 978-0190948207 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 6.1 x 0.9 x 9.3 inches (15.5 x 2.3 x 23.6 cm) |
Who Should Buy?
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Data Scientists
Ideal for data scientists looking to integrate ethical considerations into algorithm design and decision-making processes.
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Policy Makers
Beneficial for policy makers interested in understanding the impact of algorithms on society and ensuring responsible use.
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Ethics Enthusiasts
Great for individuals passionate about ethics in technology and wanting to explore socially responsible algorithm practices.
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Casual Readers
May not engage casual readers who prefer lighter, non-technical discussions over complex algorithmic ethics topics.
PRODUKTO APRAŠYMAS
The Ethical Algorithm: The Science of Socially Aware Algorithm Design
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Ethics Editorial Review
The Ethical Algorithm: The Science of Socially Aware Algorithm Design is a well-researched and easily digestible book for those interested in computer science, software development, data analytics, policy making, and technology. The author's exploration of various Constraints such as fairness, k-anonymity, differential privacy, and the process of analyzing data for research has helped readers better understand their work in terms of ethical data handling. The book is described as an excellent introduction to machine learning concepts and ethics in computer science, tackling the threats that AI and data mining pose to our society. However, some readers found the latter half of the book lacking, as the author proposes policymakers should choose among different accuracy/equity tradeoffs instead of creating a definition of algorithmic fairness. Overall, readers found the book to be a great introductory read with many clear and honest suggestions for minimizing AI risks.
Customer Reviews & Ratings
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Argumentai
- Well-researched and informative
- Great introduction to machine learning concepts and ethics in computer science
- Clear and honest suggestions for minimizing AI risks
- Easy to follow scientific descriptions and theories
- Great examples
Minusai
- Some readers found the latter half of the book lacking and a lazy solution
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