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The Ethical Algorithm: The Science of Socially Aware Algorithm Design
Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century.
The Ethical Algorithm: The Science of Socially Aware Algorithm Design
Vara #: 27135215

The Ethical Algorithm: The Science of Socially Aware Algorithm Design

Vara #: 27135215

ISK 4447

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Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century.
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What Stands Out

Social Awareness
Focuses on integrating ethical considerations into algorithm design, addressing modern challenges of bias and fairness in technology, making it ideal for socially responsible developers and businesses.
Illustrated Edition
Enhanced with visuals that simplify complex concepts, making it accessible to a wider audience including students, educators, and professionals looking to understand ethical algorithm design effectively.
Comprehensive Guides
Offers detailed frameworks and practical approaches for implementing ethical practices in algorithm development, providing invaluable insights for users aiming to create accountable and transparent technologies.

Upplýsingar um vöru

Get The Ethical Algorithm: The Science of Socially Aware Algorithm Design at Ubuy Iceland. Shop now for the best deals and worldwide delivery.
  • Algorithms have become powerful mediators of daily life, making our lives more efficient, entertaining, and better informed.
  • However, complex algorithms are also increasingly violating the basic rights of individual citizens, leaking sensitive personal information and reflecting bias in various statistical models.
  • The book 'The Ethical Algorithm' addresses the pressing issue of understanding and improving the science behind these algorithms.
  • It offers principled solutions based on the emerging science of socially aware algorithm design and proposes embedding human principles into machine code without hindering data-driven scientific exploration.
  • The authors, Michael Kearns and Aaron Roth, weave together innovative research with real stories to offer a compelling vision for a future where humans can be better protected from the unintended impacts of algorithms while inspiring advances in technology.
  • The book provides a new approach to addressing the ethical challenges posed by the increasing influence of algorithms, offering a valuable perspective for citizens, scientists, and activists.
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?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to integrate ethical considerations into algorithm design and decision-making processes.

  • Policy Makers

    Beneficial for policy makers interested in understanding the impact of algorithms on society and ensuring responsible use.

  • Ethics Enthusiasts

    Great for individuals passionate about ethics in technology and wanting to explore socially responsible algorithm practices.

Not Suitable For
  • Casual Readers

    May not engage casual readers who prefer lighter, non-technical discussions over complex algorithmic ethics topics.

VÖRULÝSING

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.

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Kostir

  • 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

Gallar

  • Some readers found the latter half of the book lacking and a lazy solution

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