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The ethical algorithm

Contributor(s): Material type: TextTextLanguage: English Publication details: Oxford University Press, 2019Description: 256 pages; 23 cmISBN:
  • 9780190948207
Subject(s):
Contents:
Chapter 1: Algorithmic Privacy: The Power of Randomization Chapter 2: Fairness: Discriminating Algorithms-- Chapter 3: Games People Play (With Algorithms)-- Chapter 4: Lost in the Garden: Led Astray by Data-- Chapter 5: Risky Business: Interpretability, Morality, and the Singularity-- Some Concluding Thoughts--
Summary: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. In evolving from static computer programs hand-coded by engineers to the products of machine learning, these technologies have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly crushing the basic rights of individual citizens. Allegedly anonymized datasets and statistical models routinely leak our most sensitive personal information; applications for everything from loans to college reflect racial and gender bias. Meanwhile, users manipulate algorithms to 'game' search engines, spam filters, online reviewing services and navigation apps. ; ; Understanding and improving the science behind the algorithms that run our lives is quickly becoming one of the most pressing issues of this century. Traditional solutions, such as laws, regulations and watchdog groups, have proven woefully inadequate, at best. Derived from the cutting-edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Weaving together the science behind algorithm design with stories of citizens, lawyers, scientists, and activists experiencing the trial-and-error of research in real-time, Michael Kearns and Aaron Roth present a strikingly original way forward, showing how we can begin to work together to protect people from the unintended impacts of algorithms-and, sometimes, protect the science that could save us from ourselves.
Holdings
Item type Current library Call number Status Date due Barcode
Book TBS Barcelona Libre acceso HC79.I55 KEA (Browse shelf(Opens below)) Available B01957

Chapter 1: Algorithmic Privacy: The Power of Randomization Chapter 2: Fairness: Discriminating Algorithms-- Chapter 3: Games People Play (With Algorithms)-- Chapter 4: Lost in the Garden: Led Astray by Data-- Chapter 5: Risky Business: Interpretability, Morality, and the Singularity-- Some Concluding Thoughts--

Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. In evolving from static computer programs hand-coded by engineers to the products of machine learning, these technologies have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly crushing the basic rights of individual citizens. Allegedly anonymized datasets and statistical models routinely leak our most sensitive personal information; applications for everything from loans to college reflect racial and gender bias. Meanwhile, users manipulate algorithms to 'game' search engines, spam filters, online reviewing services and navigation apps. ; ; Understanding and improving the science behind the algorithms that run our lives is quickly becoming one of the most pressing issues of this century. Traditional solutions, such as laws, regulations and watchdog groups, have proven woefully inadequate, at best. Derived from the cutting-edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Weaving together the science behind algorithm design with stories of citizens, lawyers, scientists, and activists experiencing the trial-and-error of research in real-time, Michael Kearns and Aaron Roth present a strikingly original way forward, showing how we can begin to work together to protect people from the unintended impacts of algorithms-and, sometimes, protect the science that could save us from ourselves.

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