The Ethical Algorithm: The Science of Socially Aware Algorithm Design

Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic
rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions 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 rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting 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. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of
data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while
continuing to inspire wondrous advances in technology.


Author: Michael Kearns, Aaron Roth
Publisher: Oxford University Press, USA
Published: 11/01/2019
Pages: 232
Binding Type: Hardcover
Weight: 1.15lbs
Size: 9.30h x 6.10w x 0.90d
ISBN13: 9780190948207
ISBN10: 0190948205
BISAC Categories:
- Computers | General
- Technology & Engineering | General
- Business & Economics | Business Ethics

About the Author

Michael Kearns is Professor and the National Center Chair in the Computer and Information Science department of the University of Pennsylvania, where he has secondary appointments in Economics and the Wharton School. He is also the Founding Director of Penn's Warren Center for Network and Data
Sciences. Kearns has published widely in machine learning, artificial intelligence, algorithmic game theory and quantitative finance. He has worked extensively in the finance and technology industries, and consulted on various legal and regulatory matters involving algorithms, data, and machine
learning. Together with U.V. Vazirani, he is the author of An Introduction to Computational Learning Theory.

Aaron Roth is the class of 1940 Bicentennial Term Associate Professor in the Computer and Information Science department at the University of Pennsylvania, where he co-directs Penn's program in Networked and Social Systems Engineering. Roth has published widely in algorithms, machine learning, data
privacy, and algorithmic game theory, and has consulted extensively about algorithmic privacy. He is the recipient of numerous awards, including a Presidential Early Career Award for Scientists and Engineers (PECASE) awarded by President Obama in 2016. Together with Cynthia Dwork, he is the author
of The Algorithmic Foundations of Differential Privacy.