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 at Wharton. He has consulted extensively in the finance and technology industries, and on various legal and regulatory matters involving algorithms, data and machine learning. Aaron Roth is the class of 1940 Bicentennial Term Associate Professor in the Computer and Information Science department at the University of Pennsylvania. He is the recipient of a Presidential Early Career Award for Scientists and Engineers (PECASE), an Alfred P. Sloan Research Fellowship, an NSF CAREER award, a Google Faculty Research Award, and a Yahoo Academic Career Enhancement award.

...the authors take us on a journey through the main socio-algorithmic problems representing social constraints upon algorithms, their consequences and trade-offs. [T]hey provide concrete technical solutions for the challenges discussed throughout the book's 5 chapters: privacy, fairness, user-data-algorithm feedback loop, data-driven scientific discoveries and (brief) thoughts on the ethical issues (transparency, accountability, morality) yet to be pursued scientifically.

• IntroductionChapter 1: Algorithmic Privacy: The Power of RandomizationChapter 2: Fairness: Discriminating AlgorithmsChapter 3: Games People Play (With Algorithms)Chapter 4: Lost in the Garden: Led Astray by DataChapter 5: Risky Business: Interpretability, Morality, and the SingularitySome Concluding ThoughtsAcknowledgementsNotes

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 at Wharton. He has consulted extensively in the finance and technology industries, and on various legal and regulatory matters involving algorithms, data and machine learning. Aaron Roth is the class of 1940 Bicentennial Term Associate Professor in the Computer and Information Science department at the University of Pennsylvania. He is the recipient of a Presidential Early Career Award for Scientists and Engineers (PECASE), an Alfred P. Sloan Research Fellowship, an NSF CAREER award, a Google Faculty Research Award, and a Yahoo Academic Career Enhancement award.

...the authors take us on a journey through the main socio-algorithmic problems representing social constraints upon algorithms, their consequences and trade-offs. [T]hey provide concrete technical solutions for the challenges discussed throughout the book's 5 chapters: privacy, fairness, user-data-algorithm feedback loop, data-driven scientific discoveries and (brief) thoughts on the ethical issues (transparency, accountability, morality) yet to be pursued scientifically.

• IntroductionChapter 1: Algorithmic Privacy: The Power of RandomizationChapter 2: Fairness: Discriminating AlgorithmsChapter 3: Games People Play (With Algorithms)Chapter 4: Lost in the Garden: Led Astray by DataChapter 5: Risky Business: Interpretability, Morality, and the SingularitySome Concluding ThoughtsAcknowledgementsNotes

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 at Wharton. He has consulted extensively in the finance and technology industries, and on various legal and regulatory matters involving algorithms, data and machine learning. Aaron Roth is the class of 1940 Bicentennial Term Associate Professor in the Computer and Information Science department at the University of Pennsylvania. He is the recipient of a Presidential Early Career Award for Scientists and Engineers (PECASE), an Alfred P. Sloan Research Fellowship, an NSF CAREER award, a Google Faculty Research Award, and a Yahoo Academic Career Enhancement award.

...the authors take us on a journey through the main socio-algorithmic problems representing social constraints upon algorithms, their consequences and trade-offs. [T]hey provide concrete technical solutions for the challenges discussed throughout the book's 5 chapters: privacy, fairness, user-data-algorithm feedback loop, data-driven scientific discoveries and (brief) thoughts on the ethical issues (transparency, accountability, morality) yet to be pursued scientifically.

• IntroductionChapter 1: Algorithmic Privacy: The Power of RandomizationChapter 2: Fairness: Discriminating AlgorithmsChapter 3: Games People Play (With Algorithms)Chapter 4: Lost in the Garden: Led Astray by DataChapter 5: Risky Business: Interpretability, Morality, and the SingularitySome Concluding ThoughtsAcknowledgementsNotes