Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.

Introduction 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 Acknowledgements Notes

"...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." -- ESSSAT News & Reviews "It is elegantly written, easy to read and full of entertaining examples." -- Martin Peterson, Prometheus "The data science revolution has important ethical underpinnings. The authors make a powerful case for the development of AI ethics as a subject in its own right. The Ethical Algorithm shows that apocalyptic predictions of an algorithmized society are far from inevitable. Anyone interested in AI should read and process this essential book." --Dr. Marcos Lopez de Prado, C.E.O. of True Positive Technologies, L.P., and Quant of the Year 2019 (The Journal of Portfolio Management) "Is the road to hell paved with well-intentioned algorithms? Many think so. For a more level-headed view, read this timely book by two leading experts: clear, concise, focused on understanding the problems and figuring out solutions, it's your perfect guide to the new science of ethical algorithms." --Dr. Pedro Domingos, Professor of Computer Science at the University of Washington and Author of The Master Algorithm "Can ethics ever be 'encoded' into algorithms? In this very timely book, Michael Kearns and Aaron Roth present a range of algorithmic solutions to problems seemingly inherent to algorithmic decision-making. In a very methodical yet entertaining manner, they highlight the potential of fixing issues related to privacy, fairness, and interpretability within algorithms without losing sight of the ongoing importance of human judgment." --Dr. Dorothea Baur, Author and International Technology Ethics Consultant "In a world with unprecedented access to data, this well researched book tackles the near term risks with concrete, real world examples that are facing algorithms today. The Ethical Algorithm is clearly articulated and full of insights." --Carol E. Reiley, Cofounder, Advisor, and Board Member of Drive.ai "Both Kearns and Roth, professors of computer and information science at the University of Pennsylvania, who have written extensively on algorithms and data science, here do a thorough job of explaining the science of algorithm design and the ethical and inherent technical difficulties in doing so."--Library Journal "If you are interested in your online footprint, or just confused about the adverts you receive, I cannot recommend The Ethical Algorithm enough. It is a thought-provoking yet easy read, demystifies the processing of large datasets and neatly lays out the power -- and ultimately the limits -- of designing more responsible machine-learning algorithms." --Nature Physics "Recommended for anyone with an interest in technology and the ethical implications of our increasing use of algorithms."--Andrei Rogobete, The Centre for Enterprise, Markets, and Ethics

Selling point: Presents cutting-edge research in the science of socially aware algorithm design Selling point: Interweaves fascinating case studies from business, law, and medicine with analysis of the science behind new technologies Selling point: Written in a clear and engaging style

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.

Selling point: Presents cutting-edge research in the science of socially aware algorithm design Selling point: Interweaves fascinating case studies from business, law, and medicine with analysis of the science behind new technologies Selling point: Written in a clear and engaging style