Patrick K. Lin is a New York City-based author focused on researching technology law and policy, artificial intelligence, surveillance, and predictive algorithms. He has worked for a variety of public interest organizations, including the ACLU's Speech, Privacy & Technology Project, the Federal Trade Commission, and the Electronic Frontier Foundation. Previously, he interned for federal judges in the Eastern District of New York and the Southern District of New York.
Patrick K. Lin has the rare ability to explain complex technical matters in plain English, and his book is a valuable contribution to the literature of AI. As Lin warns, unless we ask the right questions right now, AI is more likely to replicate the problems of yesterday than to create the solutions for tomorrow. - Ben Wizner, Director of the ACLU's Speech, Privacy & Technology Project If you care about the future of our civil liberties, you must also care about AI and algorithms that are being developed and deployed today. Machine See, Machine Do is a clarion call to recognize the serious consequences of treating technology as neutral and ensure that the speed of AI does not outstrip our ability to control its impact. Lin does a masterful job of demystifying the overpromise of AI and folly of tech solutionism in the criminal justice system, while centering the tech conversation on where it should be: our humanity. - David Ryan Polgar, Founder and Director of All Tech Is Human Our technology reflects our priorities. That is Patrick K. Lin's message as he educates us about the human relationship with technology throughout history. Machine See, Machine Do reminds us that we must evaluate the purpose of AI when we are the data that trains it. This is a must-read book you will go back to again and again. - Sudha Jamthe, Instructor at Stanford University Continuing Studies and Author of AIX: Designing Artificial Intelligence There's nothing quite like reading a non-fiction book written by a passionate expert, and Patrick K. Lin certainly fits this description; breaking down the technical matters into understandable pieces, consistently demonstrating and exploring the crux of the complex issue, and writing with a view to educate and inform change. As a layman on the details of computer programming, I appreciated the author's natural ability to break the technical side of things down to an accessible level in order to focus on the social and philosophical issues at stake. This is an important book in its genre with serious warnings about the implications of current AI application on our civil liberties, with frequent moments to discuss the wider societal issues that have been inadvertently embedded in the things we've built. Overall, Machine See, Machine Do offers constant reminders that if we stop reflecting on ourselves and the information we feed into our machines as they learn about the world, then we risk amplifying the problems that we currently face, especially with society-wide issues such as law and order. - K.C. Finn, Reviewer at Readers' Favorite Machine See, Machine Do is a captivating and thoughtful introduction to the intersection of algorithmic bias and criminal justice. Lin has crafted an approachable and clarifying guide by interviewing experts and sharing personal anecdotes. Machine See, Machine Do focuses on the criminal justice system, but its lessons and warnings are applicable to other spaces, such as hiring and college admissions, just two hotbeds of scrutiny and activity today. This book is a must-read. - Sang Lee, Co-Founder and CEO of Thine