Machine See, Machine Do: How Technology Mirrors Bias in Our Criminal Justice System

by Patrick K. Lin

“When today’s technology relies on yesterday’s data, it will simply mirror our past mistakes and biases.”

AI and other high-tech tools embed and reinforce America’s history of prejudice and exclusion — even when they are used with the best intentions. Patrick K. Lin’s Machine See, Machine Do: How Technology Mirrors Bias in Our Criminal Justice System takes a deep and thorough look into the use of technology in the criminal justice system, and investigates the instances of coded bias present at every level.

In this book, you’ll learn how algorithms and high-tech tools are used in unexpected ways: suggesting which neighborhoods to police, predicting whether someone is more or less likely to commit a crime, and determining how long someone’s prison sentence should be.

Machine See, Machine Do takes you on an eye-opening journey of discovery, encouraging you to think twice about our current system of justice and the technology that supposedly makes it more “objective” and “fair.” If you are someone who cares deeply about criminal justice reform, is curious about the role of technology in our day-to-day lives, and ultimately believes we should aspire to make both of these spaces more ethical and safe, this book is for you.

Genres: Technology, Nonfiction

252 pages, Paperback

Published December 13, 2021

About the author

Patrick K. Lin is an author and researcher focused on artificial intelligence, privacy law, technology policy and regulation, and intellectual property. Previously, he worked for the ACLU's Speech, Privacy & Technology Project, FTC, and EFF, among others. Currently, he is the Judith Bresler Fellow at the Center for Art Law. Patrick also serves on the junior board of the Surveillance Technology Oversight Project (STOP) and advises Snap Inc. as an AI specialist on its Safety Advisory Board.

He is a frequent speaker on AI, civil rights law, the history and politics of surveillance, and technology regulation. Patrick has presented before a wide range of professional and academic groups, including Stanford University, UNC School of Law, State of the Net, Cloudflare TV, and various podcasts.

He earned his J.D. from Brooklyn Law School and B.A. in Economics from NYU. While completing his law degree, he wrote Machine See, Machine Do, an approachable and informative book about technology, policy, and the criminal legal system.

Reviews

[Daniel Keesey · Rating 5 out of 5]

10/10 this book is a must read. A remarkably well-constructed crash course of the intersection between the flawed nature of algorithmic problem solving and the true meaning of justice. If you are someone not well versed in these topics, this book is a beacon in the dark and does an excellent job of getting the reader up to speed on legal and technological concepts all while providing spot-on anecdotes and relevant context. Furthermore, the sources are extensive should you want to go the extra mile, yet they never detract from Lin’s succinct analysis. This book not only sounds the proverbial alarm that the expediency of modern technology should warrant careful reflection of the institutions and historical context of our society, but also provides a ray of hope and call to action that leaves the reader more cognizant of the world we are actively shaping for ourselves and how we can shape it for the betterment of everyone, both with and without advanced technology.

[Krys · Rating 5 out of 5]

Great read. Highly recommend for its comprehensive overview of predatory tech, from the legal perspective; and for Lin’s easy-to-digest writing style.

[Rachel Fikslin · Rating 5 out of 5]

Great read - I learned a lot!!! This book is an enjoyable, accessible introduction to the complex and multi-faceted topic of the role of AI in racial bias in policing.! Each chapter provides an example of a different part of this problem and includes helpful descriptions of commonly used technology and compelling case studies that are compelling to read. I think this whole book or individual chapters would make great reading for an undergraduate college course for students new to the topic. Would recommend to anyone interested in AI, transforming our racist policing system, or the connections between the two.

[Luong Trung · Rating 5 out of 5]

Before reading this book, I had some information about bias based on algorithms and implementation, and this book is provided more details about each insdutry and is integrated into social, real-world…

Camera, abuse situation and privacy violence with 3rd (sharing DNA and family tree, allowance remote private camera…) are need to consider and well protected.

Easy to read but it's need time to imagine what will impacts to future

[Ricardo · Rating 4 out of 5]

The right questions about algorithm bias, and issues of justice. Machine learning is based on existing datasets, and these already include bias. Good insights in a nice fast book.

[Marvin Fender · Rating 3 out of 5]

I received this book on 8/8/2022 from the author. I was informed by this book regarding the human influence on so called AI (Artificial Intelligence) which Mr. Lin suggests shapes software used to evaluate individuals in the judicial system. I'm not sure I'm the right audience to evaluate this book but after reading it I am sure that those in the judicial system should be reading it, i.e.: prosecutors, defense lawyers, judges, the ACLU, anyone in the court systems who use AI evaluation tools. These tools (AI) are created by programmers (Code Writers) and the biases formerly in earlier evaluation writeups are carried over in the programs (AI) the same faults and biases as before. Company's selling these evaluation programs claim they cannot reveal the criteria used (trade secrets) would be unfair and hurt their businesses. What I now think is these tools maybe unfairly harming the people being assessed by these flawed programs. There needs to be transparency to repair the damages that are in the code that are humane bias.

[Brooke Buonauro · Rating 5 out of 5]

“AI isn’t going to take over the world, at least not in the Terminator-style apocalypse we might think. Instead, if we are not careful, AI will take our human mistakes and immortalize them.”

I learned so much from this book and think it’s an excellent examination of the myth that tech is somehow neutral and objective. Really appreciated how the author grounded the book by positioning the long-standing institutions many of us take for granted (like Robert Moses’ NYC, hello!!) and the baggage they come with (who benefits from them? Who suffered as a direct result of their creation? Etc.) as analogous to what we’re seeing with the rise of tech and AI.

This is a great nonfiction read because it gives you a solid foundation on the issues at hand and points you to many, many amazing sources if you’d like to learn more. In fact, I thought there were so many interesting quotes from tech and civil liberties experts that I think the author should consider starting a companionate podcast. 👀 👀 👀

[Miko Y · Rating 5 out of 5]

Lin has written a well researched and accessible text on the inner workings of an oft misunderstood or little known technology, artificial intelligence, which in fact, has established an eerily ubiquitous foothold in our daily lives. I appreciate that this book in particular uses a social justice lens to articulate the impact this technology has on our justice systems including the legal system and law enforcement. Additionally, Lin overtly calls out White supremacy and it’s persistence in the data and technology industry. This has been tech-washed time and time again, especially by tech companies who are not yet willing to acknowledge it. Ultimately he leaves us with all the information we need to take the next steps, and urges the reader to think critically.

[Rebecca · Rating 5 out of 5]

I recently read this book on vacation after Patrick sent it to me himself. Machine See, Machine Do focuses on the impact of AI from a more liberal perspective. Something you might not consider is how AI being used to make employment decisions might maintain the same biases as its creators, which caused female applicants to be dismissed in some cases. You’d think a machine would be completely independent, but how can that be possible when the information it receives is already from a human mind?
Fascinatingly, there are statistics on incarceration in this book. “The FBI’s DNA database, they found people of color made up 48 percent of the database even though they constitute only 39 percent of the US population.” Lin highlights that this technology is imperfect, and our current legal system is already unforgiving towards the impoverished as well as minorities.
I highly recommend this book, his knowledge and his character have made this an enjoyable read on vacation.