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

by Patrick K. Lin

Overview

"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.

Product Details

ISBN-13:	9781637309674
Publisher:	New Degree Press
Publication date:	12/13/2021
Sold by:	Barnes & Noble
Format:	eBook
Pages:	252
Sales rank:	262,370
File size:	2 MB

About the Author

𝗣𝗮𝘁𝗿𝗶𝗰𝗸 𝗞. 𝗟𝗶𝗻 is an attorney and researcher focused on AI, privacy, and technology regulation. He is the author of 𝘔𝘢𝘤𝘩𝘪𝘯𝘦 𝘚𝘦𝘦, 𝘔𝘢𝘤𝘩𝘪𝘯𝘦 𝘋𝘰, a book that explores the ways public institutions use technology to surveil, police, and make decisions about the public, as well as the historical biases that impact that technology.Patrick has extensive experience in litigation and policy, having worked for the ACLU, FTC, EFF, and other organizations that advocate for digital rights and social justice. He is passionate about addressing the ethical and legal challenges posed by emerging technologies, especially in the areas of surveillance, algorithmic bias, and data privacy. He serves as the junior board chair of the Surveillance Technology Oversight Project (STOP). He has also published multiple articles and papers on topics such as facial recognition, data protection, and copyright law.

Table of Contents

Part 1: Ghost in the Machine

Chapter 1. Franglen's Monster

Chapter 2. Automating Bias

Part 2: Automating the Watchers

Chapter 3. Lights, Camera, Surveillance!

Chapter 4. Cloudy Crystal Ball: Predictive Policing

Chapter 5. Smile! You're on Camera: Video Surveillance

Chapter 6. AI Spy with My Little Eye

Part 3: False Positive

Chapter 7. Smoking Gun or Smoke and Mirrors: Forensic Evidence

Chapter 8. Beyond a Relative Doubt: Forensic DNA Databases & Familial Searches

Part 4: May it Please the Algorithm

Chapter 9. Algorithms Get Their Day in Court

Chapter 10. Behind Closed Source: How the Law Keeps Algorithms Hidden From Us

Chapter 11. Digital Shackles: How Parole Apps Put Prison in Your Pocket

Part 5. Troubleshooting the Problem

Chapter 12. Futureproofing Our Civil Liberties

Chapter 13. The Wild, Wild West: The Role of Government

Chapter 14. Flipping the Script: The Role of the Private Sector

Chapter 15. Beyond Technology: Expecting More From AI