Book by Christopher Slobogin.
Published by Cambridge University Press.
Statistically-derived algorithms, adopted by many jurisdictions in an effort to identify the risk of reoffending posed by criminal defendants, have been lambasted as racist, de-humanizing, and antithetical to the foundational tenets of criminal justice. Just Algorithms argues that these attacks are misguided and that, properly regulated, risk assessment tools can be a crucial means of safely and humanely dismantling our massive jail and prison complex. The book explains how risk algorithms work, the types of legal questions they should answer, and the criteria for judging whether they do so in a way that minimizes bias and respects human dignity. It also shows how risk assessment instruments can provide leverage for curtailing draconian prison sentences and the plea-bargaining system that produces them. The ultimate goal of Christopher Slobogin’s insightful analysis is to develop the principles that should govern, in both the pretrial and sentencing settings, the criminal justice system’s consideration of risk.
Table of Contents
- Rationale: what risk algorithms can do for the criminal justice system;
- Fit: why and when data about groups are relevant to individuals;
- Validity: figuring out when risk algorithms are sufficiently accurate;
- Fairness: avoiding unjust algorithms egalitarian injustice;
- Structure: limiting retributivism and individual prevention;
- Moving forward: the need for experimentation.
About the Author
Christopher Slobogin holds the Milton Underwood Chair at Vanderbilt University Law School. He has authored or co-authored eight books and over 150 articles on criminal justice issues. He is one of the most heavily cited law professors in the criminal justice field and is the only law professor to have received Distinguished Scholar awards from both the American Psychology-Law Society and the American Board of Forensic Psychology.