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List of contents
Preface; 1. Rationale: what risk algorithms can do for the criminal justice system; 2. Fit: why and when data about groups are relevant to individuals; 3. Validity: figuring out when risk algorithms are sufficiently accurate; 4. Fairness: avoiding unjust algorithms egalitarian injustice; 5. Structure: limiting retributivism and individual prevention; 6. 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.
Summary
This book is for anyone concerned about human and fiscal costs of jails and prisons. It shows how properly-developed algorithms can force the adoption of more legally sophisticated bail and sentencing practices that reduce incarceration, minimize racially biased decision-making, and maximize the use of resources, without sacrificing public safety.
Additional text
'Just Algorithms puts risk assessment instruments at the center of American decarceration policy, arguing that they should be the main guideposts for parole-release decisions to shorten the nation's overlong prison terms. At the same time, Professor Slobogin advocates Olympian legal protections to guard against inaccuracy, unfairness, and racial bias in risk-influenced decisions. His vision would give unprecedented new rights to incarcerated persons – reaching toward a much-needed Due Process revolution in US prison policy.' Kevin R. Reitz, James Annenberg La Vea Professor of Law, University of Minnesota
