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Just Algorithms: Using Science to Reduce Incarceration and Inform a Jurisprudence of Risk

Just Algorithms: Using Science to Reduce Incarceration and Inform a Jurisprudence of Risk

Name: Just Algorithms: Using Science to Reduce Incarceration and Inform a Jurisprudence of Risk
Brand: Cambridge University Press
SKU: 9781108984348
Price: 428.74 HKD
Availability: InStock
Author: Christopher Slobogin
ISBN: 9781108984348

By Christopher Slobogin

Cambridge University Press July 2021

Specifications

ISBN-13: 9781108984348
Publisher: Cambridge University Press
Publication: July 2021
Format: Paperback
Jurisdiction: U.K. ? Countri(es) for reference only

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Details

Statistically-derived algorithms, adopted by many jurisdictions in an effort to identify the risk of reoffending posed by criminal defendants and offenders, 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, these 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 racial and other types of 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. Christopher Slobogin's insightful analysis ultimately develops principles that should govern the criminal justice system's consideration of risk in both pretrial and post-conviction settings.

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

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