Evidence, Respect and Truth: Knowledge and Justice in Legal Trials

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Evidence, Respect and Truth: Knowledge and Justice in Legal Trials

By Liat Levanon
Hart Publishing November 2022

Specifications

ISBN-13
9781509942657
Publisher
Hart Publishing
Publication
November 2022
Format
Hardback
Jurisdiction
U.K. ? Countri(es) for reference only

Also available as

Paperback

Details

Should statistical evidence be used as legal evidence?

This book takes a holistic approach to addressing this question by considering the relationship between evidence, randomness and justifying reasons. It situates the problem of 'evidence and chance' within the broader sweep of the administration of criminal justice.

The book draws a distinction between evidence that can justify critical judgments and evidence that can only justify non-critical judgments. It considers the way that evidence can justify critical judgment only if it can support all the propositions of the judgment, thus leaving none of the propositions random and explains that evidence can justify non-critical judgments even where it leaves some propositions random. One implication is that 'naked statistical evidence' can only justify non-critical judgments. The evidential distinction is explored and attuned in a range of legal and related extra-legal contexts including:

  • criminal and civil judgments;
  • allocation of burdens based on profiling (like in 'stop and search');
  • distribution of resources based on profiling
  • private judgements in everyday life
  • justified belief

Table of Contents

Introduction
PART I: THE EPISTEMOLOGY OF LEGAL FACT FINDING
1. The Rationality of Belief and Error Eliminability
I. Epistemology and Proof Paradoxes: A Very Brief Introduction
II. Legal Practice: Logically Ineliminable Errors
III. Rational Legal Belief
IV. Error Eliminability and Truth Tracking
V. Error Eliminability and Eliminative Induction
2. The Challenge from Error and Error Eliminability
I. Sceptical Challenges
II. Error Eliminability and the Argument about Error
III. Error Eliminability and Other Sceptical Arguments
3. Between the Epistemic and the Practical: Pushing against a Persisting Difficulty
I. Does Knowledge Have Practical Value?
II. The Practical Value of Epistemic Reasons: Stability of Belief and Successful Action
III. Pragmatism: The Epistemic Value of Practical Reasons
IV. A Shared Method of Reasoning for the Epistemic and the Practical
V. An Overarching Value: Introducing Respect
PART II: THE PRACTICALITY OF LEGAL FACT FINDING
4. Respecting, Asserting and Error Eliminability
I. Legal Assertions
II. Informing of Wrongdoing
III. Reasons to Inform as Reasons to Assert: Respect for Persons
IV. Respect and the Norm of (Legal) Assertion
V. Conclusions
5. Respecting, Doing Justice and Error Eliminability
I. Justice as Fairness and Justified Belief: The Convergence of Justifications
II. The Context of a Legal Trial
III. Accounting for the Convergence and Taking it Forward: Respect, Evidential Conditions and 'Disaster Prevention'
IV. A More Rigid Account: Epistemic Value as a Source of Moral Value
V. Conclusions
6. Resolution
I. Conflict Resolution Outside and Inside Legal Discourse
II. Error Eliminability and Legal Resolution
III. Some Procedural Implications
7. From Respect to Cost Analysis in Criminal Judgments
I. Evidence of Past Misconduct
II. Statistical Evidence that Indicates Propensity
III. Statistical Evidence that Does Not Indicate Propensity
IV. A Mutual Tragedy: The Error of the Legal System
V. Practical Implications: Aesthetics, Ethics and the Value of Choice
VI. Error Eliminability and Cost Analysis
PART III: RESPONSIBILITY
8. Epistemic and Moral Responsibility
I. Legal Assertions and Epistemic Responsibility
II. Legal Assertions and Practical Responsibility
III. Conclusions
PART IV: BEYOND LEGAL FACT FINDING
9. Applications
I. Artificial Intelligence
II. Algorithmic Sentencing: Predicting how a Human Would Make Retributive Judgements
III. Algorithmic Prediction of Students' Grades
IV. Allocation of Resources in the Private and Public Domains
V. Automated Cars and Other Dangerous Machines
VI. Profiling and Individual Risk Prediction Based on Group Affiliation
VII. Personal Attitudes
VIII. Beliefs about Groups and the Problem of Prejudice
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