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OverviewCan we rely solely on statistics when we judge what is true and just? This book takes a holistic approach to addressing this question. It considers the legal trial as its paradigmatic case study before analysing a wide range of different cases, including profiling, the use of algorithms to predict students' grades, and the authorisation of automated cars. The book suggests that when we make judgements about the truth or about justice, approximations are not good enough. Truth and justice are uncompromising. They must be so, because the value that underlies them both is respect; and respect takes no compromise. Thus, in the search for truth as in the search for justice, a body of evidence that imposes a statistical compromise will not do. Only evidence that in principle allows reaching the truth and doing justice is good evidence. Once such evidence has been traced, the burden is on us to make good use of the evidence and reach truth and justice. We might or might not succeed, but once we have done our best on evidence that allows success, our judgements are justified; and as such, they can resolve conflicts over the truth and over justice. Full Product DetailsAuthor: Liat Levanon (King's College London, UK)Publisher: Bloomsbury Publishing PLC Imprint: Hart Publishing ISBN: 9781509942657ISBN 10: 1509942653 Pages: 216 Publication Date: 03 November 2022 Audience: College/higher education , Tertiary & Higher Education Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction 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 PrejudiceReviewsAuthor InformationLiat Levanon is Senior Lecturer in Law at King’s College London, UK Tab Content 6Author Website:Countries AvailableAll regions |
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