Designing and Understanding Forensic Bayesian Networks using Argumentation

S.T. Timmer

Designing and Understanding Forensic Bayesian Networks using Argumentation

S.T. Timmer

Research output: Thesis › Doctoral thesis 1 (Research UU / Graduation UU)

Abstract

The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist between forensic and legal experts.Judges, lawyers and other legal experts are accustomed to argumentative reasoning, whereas forensic experts usually quantify uncertainty with probabilities. This has resulted in a heated discussion among legal scholars about the role of numerical analyses of evidence in court. It has been argued that the source of the discussion may lie in the different ways in which experts (legal and forensic) deal with uncertainty of evidence. Argumentation theory and probability theory provide two different perspectives on uncertainty.
In this thesis I combine these two perspectives in an attempt to unite the worlds of legal and forensic reasoning with uncertain legal evidence.

Original language	English
Awarding Institution	Utrecht University
Supervisors/Advisors	Meyer, John-Jules, Primary supervisor Prakken, Henry, Supervisor Verheij, H.B., Supervisor, External person Renooij, Silja, Co-supervisor
Award date	1 Feb 2017
Publisher	Utrecht University
Print ISBNs	978-90-393-6695-0
Publication status	Published - 1 Feb 2017

Keywords

Legal reasoning
Bayesian networks
Legal argumentation
Reasoning with evidence
Reasoning under uncertainty

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title = "Designing and Understanding Forensic Bayesian Networks using Argumentation",

abstract = "The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist between forensic and legal experts.Judges, lawyers and other legal experts are accustomed to argumentative reasoning, whereas forensic experts usually quantify uncertainty with probabilities. This has resulted in a heated discussion among legal scholars about the role of numerical analyses of evidence in court. It has been argued that the source of the discussion may lie in the different ways in which experts (legal and forensic) deal with uncertainty of evidence. Argumentation theory and probability theory provide two different perspectives on uncertainty. In this thesis I combine these two perspectives in an attempt to unite the worlds of legal and forensic reasoning with uncertain legal evidence.",

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N2 - The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist between forensic and legal experts.Judges, lawyers and other legal experts are accustomed to argumentative reasoning, whereas forensic experts usually quantify uncertainty with probabilities. This has resulted in a heated discussion among legal scholars about the role of numerical analyses of evidence in court. It has been argued that the source of the discussion may lie in the different ways in which experts (legal and forensic) deal with uncertainty of evidence. Argumentation theory and probability theory provide two different perspectives on uncertainty. In this thesis I combine these two perspectives in an attempt to unite the worlds of legal and forensic reasoning with uncertain legal evidence.

AB - The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist between forensic and legal experts.Judges, lawyers and other legal experts are accustomed to argumentative reasoning, whereas forensic experts usually quantify uncertainty with probabilities. This has resulted in a heated discussion among legal scholars about the role of numerical analyses of evidence in court. It has been argued that the source of the discussion may lie in the different ways in which experts (legal and forensic) deal with uncertainty of evidence. Argumentation theory and probability theory provide two different perspectives on uncertainty. In this thesis I combine these two perspectives in an attempt to unite the worlds of legal and forensic reasoning with uncertain legal evidence.

KW - Legal reasoning

KW - Bayesian networks

KW - Legal argumentation

KW - Reasoning with evidence

KW - Reasoning under uncertainty

M3 - Doctoral thesis 1 (Research UU / Graduation UU)

SN - 978-90-393-6695-0

PB - Utrecht University

ER -

Designing and Understanding Forensic Bayesian Networks using Argumentation

Abstract

Keywords

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