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From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation
7 references·0 citing·27 second hop
From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation (2024)From understanding to justifying: Computa…The scientific reinvention of forensic science (2023)The scientific reinvention of…Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science (2022)Advancing a paradigm shift in…Validation of Forensic Automatic Likelihood Ratio Methods (2020)Validation of Forensic Automa…Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism (2018)Grounds for Trust: Essential …A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation (2016)A guideline for the validatio…Simulation and Similarity (2013)Simulation and SimilarityVerification and Validation in Scientific Computing (2010)Verification and Validation i…Statistics and the Evaluation of Evidence for Forensic Scientists (1996)A model for case assessment and interpretation (1998)Statistics and the Evaluation of Evidence for Forensic Scientists (2004)Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis (2018)Validity and reliability of forensic firearm examiners (2019)What is Justified Belief? (1979)Rethinking Expertise (2007)Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer (2019)AI as an Epistemic Technology (2023)Connecting ethics and epistemology of AI (2023)The Structure of Scientific Revolutions (1963)Interpretation of statistical evidence in criminal trials: The prosecutor's fallacy and the defense attorney's fallacy. (1987)Standards for the formulation of evaluative forensic science expert opinion (2009)Towards a forensic semiotics (2024)A guide to ISO 21043 Forensic Sciences from the perspective of the forensic-data-science paradigm (2025)The case for motivated reasoning. (1990)Confirmation Bias: A Ubiquitous Phenomenon in Many Guises (1998)Strengthening Forensic Science in the United States: A Path Forward (2009)A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (2011)Imprecise probabilities in engineering analyses (2013)Combustion kinetic model uncertainty quantification, propagation and minimization (2014)The strange persistence of (source) “identification” claims in forensic literature through descriptivism, diagnosticism and machinism (2022)An overview of log likelihood ratio cost in forensic science – Where is it used and what values can we expect? (2024)From data to a validated score-based LR system: A practitioner’s guide (2024)Minimal Model Explanations (2014)Are More Details Better? On the Norms of Completeness for Mechanistic Explanations (2018)Model Evaluation: An Adequacy-for-Purpose View (2020)
this work references cited by second hop

References

  • 2010Verification and Validation in Scientific Computing1,551 cited
  • 2013Simulation and Similarity751 cited
  • 2016A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation153 cited
  • 2018Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism138 cited
  • 2022Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science52 cited
  • 2023The scientific reinvention of forensic science35 cited
  • 2020Validation of Forensic Automatic Likelihood Ratio Methods33 cited

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