The myth of judicial objectivity: why subjectivity is the only path to a transparent trial
Descargas
Resumen
This comment addresses the “prior challenge” in forensic Bayesian modelling, recently highlighted by Anne Ruth Mackor (2026). We argue that the perceived lack of frequency data is not an insurmountable obstacle but a misconception rooted in an outdated view of probability. By adopting a radical subjectivist perspective based on de Finetti’s teachings, we reframe probability as a coherent representation of a decision-maker’s state of knowledge. We advocate for a strict functional separation: forensic experts provide the likelihood ratio based on technical findings, while the court assigns prior odds based on the specific case context. Through sensitivity analysis, we demonstrate that the subjectivity of priors can be viewed not as a source of arbitrariness but rather as a transparent and auditable mechanism that enhances judicial accountability. Ultimately, the Bayesian model is presented as a logical necessity for preventing miscarriages of justice.
Palabras clave
Bayesian modelling, Forensic science, Subjective probabilityDescargas
Citas
Aitken, C. G. G., Gammerman, A. (1989). Probabilistic reasoning in evidential assessment. Journal of the Forensic Science Society, 29, 303–316.
Aitken, C. G. G., Connolly, T., Gammerman, A., Zhang, G., Bailey, D., Gordon, R., & Oldfield, R. (1996). Statistical modelling in specific case analysis. Science & Justice, 36, 245–255.
Aitken, C. G. G., Taroni, F., & Bozza, S. (2021). Statistics and the Evaluation of Evidence for Forensic Scientists (3rd ed.). John Wiley & Sons.
Berger, C. E. H. (2025). Finally a really forensic worldwide standard: ISO 21043 Forensic Sciences, Part 4. Interpretation. Forensic Science International: Synergy, 10, 100589.
Bertillon, A. (1886). De l’identification par les signalements anthropométriques. Imprimé à part des Archives d’Anthropologie Criminelle et des Sciences Pénales (pp. 17–18). G. Masson.
Biedermann, A., Taroni, F., & Garbolino, P. (2007). Equal prior probabilities: Can one do any better? Forensic Science International, 172, 85–93.
Biedermann, A., Garbolino, P., & Taroni, F. (2013). The subjectivist interpretation of probability and the problem of individualization in forensic science. Science & Justice, 53, 192–200.
Biedermann, A., Bozza, S., Taroni, F., & Aitken, C. G. G. (2016). Reframing the debate: A question of probability, not of likelihood ratio. Science & Justice, 56, 392–396.
Box, G. E. P., & Tiao, G. C. (1973). Bayesian Inference in Statistical Analysis. John Wiley & Sons.
Dawid, A. P. (2004). Probability, causality and the empirical world: A Bayes–de Finetti–Popper–Borel synthesis. Statistical Science, 19, 44–57.
Dawid, A. P., & Galavotti, M. C. (2009). de Finetti’s subjectivism, objective probability, and the empirical validation of probability assessment. En M. C. Galavotti (Ed.), Bruno de Finetti, Radical Probabilist. College Publications.
de Finetti, B. (1968). Probability: The subjective approach. En R. Klibansky (Ed.), La Philosophie Contemporaine (Vol. 2, pp. 45–53). La Nuova Italia.
de Finetti, B. (1972). Probability, Induction and Statistics: The Art of Guessing. John Wiley & Sons.
de Finetti, B. (1974). Probability does not exist. En H. E. Kyburg & H. E. Smokler (Eds.), Studies in Subjective Probability (pp. 213–224). Wiley & Sons.
de Finetti, B. (1982). The proper approach to probability. En G. Koch & F. Spizzichino (Eds.), Exchangeability in Probability and Statistics (pp. 1–6). North-Holland Publishing Company.
Edwards, W. (1991). Influence diagrams, Bayesian imperialism, and the Collins case: An appeal to reason. Cardozo Law Review, 13, 1025–1074.
Eggleston, R. (1983). Evidence, Proof and Probability (2nd ed.). Weidenfeld & Nicolson.
ENFSI. (2015). ENFSI Guideline for Evaluative Reporting in Forensic Science.
Fischhoff, B., & Beyth-Marom, R. (1983). Hypothesis evaluation from a Bayesian perspective. Psychological Review, 90, 239–260.
Kadane, J. B. (1995). Prime time for Bayes. Controlled Clinical Trials, 16, 313–318.
Kadane, J. B., & Schum, D. A. (1996). A Probabilistic Analysis of the Sacco and Vanzetti Evidence. John Wiley & Sons.
Kaye, D. H. (1988). What is Bayesianism? A guide for the perplexed. Jurimetrics, 28, 161–177.
Lempert, R. (1977). Modeling relevance. Michigan Law Review, 75, 1021–1057.
Lindley, D. V. (1975). Probabilities and the law. En D. Wendt & C. Vlek (Eds.), Utility, Probability, and Human Decision Making (pp. 223–232). D. Reidel Publishing Company.
Lindley, D. V. (1991). Probability. En C. G. G. Aitken & D. A. Stoney (Eds.), The Use of Statistics in Forensic Science (pp. 27–50). Ellis Horwood.
Lindley, D. V. (2014). Understanding Uncertainty (Rev. ed.). John Wiley & Sons.
Locard, E. (1940). L’enquête criminelle. Traité de criminalistique. Tome septième. Livre VIII. Joannès Desvigne et Cie.
Mackor, A. R. (2026). Bayesian modelling of criminal cases as a whole – A philosophical reflection on Dutch case law. Quaestio facti, 10.
Press, J., & Tanur, J. M. (2001). The Subjectivity of Scientists and the Bayesian Approach. Dover Publications.
Roberts, P., & Aitken, C. G. G. (2014). Practitioner Guide 3: The Logic of Forensic Proof: Inferential Reasoning in Criminal Evidence and Forensic Science.
Robertson, B., & Vignaux, G. A. (1993). Probability – The logic of the law. Oxford Journal of Legal Studies, 13, 457–478.
Robertson, B., Vignaux, G. A., & Berger, C. E. H. (2016). Interpreting Evidence: Evaluating Forensic Science in the Courtroom (2nd ed.). John Wiley & Sons.
Savage, L. J. (1972). The Foundations of Statistics (2nd rev. ed.). Dover Publications.
Schum, D. A. (1994). Evidential Foundations of Probabilistic Reasoning. John Wiley & Sons.
Taroni, F., & Biedermann, A. (2005). Inadequacies of posterior probabilities for the assessment of scientific evidence. Law, Probability and Risk, 4, 89–114.
Taroni, F., Biedermann, A., Bozza, S., Garbolino, P., & Aitken, C. G. G. (2014). Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science (2nd ed.). John Wiley & Sons.
Taroni, F., Garbolino, P., Biedermann, A., Aitken, C. G. G., & Bozza, S. (2018). Reconciliation of subjective probabilities and frequencies in forensic science. Law, Probability and Risk, 17, 243–264.
Taroni, F., Garbolino, P., Bozza, S., & Aitken, C. G. G. (2021). The Bayes’ factor: The coherent measure for hypothesis confirmation. Law, Probability and Risk, 20, 15–36.
Tillers, P. (1986). Introduction to Symposium on Probability and Inference in the Law of Evidence: The uses and limits of Bayesianism. Boston University Law Review, 66, 381–390.
Tillers, P., & Green, E. D. (Eds.). (1988). Probability and Inference in the Law of Evidence: The Uses and Limits of Bayesianism. Kluwer Academic Publishers.
Thompson, W. C., Vuille, J., Taroni, F., & Biedermann, A. (2018). After uniqueness: The evolution of forensic science opinions. Judicature, 102, 18–27.
DOI
https://doi.org/10.33115/udg_bib/qf.i11.23268Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 Franco Taroni
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.