Análisis e implementación de estrategias para prevenir o atenuar la “contaminación” cognitiva en la obtención, análisis e interpretación de las pruebas científico-forenses en el proceso penal

Resumen

Durante la obtención, análisis e interpretación de las pruebas científico-forenses en un procedimiento judicial, siempre intervienen los sesgos cognitivos. Estos afectan a las decisiones que conducen a la imposición de una condena que puede no tener nada que ver con la verdad de lo que pasó y ser todo lo contrario a lo justa que se pretende. Hay numerosos estudios que describen los sesgos cognitivos, cómo actúan sobre expertos e inexpertos, y describen cómo han afectado a numerosos procedimientos judiciales dando lugar a la puesta en libertad de cientos de personas que han sido ingresados en prisión injustamente. Implementar medidas y procedimientos estandarizados que los disminuyan puede contribuir a que el precio que se ha de pagar por un error judicial no sea tan alto. Los sesgos son inconscientes e inherentes al ser humano, conocer sus fuentes y su origen permite entender cuáles son los factores que pueden influir en las decisiones de los expertos que tratan de esclarecer una verdad que solo conocen un autor, una víctima o un testigo que rara vez cuentan la misma historia. Es posible minimizar sus efectos. Existen estrategias que tratan de evitar que los sesgos influyan en las decisiones de los expertos, decisiones que, hasta hace poco, se pensaba que eran fruto de un razonamiento lógico, científico y jurídico. En este trabajo, se enumeran muchas medidas que la literatura científica propone para conseguirlo, orientadas hacia los expertos, a su entorno y a intervenir en todas las etapas de la investigación para alcanzar la legitimidad y el amparo jurídico deseado. Resulta muy difícil reunir tantas ciencias en una sola, la forense, y aplicarla teniendo en cuenta los factores psicológicos del individuo, que parecen infinitos.
  • Referencias
  • Cómo citar
  • Del mismo autor
  • Métricas
Almazrouei, M. A., Dror, I. E. y Morgan, R. M. (2020). Organizational and Human Factors Affecting Forensic Decision‐Making: Workplace Stress and Feedback. Journal of Forensic Sciences, 65(6), 1968-1977. https://doi.org/10.1111/1556-4029.14542

Bessarabova, E., Piercy, C. W., King, S., Vincent, C., Dunbar, N. E., Burgoon, J. K., Miller, C. H., Jensen, M., Elkins, A., Wilson, D. W., Wilson, S. N. y Lee, Y.-H. (2016). Mitigating bias blind spot via a serious video game. Computers in Human Behavior, 62, 452-466. https://doi.org/10.1016/j.chb.2016.03.089

Bitzer, S., Miranda, M. D., y Bucht, R. E. (2022). Forensic advisors: The missing link. WIREs Forensic Science, 4(3), e1444. https://doi.org/10.1002/wfs2.1444

Ceberio Belaza, M. (2015, 9 de mayo). “He pasado un infierno indescriptible, los peores 4.000 días de mi vida”. Falso Culpable. Recuperado de https://falsoculpable.blogspot.com/search?q=van+der

Ceberio Belaza, M. (2016, 6 de marzo). Fabricando un violador: El calvario de Romano van der Dussen, falso culpable. Falso Culpable. Recuperado de https://falsoculpable.blogspot.com/2016/03/fabricando-un-violador-el-calvario-de.html

Chan Gamboa, E. C., Estrada Pineda, C. y Rodríguez Díaz, F. J. R. (2000). Aportaciones a la psicología jurídica y forense desde Iberoamérica. Editorial EL Manual Moderno.

Cuellar, M., Mauro, J. y Luby, A. (2022). A Probabilistic Formalisation of Contextual Bias: from Forensic Analysis to Systemic Bias in the Criminal Justice System. Journal of the Royal Statistical Society Series A: Statistics in Society, 185(Supplement_2), S620-S643. https://doi.org/10.1111/rssa.12962

Curley, L. J., Munro, J., y Dror, I. E. (2022). Cognitive and human factors in legal layperson decision making: Sources of bias in juror decision making. Medicine, Science and the Law, 62(3), 206–215. https://doi.org/10.1177/00258024221080655

De la Rosa Rodríguez, P. I. y Sandoval Navarro, V. D. (2016). Los sesgos cognitivos y su influjo en la decisión judicial. Aportes de la Psicología Jurídica a los procesos penales de corte acusatorio. Derecho Penal y Criminología, 37(102), 141. https://doi.org/10.18601/01210483.v37n102.08

Ditrich, H. (2015). Cognitive fallacies and criminal investigations. Science & Justice, 55(2), 155–159. https://doi.org/10.1016/j.scijus.2014.12.007

Dror, I. (2013). The ambition to be scientific: Human expert performance and objectivity. Science & Justice, 53(2), 81-82. https://doi.org/10.1016/j.scijus.2013.03.002

Dror, I. E. (2015). Cognitive neuroscience in forensic science: understanding and utilizing the human element. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1674), 20140255. https://doi.org/10.1098/rstb.2014.0255

Dror, I. E. (2020). Cognitive and Human Factors in Expert Decision Making: Six Fallacies and the Eight Sources of Bias. Analytical Chemistry, 92(12), 7998-8004. https://doi.org/10.1021/acs.analchem.0c00704

Dror, I. E. (2023). The most consistent finding in forensic science is inconsistency. Journal of Forensic Sciences, 68, issue 6, 1851-1855. https://doi.org/10.1111/1556-4029.15369

Dror, I. E., Kukucka, J., Kassin, S. M. y Zapf, P. A. (2018). No one is immune to contextual bias‒Not even forensic pathologists. No one is immune to contextual bias—Not even forensic pathologists. By Dror, Itiel E.,Kukucka, Jeff,Kassin, Saul M.,Zapf, Patricia A. Journal of Applied Research in Memory and Cognition, Vol 7(2), Jun 2018, 316-317

Dror, I. E., y Kukucka, J. (2021). Linear Sequential Unmasking–Expanded (LSU-E): A general approach for improving decision making as well as minimizing noise and bias. Forensic Science International: Synergy, 3, 100161. https://doi.org/10.1016/j.fsisyn.2021.100161

Dror, I., Melinek, J., Arden, J. L., Kukucka, J., Hawkins, S., Carter, J., y Atherton, D. S. (2021). Cognitive bias in forensic pathology decisions. Journal of Forensic Sciences, 66(5), 1751–1757. https://doi.org/10.1111/1556-4029.14697

Dror, I. E. y Pierce, M. L. (2019). ISO Standards Addressing Issues of Bias and Impartiality in Forensic Work. Journal of Forensic Sciences, 65(3), 800-808. https://doi.org/10.1111/1556-4029.14265

Dror, I. E., Wertheim, K., Fraser-Mackenzie, P. y Walajtys, J. (2011). The Impact of Human–Technology Cooperation and Distributed Cognition in Forensic Science: Biasing Effects of AFIS Contextual Information on Human Experts. Journal of Forensic Sciences, 57(2), 343-352. https://doi.org/10.1111/j.1556-4029.2011.02013.x

Dunbar, N. E., Miller, C. H., Adame, B. J., Elizondo, J., Wilson, S. N., Lane, B. L., Kauffman, A. A., Bessarabova, E., Jensen, M. L., Straub, S. K., Lee, Y.-H., Burgoon, J. K., Valacich, J. J., Jenkins, J. y Zhang, J. (2014). Implicit and explicit training in the mitigation of cognitive bias through the use of a serious game. Computers in Human Behavior, 37, 307-318. https://doi.org/10.1016/j.chb.2014.04.053

Earwaker, H., Nakhaeizadeh, S., Smit, N. M. y Morgan, R. M. (2020). A cultural change to enable improved decision-making in forensic science: A six phased approach. Science & Justice, 60(1), 9-19. https://doi.org/10.1016/j.scijus.2019.08.006

Edmond, G., Tangen, J. M., Searston, R. A. y Dror, I. E. (2014). Contextual bias and cross-contamination in the forensic sciences: the corrosive implications for investigations, plea bargains, trials and appeals. Law, Probability and Risk, 14(1), 1-25. https://doi.org/10.1093/lpr/mgu018

Edmond, G., Towler, A., Growns, B., Ribeiro, G., Found, B., White, D., Ballantyne, K., Searston, R. A., Thompson, M. B., Tangen, J. M., Kemp, R. I. y Martire, K. (2016). Thinking forensics: Cognitive science for forensic practitioners. Science & Justice, 57(2), 144-154. https://doi.org/10.1016/j.scijus.2016.11.005

Findley, K. A. (2011). Tunnel vision. En Conviction of the innocent: Lessons from psychological research (pp. 303-323). American Psychological Association. https://doi.org/10.1037/13085-014

Gardner, B. O., Kelley, S., Murrie, D. C., y Dror, I. E. (2019). What do forensic analysts consider relevant to their decision making? Science & Justice, 59(5), 516–523. https://doi.org/10.1016/j.scijus.2019.04.005

Geven, L., Schneider, T. y Schell-Leugers, J. (s.f.). Ahmed Tommouhi. EUREX. Recuperado de https://www.registryofexonerations.eu/case_details/ahmed-tommouhi-1-sexual-offense-1994/

Giovanelli, A. (2023). The forensic’s scientist craft: toward an integrative theory. Part 2: meso- and macroapproach. Australian Journal of Forensic Sciences, 1-16. https://doi.org/10.1080/00450618.2023.2283418

Güidi Clas, E. M. (2003). El perfil criminológico del juez prevaricador. J.M. Bosch Editor.

Guthrie, C., Rachlinski, J. J., y Wistrich, A. J. (2007). Blinking on the bench: How judges decide cases. Cornall Law Review, 93(1), 1-43.

Kassin, S. M., Dror, I. E. y Kukucka, J. (2013). The forensic confirmation bias: Problems, perspectives, and proposed solutions. Journal of Applied Research in Memory and Cognition, 2(1), 42-52. https://doi.org/10.1016/j.jarmac.2013.01.001

Koen, W. J. y Kukucka, J. (2018). Confirmation bias in forensic science. En The Psychology and Sociology of Wrongful Convictions: Forensic Science Reform (pp. 215–245). Elsevier. https://doi.org/10.1016/B978-0-12-802655-7.00007-1

Kukucka, J. and Dror I. E. (2023). Human Factors in Forensic Science: Psychological Causes of Bias and Error. In David DeMatteo, and Kyle C. Scherr (eds), The Oxford Handbook of Psychology and Law (2023; online edn, Oxford Academic, 23 Feb. 2023), https://doi.org/10.1093/oxfordhb/9780197649138.013.36, accessed 24 Jan. 2025.

Kukucka, J., Kassin, S. M., Zapf, P. A. y Dror, I. E. (2017). Cognitive Bias and Blindness: A Global Survey of Forensic Science Examiners. Journal of Applied Research in Memory and Cognition, 6(4), 452-459. https://doi.org/10.1016/j.jarmac.2017.09.001

Kunkler, K. S. y Roy, T. (2023). Reducing the impact of cognitive bias in decision making: Practical actions for forensic science practitioners. Forensic Science International Synergy, 7, 100341. https://doi.org/10.1016/j.fsisyn.2023.100341

Lidén, M. y Almazrouei, M. A. (2023). “Blood, Bucks and Bias”: Reliability and biasability of crime scene investigators’ selection and prioritization of blood traces. Science & Justice, 63(2), 276-293. https://doi.org/10.1016/j.scijus.2023.01.005

MacLean, C. L. (2022). Cognitive bias in workplace investigation: Problems, perspectives and proposed solutions. Applied Ergonomics, 105, 103860. https://doi.org/10.1016/j.apergo.2022.103860

MacLean, C. L., y Dror, I. E. (2016). A Primer on the Psychology of Cognitive Bias. In Blinding as a Solution to Bias: Strengthening Biomedical Science, Forensic Science, and Law (pp. 13–24). Elsevier. https://doi.org/10.1016/B978-0-12-802460-7.00001-2

Manzanero, A. L. (2020). Incidencia de las falsas identificaciones. Falso Culpable. Recuperado de https://falsoculpable.blogspot.com/p/incidencia-de-las-falsas.html

Meterko, V. y Cooper, G. (2021). Cognitive Biases in Criminal Case Evaluation: A Review of the Research. Journal of Police and Criminal Psychology, 37(1), 101-122. https://doi.org/10.1007/s11896-020-09425-8

Murrie, D. C., Boccaccini, M. T., Turner, D. B., Meeks, M., Woods, C. y Tussey, C. (2009). Rater (dis)agreement on risk assessment measures in sexually violent predator proceedings: Evidence of adversarial allegiance in forensic evaluation? Psychology, Public Policy, and Law, 15(1), 19-53. https://doi.org/10.1037/a0014897

O’Brien, B. (2009). Prime Suspect: an Examination of Factors that Aggravate and Counteract Confirmation Bias in Criminal Investigations. Psychology, Public Policy, and Law, 15(4), 315-334. https://doi.org/10.1037/a0017881

O’Brien, É., Nic Daeid, N., y Black, S. (2015). Science in the court: pitfalls, challenges and solutions. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1674), 20150062. https://doi.org/10.1098/rstb.2015.0062

Páez, A. (2021). Los sesgos cognitivos y la legitimidad racional de las decisiones judiciales (Cognitive Bias and the Rational Legitimacy of Judicial Decisions). Razonamiento Jurídico y Ciencias Cognitivas, 187-222. https://ssrn.com/abstract=3956986

Pronin, E., Lin, D. Y., y Ross, L. (2002). The Bias Blind Spot: Perceptions of Bias in Self Versus Others. Personality and Social Psychology Bulletin, 28(3), 369–381. https://doi.org/10.1177/0146167202286008

Rachlinski, J. J. y Wistrich, A. J. (2017). Judging the Judiciary by the Numbers: Empirical Research on Judges. Annual Review of Law and Social Science, 13, 203-229. https://doi.org/10.1146/annurev-lawsocsci-110615-085032

Rassin, E. (2018). Reducing tunnel vision with a pen-and-paper tool for the weighting of criminal evidence. Journal of Investigative Psychology and Offender Profiling, 15(2), 227-233.

Reese, E. J. (2011). Techniques for mitigating cognitive biases in fingerprint identification. UCLa L. Rev., 59, 1252.

Roux, C., Bucht, R., Crispino, F., De Forest, P., Lennard, C., Margot, P., Miranda, M. D., NicDaeid, N., Ribaux, O., Ross, A. y Willis, S. (2022). The Sydney declaration – Revisiting the essence of forensic science through its fundamental principles. Forensic Science International, 332, 111182. https://doi.org/10.1016/j.forsciint.2022.111182

Roux, C., Talbot-Wright, B., Robertson, J., Crispino, F., y Ribaux, O. (2015). The end of the (forensic science) world as we know it? The example of trace evidence. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1674), 20140260. https://doi.org/10.1098/rstb.2014.0260

Roux, C., Willis, S. y Weyermann, C. (2021). Shifting forensic science focus from means to purpose: A path forward for the discipline? Science & Justice, 61(6), 678-686. https://doi.org/10.1016/j.scijus.2021.08.005

Saks, M. J. (2010). Forensic identification: From a faith-based “Science” to a scientific science. Forensic Science International, 201(1), 14–17. https://doi.org/10.1016/j.forsciint.2010.03.014

Stacey, R. B. (2005). Report on the Erroneous Fingerprint Individualization in the Madrid Train Bombing Case, vol. 35, issue 1. https://archives.fbi.gov/archives/about-us/lab/forensic-science-communications/fsc/jan2005/special_report/2005_special_report.htm

Steblay, N., Hosch, H. M., Culhane, S. E., y McWethy, A. (2006). The impact on juror verdicts of judicial instruction to disregard inadmissible evidence: A meta-analysis. Law and Human Behavior, 30(4), 469–492. https://doi.org/10.1007/s10979-006-9039-7

Tversky, A. y Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131. https://doi.org/10.1126/science.185.4157.1124

UCI Newkirk Center for Science and Society. (2024). The National Registry of Exonerations. Consultado el 12 de diciembre de 2024, en https://www.law.umich.edu/special/exoneration/Pages/about.aspx

Van Koppen, P. J. y Mackor, A. R. (2019). A Scenario Approach to the Simonshaven Case. TopicsinCognitive Science, 12(4), 1132-1151. https://doi.org/10.1111/tops.12429

Vredeveldt, A., van Rosmalen, E. A. J., van Koppen, P. J., Dror, I. E., y Otgaar, H. (2022). Legal psychologists as experts: guidelines for minimizing bias. Psychology, Crime & Law, 30(7), 705-729. https://doi.org/10.1080/1068316X.2022.2114476

Wells, G. L., Wilford, M. M., y Smalarz, L. (2013). Forensic science testing: The forensic filler-control method for controlling contextual bias, estimating error rates, and calibrating analysts' reports. Journal of Applied Research in Memory and Cognition, 2(1), 53–55. https://doi.org/10.1016/j.jarmac.2013.01.004
Amezcua de Miguel, R. (2024). Análisis e implementación de estrategias para prevenir o atenuar la “contaminación” cognitiva en la obtención, análisis e interpretación de las pruebas científico-forenses en el proceso penal. Ciencia Policial, 183, 43–89. https://doi.org/10.14201/cp.32165
+