The impact of cognitive bias on the interpretation of forensic evidence
DOI:
https://doi.org/10.61347/psa.v3i1.78Keywords:
Cognitive bias, DNA analysis, expert interpretation, fingerprints, forensic ballistics, forensic scienceAbstract
Cognitive bias in the interpretation of forensic evidence undermines the objectivity and accuracy of expert analyses, posing significant risks of judicial errors. Among the most common biases are confirmation bias, anchoring bias, the halo effect, and contextual bias, all of which can distort the evaluation of evidence such as DNA, fingerprints, or ballistics. This study examined how these biases affect forensic analysis through a systematic literature review with a qualitative approach, based on more than 50 peer-reviewed studies published between 2010 and 2024. The study found that confirmation bias is the most persistent, as it leads experts to favor prior hypotheses or institutional expectations, often disregarding contradictory information. It also highlighted the impact of anchoring bias, where initial data disproportionately influences the entire analytical process. To mitigate these effects, strategies such as implementing blind protocols, separating roles between forensic experts and investigators, peer review, and ongoing training in critical thinking and metacognition are recommended. In conclusion, although cognitive biases are a natural part of human thinking, their influence in forensic science can be reduced through structural and methodological interventions. Applying these strategies not only enhances the objectivity and quality of forensic reports but also contributes to a more equitable justice system and reinforces respect for due process.
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Arcos-Chaparro, I., & Epia-Silva, M. (2024). La transverzalización del debido proceso en las relaciones laborales particulares. Journal of Economic and Social Science Research, 4(2), 17-43. https://doi.org/10.55813/gaea/jessr/v4/n2/100
Arias, W. L. (2021). Antecedentes, desarrollo y consolidación de la psicología cognitiva: un análisis histórico. Tesis Psicológica, 16(2), 172-198. https://doi.org/10.37511/tesis.v16n2a9
Belshaw, S. (2019). Next Generation of Evidence Collecting: The Need for Digital Forensics in Criminal Justice Education. Journal of Cybersecurity Education, Research and Practice, 2019(1). https://acortar.link/PQGXqr
Biedermann, A., Bozza, S., & Taroni, F. (2008). Decision theoretic properties of forensic identification: Underlying logic and argumentative implications. Forensic Science International, 177(2-3), 120-132. https://doi.org/10.1016/j.forsciint.2007.11.008
Candal-Pedreira, C., Rey-Brandariz, J., Varela-Lema, L., Pérez-Ríos, M., & Ruano-Ravina, A. (2023). Los desafíos de la revisión por pares: cómo garantizar la calidad y transparencia del proceso editorial de las revistas científicas. Anales de Pediatría, 99(1), 54-59. https://doi.org/10.1016/j.anpedi.2023.05.017
Cooper, G. S., & Meterko, V. (2019). Cognitive bias research in forensic science: A systematic review. Forensic Science International, 297, 35-46. https://doi.org/10.1016/j.forsciint.2019.01.016
Dror, I. E., & Hampikian, G. (2011). Subjectivity and bias in forensic DNA mixture interpretation. Science & Justice, 51(4), 204-208. https://doi.org/10.1016/j.scijus.2011.08.004
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., & Langenburg, G. (2018). “Cannot Decide”: The fine line between appropriate inconclusive determinations versus unjustifiably deciding not to decide. Journal of Forensic Science, 64(1), 17-24. https://doi.org/10.1111/1556-4029.13854
Edmond, G., Tangen, J., Searston, R., & Dror, I. (2015). 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
Findley, K. A., & Scott, M. S. (2006). The multiple dimensions of tunnel vision in criminal cases. Wisconsin Law Review, 2006(1), 291-397. https://acortar.link/hWg14h
García-Perdomo, H., & López-Ramos, H. (2021). La importancia de la revisión por pares para avanzar en ciencia. Revista Urología Colombiana, 30(2), 87-88. https://doi.org/10.1055/s-0041-1730409
Garrett, B. L., & Neufeld, P. J. (2009). Invalid forensic science testimony and wrongful convictions. Virginia Law Review, 95(1), 1-97. https://www.jstor.org/stable/25475240
Guerra, Y. (2022). Importancia de la identificación humana a través de las huellas dactilares [Tesis de especialidad, Universidad UMECIT]. Repositorio institucional. https://acortar.link/LvZVqs
Kassin, S. M., Dror, I. E., & 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
Kukucka, J., Kassin, S., Zapf, P., & Dror, I. (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.2017.07.002
Kukucka, J., & Dror, I. (2022). Human Factors in Forensic Science: Psychological Causes of Bias and Error. The Oxford Handbook of Psychology and Law, 621-642. https://doi.org/10.1093/oxfordhb/9780197649138.013.36
Lopez-Mallama, O., Lemos-Muñoz, A., & Córdova-Ardila, Y. (2023). Protección social en la región Caribe de Colombia: una mirada desde la equidad en 2021. Journal of Economic and Social Science Research, 3(3), 13-24. https://doi.org/10.55813/gaea/jessr/v3/n3/70
Nogales, Á., & Montero, J. (2024). Los principios que aplican los peritos médicos para la resolución de casos judiciales y forenses. Polo del Conocimiento, 9(11), 138-160. https://polodelconocimiento.com/ojs/index.php/es/article/view/8264
Ortega, V. (2023). El estándar de prueba de inferencia razonable: fundamento epistemológico del auto que decreta la medida de aseguramiento preventiva. Revista Criterios, 30(2), 83-98. https://doi.org/10.31948/rev.criterios/30.2-art6
Rodríguez, H. A. (2024). Sesgos implícitos, injusticia explícita: efectos epistémicos de los sesgos inconscientes en el razonamiento probatorio en México. Quaestio facti, (7), 103-135. https://acortar.link/D8Ggw9
Romero-Carazas, R., Manchay, N., Alberca, A., Apaza-Romero, I., & Pérez-Mamani, R. (2023). Auditoría forense como herramienta preventiva de la apropiación inadecuada de activos en microempresas de Lima, Perú. Tesla Revista Científica, 3(1), e141. https://doi.org/10.55204/trc.v3i1.e141
Saks, M. J., & Koehler, J. J. (2005). The coming paradigm shift in forensic identification science. Science, 309(5736), 892-895. https://doi.org/10.1126/science.1111565
Van-Straalen, E., De Poot, C., Malsch, M., & Elffers, H. (2023). The interpretation of forensic conclusions by professionals and students: Does experience matter?. Forensic Science International: Synergy, 7, 100437. https://doi.org/10.1016/j.fsisyn.2023.100437
Veleda, D. (2024). Sin deberes, ni indiferencia. Una aproximación a la actividad probatoria de la persona imputada en el proceso penal. Revista Argentina de Teoría Jurídica, 24(2), 1-33. https://acortar.link/eqzY2P
Zanabria, J. (2025). Sesgos cognitivos en fuentes de prueba del proceso especial de colaboración eficaz e implicancias en el proceso penal [Tesis doctoral, Universidad César Vallejo]. Repositorio institucional. https://acortar.link/RRxAUo
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