Challenges and future directions in studying sequencing as a debiasing strategy in forensic psychological assessment: A commentary on Kukucka and Quigley‐McBride (2025)
Year: 2025
Type: article
Abstract: In 1979, Kahneman and Tversky showed that human information processing is subject to bias.They identified a number of factors, such as the order in which information is presented, that systematically lead people to make decisions that are not rational.In 2020, an international group of researchers tested N = 4099 participants from 19 countries and 13 languages and found that 94% of Kahneman and Tversky's (1979) findings were replicated (Ruggeri et al., 2020).This makes the evidence for human susceptibility to bias one of the most replicated findings in psychology, and one in urgent need of remedy.Intuitively, the most effective way to avoid being biased by certain information is to not have that information.This technique is called masking (or blinding) and inspired the debiasing approach Linear Sequencing Unmasking-Expanded (LSU-E, Dror & Kukucka, 2021).The LSU-E approach is based on empirically verified principles and has been applied to several forensic sciences, including the detection of deep-fake images (Casu et al., 2024) or the identification of victims (Dahal et al., 2022).Against this background, LSU-E is a promising approach for reducing bias in forensic psychological assessments.In an initial study, we tested whether a core factor, that is the sequencing of case information, was effective in reducing bias in criminal risk assessment as an exemplary area of forensic psychological assessment (Oberlader & Verschuere, 2024a).In their commentary on our article 'Bias is persistent: Sequencing case information does not protect against contextual bias in criminal risk assessment' (Oberlader & Verschuere, 2024a), Kukucka and Quigley-McBride (2025) critically assessed the validity of our study.The authors warned that our results and interpretations may give an overly pessimistic picture of the effectiveness of the debiasing approach LSU-E (Dror & Kukucka, 2021).Here, we first address what we consider to be their main criticisms of our study and then suggest future avenues for investigating the effectiveness of this promising debiasing method.
DOI: 10.1111/lcrp.12314
Authors: Verena Oberlader, Bruno Verschuere
Institutions: Johannes Gutenberg University Mainz, University of Amsterdam
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,700
OpenAlex ID: W4409955887