Subjectivity and bias in forensic DNA mixture interpretation
Abstract
The objectivity of forensic science decision making has received increased attention and scrutiny. However, there are only a few published studies experimentally addressing the potential for contextual bias. Because of the esteem of DNA evidence, it is important to study and assess the impact of subjectivity and bias on DNA mixture interpretation. The study reported here presents empirical data suggesting that DNA mixture interpretation is subjective. When 17 North American expert DNA examiners were asked for their interpretation of data from an adjudicated criminal case in that jurisdiction, they produced inconsistent interpretations. Furthermore, the majority of 'context free' experts disagreed with the laboratory's pre-trial conclusions, suggesting that the extraneous context of the criminal case may have influenced the interpretation of the DNA evidence, thereby showing a biasing effect of contextual information in DNA mixture interpretation.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
New psychological work has examined cognitive-bias issues in forensics, including how biases in information and practices can alter forensic analysts' conclusions.
“A new generation of psychological work has examined cognitive-bias issues in forensics, including how a range of biases in information and practices can alter the conclusions that forensic analysts reach (see Dror et al. 2006, Dror & Hampikian 2011).”
From Wrongful Convictions (2020) · cites this paper as Dror & Hampikian 2011
Experience does not reduce bias, and it can actually increase or create bias because it enhances the prevalence, power, and impact of top-down processes.
“On the contrary, experience does not reduce bias, and it can actually increase or create bias because it enhances the prevalence, power, and impact of the top-down processes mentioned earlier”
From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as I. E. Dror, 2011
The power of contextual irrelevant information has been demonstrated in DNA and fingerprinting.
“The power of such contextual irrelevant information has even been demonstrated in the most used and highly regarded evidence in the justice and legal systems, e.g., DNA and fingerprinting (I. E. Dror & Hampikian, 2011; I. E. Dror et al., 2006).”
From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as I. E. Dror & Hampikian, 2011
Cites
Strengthening Forensic Science in the United States: A Path Forward
Council, N. R. (2009) · CrimRxiv · doi:10.21428/cb6ab371.b2d683d2 · Cited by 1,461 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Thinking forensics: Cognitive science for forensic practitioners
Edmond, G., Towler, A., Growns, B., Ribeiro, G., Found, B., White, D., Ballantyne, K., Searston, R. A., Thompson, M. B., Tangen, J. M., et al. (2017) · Science & Justice · doi:10.1016/j.scijus.2016.11.005 · Cited by 95 · see citing works
Wrongful convictions and claims of false or misleading forensic evidence
Morgan, J. (2023) · Journal of Forensic Sciences · doi:10.1111/1556-4029.15233 · Cited by 63 · see citing works
Garrett, B. L. (2020) · Annual Review of Criminology · doi:10.1146/annurev-criminol-011518-024739 · Cited by 35 · see citing works
Preservation of DNA for Data Storage
Tan, X., Ge, L., Zhang, T., & Lu, Z. (2021) · Russian Chemical Reviews · doi:10.1070/rcr4994 · Cited by 31 · see citing works
Biased and biasing: the hidden bias cascade and bias snowball effects
Dror, I. E. (2025) · Behavioral Sciences · doi:10.3390/bs15040490 · Cited by 29 · see citing works
Self-citationHuang, C.-Y., & Bull, R. (2021) · Psychiatry, Psychology and Law · doi:10.1080/13218719.2020.1770634 · Cited by 16 · see citing works
Forensic DNA Interpretation and Human Factors: Improving the Practice Through a Systems Approach
Taylor, M. K. (2024) · doi:10.6028/nist.ir.8503 · Cited by 14 · see citing works
- Authors
- Dror, I. E., & Hampikian, G.
- Affiliations
- University College London (GB)
- Boise State University (US)
- Corresponding author
- Dror, Itiel E.
- Venue
- Science & Justice
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 51
- Issue
- 4
- Pages
- 204-208
- ISSN
- 1355-0306 (ISSN-L)
- OpenAlex
- W2071849351
- Cited by
- 348
- References
- 1
- Citations by year
- 2026: 20 · 2025: 17 · 2024: 14 · 2023: 21 · 2022: 19 · 2021: 37 · 2020: 30 · 2019: 48 · 2018: 16 · 2017: 30 · 2016: 19 · 2015: 28 · 2014: 22 · 2013: 17 · 2012: 8
- FWCI
- 9.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science & Justice (publishedVersion)
- PubMed (publishedVersion)
- ScholarWorks (Boise State University) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Social Sciences › Law › Legal processes and jurisprudence
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Keywords
- subjectivity, contextual bias, expert witnesses, inter-examiner agreement, DNA evidence
- MeSH terms
- Adult, Decision Making, Female, Humans, Judgment, Male, Professional Competence, Observer Variation, DNA Fingerprinting, Forensic Genetics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
