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Wrongful conviction, or the conviction of a person for a crime that they did not commit, is one of the greatest travesties of the criminal justice system. As of 2023, The National Registry of Exonerations has recorded over 3,000 cases of wrongful convictions in the United States.1] Organizations such as [The Innocence Project work to free the innocent and prevent these convictions, so far exonerating 375 people, including 21 who served on death row.

Dr. Jon Gould of the University of California at Irvine has claimed that faulty forensic science is partly to blame for some of these convictions.[2] As one of the architects of research that assesses the impact of forensic science on wrongful convictions, he has cited flawed eyewitness identification, confessions, testimony, police and prosecutorial conduct, defense lawyering, and forensic science as factors related to wrongful convictions. He stressed these are “factors” rather than “causes” because in prior analyses researchers have not been able to draw conclusions about causation because the studies did not use control groups.

Forensic scientists at the National Institute of Justice (NIJ) wanted to understand the causes, or etiology, of the errors in forensic science specifically. To explore the issue, NIJ enlisted the help of Dr. John Morgan, independent research consultant, to analyze and describe the impact of forensic science on erroneous convictions that the National Registry of Exonerations classified as being associated with “false or misleading forensic evidence.”[3]

From prior analysis of these data, Samuel Gross and Michael Shaffer of the University of Michigan Law School concluded, “The problems with forensic evidence range from simple mistakes to invalid techniques to outright fraud. We see clear examples of all these, although in some cases it’s impossible to distinguish one type of forensic error from another.”[4] Although their analysis cautioned there were problems with forensic evidence, it did not identify the root causes of the errors.

To advance this, Dr. Morgan designed a study to examine the specific types of errors associated with forensic evidence — research that is essential to identify past problems, mitigate future errors, and support the development of targeted, systems-based reforms by forensic practitioners.

Findings from this work led to the development of a forensic error typology, or codebook, which categorizes factors related to misstatements in forensic science reports, errors of individualization or classification, testimony errors, issues related to trials and officers of the court, and evidence handling and reporting issues (Table 1).

Error TypeDescriptionExamples
Type 1 – Forensic Science ReportsA forensic science report has a misstatement of the scientific basis of a forensic science examination.Lab error, poor communication (information excluded), or resource constraints in laboratory.
Type 2 – Individualization or ClassificationA forensic science examination has an incorrect individualization or classification of a piece of evidence or the incorrect interpretation of a forensic result that implies an incorrect individualization or association.Interpretation error or fraudulent interpretation of intended association.
Type 3 – TestimonyTestimony at trial reported forensic science results in an erroneous manner. An error may be intended or unintended.Mischaracterized statistical weight or probability.
Type 4 – Officer of the CourtAn officer of the court created an error related to forensic evidence.Excluded evidence or faulty testimony accepted over objection.
Type 5 – Evidence Handling and ReportingPotentially probative forensic evidence (that could provide proof) was not collected, examined, or reported during a police investigation or reported at trial.Chain of custody, lost evidence, or police misconduct.

Serology, Hair, Forensic Pathology, and Seized Drug Analyses Contributed Disproportionately to Case Errors

In his examination, Dr. Morgan analyzed 732 cases and 1,391 forensic examinations from the National Registry of Exonerations. The dataset included examples from 34 forensic disciplines, including serology, forensic pathology, hair comparison, forensic medicine, seized drugs, latent prints, fire debris, DNA, and bitemark comparisons (Table 2).

Cases

  • 732 total cases examined.
  • 635 cases had errors related to forensic evidence.
  • 97 cases had no errors related to forensic evidence**.**

Forensic Investigations

  • 1391 total forensic examinations included.
  • 891 had an error related to forensic evidence.
  • 500 were valid with no associated or known case error related to forensic evidence.
Discipline*Number of ExaminationsPercentage of Examinations Containing At Least One Case ErrorPercentage of Examinations Containing Individualization or Classification (Type 2) Errors
Seized drug analysis #130100%100%
Bitemark4477%73%
Shoe/foot impression3266%41%
Fire debris investigation (not chemical analysis)4578%38%
Forensic medicine (pediatric sexual abuse)6472%34%
Blood spatter (crime scene)3358%27%
Serology20468%26%
Firearms identification6639%26%
Forensic medicine (pediatric physical abuse)6083%22%
Hair comparison14359%20%
Latent fingerprint8746%18%
Fiber/trace evidence3546%14%
DNA6464%14%
Forensic pathology (cause and manner)13646%13%
  • Disciplines with case error sample sizes of greater than 30 included here.

The high number of seized drug analysis errors were due to errors using drug testing kits in the field, not the laboratory.

Most errors related to forensic evidence were not identification or classification errors made by forensic scientists (Table 3). When forensic scientists made errors, they were often associated with:

  • Incompetent or fraudulent examiners.
  • Disciplines with an inadequate scientific foundation (sometimes referred to as “junk science”).
  • Organizational deficiencies in training, management, governance, or resources.
DisciplineFinding
SerologyMost errors were related to blood typing (serological typing) and characterized by testimony errors, best practice failures (such as failure to collect reference samples or conduct tests correctly), and inadequate defense (for example, when practitioners did not recognize evidence that could have proved innocence).
Hair comparisonMost testimony errors conformed to the standards recognized at the time of the trial but would not conform to current standards.
Latent fingerprintsAlmost all errors were associated with fraud or uncertified examiners who clearly violated basic standards.
Gunshot residueTestimony often did not clarify the limits of the analysis such as the possibility of secondary transfer and uncertainties of interpretation.
DNA evidenceEvidence was often associated with identification and classification errors. Most commonly, labs used early DNA methods that lacked the ability to apply the testing or interpretation in a reliable way. DNA mixture samples were the most common source of evidence interpretation error.
BitemarkCases were associated with a disproportionate share of incorrect identifications and wrongful convictions. Bitemark examiners were almost always independent consultants outside the structure of forensic science organizations. This may have supplied inadequate mechanisms for enforcement of standards.
Seized drug analysisOnly one of the 130 errors occurred in an actual forensic laboratory. The remaining 129 were due to errors using drug testing kits in the field.

Special Note About Cognitive Bias

Dr. Morgan cautions that some disciplines were more likely to be associated with cognitive bias (such as bitemark comparison, fire debris investigation, forensic medicine, and forensic pathology) and therefore required scientists to consider contextual information to produce reliable results. Other disciplines were less likely** **to be associated with cognitive bias (such as seized drug analysis, latent palm print comparisons, toxicology, fire debris chemical analyses, and DNA analyses). As such, reforms should balance cognitive bias concerns with the requirements for reliable scientific and medical assessment.

Summary: High-Reliability Fields Must Conduct Follow-Up Analyses

In many fields outside of the forensic sciences, especially those considered “high-reliability” fields like air traffic control, when a grievous error is committed, administrators require follow-up analysis to prevent recurrence of errors. In forensic science, arguably a field with some of the most dire and lasting consequences, this type of quality control has been lacking.

Forensic science organizations should treat wrongful convictions as sentinel events that elucidate system deficiencies within specific laboratories.” – John Morgan, Ph.D.

Dr. Morgan noted that actors within the broader criminal justice system, but not under the purview of any forensic science organization, cause errors related forensic evidence. Investigators or prosecutors, for example, may discount or ignore exculpatory forensic results due to their own biases.

Dr. Morgan’s typology will be an indispensable resource for the forensic science community, allowing researchers to reproduce this type of work and pinpoint areas within forensic science that need improvement. His work highlighted several forensic evidence factors associated with wrongful convictions, chiefly:

  • Poorly validated scientific standards or poor adherence to practice and testimony standards.
  • Overly complex forensic analysis.
  • Reliance on presumptive tests without confirmation by a forensic laboratory.
  • Use of independent experts outside the administrative control of public laboratories.
  • Suppression or misrepresentation of forensic evidence by investigators or prosecutors.

In approximately half of wrongful convictions analyzed, improved technology, testimony standards, or practice standards may have prevented a wrongful conviction at the time of trial.” – John Morgan, Ph.D.

The development and enforcement of clear standards within each forensic science discipline, as well as the governance structures to enforce such standards, will minimize wrongful convictions and boost public trust in the criminal justice system.

About This Article

The work described in this article was supported by NIJ contract number GS10F0114L/OJP2002BF.

This article is based on a report entitled “Forensic Testimony Archaeology: Analysis of Exoneration Cases and Its Implications of Forensic Science Testimony and Communications” (pdf, 162 pages), by John Morgan, Ph.D. The National Institute of Justice commissioned this report.

This article is also based on an accompanying article, John Morgan, “Wrongful Convictions and Claims of False or Misleading Forensic Evidence,” Journal of Forensic Sciences 00 (2023): 1-54, https://doi.org/10.1111/1556-4029.15233.

Notes

[note 1] The NRE is affiliated with the Newkirk Center for Science & Society at University of California Irvine, the University of Michigan Law School, and Michigan State University College of Law.

note 2] Jon Gould et al., "Predicting Erroneous Convictions: A Social Science Approach to Miscarriages of Justice," Final report to the National Institute of Justice, award number 2009-IJ-CX-4110, December 2012, NCJ 241389, [https://www.ojp.gov/pdffiles1/nij/grants/241389.pdf.

[note 3] John Morgan, “Wrongful Convictions and Claims of False or Misleading Forensic Evidence,” Journal of Forensic Sciences 68 (2023): 908-961.

note 4] This analysis was based on only some of the data, not the entire data set. Samuel Gross and Mi Shaffer, “Exonerations in the United States, 1989–2012,” National Registry of Exonerations 2012. Available from: [https://repository.law.umich.edu/cgi/viewcontent.cgi?article=1091&context=other. Accessed 3 Feb 2023.

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