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Human Factors in Identification Decisions: 

Cross-cutting Interdisciplinary Research

Cleotilde (Coty) Gonzalez

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Dynamic Decision Making Laboratory

Social and Decision Sciences Department

Carnegie Mellon University

www.cmu.edu/ddmlab

• Investigate how socio-cognitive human factors 

influence identification decisions of forensic 

evidence through human laboratory 

experiments.

• Inform current statistical models and tools with 

results from experiments to improve human 

identification decisions across forensic domains.

• Explore how actionable models of decision 

making can be integrated with statistical models 

of Forensic evidence.

Goals of this project

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• Making a classification based on 

examination of physical evidence.

• An examiner determines whether an 

evidentiary sample (e.g., from a crime 

scene) is associated to a source sample 

(e.g., from a suspect)

– Non-match, Exclusion

– Match, Identification (above a critical 

threshold)

– Inconclusive

Identification Decisions

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Identification decisions are ubiquitous
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Forensic Science is more complex

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• Examination of physical 

evidence

– Feature comparison, often 

through visual processing 

(perception & attention 

processes)

• Classification decision

– Match identification based on 

similarity processing (memory & 

decision making)

Process in identification decisions

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Statistical models; 

Machine Learning

Mathematical/Visual 

Processing

Technology-supported 

decisions 
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In any forensic domain (with or without help of 

statistical tools) a HUMAN makes identification 

decisions

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• Examiner

• Laboratory 

Director

• Crime 

investigator

Human is always in the loop

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Humans are vulnerable to recognition, 

cognitive, and social biases
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Perception and Attention

Yarbus, A. L. (1967).

 Eye movements during perception of complex objects, in L. A. Riggs, ed., `Eye 

Movements and Vision', Plenum Press, New York, chapter VII, pp. 171-196.
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Free examination

Estimate the material circumstances 

of the family
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Give the ages of people

Remember the clothes worn by 

people
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• Visual identification is NOT determined by 

the stimulus alone

• Visual identification depends on the 

questions the observer has in mind

• Attention is selective:

– Focus on some information while ignoring the 

rest

– Attention is guided by expectations

Implications to Forensic Science

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Inter-reliability of fingerprinting (Dror, 

2015, 2016)

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Lack of consistency across experts:

Different experts observe largely different minutia from the same fingerprints
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Intra-reliability of fingerprinting (Dror, 

2015, 2016)

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Lack of consistency with the same expert:

Same expert observe different minutia from the same fingerprints in 2 

different times

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Match identification and 

similarity
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• Decisions are influenced by past experience.

• Experience creates expectations

• Experience is shaped from memory:

– We remember the most frequent cases

– We forget

– We mix up cases (judge by similarity)

• We tend to recall (and judge more probable) things that 

occur more frequently, more recently, and are more 

similar to the current cases.

– With experience the brain picks up regularities in the 

information it receives and then uses them to guide 

future information processing.

Implications to Forensic Science

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• Confirmation Bias

– Identification decisions can be influenced by knowledge about other 

forensic examiners’ decisions (Dror, Charlton & Peron, 2006; Kassin, 

Dror, Kakucka, 2013)

– FBI scientists have shown that examiners typically alter the features 

that they initially mark in a latent print based on comparison with an 

apparently matching exemplar.

• Contextual Bias

– Examiners’ judgments can be influenced by irrelevant information 

about the facts of a case (‘target suspect’) (Dror et al., 2011)

– Criminal stereotypes are a source of bias in forensic evidence 

(Smalarz et al., 2016)

• Continue investigation of systematic biases in forensic 

domains

Cognitive Biases: A serious problem in 

forensic domains

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Ok we are biased, now what?

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Where do biases come from? 

- understanding of the processes that 

produce the biases

What are possible interventions?

- Debiasing examiners

• Analyses of incentives

• Information presentation and feedback 

(e.g., nudges reduce errors; restructuring 

the task to make it compatible to the 

thought process)

• Learning and training

– Can we improve identification decisions 

through learning/training interventions?

– Can we produce long-term reductions in 

cognitive biases?

Debiasing in forensic domains
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Can we improve identification 

decisions?

• Madhavan & Gonzalez (2006)

• Madhavan, Gonzalez & Lacson 

(2007)

• Lacson, Gonzalez & Madhavan 

(2008)

• Brehnnan, Madhavan & 

Gonzalez (2009)

• Gonzalez, Thomas, & Madhavan 

(2009)

• Madhavan & Gonzalez (2010)

• Gonzalez & Madhavan (2011)

• Madhavan, Lacson, Gonzalez, & 

Brennan, (2012)

*X-ray images of individual items provided by the Dept. of Homeland Security 

Low categorical diversity

High categorical 

diversity

Transfer 

targets

Training and transfer exemplars 

were equally difficult to find.

Similarity scaling methods helped 

define the categories

Effects of categorical diversity on identification 

decisions Gonzalez & Madhavan (2011)
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• In making identification decisions in forensic 

domains a human (examiner, analyst, 

investigator) is in the loop

• Identification decisions will be subject to human 

information processing, experience, similarity 

judgments, expectations...

• We cannot scape subjective judgment; but we 

can understand where biases come from and 

design effective interventions

• Interventions through learning and training are 

likely to be most permanent.

Conclusions

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