This study aims to examine own-race bias (ORB) through a facial reconstruction experiment. Participants from different racial groups will study faces of their own or other races and then reconstruct the faces using a computer program. The reconstructions will be compared to the original faces to analyze accuracy of individual features and overall composition between same-race and cross-race reconstructions. It is hypothesized that cross-race reconstructions will be less accurate overall and focus more on individual features rather than composition. The study seeks to quantify patterns in cross-race facial recognition and determine if ORB can be manipulated through feedback.

1. Running head: FACIAL RECONSTRUCTION THROUGH MEMORY 1
Systematic Facial Reconstruction Through Memorization
Kyle Barrett
Arizona State University

2. FACIAL RECONSTRUCTION THROUGH MEMORY 2
Introduction
“They all look the same.”“We all look alike to them.” These are common
dictums that most people have probably heard at one point or another, and they
illustrate the effect known as own-race bias (ORB). ORB is the empirically
documented finding that people genuinely do have a more difficult time
distinguishing between faces that are of a different race than they do
distinguishing betweenfaces of their own race.Similar bodies of research,
however, also demonstrate just how powerful and accurate the human mind can
be at facial recognition. The question, then, is what causes people to look at and
remember each other differently?
Current research suggestsORB happens during initial encoding, and that it
is mostly unrelated toracial attitudes and prejudices (Brigham &Meissner 2001).
Perceived race, however, does come into play. Studies have shown that people
tend to focus on different areas of the face depending on whether or not they
believe they are looking at a different race than that of their own (Goldinger, H.E.,
&Papesh 2009).More specifically, findings show that people who believe they are
lookingat different-race faces will encode them differently, even if the faces are
structurally identical to that of their own race. When this is the case, it appears
that people focus too specifically on individual facial features, making them lose
the overall composition of the face in memory (M.H. Papesh, S.D. Goldinger
2010).
This proposed experiment intends to find exactly what features people pay
attention to when cross-face processing, and whether ORB can be reduced or

3. FACIAL RECONSTRUCTION THROUGH MEMORY 3
increased through simple manipulation and feedback. Participants will be given a
certain amount of time to study a sample face (either of their own or a different
race) and then asked to reconstruct it through a computerized reconstruction
program. Facial reconstruction programs have become popular tools used in
modern video games, and have developed relatively accessible user interfaces
that allow for fairly complex facial reconstructions. The system will keep track of
which parts of the face are held stronger in memory in proportion to others and
how this relationship changes across various races.
Methods
Participants
This study will incorporate 90 introductory Psychology students of African
American, Asian American, and Caucasian descent, with 30 participants from
each prospective race.Participants will be given a visual intelligence test and
sorted into groups of high, medium, and low visual intelligence. Extremely high or
low scores will have their data excluded.
Stimuli
There are two primary stimuli throughout all conditions. Firstly, participants
will be shown an 8.5” by 11” image of a face, either of their own race or that of
another. There will be three prototypical faces for each race, making nine facial
variants total. Each prototypical face will have been generated from the facial
reconstruction program that participants will be using. This will allow for precise
comparison scores as well as the possibility for a perfect facial reconstruction.

4. FACIAL RECONSTRUCTION THROUGH MEMORY 4
The second stimulus will be that of the reconstruction program itself. The
starting facial build will be the same in all conditions, and consist of an initially
colorless face with minimized features that must then be manipulated for the
reconstruction. This will allow for as neutral of a starting point as possible. The
system will rely on categorical feature sets that participants will be able to select
and then manipulate proportionally through a slider bar. Special attention will be
given to make sure that the system interface does not suggest a specific ordering
or hierarchy of what features to use.

5. FACIAL RECONSTRUCTION THROUGH MEMORY 5
Procedure
Participants of all visual intelligence levels will be evenly distributed
throughoutfour primary conditions. In the first two conditions, participants will be
allowed to study a face of their own or of a differentrace for one minute. The
image will then be removed and participants will be familiarized with the facial
reconstruction system, which will doubly act as interference and eliminate short-
term memory as a variable. Participants will then be left to reconstruct the face
without any indication of time limit.
In the second two conditions, participants will again be shown a face of
their own or another race, but will not have it removed after one minute. They will
be able to keep the initial facial image and reference it during the reconstruction.
These will be referred to as the side-by-side conditions.

6. FACIAL RECONSTRUCTION THROUGH MEMORY 6
Participant reconstruction accuracy will be measured through direct
comparison with the original facial model. The system’s facial feature sliderswill
be assigned numerical values based on their positions with a high level
sensitivity. Since the prototypical faces will have been generated within the
program, they will have their own specific scores to allow for exact difference
scores with their reconstructions. This will provide a measure for total accuracy,
individual feature accuracy, and feature group accuracy between reconstructions.
Expected Results
This system will make it relatively easy to quantify what would normally be
qualitative and otherwise immeasurable data. We should be able to see how
different races score differently when viewing one another, and if there are
specific trends of reconstruction between some races and not others.

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Firstly, we should see a decrease in overall accuracy for participants
reconstructing different-race faces. Similarly, participants who reconstructedfaces
in the side-by-side condition should have more overall accurate reconstructions,
but ultimately have errors in similar areas as the other conditions fall into similar
trends.
Individual feature and group accuracy will vary between races. In cross-
racial reconstructions specifically, we should see a less even spread, with certain
features being significantly more/less accurate than others. These outstanding
features should stay relatively the same through cross-racial comparisons, and
will likely be rebuilt in a similar ordering. In same-race conditions, however, facial
features should receive a more even spread of accuracy and will most likely be
more varied in the order of their reconstruction. This should coincide with

8. FACIAL RECONSTRUCTION THROUGH MEMORY 8
previous findings that suggest same-race faces are viewed as an overall
composition.
We should also be able to see different trends emerge between different
racial comparisons. Caucasians will reconstruct Asian American faces differently
then they do African American faces, and vice versa. I do believe, however, that
overall strategies will emerge, such that African Americans and Asian Americans
would both go about reconstructing Caucasian faces in a similar way. A hierarchy
of facial features should also begin to emerge through each cross-race and
same-race reconstruction. Ideally, from race to race we will be able to see which
features take precedence in the mind and which features get neglected. These

9. FACIAL RECONSTRUCTION THROUGH MEMORY 9
relationships will most likely engage stereotypes, and will be critical to the follow-
up part of this experiment.
Although more visually intelligent participants will probably create more
accurate reconstructions, it is likely that similar errors will exist throughout all
groups of visual intelligence levels.
Conclusion
If this test does indeed reliably indicate cross-racial patters in facial feature
recognition, the next step will then be to manipulate that feedback in future
participant reconstructions. This will essentially be the second half of the study. It
will allow for several conditions, each attempting to manipulate ORB through the
basis of providing participants incorrect/correct feedback based on the previous

10. FACIAL RECONSTRUCTION THROUGH MEMORY 10
experiment. The study’s feedback would also shift between single feature and
group-based feature feedback, playing with the different compositional strategies
participants would use. The ultimate effect would hopefully allow for a better
understanding of ORB and how it can be precisely manipulated.
If the test fails to produce predicted results, there are several possible
conclusions. Firstly, since the premise of this proposal lies on the use of a new
tool- digital facial reconstruction.it is possible that the tool itself was flawed. Also,
factors other than visual intelligence, such as digital interface familiarity, may
prove to be confounds. Lastly, surprising results could simply be due to the fact
that participants were examining faces in an unexpected way. If that is the case,
then the system should still be able to indicate what these unexpected trends are
and allow for equally fascinating follow-up research.

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