Witnesses to a crime will often be asked to identify the perpetrator of the crime. So
this means that witnesses need to remember the face of the suspect. So, it’s worth
us spending some time understanding how people recognise faces as this has implications for
how we deal with this issue during an investigation.
One technique for getting eyewitnesses to recreate an image of the face of the criminal
is known as photofit, originally known as identikit. This involves eyewitnesses reconstructing
a suspect’s face feature by feature using a library of different features. However,
there is a problem with this. The problem is that the technique has been found in multiple
psychological studies to be very poor.
Can psychology tell us why photofits are so poor at producing recognisable likenesses?
Psychologists have been researching face recognition for a long time. One of the key early findings
was a phenomenon known as the inverted face effect. This was investigated in an experiment
by Robert Yin of the Massachusetts Institute of Technology.
He showed participants a series of pictures of faces as well as other types of objects
– such as houses and airplanes. Then he gave everyone a recognition memory test on
the items, where he showed them pairs of pictures in which one had been previously shown and
the other was new. Participants had to choose which of the pictures they’d seen previously.
Crucially, some of these picture pairs were presented upside down. And here's the results.
On the vertical axis we have the number of identification errors they made. What Robert
Yin found was that people had proportionally greater difficulty recognising upside down
faces as compared with other types of objects. So, most people should find these faces proportionally
harder to recognise upside down, but easy to recognise the right way up.
Yin interpreted this as indicating that the mechanisms we use for face recognition are
inherently different from those we use for processing other classes of objects. He suggested
that in our brains there is a processor that specialises in dealing with human faces. This
idea has since been supported by lots of different strands of evidence, such as patterns of brain
damage, neuro-imaging studies, and behavioural experiments.
It’s been argued that the reason that faces have their own special recognition mechanism
is because they’re a class of stimuli that we’ve been exposed to every day of our lives,
and we have become super expert in telling apart faces. That is, our brains have developed
a specialist recognition system for faces because, as social animals, we have to be
able to recognise faces, we have to be able to tell people apart.
So, why does being super experts in recognising faces mean that they’re proportionally harder
to detect upside down relative to other objects? Martha Farah of the University of Pennsylvania
proposed that we recognise objects via two mechanisms that are housed in anatomically
different areas of the brain. The first mechanism for recognising objects is via the strategy
of decomposing the object into its component parts or features. So, if we were looking
at something like a building, our brain dissects it into features, such as its doors, windows,
and so on and analyses whether it is a familiar building or not based on those features.
The second object recognition mechanism involves a more holistic approach where we recognise
objects as an un-dissected whole, where our brains are explicitly not breaking the object
down into its component features. Martha Farah argues, on the back of a considerable amount
of research, that faces are an extreme example of a class of object that is recognised almost
entirely holistically and only a tiny part by dissection.
So, when we look at objects we can use both these strategies but the proportion of each
that we use either depends on the type of object. For most everyday objects, such as
houses, airplanes, printed words, and so on, we rely much more on our feature-based recognition
system. However, for certain over-learned objects like faces, we rely much more on the holistic
strategy. This means that, when we look at a face, our brains are not attempting to dissect
it into its component features. And what she argues is that this is the key difference
that means that we find faces harder to differentiate when they’re inverted.
When you turn something, usually something that’s only seen upright, upside down, the
idea is that if it’s something that we recognise mainly on the basis of features through the
analysis of its parts, like buildings or airplanes, then it won’t matter so much. However if
it’s something that that we recognise more on the basis of more holistic information,
then it will matter more. This holistic information is proportionally much more likely to be impaired
by inversion which is exactly what Martha Farah’s experiments appear to demonstrate.
In the next presentation I’ll explain what all of this work on face recognition tells
us about photofits and whether it could lead to a better way of helping eyewitnesses generate
the likeness of a suspect.