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  • This gray 3D-printed face is my actual face.

  • But this white one is based solely on my DNA.

  • That's not what I expected at all.

  • It's not an exact match, to say the least.

  • But forensic scientists are tirelessly

  • improving their ability to identify people

  • without ever seeing their faces.

  • Why?

  • In criminal cases involving unidentified remains,

  • recognition can be the last chance to develop leads

  • after traditional methods fall short.

  • And if they're lucky,

  • giving a victim their identity back could close the case.

  • That's what happened in 2017

  • when a company called Parabon

  • created this facial reconstruction.

  • The image got 26-year-old Shaquana Caldwell recognized,

  • and, in turn, caught her killer after months with no leads.

  • Parabon combined two methods of facial reconstruction,

  • forensic sculpture and DNA phenotyping.

  • Forensic sculpture uses skull remains

  • and population samples to create an idea

  • of what the victim looked like.

  • But this method won't ever be 100% accurate.

  • DNA, on the other hand,

  • could get us as close as we can to a copy machine.

  • That's how we ended up at Shriver Lab at Penn State.

  • Sarita: This is just envelopes and envelopes of hair.

  • Abby: In any other place,

  • this cabinet full of hair would be really weird.

  • They're collecting data about

  • people's hair type, facial features,

  • and more to build an algorithm

  • to take my DNA

  • and spit out a replica of my face.

  • Producer: Does everyone sound like this when they do it?

  • [all laughing]

  • Sarita: No! I've never heard anyone sound like this.

  • I'm nervous I'm not going to recognize myself

  • when I see it on the screen,

  • not because it's not a good reproduction,

  • but because I

  • have a different vision of myself than reality.

  • Mark: Ready? Abby: I'm ready.

  • OK! That's not what I expected at all.

  • This final image is a composite

  • of my genetic info and the collected data

  • from people who share my genetic ancestry.

  • Right now, the algorithm works best,

  • meaning the predicted face is most recognizable,

  • when a person looks, well,

  • statistically average.

  • So, you can get ancestry axes

  • estimated from the genotypes,

  • and then we layer on top

  • the feature-specific genotypes.

  • Abby: Mm, gotcha.

  • There are some big differences

  • between my actual and predicted faces.

  • Mark: Which is telling me that

  • we need more information in the model.

  • Abby: Humans share about 99.9% of DNA,

  • but what makes me look like me

  • is in the last 0.1%.

  • And that's thanks to single-nucleotide polymorphisms,

  • the variations in base pairs throughout our genes.

  • This is easiest to see with our eyes.

  • I have two adenine at the base pair,

  • most associated with having brown or hazel eyes.

  • Which I do.

  • Now, if you take the A's out,

  • and you replace them with two guanine,

  • then that likelihood shifts

  • towards blue or green.

  • Mark and his team are building a database

  • of which SNPs affect which features.

  • Mark: We're really at an early stage.

  • I mean, we have 200 genes

  • that have significant effects on the face.

  • Abby: At the moment, their formula isn't perfect.

  • A lot of traits are controlled by multiple SNPs,

  • so it isn't a simple one-to-one connection.

  • You know, the distinctive features

  • that we really rely on to identify each other

  • are not necessarily coming through.

  • Abby: Small details are missing,

  • like my cheek mole.

  • And my nose is a bit pointier in reality.

  • I don't usually think I look like my dad,

  • but without the mapping,

  • the texture mapping, I think,

  • this looks a lot like him.

  • Then those are probably genes with big effects,

  • because, you know, those differences that you see

  • that make somebody distinctive

  • often stand out in their siblings.

  • Like you said, your face looks like your dad.

  • Abby: Plus, SNPs are associated with different traits,

  • not definitive proof of them.

  • Like, I have all the right SNPs

  • for not having a cleft chin,

  • but tell that to all of my bullies

  • who called me butt-chin growing up.

  • With so much variation,

  • to get this closer to this,

  • Mark and his team need data from as many people as possible.

  • And so if you already have our DNA,

  • what are we getting here?

  • Sarita: In order to inform our research,

  • we need to take measurements and data on many phenotypes.

  • The idea is that, hopefully,

  • by collecting all of this data

  • and associating it with what you really look like,

  • we can then use that to inform

  • an algorithm to predict on someone

  • that we don't know this information about.

  • Abby: So I decided to offer up my data to the algorithm.

  • All right, snip away.

  • Hair can make or break a case,

  • but the most common form of forensic hair analysis

  • isn't scientific.

  • Sarita: The most common forensic form of hair analysis

  • often uses racial categories to categorize hair.

  • And so, in this way,

  • we're able to study hair more objectively.

  • So we're going to embed your hair

  • in a low-melt-point plastic

  • and then cut that embedded chip in half,

  • and that'll allow us to look down the shaft of the hair.

  • And so we call that cross-sectional.

  • And we can look at the elliptical nature of your hair,

  • whether it's more circular, the thickness,

  • see if you have a medulla,

  • because some people don't have a medulla in their hair.

  • Abby: What is a medulla?

  • Sarita: The medulla is the center portion of the hair.

  • You can kind of think of it as like

  • the bone marrow of the hair.

  • This is really important forensically

  • because if you are a forensic scientist,

  • you get up on the stand, you say it's an African hair type,

  • then you're going to sway the jury into thinking

  • that the perpetrator was a specific race.

  • Abby: They also sample your skin pigmentation.

  • Javier: So, what this does is it measures

  • the melanin in your skin.

  • I'm going to need three parts.

  • I'm going to need this part of your arm right here,

  • with your palm facing up,

  • because it's not exposed to a lot of light.

  • Abby: Oh, yeah, I hide that. Javier: We need your forehead,

  • because that's exposed to a lot of light actually.

  • And we're going to need your hair,

  • because we're going to be also looking at

  • your hair pigmentation.

  • Abby: This little thing is sort of like

  • what they use in makeup stores.

  • Javier: Yep, that's right.

  • Abby: For weight and BMI,

  • the Tanita scale shoots a small amount of electricity

  • through your body.

  • Sarah: OK, we're going to electrocute you.

  • Abby: OK.

  • Sarah: Small. Abby: What about my mic pack?

  • Sarita: It should be fine.

  • Abby: OK.

  • Oh, no. Sarah: You don't feel it.

  • Abby: I know, I'm just nervous.

  • Because I'm a participant in the research,

  • they need to know what my actual face looks like.

  • Sam: So, this is essentially our low-tech

  • zero-gravity machine.

  • [both laughing]

  • Oh, I feel it. I'm in space.

  • Gravity affects how your face lies on top of your skull.

  • So getting photos from all angles