Hiding Your Age?

It just got harder with new 'age-guessing' apps

by JP Faber | Updated 14 Jul 2015 at 11:31 AM

By now you’ve likely heard of — and used — how-old.net, Microsoft’s age reading IT that tells you how old you look, based on the photo you upload.

Smokers typically look older than they are, while those who drink a lot of water, exercise and eat right generally look younger than they are.

From talk show hosts to anybody with an online hookup, the program went viral overnight. How accurate is it? How we look, which is a reflection of how we’re aging biologically, doesn’t always match our birthdays. Smokers typically look older than they are, while those who drink lots of water, exercise and eat right generally look younger than they are. A subtle nip-and-tuck can also help.

According to one of Miami’s premier beauty docs, dermatologist Debora Longwill, there are a catalog of cues to aging, the same ones that skin docs and plastic surgeons manipulate to make us look younger, the same ones face reading technology uses to peg our age.  Such as?  Here are the five main age cues:

1: We lose face fat. The main age indicator, Longwill said, is the loss of volume in our face. This is why we lose those high cheekbones and instead see saggy, wrinkled skin.

2: Nose grows. Yes, the nose tends to widen and lengthen.

3: The “nip” — the distance between the nose and the upper lip — gets longer. Look at magazine images of young models, often you can see the top teeth, a cue of youth. As the upper lip lengthens, it covers this, and cues “older.”

4: Temples sink. As we lose bone mass, other things happen as well. Our temples begin to deflate.

5: Chins change. In general, with loss of bone mass, chins begin to recede. In women, the jaw narrows, making the smile look thinner and the chin more pointed. In men, the jaw widens, giving men that fathead look as they age — just think Sinatra,  Tom Hanks, or William Shatner. The jaws in men also come forward, creating jowls.

Which brings us back to how-old.com, a program that tries to read all these things using algorithms and feedback. Microsoft released it at a developer’s conference in San Francisco, an offshoot of their face-detection software. It was supposed to demonstrate the power of machine learning and Microsoft’s platforms for developers. It is supposed to learn and get better as it goes.

For the rest of us, we’re hoping it will continue to err on the side of judging us younger.

  1. AgeApp
  2. HowOld
  3. Microsoft
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