The general public’s lack of tech understanding often takes the fun out of things for me. The “How Hard Did Aging Hit You” or the 10-Year Challenge is one of those things. Normally, I don’t tend to participate, but as I saw how amazing, healthy and happy many of my friends have continued to look over time, I wanted to join in the fun.
This is the photo comparison that I posted to my personal Facebook account. On the left is my very first Facebook profile picture (yeah, go ahead and laugh) and on the right is my current profile picture. NOTHING I’ve shared here hasn’t already been publicly available. Most of us in the internet and tech industry are hyper aware that when we share something, it’s public. Facebook and all of social media are PUBLIC spaces, not private. So, I conduct my digital self the same way I do my public self. I participated in this photo sharing thing because it was fun and it’s a good reminder of how I’ve changed (mostly for the better) over the years.
But THEN came Kate O’Neil’s article in WIRED.
In the article, O’Neal claims that the purpose of the meme challenge is to get clean data to train the facial recognition AI.
Imagine that you wanted to train a facial recognition algorithm on age-related characteristics and, more specifically, on age progression (e.g., how people are likely to look as they get older). Ideally, you’d want a broad and rigorous dataset with lots of people’s pictures. It would help if you knew they were taken a fixed number of years apart—say, 10 years….
In other words, it would help if you had a clean, simple, helpfully labeled set of then-and-now photos.
The argument here is that although Facebook does indeed have all of these photos in the system, people aren’t great at providing consistent data around those photos. Just because we posted a photo on a certain date doesn’t necessarily mean that it was taken on that date. Things like that. Her point is that Facebook’s system benefited from clean data that they didn’t have to sift through.
Then she goes on to discuss issues of privacy and makes the reader feel like we’ve somehow been duped into giving away even more information about ourselves.
First of all Facebook did not need our 10 Year comparisons at all.
This article, written by Sebastian Anthony back in March of 2014 is to my point. And I have to give credit to my colleague Kristine Schachinger for bringing it to my attention.
Facebook tries to impress upon us that verification (matching two images of the same face) isn’t the same as recognition (looking at a new photo and connecting it to the name of an existing user)… but that’s a lie. DeepFace could clearly be used to trawl through every photo on the internet, and link it back to your Facebook profile (assuming your profile contains photos of your face, anyway). Facebook.com already has a facial recognition algorithm in place that analyzes your uploaded photos and prompts you with tags if a match is made. I don’t know the accuracy of the current system, but in my experience it only really works with forward-facing photos, and can produce a lot of false matches. Assuming the DeepFace team can continue to improve accuracy (and there’s no reason they won’t), Facebook may find itself in the possession of some very powerful software indeed.
Sebastian Anthony for ExtremeTech 3/19/14
This was almost 5 years ago. Our willingness to post and tag people over the years has made DeepFace even more accurate. How do you think that really cool feature that asks if you want to tag your friend in that picture you’re about to post works?
Honestly, I believe there’s so much more to the system’s sophistication.
My mother and daughter gave me full permission to share these Facebook photos with you.
Not only is Facebook already capable of recognizing my face and your face with a high degree of accuracy, but it’s quite capable of predicting how we will age. My mother and daughter are both Facebook users. My familial relationship to both of them is confirmed. I have willingly identified them as my mother and daughter and they each confirmed that relationship independent of any photos of us together. Despite the family resemblance Facebook is 100% in identifying the faces in all of these photos. Facebook has all the data it needs to predict what I will look like in my mid seventies and how my daughter will look when she’s that age. Facebook didn’t need me to compare photos for that.
But there is a bigger point to make here
Facebook is a public space. EVERYTHING you do there is available for the system to use to provide you with a highly engaging and interactive experience.
I used to tell people that the first and best privacy filter is the one between your ears. If you want to keep it private, then you can’t share it. I need to adjust the way I explain this and from now on remind people that the moment it’s shared is the moment it’s no longer private.
Think of it this way:
If you went out for happy hour after work with your colleagues and decided to dance on the bar at the pub, you’re not going to expect them to keep that private and not discuss how much fun you had that evening. Nor could you expect that the incident would be forgotten and would never color their option of you thereafter. You chose to behave that way in a public space. Same goes for social media. You make a choice with every post, every comment, every reaction to do something in public. The only reasonable expectation is that it will be remembered and influence later interactions.
Facebook users actually benefit greatly from this systematic feedback loop. Facebook is able to put the people and events that matter most to you in your news feed so that you don’t have to waste time hunting for it. Facebook is able to facilitate your ability to easily share the delightful moments you’ve had with friends and family. It gives all of us a place to go to discuss news, politics, culture… life with others of all kinds of backgrounds.
If Facebook makes you uncomfortable, you are responsible to leave and not feed the system at all, or consider very carefully how you are going to train it to interact with you.
Michelle Stinson Ross is Apogee’s internal marketing strategist. She is responsible for growing our website, blog, social marketing, industry thought leadership and advertising footprints. She is also a key consultant to the internal team and the clients.
Michelle has written about digital marketing for Search Engine Journal, Search Engine Watch, and Forbes. She is national industry conference speaker for SMX, Pubcon, Digital Summit.
To get updated information about the team at Apogee Results, please follow us on your favorite social media channels.