Facebook’s ’10 Year Challenge’ Is Just a Harmless Meme—Right?

Excerpt from this article:

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.

Sure, you could mine Facebook for profile pictures and look at posting dates or EXIF data. But that whole set of profile pictures could end up generating a lot of useless noise. People don’t reliably upload pictures in chronological order, and it’s not uncommon for users to post pictures of something other than themselves as a profile picture. A quick glance through my Facebook friends’ profile pictures shows a friend’s dog who just died, several cartoons, word images, abstract patterns, and more.

In other words, it would help if you had a clean, simple, helpfully labeled set of then-and-now photos.

Advertisements

Artificial Intelligence Can Detect Alzheimer’s Disease in Brain Scans Six Years Before a Diagnosis

a PET scan of the brain of a person with Alzheimer's disease

Excerpt from this article:

Once the algorithm was trained on 1,921 scans, the scientists tested it on two novel datasets to evaluate its performance. The first were 188 images that came from the same ADNI database but had not been presented to the algorithm yet. The second was an entirely novel set of scans from 40 patients who had presented to the UCSF Memory and Aging Center with possible cognitive impairment.

The algorithm performed with flying colors. It correctly identified 92 percent of patients who developed Alzheimer’s disease in the first test set and 98 percent in the second test set. What’s more, it made these correct predictions on average 75.8 months – a little more than six years – before the patient received their final diagnosis.

My Father Says He’s a ‘Targeted Individual.’ Maybe We All Are

Excerpt from this article:

The story he told sounded unlikely: that he was one of thousands of “targeted individuals,” who had been covertly spied on and manipulated by the CIA in the early 2000s. (So-called TIs have begun banding together around the country and across the internet.) But he didn’t sound agitated or disturbed the way I had imagined a paranoid schizophrenic might.

The hypothesis started to broaden: In our digital economy, covert players are constantly harvesting our data and churning out exquisitely tuned consumer profiles to tap into our dreams and desires. We are being surveilled. We are being controlled and manipulated. We are perhaps being tortured. But it’s not the CIA or aliens perpetrating all this. We are doing it to ourselves.

A thought occurred to me: Could the stories of “targeted individuals” be a warning, a cautionary tale about the real targeting we experience as digital technologies pervade our lives? Perhaps my father’s perception of electronic harassment is the result of his sensitivity to the mechanics of things. He may be seeing through to the nuts and bolts of the web, weaving a story out of its danger and turning it into a terrifying delusion of persecution, suffering, and torment.

The New Kid Defense: The Algorithm Made Me Do It

Excerpt from this article:

All my noble dreams of raising my two daughters around wooden Montessori-approved toys and bright-red metal wagons has completely degraded. But watching someone else play with toys is where I draw the line. “Is that a toy video?” I call warningly from across the room. Both girls suddenly jump back from the screen. “iPad picked it!” they defend.

And there it is. The algorithm defense — essentially the modern-day equivalent of “my dog ate my homework.” Like most streaming services we’re all familiar with, YouTube Kids automatically advances from one video to the next, attempting to predict what my kids will like.

Sadly, my children have watched enough of these toy videos without me noticing that the app often jumps there. So instead of blaming each other for the video selection, my kids blame a third thing I need to discipline: the machine.

 

Contraceptive app hit with complaints after being blamed for 37 unwanted pregnancies

Excerpt from this article:

Natural Cycles, a contraceptive app that became certified in the EU as a form of birth control, has been hit with a complaint after being blamed for causing 37 unwanted pregnancies, reports Swedish agency SVT. Södersjukhuset hospital in Stockholm reported the app to Swedish regulator MPA (the Medical Product Agency), after 37 women visited the hospital for an abortion after becoming pregnant while using Natural Cycles.

The app uses an algorithm and measures factors like temperature to determine the period when a woman may be fertile.

How Facebook Figures Out Everyone You’ve Ever Met

Excerpt from this article:

In the months I’ve been writing about PYMK, as Facebook calls it, I’ve heard more than a hundred bewildering anecdotes:

A man who years ago donated sperm to a couple, secretly, so they could have a child—only to have Facebook recommend the child as a person he should know. He still knows the couple but is not friends with them on Facebook.

A social worker whose client called her by her nickname on their second visit, because she’d shown up in his People You May Know, despite their not having exchanged contact information.

A woman whose father left her family when she was six years old—and saw his then-mistress suggested to her as a Facebook friend 40 years later.

An attorney who wrote: “I deleted Facebook after it recommended as PYMK a man who was defense counsel on one of my cases. We had only communicated through my work email, which is not connected to my Facebook, which convinced me Facebook was scanning my work email.”

Connections like these seem inexplicable if you assume Facebook only knows what you’ve told it about yourself. They’re less mysterious if you know about the other file Facebook keeps on you—one that you can’t see or control.

Signs of the Times

_DSC0124_MOUNTAIN_29june_alt.jpg

Excerpt from this website:

Who run the world? Collaborative filtering recommender algorithms. Also known as ‘Customers who bought this item also bought…’ suggestions. They’ve become ubiquitous in the online world, determining what we look at, buy and like…

Hopefully, you are now. Which was the point of putting these giant signs up in locations around New Zealand.

See also this video on BBC.