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The Seemingly Pervasive Sinister Side of Algorythmic Screen Time for Children

Writer and artist James Bridle writes in Medium:

“Someone or something or some combination of people and things is using YouTube to systematically frighten, traumatize, and abuse children, automatically and at scale, and it forces me to question my own beliefs about the internet, at every level.

To begin: Kid’s YouTube is definitely and markedly weird. I’ve been aware of its weirdness for some time. Last year, there were a number of articles posted about the Surprise Egg craze. Surprise Eggs videos depict, often at excruciating length, the process of unwrapping Kinder and other egg toys. That’s it, but kids are captivated by them. There are thousands and thousands of these videos and thousands and thousands, if not millions, of children watching them. […] What I find somewhat disturbing about the proliferation of even (relatively) normal kids videos is the impossibility of determining the degree of automation which is at work here; how to parse out the gap between human and machine.”

Sapna Maheshwari also explores in The New York Times:

“Parents and children have flocked to Google-owned YouTube Kids since it was introduced in early 2015. The app’s more than 11 million weekly viewers are drawn in by its seemingly infinite supply of clips, including those from popular shows by Disney and Nickelodeon, and the knowledge that the app is supposed to contain only child-friendly content that has been automatically filtered from the main YouTube site. But the app contains dark corners, too, as videos that are disturbing for children slip past its filters, either by mistake or because bad actors have found ways to fool the YouTube Kids algorithms. In recent months, parents like Ms. Burns have complained that their children have been shown videos with well-known characters in violent or lewd situations and other clips with disturbing imagery, sometimes set to nursery rhymes.”

Very horrible and creepy.

The rise of big data policing

An excerpt from the book The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement (2017):

“Data-driven policing means aggressive police presence, surveillance, and perceived harassment in those communities. Each data point translates to real human experience, and many times those experiences remain fraught with all-too-human bias, fear, distrust, and racial tension. For those communities, especially poor communities of color, these data-collection efforts cast a dark shadow on the future.”

What Makes You Click (2016)

“The biggest psychological experiment ever is being conducted, and we’re all taking part in it: every day, a billion people are tested online. Which ingenious tricks and other digital laws ensure that we fill our online shopping carts to the brim, or stay on websites as long as possible? Or vote for a particular candidate?

The bankruptcies of department stores and shoe shops clearly show that our buying behaviour is rapidly shifting to the Internet. An entirely new field has arisen, of ‘user experience’ architects and ‘online persuasion officers’. How do these digital data dealers use, manipulate and abuse our user experience? Not just when it comes to buying things, but also with regards to our free time and political preferences.

Aren’t companies, which are running millions of tests at a time, miles ahead of science and government, in this respect? Now the creators of these digital seduction techniques, former Google employees among them, are themselves arguing for the introduction of an ethical code. What does it mean, when the conductors of experiments themselves are asking for their power and possibilities to be restricted?”

Facebook: Cracking the Code (2017)

“What’s on your mind?” It’s the friendly Facebook question which lets you share how you’re feeling. It’s also the question that unlocks the details of your life and helps turn your thoughts into profits.

Facebook has the ability to track much of your browsing history, even when you’re not logged on, and even if you aren’t a member of the social network at all. This is one of the methods used to deliver targeted advertising and ‘news’ to your Facebook feed. This is why you are unlikely to see anything that challenges your world view.

This feedback loop is fuelling the rise and power of ‘fake news’. “We’re seeing news that’s tailored ever more tightly towards those kinds of things that people will click on, and will share, rather than things that perhaps are necessarily good for them”, says one Media Analyst.

This information grants huge power to those with access to it. Republican Party strategist Patrick Ruffini says, “What it does give us is much greater level of certainty and granularity and precision down to the individual voter, down to the individual precinct about how things are going to go”. Resultantly, former Facebook journalist, Adam Schrader thinks that there’s “a legitimate argument to this that Facebook influenced the election, the United States Election results.

Is Google’s AI-driven image resizing algorithm ‘dishonest’?

The Stack reports on Google’s “new research into upscaling low-resolution images using machine learning to ‘fill in’ the missing details,” arguing this is “a questionable stance…continuing to propagate the idea that images contain some kind of abstract ‘DNA’, and that there might be some reliable photographic equivalent of polymerase chain reaction which could find deeper truth in low-res images than either the money spent on the equipment or the age of the equipment will allow.”

“Rapid and Accurate Image Super Resolution (RAISR) uses low and high resolution versions of photos in a standard image set to establish templated paths for upward scaling… This effectively uses historical logic, instead of pixel interpolation, to infer what the image would look like if it had been taken at a higher resolution.

It’s notable that neither their initial paper nor the supplementary examples feature human faces. It could be argued that using AI-driven techniques to reconstruct images raises some questions about whether upscaled, machine-driven digital enhancements are a legal risk, compared to the far greater expense of upgrading low-res CCTV networks with the necessary resolution, bandwidth and storage to obtain good quality video evidence.”

The article points out that “faith in the fidelity of these ‘enhanced’ images routinely convicts defendants.”

The Outrage Machine

This short video explores how the online world has overwhelmingly become the popular outlet for public rage by briefly illustrating some of the many stories of everyday people which have suddenly become public enemy number one under the most misunderstood of circumstances and trivial narratives. With the web acting like a giant echo-chamber, amplifying false stories and feeding on the pent-up aggression of the audience watching the spectacle, The Outrage Machine shows how these systems froth the mob mentality into a hideous mess, as a good example of where the spectacle goes and how its intensity has to keep ratcheting up in order maintain the audience attention, in a culture of dwindling attention spans, distraction and triviality.

Filmmaker and author Jon Ronson also recently wrote a book about this topic too, which is quite good. So You’ve Been Publicly Shamed. His TED talk is essentially a 17 min overview:

And a longer presentation with interview and Q&A from earlier this year: