TED2018
James Bridle: The nightmare videos of children's YouTube -- and what's wrong with the internet today
Filmed:
Readability: 4.1
5,404,429 views
Writer and artist James Bridle uncovers a dark, strange corner of the internet, where unknown people or groups on YouTube hack the brains of young children in return for advertising revenue. From "surprise egg" reveals and the "Finger Family Song" to algorithmically created mashups of familiar cartoon characters in violent situations, these videos exploit and terrify young minds -- and they tell us something about where our increasingly data-driven world is headed. "We need to stop thinking about technology as a solution to all of our problems, but think of it as a guide to what those problems actually are, so we can start thinking about them properly and start to address them," Bridle says.
James Bridle - Artist, writer
Working across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future. Full bio
Working across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future. Full bio
Double-click the English transcript below to play the video.
00:12
I'm James.
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I'm a writer and artist,
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and I make work about technology.
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I do things like draw life-size outlines
of military drones
of military drones
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in city streets around the world,
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so that people can start to think
and get their heads around
and get their heads around
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these really quite hard-to-see
and hard-to-think-about technologies.
and hard-to-think-about technologies.
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I make things like neural networks
that predict the results of elections
that predict the results of elections
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based on weather reports,
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because I'm intrigued about
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what the actual possibilities
of these weird new technologies are.
of these weird new technologies are.
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Last year, I built
my own self-driving car.
my own self-driving car.
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But because I don't
really trust technology,
really trust technology,
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I also designed a trap for it.
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(Laughter)
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And I do these things mostly because
I find them completely fascinating,
I find them completely fascinating,
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but also because I think
when we talk about technology,
when we talk about technology,
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we're largely talking about ourselves
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and the way that we understand the world.
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So here's a story about technology.
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This is a "surprise egg" video.
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It's basically a video of someone
opening up loads of chocolate eggs
opening up loads of chocolate eggs
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and showing the toys inside to the viewer.
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That's it. That's all it does
for seven long minutes.
for seven long minutes.
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And I want you to notice
two things about this.
two things about this.
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First of all, this video
has 30 million views.
has 30 million views.
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(Laughter)
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And the other thing is,
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it comes from a channel
that has 6.3 million subscribers,
that has 6.3 million subscribers,
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that has a total of eight billion views,
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and it's all just more videos like this --
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30 million people watching a guy
opening up these eggs.
opening up these eggs.
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It sounds pretty weird, but if you search
for "surprise eggs" on YouTube,
for "surprise eggs" on YouTube,
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it'll tell you there's
10 million of these videos,
10 million of these videos,
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and I think that's an undercount.
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I think there's way, way more of these.
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If you keep searching, they're endless.
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There's millions and millions
of these videos
of these videos
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in increasingly baroque combinations
of brands and materials,
of brands and materials,
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and there's more and more of them
being uploaded every single day.
being uploaded every single day.
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Like, this is a strange world. Right?
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But the thing is, it's not adults
who are watching these videos.
who are watching these videos.
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It's kids, small children.
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These videos are
like crack for little kids.
like crack for little kids.
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There's something about the repetition,
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the constant little
dopamine hit of the reveal,
dopamine hit of the reveal,
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that completely hooks them in.
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And little kids watch these videos
over and over and over again,
over and over and over again,
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and they do it for hours
and hours and hours.
and hours and hours.
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And if you try and take
the screen away from them,
the screen away from them,
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they'll scream and scream and scream.
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If you don't believe me --
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and I've already seen people
in the audience nodding --
in the audience nodding --
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if you don't believe me, find someone
with small children and ask them,
with small children and ask them,
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and they'll know about
the surprise egg videos.
the surprise egg videos.
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So this is where we start.
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It's 2018, and someone, or lots of people,
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are using the same mechanism that, like,
Facebook and Instagram are using
Facebook and Instagram are using
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to get you to keep checking that app,
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and they're using it on YouTube
to hack the brains of very small children
to hack the brains of very small children
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in return for advertising revenue.
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At least, I hope
that's what they're doing.
that's what they're doing.
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I hope that's what they're doing it for,
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because there's easier ways
of making ad revenue on YouTube.
of making ad revenue on YouTube.
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You can just make stuff up or steal stuff.
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So if you search for really
popular kids' cartoons
popular kids' cartoons
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like "Peppa Pig" or "Paw Patrol,"
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you'll find there's millions and millions
of these online as well.
of these online as well.
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Of course, most of them aren't posted
by the original content creators.
by the original content creators.
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They come from loads and loads
of different random accounts,
of different random accounts,
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and it's impossible to know
who's posting them
who's posting them
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or what their motives might be.
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Does that sound kind of familiar?
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Because it's exactly the same mechanism
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that's happening across most
of our digital services,
of our digital services,
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where it's impossible to know
where this information is coming from.
where this information is coming from.
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It's basically fake news for kids,
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and we're training them from birth
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to click on the very first link
that comes along,
that comes along,
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regardless of what the source is.
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That's doesn't seem like
a terribly good idea.
a terribly good idea.
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Here's another thing
that's really big on kids' YouTube.
that's really big on kids' YouTube.
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This is called the "Finger Family Song."
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I just heard someone groan
in the audience.
in the audience.
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This is the "Finger Family Song."
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This is the very first one I could find.
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It's from 2007, and it only has
200,000 views,
200,000 views,
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which is, like, nothing in this game.
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But it has this insanely earwormy tune,
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which I'm not going to play to you,
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because it will sear itself
into your brain
into your brain
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in the same way that
it seared itself into mine,
it seared itself into mine,
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and I'm not going to do that to you.
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But like the surprise eggs,
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it's got inside kids' heads
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and addicted them to it.
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So within a few years,
these finger family videos
these finger family videos
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start appearing everywhere,
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and you get versions
in different languages
in different languages
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with popular kids' cartoons using food
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or, frankly, using whatever kind
of animation elements
of animation elements
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you seem to have lying around.
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And once again, there are millions
and millions and millions of these videos
and millions and millions of these videos
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available online in all of these
kind of insane combinations.
kind of insane combinations.
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And the more time
you start to spend with them,
you start to spend with them,
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the crazier and crazier
you start to feel that you might be.
you start to feel that you might be.
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And that's where I
kind of launched into this,
kind of launched into this,
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that feeling of deep strangeness
and deep lack of understanding
and deep lack of understanding
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of how this thing was constructed
that seems to be presented around me.
that seems to be presented around me.
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Because it's impossible to know
where these things are coming from.
where these things are coming from.
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Like, who is making them?
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Some of them appear to be made
of teams of professional animators.
of teams of professional animators.
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Some of them are just randomly
assembled by software.
assembled by software.
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Some of them are quite wholesome-looking
young kids' entertainers.
young kids' entertainers.
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And some of them are from people
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who really clearly
shouldn't be around children at all.
shouldn't be around children at all.
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(Laughter)
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And once again, this impossibility
of figuring out who's making this stuff --
of figuring out who's making this stuff --
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like, this is a bot?
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Is this a person? Is this a troll?
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What does it mean
that we can't tell the difference
that we can't tell the difference
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between these things anymore?
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And again, doesn't that uncertainty
feel kind of familiar right now?
feel kind of familiar right now?
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So the main way people get views
on their videos --
on their videos --
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and remember, views mean money --
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is that they stuff the titles
of these videos with these popular terms.
of these videos with these popular terms.
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So you take, like, "surprise eggs"
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and then you add
"Paw Patrol," "Easter egg,"
"Paw Patrol," "Easter egg,"
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or whatever these things are,
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all of these words from other
popular videos into your title,
popular videos into your title,
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until you end up with this kind of
meaningless mash of language
meaningless mash of language
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that doesn't make sense to humans at all.
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Because of course it's only really
tiny kids who are watching your video,
tiny kids who are watching your video,
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and what the hell do they know?
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Your real audience
for this stuff is software.
for this stuff is software.
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It's the algorithms.
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It's the software that YouTube uses
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to select which videos
are like other videos,
are like other videos,
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to make them popular,
to make them recommended.
to make them recommended.
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And that's why you end up with this
kind of completely meaningless mash,
kind of completely meaningless mash,
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both of title and of content.
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But the thing is, you have to remember,
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there really are still people within
this algorithmically optimized system,
this algorithmically optimized system,
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people who are kind
of increasingly forced to act out
of increasingly forced to act out
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these increasingly bizarre
combinations of words,
combinations of words,
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like a desperate improvisation artist
responding to the combined screams
responding to the combined screams
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of a million toddlers at once.
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There are real people
trapped within these systems,
trapped within these systems,
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and that's the other deeply strange thing
about this algorithmically driven culture,
about this algorithmically driven culture,
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because even if you're human,
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you have to end up behaving like a machine
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just to survive.
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And also, on the other side of the screen,
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there still are these little kids
watching this stuff,
watching this stuff,
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stuck, their full attention grabbed
by these weird mechanisms.
by these weird mechanisms.
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And most of these kids are too small
to even use a website.
to even use a website.
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They're just kind of hammering
on the screen with their little hands.
on the screen with their little hands.
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And so there's autoplay,
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where it just keeps playing these videos
over and over and over in a loop,
over and over and over in a loop,
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endlessly for hours and hours at a time.
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And there's so much weirdness
in the system now
in the system now
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that autoplay takes you
to some pretty strange places.
to some pretty strange places.
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This is how, within a dozen steps,
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you can go from a cute video
of a counting train
of a counting train
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to masturbating Mickey Mouse.
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Yeah. I'm sorry about that.
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This does get worse.
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This is what happens
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when all of these different keywords,
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all these different pieces of attention,
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this desperate generation of content,
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all comes together into a single place.
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This is where all those deeply weird
keywords come home to roost.
keywords come home to roost.
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You cross-breed the finger family video
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with some live-action superhero stuff,
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you add in some weird,
trollish in-jokes or something,
trollish in-jokes or something,
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and suddenly, you come
to a very weird place indeed.
to a very weird place indeed.
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The stuff that tends to upset parents
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is the stuff that has kind of violent
or sexual content, right?
or sexual content, right?
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Children's cartoons getting assaulted,
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getting killed,
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weird pranks that actually
genuinely terrify children.
genuinely terrify children.
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What you have is software pulling in
all of these different influences
all of these different influences
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to automatically generate
kids' worst nightmares.
kids' worst nightmares.
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And this stuff really, really
does affect small children.
does affect small children.
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Parents report their children
being traumatized,
being traumatized,
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becoming afraid of the dark,
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becoming afraid of their favorite
cartoon characters.
cartoon characters.
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If you take one thing away from this,
it's that if you have small children,
it's that if you have small children,
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keep them the hell away from YouTube.
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08:56
(Applause)
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But the other thing, the thing
that really gets to me about this,
that really gets to me about this,
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is that I'm not sure we even really
understand how we got to this point.
understand how we got to this point.
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We've taken all of this influence,
all of these things,
all of these things,
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and munged them together in a way
that no one really intended.
that no one really intended.
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And yet, this is also the way
that we're building the entire world.
that we're building the entire world.
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We're taking all of this data,
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a lot of it bad data,
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a lot of historical data
full of prejudice,
full of prejudice,
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full of all of our worst
impulses of history,
impulses of history,
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and we're building that
into huge data sets
into huge data sets
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and then we're automating it.
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And we're munging it together
into things like credit reports,
into things like credit reports,
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into insurance premiums,
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into things like predictive
policing systems,
policing systems,
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into sentencing guidelines.
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This is the way we're actually
constructing the world today
constructing the world today
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out of this data.
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And I don't know what's worse,
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that we built a system
that seems to be entirely optimized
that seems to be entirely optimized
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for the absolute worst aspects
of human behavior,
of human behavior,
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or that we seem
to have done it by accident,
to have done it by accident,
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without even realizing
that we were doing it,
that we were doing it,
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because we didn't really understand
the systems that we were building,
the systems that we were building,
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and we didn't really understand
how to do anything differently with it.
how to do anything differently with it.
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There's a couple of things I think
that really seem to be driving this
that really seem to be driving this
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most fully on YouTube,
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and the first of those is advertising,
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which is the monetization of attention
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without any real other variables at work,
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any care for the people who are
actually developing this content,
actually developing this content,
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the centralization of the power,
the separation of those things.
the separation of those things.
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And I think however you feel
about the use of advertising
about the use of advertising
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to kind of support stuff,
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the sight of grown men in diapers
rolling around in the sand
rolling around in the sand
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in the hope that an algorithm
that they don't really understand
that they don't really understand
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will give them money for it
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suggests that this
probably isn't the thing
probably isn't the thing
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that we should be basing
our society and culture upon,
our society and culture upon,
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and the way in which
we should be funding it.
we should be funding it.
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And the other thing that's kind of
the major driver of this is automation,
the major driver of this is automation,
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which is the deployment
of all of this technology
of all of this technology
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as soon as it arrives,
without any kind of oversight,
without any kind of oversight,
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and then once it's out there,
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kind of throwing up our hands and going,
"Hey, it's not us, it's the technology."
"Hey, it's not us, it's the technology."
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Like, "We're not involved in it."
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That's not really good enough,
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because this stuff isn't
just algorithmically governed,
just algorithmically governed,
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it's also algorithmically policed.
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When YouTube first started
to pay attention to this,
to pay attention to this,
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the first thing they said
they'd do about it
they'd do about it
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was that they'd deploy
better machine learning algorithms
better machine learning algorithms
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to moderate the content.
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Well, machine learning,
as any expert in it will tell you,
as any expert in it will tell you,
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is basically what we've started to call
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software that we don't really
understand how it works.
understand how it works.
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And I think we have
enough of that already.
enough of that already.
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We shouldn't be leaving
this stuff up to AI to decide
this stuff up to AI to decide
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what's appropriate or not,
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because we know what happens.
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It'll start censoring other things.
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It'll start censoring queer content.
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It'll start censoring
legitimate public speech.
legitimate public speech.
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What's allowed in these discourses,
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it shouldn't be something
that's left up to unaccountable systems.
that's left up to unaccountable systems.
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It's part of a discussion
all of us should be having.
all of us should be having.
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But I'd leave a reminder
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that the alternative isn't
very pleasant, either.
very pleasant, either.
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YouTube also announced recently
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that they're going to release
a version of their kids' app
a version of their kids' app
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that would be entirely
moderated by humans.
moderated by humans.
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Facebook -- Zuckerberg said
much the same thing at Congress,
much the same thing at Congress,
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when pressed about how they
were going to moderate their stuff.
were going to moderate their stuff.
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He said they'd have humans doing it.
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And what that really means is,
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instead of having toddlers being
the first person to see this stuff,
the first person to see this stuff,
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you're going to have underpaid,
precarious contract workers
precarious contract workers
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without proper mental health support
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being damaged by it as well.
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(Laughter)
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And I think we can all do
quite a lot better than that.
quite a lot better than that.
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(Applause)
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The thought, I think, that brings those
two things together, really, for me,
two things together, really, for me,
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is agency.
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It's like, how much do we really
understand -- by agency, I mean:
understand -- by agency, I mean:
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how we know how to act
in our own best interests.
in our own best interests.
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Which -- it's almost impossible to do
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in these systems that we don't
really fully understand.
really fully understand.
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Inequality of power
always leads to violence.
always leads to violence.
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And we can see inside these systems
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that inequality of understanding
does the same thing.
does the same thing.
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If there's one thing that we can do
to start to improve these systems,
to start to improve these systems,
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it's to make them more legible
to the people who use them,
to the people who use them,
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so that all of us have
a common understanding
a common understanding
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of what's actually going on here.
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The thing, though, I think
most about these systems
most about these systems
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is that this isn't, as I hope
I've explained, really about YouTube.
I've explained, really about YouTube.
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It's about everything.
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These issues of accountability and agency,
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of opacity and complexity,
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of the violence and exploitation
that inherently results
that inherently results
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from the concentration
of power in a few hands --
of power in a few hands --
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these are much, much larger issues.
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And they're issues not just of YouTube
and not just of technology in general,
and not just of technology in general,
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and they're not even new.
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They've been with us for ages.
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But we finally built this system,
this global system, the internet,
this global system, the internet,
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that's actually showing them to us
in this extraordinary way,
in this extraordinary way,
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making them undeniable.
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Technology has this extraordinary capacity
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to both instantiate and continue
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all of our most extraordinary,
often hidden desires and biases
often hidden desires and biases
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and encoding them into the world,
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but it also writes them down
so that we can see them,
so that we can see them,
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so that we can't pretend
they don't exist anymore.
they don't exist anymore.
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We need to stop thinking about technology
as a solution to all of our problems,
as a solution to all of our problems,
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but think of it as a guide
to what those problems actually are,
to what those problems actually are,
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so we can start thinking
about them properly
about them properly
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and start to address them.
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Thank you very much.
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(Applause)
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Thank you.
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(Applause)
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Helen Walters: James, thank you
for coming and giving us that talk.
for coming and giving us that talk.
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So it's interesting:
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when you think about the films where
the robotic overlords take over,
the robotic overlords take over,
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it's all a bit more glamorous
than what you're describing.
than what you're describing.
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But I wonder -- in those films,
you have the resistance mounting.
you have the resistance mounting.
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Is there a resistance mounting
towards this stuff?
towards this stuff?
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Do you see any positive signs,
green shoots of resistance?
green shoots of resistance?
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James Bridle: I don't know
about direct resistance,
about direct resistance,
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because I think this stuff
is super long-term.
is super long-term.
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I think it's baked into culture
in really deep ways.
in really deep ways.
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A friend of mine,
Eleanor Saitta, always says
Eleanor Saitta, always says
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that any technological problems
of sufficient scale and scope
of sufficient scale and scope
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are political problems first of all.
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So all of these things we're working
to address within this
to address within this
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are not going to be addressed
just by building the technology better,
just by building the technology better,
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but actually by changing the society
that's producing these technologies.
that's producing these technologies.
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So no, right now, I think we've got
a hell of a long way to go.
a hell of a long way to go.
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But as I said, I think by unpacking them,
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by explaining them, by talking
about them super honestly,
about them super honestly,
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we can actually start
to at least begin that process.
to at least begin that process.
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HW: And so when you talk about
legibility and digital literacy,
legibility and digital literacy,
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I find it difficult to imagine
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that we need to place the burden
of digital literacy on users themselves.
of digital literacy on users themselves.
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But whose responsibility
is education in this new world?
is education in this new world?
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JB: Again, I think this responsibility
is kind of up to all of us,
is kind of up to all of us,
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that everything we do,
everything we build, everything we make,
everything we build, everything we make,
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needs to be made
in a consensual discussion
in a consensual discussion
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with everyone who's avoiding it;
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that we're not building systems
intended to trick and surprise people
intended to trick and surprise people
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into doing the right thing,
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but that they're actually involved
in every step in educating them,
in every step in educating them,
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because each of these systems
is educational.
is educational.
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That's what I'm hopeful about,
about even this really grim stuff,
about even this really grim stuff,
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that if you can take it
and look at it properly,
and look at it properly,
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it's actually in itself
a piece of education
a piece of education
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that allows you to start seeing
how complex systems come together and work
how complex systems come together and work
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and maybe be able to apply
that knowledge elsewhere in the world.
that knowledge elsewhere in the world.
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HW: James, it's such
an important discussion,
an important discussion,
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and I know many people here
are really open and prepared to have it,
are really open and prepared to have it,
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so thanks for starting off our morning.
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JB: Thanks very much. Cheers.
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(Applause)
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ABOUT THE SPEAKER
James Bridle - Artist, writerWorking across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future.
Why you should listen
James Bridle is an artist and writer working across technologies and disciplines. His artworks and installations have been exhibited in Europe, North and South America, Asia and Australia, and have been viewed by hundreds of thousands of visitors online. He has been commissioned by organizations including the Victoria & Albert Museum, the Barbican, Artangel, the Oslo Architecture Triennale and the Istanbul Design Biennial, and he has been honored by Ars Electronica, the Japan Media Arts Festival and the Design Museum, London. His writing on literature, culture and networks has appeared in magazines and newspapers including Frieze, Wired, Domus, Cabinet, The Atlantic, the New Statesman and many others, and he has written a regular column for The Observer.
New Dark Age, Bridle's book about technology, knowledge and the end of the future is forthcoming from Verso (UK & US) in 2018. He lectures regularly on radio, at conferences, universities and other events including SXSW, Lift, the Global Art Forum and Re:Publica. He has been a resident at Lighthouse, Brighton, the White Building, London and Eyebeam, New York, and an adjunct professor on the interactive telecommunications program at New York University.
James Bridle | Speaker | TED.com