The internet has always been a bit of a minefield when it comes to finding
correct information from reliable sources and reputable people.
So this time on the Future of Tech, I'm not going to make that task much easier.
As we look into the deep neural networks,
machine learning and devious minds that concoct deep fakes.
This technology takes one person's face and replaces it with another,
in an image or video. This is the Future of Tech.
The show that puts on a new face in every episode to pretend our host is
way more knowledgeable than real life would suggest.
While the word deepfake sounds mysterious and straight out of a spy
novel. What does it actually mean?
The word is made up by combining deep learning and fake. With deepfake,
you can switch any footage of a person's face with another person's face
deepfake. Isn't only about manipulating video though.
There are also examples of audio fakes,
where you can create any sentence said in a specific person's voice.
For example, I could make my colleague,
Scott say that Lars is the coolest guy in the world,
which of course would be true because it is. Don't question it.
While deepfakes are kind of fun and impressive.
What are some of the real use cases for them?
Let's start with the most obvious that you may have seen,
manipulating video footage. Often this has seen with something silly,
like a celebrity face swap or putting one person's voice on someone else's face,
but it goes much further than that.
You can also bring back actors from the dead.
If a sequel to a popular sci-fi franchise, for example,
needed to use those actors, again. Museums are looking at bringing back to life,
historic characters, such as David Crockett, John F. Kennedy, or even Ghandi.
Having historic events recreated with the real people and voices would
enhance the learning experience dramatically. A clinic in Boston,
in the US in conjunction with Northeastern University is recreating
voices for people that have lost their own.
This pioneering project can give people an important part of their identity
back, which is really cool. Of course,
it isn't only the good guys that get hold of amazing technology.
In one instance, a UK energy company's Chief Executive was tricked into wiring
200,000 euros to a Hungarian supplier because he believed his boss was
instructing him to do so.
Now let my esteemed colleagues, Scott, take it from here.
Why not imagine you could make any politician say
anything you want?
A famous example is of Barack Obama saying things he would never say, well,
at least not in public.
It was done by a comedian Jordan Peele who mimicked his voice deepfake
technology then applied Obama's face and voilá.
A more subtle example is Indian politician Manoj Tiwari who used
deepfake to make himself appear to speak fluently in the dialect of his target
voters. Now, does that mean we can't trust what politicians are saying anymore?
Oh, wait. Nevermind.
The real threat is the use of this technology to spread disinformation
to explain more here is my colleague Scott.
Okay then.
The ethical implications and considerations for a technology like deepfake are
vast. Imagine this: a criminal is charged with a crime, the criminal's defense,
they find a video from some surveillance footage from a place in a
completely different city.
The footage is then put through a deepfake process to put the criminals face
and person into the footage. Tada, alibi done.
Or what if phone calls could be manufactured with the exact voiceprint of a
different person,
that could lead to identity theft fraud and so
much more.
So how does the technology work? And can we in fact harness it.
The technology behind deepfakes as a subdiscipline of machine learning,
known as deep learning.
Deep Learning uses something called neural networks,
a design that was inspired by how our own brain cells work.
To create a deepfake we need to teach our neural network,
how to create something completely new.
We can do this through a process called training,
which involves feeding in lots and lots of examples of the thing we want to
ultimately recreate. Now after much time and number crunching,
our training process will provide us with a set of instructions for how to
create that new thing. It's this thing that we call our model. Now,
this model is ultimately used to generate entirely new videos,
pictures, or audio based on the examples that we provided.
So how long does the training process take? Well,
models can take anywhere from 12 hours to 12 weeks or more,
depending on the quality and quantity of examples,
the complexity of the subjects,
the computing power you have available and how much money you're willing to
throw at the problem.
The example of Lars and myself used in this episode are
snapshots of our model over a 24 hour training period. Now,
if you want to know more about machine learning and deep neural networks,
check out the episode of future of tech on machine learning.
Now,
as we've seen deepfakes hold the potential to cast doubt on the legitimacy
of any form of digital media.
So how in the world are we to believe anything anymore? Last year,
a consortium of over 100 tech companies, including AWS,
Facebook and Microsoft created something called a Deepfake Detection
Challenge,
offering $1 million in prizes for anybody able to create
an effective way to detect deepfakes. Now,
another idea that's being kicked around is some form of digital watermark
issued and stored using a blockchain.
When the digital asset is created, it's assigned a unique ID.
That's a sort of fingerprint generated from the original.
This could then be used to verify the authenticity of that asset later
or uncover fakes. Oh, what's blockchain? Well,
this show has an episode for explaining that too.
Well, thanks for that Scotty boy,
my expectation is that there will be two main streams of future deepfake tech.
One side will be enhancing the use and believability of it.
The other will be detecting what is a deepfake and what isn't,
both will be equally important. Want to contribute on the debate of deepfakes?
Start the conversation in the forum for the show. Link is in the description.
And you can of course,
find me on Twitter @larsklint or through the A Cloud Guru Facebook page,
and other social media channels. This has been the Future of Tech,
a show being made entirely inside Scott's farm of EC2 instances.