Made by a dude who has next to no experience in the field. Now imagine what a guy who knows what he's doing can do with a bit more money. That's what the allusion here is; the fact that a Reporter with 500$ even comes close should be an alarm signal to you.
I think one thing that could have helped the reporter is if they had reencoded the original Zuckerberg footage into something with a lower bitrate. The fine details/imperfections on his forehead contrasted with the lower fidelity of data's face provides a little too much contrast. It doesn't help that most of the source data for Data's face is lower quality, plus he has so much makeup pancaked on his face. I think if those factors were accounted for, the reporter's results would have been much more convincing even though he's a deepfake neophyte.
Oh man; I’ve watched a bunch of Ctrl+Alt+Face videos, but I’d never seen that Tom Cruise one. Thanks — hilarious. Also, I love how they fade in Seth Rogan for, like, two seconds — especially considering the effort required to put together the training data, run the app, etc.
I'm under the impression that these things are easier to come infinitesimally close to, but very hard to get right: i.e. the old uncanny valley problem. A reporter with $500 can get very close, but a team of PhD with thousands of dollars and a lot of time may never be able to produce something that'll convince the public.
I'm NOT claiming that this is the case, I'm just saying we don't have a reason to believe why this can't be the case.
I'd really hesitate to bet on never in this case--even if never were scoped to mean not within 20 years.
There really are two separate questions though:
- Can experts with a big budget create videos that even equally expert analysis can't tell from the real thing? (Maybe yes, maybe no. But it's hard.
- With modest skill and budget, are people increasingly able to create fake videos that stand up a cursory glance and can fool people as a result? (Absolutely--or at least we're getting close.)
My point is, there is no close or far in this business. It's binary, either it looks real, or it doesn't. If your intention is to make deepfake to put it in a movie, video game or any other entertainment system, then sure you're right.
But that already exists, DeepFake isn't a fundamental development for that. What is the "big thing" about deepfake is that we can imitate speeches of people in leadership positions. For this, we can get really really close; but it's unclear if it'll ever be realistic enough to be a problem in court cases, politics etc...
Voice actor reads a poem in voices of famous people; his face gets swapped with the actor's face; the combination of voice and face makes it very believable.
Yes. The cost alone could have been significantly reduced. As the article notes, using an owned GPU locally instead of renting one for a cloud instance would have reduced the cost. The author also overspent on virtual CPU resources - paying for unused RAM and CPU cores when most of the processing was done on GPUs. And once you have a good model trained, actually putting it to use in inference is much faster and cheaper.
How to create news when there is no news: try to write a tutorial about it, fail, then state that thing-that-people-irrationally-fear-because-nipples is not something to fear yet, because even seasoned tech & blockchain journalists can't do it.
The absolute autofellatio state of hype media these days. Ha-ha, look at how this autistic CEO looks like a robot, and shame on you for imagining what Charlize Theron looks like naked. Tune in next week where I try and fail to launch an ERC-token, and use that experience to argue that cryptocurrency adoption will be delayed.
Man, you're reading way too much into my headline. The headline describes the article accurately: I created a deepfake. It took me two weeks and I spent $552. The headline doesn't say anything about whether it was convincing or not.
> The headline doesn't say anything about whether it was convincing or not.
I guess I always assumed the 'deep' in deepfake meant it was convincing, but upon further consideration it's probably just a nod to DNNs. Well played sir.
A few weeks ago my girlfriend made me discover Instagram filters. Obviously they're not in "deep fake" territory but I was still massively impressed by the quality of the face recognition and tracking coupled with some rather advanced 3D reconstructions on top.
15 years ago that would've been science fiction, today it's a free gimmicky feature in an app running on commodity hardware. There are also apps that will smooth your skin or change the shape of your eyes in real time.
All these technologies are evolving at a ridiculously fast pace, I'm sure that a decade from now you'll be able to do a much more convincing fake in a fraction of the time. We're getting deeper and deeper into a post-truth world.
I don't really understand this argument at all. We've been in this "post truth" world for a long time already for every form of media other than video. Text quotes, photos, and audio can all be easily faked. If I post a ridiculous quote here and say it's from Obama, you won't believe me. But if the NYTimes does the same thing, it carries a lot more weight. We've been here for a long time already, now those standards will just apply to video as well. Doesn't seem that crazy.
Also, I'm fascinated by the idea of using AI to detect the use of AI. How good will your deep fake have to be in order to fool a deep fake detection AI?
I can just hear people saying it now. Joking aside, and not taking in ANY ethical/unethical misuse considerations this software is capable of, it is really cool tech.
> But if the NYTimes does the same thing, it carries a lot more weight.
Sure, and that's part of the danger. Convincing deep fakes will be used to delegitimize mainstream news organizations, as with what happened with Dan Rather - a trusted source presented faked documents.
But why is this the danger now in a way that it hasn't been previously? You could have presented fake documents for hundreds of years now, but it's not like we don't have any credible news organizations as a result.
It gets increasingly cheap to manufacture convincing fakes, but it doesn't get any cheaper to do quality journalism. The risk as I see it is that there is such an overwhelming tsunami of manufactured reality that it becomes impossible to tell truth from fiction.
It was never that expensive to manufacture fake text. Minorly expensive to manufacture fake images.
And we've been hit by tabloids, spam and so on before. None of that is new. Overwhelmed by content is/was/will be a problem that is solved very simply: people limit the distribution lanes they consume, and naturally establish "trust networks" and hierarchies.
Nyt didn't become "trusted" by accident. People aren't as dumb as you seem to think.
Anyways the problem is of distribution, not that a lie can be told. If we can't trust our distribution lanes to actually reflect the institutions we're trusting, then we can't establish our trust networks.
And this is a real problem: our distribution lanes are divorced now from our actual information distrubuters; medium, Facebook, Twitter, etc fuck around with our trust networks, randomly injecting their own bullshit into our feeds and messing around with feed-order based on non-trust metrics (eg money paid) such that they've become fairly unreliable.
And our classical trustable institutions have become less trustworthy, as they flounder about trying to make sense of the "digital age", and have so far done so in a pathetic fashion
In the past you had to pay a person to write that fake text. Wait a few more years and you'll see convincing text coming out of some algorithm at the cost of an EC2 instance.
That's fine and well, but again, I don't think the existence of it is new; if they generate 1 lie a day, or 1000, or a million, it doesn't change much. It gets resolved by the trust distribution network.
When that network breaks down, you only need a single good lie to do the damage.
The funny part is that Dan Rather and his producers were fooled by a deeply unconvincing fake — a supposedly Vietnam-era typewritten document that was obviously made using Microsoft Word using default settings. Furthermore, many many people continued to defend it as real for a long time after partisans on the other side had thoroughly debunked it.
If 2004 news could be fooled by a fake that took a couple of minutes to make, I’m not that worried that today’s news is any better.
The major problem of our time is trust (for both "small t" personal trust and "capital T" trust in a crypto sense). While any feeling of absolute or universal truth is probably beyond our grasp at this point, people will (and largely have) learned which sources are considered 'trusted' within the circles of influence they travel in.
The people who care about the 'legitimacy' of a news organization are moderates who are passively engaged and are being rapidly driven to the margins. The 'objective truth' of the matter is less relevant than how it is received. Activist politics is en vogue thanks to the feelings of helplessness brought on by globalization, and if you're not an activist your views are not really an important part of the process anymore. You'll have to pick one of the two options that the activists come up with because they won't show up to vote for a centrist candidate. In either case, a moderate platform cannot win.
For the record, I feel the above situation is incredibly dystopian; but we're hardly the first country where pathos supersedes logos and ethos.
That trusted source didn't bother to vet the faked documents and instead rushed it onto the air. That trusted source continued to push that narrative even going so far as to say, "fake but accurate," destroying all credibility and ultimately retiring.
The only difference is today, they don't retire out of shame, they just keep on doing it, keeping viewership via emotional draw rather than rational news. Real news has been dead since that incident in my view. It's mostly state propaganda, regardless of party.
You're mixing up Rather with the trusted source. Rather received documents from what was apparently a long-term, trusted source. CBS certainly screwed the pooch in that incident, but a long-term relationship with a well-placed source is inherently a form of vetting.
I think it is the other way around: mainstream news organizations will cry fake news to delegitimize bloggers and amateurs. If everything is easily faked, the only ones to trust with the truth, are the entrenched media companies. Powerful people will be the first to benefit from fake media, when they can claim that the video evidence must be fake ("They photoshopped my arm around her waist!").
The delegitimization didn't come so much from the forged documents themselves. It came more from, after the whole scandal erupted and it became blatantly obvious that they were faked, not only CBS and Rather, but the entire Mainstream Media doubled down on them being real, and the narrative being real. They all still, to this day, insist that they were real. That's what couldn't be engineered or tricked.
> They all still, to this day, insist that they were real.
This is, itself, "fake news". I can't find any indication that other mainstream media outlets defend the documents "to this day". The reporting largely seems to be "certainly smells like bullshit, and we can point to specific issues with them that seem to support that".
https://www.nytimes.com/2004/09/13/opinion/those-discredited... cites a wide variety of news organizations looking into them and finding problems, stating "When the mainstream press checked the sources mentioned or ignored by '60 Minutes II,' the story came apart." and noting Newsweek specifically calling them "discredited".
If you post a ridiculous quote, say it’s from Obama, then provide a link to a video where Obama says that quote, more people believe you. People already believe tabloid journalism. Just because you might exclusively trust NYTimes doesn’t mean easily accessible mechanisms for fabricating evidence aren’t a problem for a massive chunk of the world population.
And what about when this happens at a state-sponsored level (This is absolutely already in development, if it hasn’t happened already...). “Did you see that Fox News exclusive video leaked from the Bernie Sanders campaign? Yeah he was holding a private dinner for a bunch of Billionaires. They say they got it from some Russian oligarch he invited. So much for grass roots change, I think I’ll just stay home this Election Day.” Or the corollary: “That smoking-gun tape the Do-Nothing Dems have of me at Putin’s personal sex trafficking center, where the two of us are laughing about having Epstein take the hit? Fake news! They’re called deepfakes, and they make these just absolutely incredible fake videos. Not real at all though. Only trust what the Government-sanctioned media says!”
As per your other point, given the GANs that are used to make these are precisely a deep fake AI fooling a deep fake detection AI, aren’t we already there? Further, when the government is making the generator, a privately trained discriminator has no chance. How would you even train that? Get the government to give you a bunch of generated fake media so that you can develop a really spot-on model? I don’t think so.
Two predictions:
Deepfakes will play a roll in the 2020 election.
Deepfakes will play a roll in every election thereafter.
If this doesn’t concern you, I don’t know what would. The thing with the “post-truth world” is that once people think we’re in it, we are.
I don't think the argument is that deepfakes won't matter. It's that they don't represent a new paradigm, but are instead just an additional medium (video) which must be more scrutinized than before.
Long have documents and news been the subject of fraud. And for a few decades photo alterations have been common. Now we are adding video to the list.
But there is nothing new about the faking of libelous material (eg Killian documents 2004)
Video is massively different for swaying public opinion. There’s a reason most news on Facebook/Instagram is in the form of 15-60 second video montages. People can tune in quickly, get information passively, and leave. Video isn’t just “another item on the list”. It’s the most powerful means of sharing information we have.
How many people do you think actually read those “Killian documents”? How many people do you think a state-sponsored social media campaign built on the most accessible media would reach?
"With software there are only two outcomes: either the users control the program or the program controls the users. If the program is not under user control, and the developer controls everything, then the program is an instrument of unjust power, applied by the powers that be."
Deepfakes are just a continuation of "fake news" (formerly known as propaganda), and the end outcome is we either succumb to those who use it, or adapt - filtering out the bs isn't easy, but it's not an insurmountable task, either.
I don't think it's so much that people will be fooled by fake video, as that people can no longer rely on video as evidence. Up until now, video has been the gold standard of "proof" that an event happened. Quotes, photos, and (to an extent) audio have been fakeable for a long time, and they are mistrusted accordingly. And while CGI has slowly made it harder to spot fake events, videos of speech remained mostly safe.
It's won't upend the world, but we are losing a hugely helpful tool that has been relied upon for 60 years.
It'll certainly be weakened, but I don't think it'll necessarily have to be discarded altogether. The need now will be for processes and tools to guarantee the provenance of a video.
The technology to fake paper ballots is trivial, but they still (mostly) work fine for elections, because we've developed strict rules for how they need to be handled in order to retain credibility.
I was saying something like that for a long time now, but recently I started thinking that it's even more on an non-issue than I thought. I mean, what I was saying is that "yeah, this is all new and weird, but when everybody started using Photohop it was also weird, and yet we are moving on".
But recently I read "Tlön, Uqbar, Orbis Tertius", and I thought that the point Borges was making could be easily described as critique of "fake-news post-realism of today", except it was 80 years ago. And while the notion of this problem not being new at first seemed weird to me, eventually I figured this is pretty natural: while 80 (or 800 for that matter) years ago there wasn't any such tools to manipulate information on that scale, nobody had the access to information on that scale in the first place. So anyone could be fooled by more powerful actor anyway. Offensive tools of any time are roughly the same as the defensive tools.
It's just that these 20 years at the turn of the century were somewhat the sweet spot, when we had this "Internet for people like us", so it was us who was fooling the less knowledgeable people, while keeping the belief that we are relatively safe from being maleficently disinformed by somebody else. And now we can clearly see it's not necessarily the case anymore, ao it feels like something new.
> How good will your deep fake have to be in order to fool a deep fake detection AI?
The best generator and the best detector are actually part of the same model! If you create a better detector, you are making the generator better at the same time so you have not accomplished anything.
"GANs are a clever way of training a generative model by framing the problem as a supervised learning problem with two sub-models: the generator model that we train to generate new examples, and the discriminator model that tries to classify examples as either real (from the domain) or fake (generated). The two models are trained together in a zero-sum game, adversarial, until the discriminator model is fooled about half the time, meaning the generator model is generating plausible examples."
Is the generator always assumed to be able to keep up when the discriminator is improved algorithmically? I've always wondered that when I hear this counter-argument.
Well, from the pure GAN theory perspective, it is theoretically possible for a perfect generator to exist which generates samples that perfectly match the 'source data distribution' (the only question is how do we obtain one or close to it), and thus a perfect discriminator can't exist - a fake image could be realistic and indistinguishable in all aspects.
And it does seem that the human-visible weaknesses of many currently published deepfake examples are those that would be hard for the current discriminator architectures to detect, not those which would be harder to generate than any other part of the fake.
The problem of fake news is not actually that you (a rhetoric "you"), with a presumably above average intelligence, is able select or be skeptical about your sources of truth, but:
1) The researched human behavior where "1000 lies must be equal to 1 truth".
2) Monopolizing the information stream: the attention grabbing effectiveness of deepfake videos to convey fake messages and its novelty incentive to share them on social media, added to the fear-of-missing-out they generate on viewers and the fact that "the effort required to refute b* is 10 times greater than the effort required to produce it":
It's my understanding (and experience) that Snapchat filters are even more impressive and that Snap CEO Evan Spiegel has pretty much bet the company on AR [1].
I feel like that ship sailed a while ago with Photoshop being around. I think the problem now is you can do the same with videos and the technology is more commoditized so you don’t have to be very knowledgeable to do these things.
People predicted that Photoshop was the end of truth, that journalism could no longer be trusted, that photographic evidence at criminal trials would be inadmissible.
None of that actually happened because people learned to be skeptical, and to care about who took the photo, the chain of custody, and the controls to prevent digital alteration.
Maybe we need something similar but more rigorous for video. The camera itself could encode a PKI signature in every frame of the original. If subsequent edits preserve frames as is, then the viewer could determine how many frames were cut or duplicated.
If subsequent edits crop, recolor or otherwise alter the frames, that editor could encode its own digital signature so the viewer could judge how much to trust their edits.
I don't agree with your assessment. People didn't learn to be skeptical most of the time. We've seen what fake news does to people's opinions; debunking a video as fake after it was viewed by a large group of people is enough to do serious damage to people's viewpoints.
> Maybe we need something similar but more rigorous for video.
Is there evidence that deepfake videos will be worse than photos? My (naive) sense is that even for an AI, editing a photo will always be easier than editing a video with sound.
If Photoshop and deep-fake images aren't a problem, shouldn't we be less concerned about video?
>>None of that actually happened because people learned to be skeptical, and to care about who took the photo, the chain of custody, and the controls to prevent digital alteration.
This may be true in courts of law, but it absolutely is not when it comes to general public consumption of pictures.
Photo editing has been used pretty much since the beginning of mainstream photography. You should never "trust" pictures for anything serious if you don't have absolute trust in the source.
I don't completely agree, good quality photo editing, even in this day and age, is not that mainstream. You need a decent amount of skill to edit a good quality picture in a way that won't look obviously fake. Pre-digital-photography it was only possible for skilled people with a significant amount of resources (like the Soviet government, no doubt).
Besides it's one thing to edit a still image and a whole other to forge a long video, complete with audio. Look at those movies these past few years using 3D models to insert younger versions of actors (Terminator and Star Wars come to mind). They must have invested millions into it, they have very talented artists and it's pretty good but it's still quite easy to spot the fakeness of it.
Pre-digital it may have been destined for old-school newspaper pictures with the varying density dots - monochrome of course. That would mask a multitude of sins and shoddy brushwork.
The Daily Mail was at it from around WW1, perhaps earlier. Though their main WW1 fake was, of course, the cadaver factories. Surprisingly the Times bought that tale too.
Please don't tell this to mainstream economists though (and their buddies in tech). They don't like to be challenged on the notion that this tech progress is business-as-usual, and that obsolete jobs will be replaced with new kinds of jobs.
I'm old enough to remember when people still attempted to claim that fashion magazines were forcing airbrushing on women. Clearly, there's a large amount of market interest for this sort of capability.
> We're getting deeper and deeper into a post-truth world.
Are we though? Or is it just becoming much more obvious the limitations of relying on the media in general. This very well might lead to a better understanding of truth, and our personal responsibility in understanding it.
At the very least, it's not a foregone conclusion that this will lead to worse outcomes than what we have today. It might be what tips us in a new and better direction.
I do not agree this _might_ leads us in a better direction.
What we'll continue to see are rising sects of flat-earthers, anti-vaxxers, cultists, polarization and deniying of anything not-in-my-bubble, a complete lack of trust in journalism and media, and futile attempts of fact-checking while we're all drowning in fake news shared endlessy on unsuspecting users. It takes a lot of effort to show something was manipulated digitally, and you'll have to fact-check by yourself, that doesn't scale at all.
The problem is that we have always accepted what we see because we've assumed that things are more or less as they've been presented to us, we've mostly blindly accepted the story from the social truthmakers. We've had no reason to question them. This will lead to humanity doing a lot more questioning. I think this very well might lead to some very positive outcomes.
The fact that we're more aware of flat-earthers today, is probably a good thing too. I'm not 100% sure that there are more of them today than before, or if they're just more noticeable. But in either case, we should be very careful to draw too many conclusions when we look around today because we're living in a time of great transition. We're basically in our teenage years of this technology.
Just as you shouldn't judge an adult by who he was at 14, I don't think we should assume we know what the adult internet will look like because we see some acne on it today.
> we have always accepted what we see because we've assumed that things are more or less as they've been presented to us
Even this is too simple. Many people have lived under propaganda regimes, yes, many have bought into them, and many people have seen through them.
Each new wave of information technology provides new ways to “pull the wool” over peoples’ eyes.
And though a propaganda machine has power... like all things it creates and equal an opposite power that eventually destroys it. The question for individuals is only: where am I in the cycle, how long will this cycle last, and what is my role to play?
I'm not really posting to refute. Just a few scattered thoughts, I guess.
Anywhere you have trust, there's a potential for abuse. A seemingly natural response to abuse of trust is to find a lapse in the victim's vigilance and start strapping on your own armor. I listened to a podcast this fall (sorry, I don't recall for certain--my best guess is that it was peter pomerantsev on Ezra Klein's podcast) where the guest suggests that some institutions/relations (like markets) depend on trust to produce value and may be undermined or degraded if enough participants take an individualist caveat emptor approach.
It is hard to know, in a complex adaptive system, what new equilibria will emerge downstream from a big disruption. We certainly could emerge through the other side with better epistemologies. But I don't see it as a given. Thinking is hard. Proving anything is harder. Skepticism can be good (and I suspect we need more--though I don't think it's terribly well distributed or applied at the moment...), but it's also easy; it requires no trust, knowledge, thinking, rigor, logic, or proof.
So, I'm troubled by the possibility we'll dig ourselves into a deep world-shrinking skepticism (a callous) of anything we didn't/can't personally experience. It can be well-founded on real abuses of trust. It may even be the sum of individual rational choices.
Neither would necessarily keep it from unmooring things we mistook for solid ground. And, when someone finally notices one drifting, there may not be enough trust left to agree on fundamentals like: is it adrift? is that a problem? was it ever tied down? is there anything we can do? should we wait for a bit to see if it drifts closer first? should we act?
I agree with everything you said, and I don't have any special insight about how things are going to play out.
But i'm terrified of the current loud support toward censorship and authoritarian suppression of incorrect ideas. We have a lot of historical evidence of just how bloody that always turns out. So I choose to believe in the power of openness and competition of ideas.
As others have posted above, we will never have a time where it's possible or desirable for each of us to validate the truth of every claim, so that means we will have to find trustworthy arbiters of truth. I think that this should happen by people showing they are trustworthy and earning respect, rather than using authoritarian control to shut down those with differing ideas.
Much of the media today has lost such respect, and deservedly so. You can not fix this by suppression of free-speech, but only by creating honest organizations that aren't afraid to respectfully show the ideas of those who see things differently -- even if it's just refute them. Organizations that _trust_ the viewer to decide between fairly articulated positions.
The contempt for our fellow man when we say that bad ideas must never see the light of day or enjoy the same platform as government-approved ideas is a deeply paternalistic and ultimately anti democratic idea. It's elitism at its worst.
Aha. And so here we are, watching something we thought was steadfast float slowly out to sea. The ability to let people say shitty things without trying to shut them up is one more thing we need trust for.
(For example, we need to be able to trust that they have a sincere opinion and aren't paid shills for a corporate lobby on a PR mission to waste our time, emotional energy, column-inches, and attention.)
If you feel a growing sense of dread as it retreats, it's a good time to consider whether you know others who have expressed a similar sense of dread that other things in our world have come unmoored, and whether they could use some help keeping them tied down.
Trust has a problem of root. You cannot exactly trust even your parents these days. They are more often wrong than not. Grandparents, even more so.
Even society is shown to be untrustworthy, and the social processes of science.
Thus some reactionaries want to replace trust with authority. Or markets, which is another name for social proof, but with much less transparency.
Ultimately the other parts of trust are verification and reputation, which are both not unassailable. (Sybil style attacks, bribery, institutional and social biases.)
But, our saving grace might be simpler: cooperation without trust is possible and might be as efficient if things get bad enough.
I'm sure that a decade from now you'll be able to do a much more convincing fake in a fraction of the time. We're getting deeper and deeper into a post-truth world.
Maybe I’m being paranoid but it seems that the public is being conditioned to believe deepfakes are so good prior to a certain cache of video recordings being made public
I'd say a post-truth world wouldn't be a world at all so to speak, because if everybody lives in their own filter bubble, with no access to a common world, the public sphere, where humans can have experiences and communicate, ceases to exist.
> You have to remember that in democratic societies citizens talking with each other is very important. We've lost a lot of that with the mass media. Now we have an opportunity for citizens to create their own communications with each other. So when these big deals with the big companies and the big governments carve up this new territory, I feel it's very important that we keep a kind of "social green belt", that we keep the ability for citizens to talk amongst each other.
> If everybody always lies to you, the consequence is not that you believe the lies, but rather that nobody believes anything any longer. This is because lies, by their very nature, have to be changed, and a lying government has constantly to rewrite its own history. On the receiving end you get not only one lie — a lie which you could go on for the rest of your days — but you get a great number of lies, depending on how the political wind blows. And a people that no longer can believe anything cannot make up its mind. It is deprived not only of its capacity to act but also of its capacity to think and to judge. And with such a people you can then do what you please.
More convincing for the face, sure, but last I checked Schwarzenegger had much, much more body mass than in that video. Does anyone know if the technology for faking body shape (and accessories too maybe) is anywhere near as good as for faces yet?
I feel like what makes this one so good is how subtle it is. It took me a moment to go from, “wow, Hader really nailed the facial expressions,” to realizing what was going on.
In this case, the body is being entirely ignored by the autoencoder. The way it works is by first doing a machine vision pass to isolate just faces and process on that region for both sets of source imagery.
> Deepfakes (a portmanteau of "deep learning" and "fake"[1]) are media that take a person in an existing image or video and replace them with someone else's likeness using artificial neural networks.
"Likeness" refers to appearance in general, not just the face.
Might be because of the original, Zuck was widely criticized for his congressional testimony for his eyes looking weirdly bloodshot and generally looking very unnatural.
The article addresses this, the point is that someone new to the technology can make this one that's ok
"The video isn't perfect. It doesn't quite capture the full details of Data's face, and if you look closely you can see some artifacts around the edges.
Still, what's remarkable is that a neophyte like me can create fairly convincing video so quickly and for so little money. And there's every reason to think deepfake technology will continue to get better, faster, and cheaper in the coming years."
The central technique used in DeepFakes is fascinating. Initially I assumed they were using Generative Adversarial Networks (GANs). But — and someone can correct if I’m wrong — Deep Fakes use two Autoencoders.
So essentially you’re training a network how to compress an image down to a very tiny representation, and then uncompress it as accurately to the original as possible.
You train two of these: one for the original face, and one for the target face. Then, you compress with the “source” autoencoder, and then uncompress with the “target” autoencoder. And, voila, ‘source‘ face becomes ‘target’ face.
Makes sense. You want to boil down the face to some sort of abstract representation of movement of lips, face alignment etc. Then put in different parameters and have it be photorealistic on the other side. Could do wonders for video chat.
How do you guarantee that the two trained autoencoders speak the "same language", i.e. the code learned by the autoencoder of the original face gives a reasonable output when uncompressed by the target autoencoder?
This is a good question. I'm not sure which paper the parent comment is referencing - and in general, DeepFakes is a very general term for a variety of techniques including GANs. The problem you describe is called the alignment problem and it's studied in several areas of applied ml: translation, multi-modal learning, etc.
For example, the canonical way to train deep machine translation systems is to make use of large parallel corpora - large set of translation pairs. In the case where this data may not exist, for structurally similar languages, one approach is to learn unsupervised word embeddings independently (i.e. using word2vec) which only require monolingual data and to find a transformation that aligns the two spaces. In many cases, neural networks still struggle with this task. However, some work in the last few years has demonstrated that a few seed word-translations is all you need to apply simple algorithms that can learn a linear or simple nonlinear transformation that work pretty well!
I think you're right that most DeepFakes use Variational AutoEncoders (As described by the article) where the latent space is jointly distributed between the two domains, allowing for translation. For additional context: AutoEncoders are also frequently adversarially regularized so you're not wrong about GANs being involved. My understanding is that the most accurate implementations also have some manual feature engineering for more tractable problems like facial orientation.
The whole "deep fake" controversy is only going on because the elite politicians all have blackmail videos that are probably in the hands of people that will soon make them public and the media is preparing the big lie that these are just "deep fakes, nothing to see here, move along." Meanwhile, the truth is that these people actually did do the heinous things we all think they did.
Just look at what Prince Andrew tried to do: He was out whoring around and had photos taken--with the whore--and he has attempted to deny it citing that the photos are faked. But honestly, his own behavior and track record makes it clear that he is lying and that in all likelihood, he did in fact have sex with a 17 year old woman and all the allegations are true.
The worst part of all this is that Prince Andrew's transgressions are the ones they WANT you to see because they are the ones that are more easy for the public to write off (she was 17 and consenting) and it was bad but just his bad judgement or what have you.
My sense is that these "simple" cases are the are the tip of the iceberg, however. The ones they DON'T want you to see haven't been made public yet. And those are truly, pitchforks and torches, bad.
Can content providers not include a digital signature in the video metadata? Then you can authenticate the video against the original provider, a bit like the green padlock next to the URL bar in Chrome.
Even better (though I'm not sure this technology exists yet), some some kind of "rolling signature", available running along side the video in metadata, that a media player can use to validate the authenticity of the video at that point in time. Then you don't need the full video to be able to verify the source.
> In the long run, the larger risk may be that public attitudes swing too far in the opposite direction: that the possibility of deepfakes completely destroys public trust in video evidence. Certain politicians are already in the habit of dismissing media criticism as "fake news." That tactic will only become more effective as public awareness of deepfake technology grows.
Deepfakes themselves will not disrupt democracies or cause the much anticipated chaos. Deepfakes are in fact pointless for agitprop / disinfo campaigns:
What is fascinating (and uncommon) is, that the damage isn't delivered with any specific deepfake itself. But the mere awareness that the technology exists, and that they could _potentially_ be used, is enough to change our risk perception. Even if the ratio cheapfakes/deepfakes usage in actual disinfo campaigns remains tiny percentage, deepfakes make much better headlines. (in a similar way the infosec industry is obsessed with 0days - but most of the risks are coming from people clicking on links in email)
Maybe one day we will look at deepfakes like "art". If pictures and videos can be art, and if "all art is propaganda" (see Orwell), then deepfakes too should be considered art, no?
This work is just at the research stage right now and isn’t available as consumer software, but it probably won’t be long until similar services go public.
Thinking ahead - will Hollywood in 50 years time be actor based or digital rights based when your film is computer rendered and you pick your own actors that get digitally placed. Effectively reducing actors to DLC!
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[ 2.7 ms ] story [ 175 ms ] threadI understand the point of the article is “look how much I did with so little.” And it’s really good in terms of how much was done.
But the final deliverable isn’t at all convincing. Clickbait title.
ex - Bill Hader/Tom Cruise - https://www.youtube.com/watch?v=VWrhRBb-1Ig
I think one thing that could have helped the reporter is if they had reencoded the original Zuckerberg footage into something with a lower bitrate. The fine details/imperfections on his forehead contrasted with the lower fidelity of data's face provides a little too much contrast. It doesn't help that most of the source data for Data's face is lower quality, plus he has so much makeup pancaked on his face. I think if those factors were accounted for, the reporter's results would have been much more convincing even though he's a deepfake neophyte.
I'm NOT claiming that this is the case, I'm just saying we don't have a reason to believe why this can't be the case.
There really are two separate questions though:
- Can experts with a big budget create videos that even equally expert analysis can't tell from the real thing? (Maybe yes, maybe no. But it's hard.
- With modest skill and budget, are people increasingly able to create fake videos that stand up a cursory glance and can fool people as a result? (Absolutely--or at least we're getting close.)
But that already exists, DeepFake isn't a fundamental development for that. What is the "big thing" about deepfake is that we can imitate speeches of people in leadership positions. For this, we can get really really close; but it's unclear if it'll ever be realistic enough to be a problem in court cases, politics etc...
https://www.youtube.com/watch?v=Wm3squcz7Aw
Voice actor reads a poem in voices of famous people; his face gets swapped with the actor's face; the combination of voice and face makes it very believable.
The absolute autofellatio state of hype media these days. Ha-ha, look at how this autistic CEO looks like a robot, and shame on you for imagining what Charlize Theron looks like naked. Tune in next week where I try and fail to launch an ERC-token, and use that experience to argue that cryptocurrency adoption will be delayed.
I guess I always assumed the 'deep' in deepfake meant it was convincing, but upon further consideration it's probably just a nod to DNNs. Well played sir.
15 years ago that would've been science fiction, today it's a free gimmicky feature in an app running on commodity hardware. There are also apps that will smooth your skin or change the shape of your eyes in real time.
All these technologies are evolving at a ridiculously fast pace, I'm sure that a decade from now you'll be able to do a much more convincing fake in a fraction of the time. We're getting deeper and deeper into a post-truth world.
Also, I'm fascinated by the idea of using AI to detect the use of AI. How good will your deep fake have to be in order to fool a deep fake detection AI?
"deepfake news"
I can just hear people saying it now. Joking aside, and not taking in ANY ethical/unethical misuse considerations this software is capable of, it is really cool tech.
Sure, and that's part of the danger. Convincing deep fakes will be used to delegitimize mainstream news organizations, as with what happened with Dan Rather - a trusted source presented faked documents.
And we've been hit by tabloids, spam and so on before. None of that is new. Overwhelmed by content is/was/will be a problem that is solved very simply: people limit the distribution lanes they consume, and naturally establish "trust networks" and hierarchies.
Nyt didn't become "trusted" by accident. People aren't as dumb as you seem to think.
Anyways the problem is of distribution, not that a lie can be told. If we can't trust our distribution lanes to actually reflect the institutions we're trusting, then we can't establish our trust networks.
And this is a real problem: our distribution lanes are divorced now from our actual information distrubuters; medium, Facebook, Twitter, etc fuck around with our trust networks, randomly injecting their own bullshit into our feeds and messing around with feed-order based on non-trust metrics (eg money paid) such that they've become fairly unreliable.
And our classical trustable institutions have become less trustworthy, as they flounder about trying to make sense of the "digital age", and have so far done so in a pathetic fashion
When that network breaks down, you only need a single good lie to do the damage.
If 2004 news could be fooled by a fake that took a couple of minutes to make, I’m not that worried that today’s news is any better.
The people who care about the 'legitimacy' of a news organization are moderates who are passively engaged and are being rapidly driven to the margins. The 'objective truth' of the matter is less relevant than how it is received. Activist politics is en vogue thanks to the feelings of helplessness brought on by globalization, and if you're not an activist your views are not really an important part of the process anymore. You'll have to pick one of the two options that the activists come up with because they won't show up to vote for a centrist candidate. In either case, a moderate platform cannot win.
For the record, I feel the above situation is incredibly dystopian; but we're hardly the first country where pathos supersedes logos and ethos.
The only difference is today, they don't retire out of shame, they just keep on doing it, keeping viewership via emotional draw rather than rational news. Real news has been dead since that incident in my view. It's mostly state propaganda, regardless of party.
This is, itself, "fake news". I can't find any indication that other mainstream media outlets defend the documents "to this day". The reporting largely seems to be "certainly smells like bullshit, and we can point to specific issues with them that seem to support that".
https://www.nytimes.com/2004/09/13/opinion/those-discredited... cites a wide variety of news organizations looking into them and finding problems, stating "When the mainstream press checked the sources mentioned or ignored by '60 Minutes II,' the story came apart." and noting Newsweek specifically calling them "discredited".
And what about when this happens at a state-sponsored level (This is absolutely already in development, if it hasn’t happened already...). “Did you see that Fox News exclusive video leaked from the Bernie Sanders campaign? Yeah he was holding a private dinner for a bunch of Billionaires. They say they got it from some Russian oligarch he invited. So much for grass roots change, I think I’ll just stay home this Election Day.” Or the corollary: “That smoking-gun tape the Do-Nothing Dems have of me at Putin’s personal sex trafficking center, where the two of us are laughing about having Epstein take the hit? Fake news! They’re called deepfakes, and they make these just absolutely incredible fake videos. Not real at all though. Only trust what the Government-sanctioned media says!”
As per your other point, given the GANs that are used to make these are precisely a deep fake AI fooling a deep fake detection AI, aren’t we already there? Further, when the government is making the generator, a privately trained discriminator has no chance. How would you even train that? Get the government to give you a bunch of generated fake media so that you can develop a really spot-on model? I don’t think so.
Two predictions:
Deepfakes will play a roll in the 2020 election.
Deepfakes will play a roll in every election thereafter.
If this doesn’t concern you, I don’t know what would. The thing with the “post-truth world” is that once people think we’re in it, we are.
Long have documents and news been the subject of fraud. And for a few decades photo alterations have been common. Now we are adding video to the list.
But there is nothing new about the faking of libelous material (eg Killian documents 2004)
How many people do you think actually read those “Killian documents”? How many people do you think a state-sponsored social media campaign built on the most accessible media would reach?
"With software there are only two outcomes: either the users control the program or the program controls the users. If the program is not under user control, and the developer controls everything, then the program is an instrument of unjust power, applied by the powers that be."
Deepfakes are just a continuation of "fake news" (formerly known as propaganda), and the end outcome is we either succumb to those who use it, or adapt - filtering out the bs isn't easy, but it's not an insurmountable task, either.
It's won't upend the world, but we are losing a hugely helpful tool that has been relied upon for 60 years.
The technology to fake paper ballots is trivial, but they still (mostly) work fine for elections, because we've developed strict rules for how they need to be handled in order to retain credibility.
Having a vague description of a need is not the same as having a workable solution, it doesn't even mean being on the way to it.
But recently I read "Tlön, Uqbar, Orbis Tertius", and I thought that the point Borges was making could be easily described as critique of "fake-news post-realism of today", except it was 80 years ago. And while the notion of this problem not being new at first seemed weird to me, eventually I figured this is pretty natural: while 80 (or 800 for that matter) years ago there wasn't any such tools to manipulate information on that scale, nobody had the access to information on that scale in the first place. So anyone could be fooled by more powerful actor anyway. Offensive tools of any time are roughly the same as the defensive tools.
It's just that these 20 years at the turn of the century were somewhat the sweet spot, when we had this "Internet for people like us", so it was us who was fooling the less knowledgeable people, while keeping the belief that we are relatively safe from being maleficently disinformed by somebody else. And now we can clearly see it's not necessarily the case anymore, ao it feels like something new.
But it really isn't. As always.
The best generator and the best detector are actually part of the same model! If you create a better detector, you are making the generator better at the same time so you have not accomplished anything.
"GANs are a clever way of training a generative model by framing the problem as a supervised learning problem with two sub-models: the generator model that we train to generate new examples, and the discriminator model that tries to classify examples as either real (from the domain) or fake (generated). The two models are trained together in a zero-sum game, adversarial, until the discriminator model is fooled about half the time, meaning the generator model is generating plausible examples."
https://machinelearningmastery.com/what-are-generative-adver...
And it does seem that the human-visible weaknesses of many currently published deepfake examples are those that would be hard for the current discriminator architectures to detect, not those which would be harder to generate than any other part of the fake.
The film "Mr. Smith Goes to Washington" came out in 1939. It should be mandatory viewing.
1) The researched human behavior where "1000 lies must be equal to 1 truth".
https://www.researchgate.net/publication/256486791_Credibili...
2) Monopolizing the information stream: the attention grabbing effectiveness of deepfake videos to convey fake messages and its novelty incentive to share them on social media, added to the fear-of-missing-out they generate on viewers and the fact that "the effort required to refute b* is 10 times greater than the effort required to produce it":
https://www.telegraphindia.com/india/social-media-fatigue-an...
3) voter apathy caused by news fatigue due to the sheer volume of fake news, to which deepfake adds a new vector:
https://www.nytimes.com/2019/11/18/us/polls-media-fake-news....,
https://www.datadriveninvestor.com/2019/07/04/chronicle-fati...
4) A majority of youngsters can't really spot (or care) about fake anymore:
https://qz.com/1750839/most-young-2020-us-election-voters-ca...
[1]: https://www.theverge.com/2019/10/22/20927521/snap-growth-ear...
None of that actually happened because people learned to be skeptical, and to care about who took the photo, the chain of custody, and the controls to prevent digital alteration.
Maybe we need something similar but more rigorous for video. The camera itself could encode a PKI signature in every frame of the original. If subsequent edits preserve frames as is, then the viewer could determine how many frames were cut or duplicated.
If subsequent edits crop, recolor or otherwise alter the frames, that editor could encode its own digital signature so the viewer could judge how much to trust their edits.
Is there evidence that deepfake videos will be worse than photos? My (naive) sense is that even for an AI, editing a photo will always be easier than editing a video with sound.
If Photoshop and deep-fake images aren't a problem, shouldn't we be less concerned about video?
This may be true in courts of law, but it absolutely is not when it comes to general public consumption of pictures.
The 9/11 Tourist Guy picture that duped a lot of people 18 years ago looks like a ridiculous MS paint edit today. https://en.wikipedia.org/wiki/Tourist_guy
Likewise, a deepfake is worth a thousand lies.
Photo editing has been used pretty much since the beginning of mainstream photography. You should never "trust" pictures for anything serious if you don't have absolute trust in the source.
Besides it's one thing to edit a still image and a whole other to forge a long video, complete with audio. Look at those movies these past few years using 3D models to insert younger versions of actors (Terminator and Star Wars come to mind). They must have invested millions into it, they have very talented artists and it's pretty good but it's still quite easy to spot the fakeness of it.
The Daily Mail was at it from around WW1, perhaps earlier. Though their main WW1 fake was, of course, the cadaver factories. Surprisingly the Times bought that tale too.
And why doesn't the government keep track of the cameras and security keys so they can trace back any images they do not approve of?
Are we though? Or is it just becoming much more obvious the limitations of relying on the media in general. This very well might lead to a better understanding of truth, and our personal responsibility in understanding it.
At the very least, it's not a foregone conclusion that this will lead to worse outcomes than what we have today. It might be what tips us in a new and better direction.
What we'll continue to see are rising sects of flat-earthers, anti-vaxxers, cultists, polarization and deniying of anything not-in-my-bubble, a complete lack of trust in journalism and media, and futile attempts of fact-checking while we're all drowning in fake news shared endlessy on unsuspecting users. It takes a lot of effort to show something was manipulated digitally, and you'll have to fact-check by yourself, that doesn't scale at all.
The fact that we're more aware of flat-earthers today, is probably a good thing too. I'm not 100% sure that there are more of them today than before, or if they're just more noticeable. But in either case, we should be very careful to draw too many conclusions when we look around today because we're living in a time of great transition. We're basically in our teenage years of this technology.
Just as you shouldn't judge an adult by who he was at 14, I don't think we should assume we know what the adult internet will look like because we see some acne on it today.
Even this is too simple. Many people have lived under propaganda regimes, yes, many have bought into them, and many people have seen through them.
Each new wave of information technology provides new ways to “pull the wool” over peoples’ eyes.
And though a propaganda machine has power... like all things it creates and equal an opposite power that eventually destroys it. The question for individuals is only: where am I in the cycle, how long will this cycle last, and what is my role to play?
Anywhere you have trust, there's a potential for abuse. A seemingly natural response to abuse of trust is to find a lapse in the victim's vigilance and start strapping on your own armor. I listened to a podcast this fall (sorry, I don't recall for certain--my best guess is that it was peter pomerantsev on Ezra Klein's podcast) where the guest suggests that some institutions/relations (like markets) depend on trust to produce value and may be undermined or degraded if enough participants take an individualist caveat emptor approach.
It is hard to know, in a complex adaptive system, what new equilibria will emerge downstream from a big disruption. We certainly could emerge through the other side with better epistemologies. But I don't see it as a given. Thinking is hard. Proving anything is harder. Skepticism can be good (and I suspect we need more--though I don't think it's terribly well distributed or applied at the moment...), but it's also easy; it requires no trust, knowledge, thinking, rigor, logic, or proof.
So, I'm troubled by the possibility we'll dig ourselves into a deep world-shrinking skepticism (a callous) of anything we didn't/can't personally experience. It can be well-founded on real abuses of trust. It may even be the sum of individual rational choices.
Neither would necessarily keep it from unmooring things we mistook for solid ground. And, when someone finally notices one drifting, there may not be enough trust left to agree on fundamentals like: is it adrift? is that a problem? was it ever tied down? is there anything we can do? should we wait for a bit to see if it drifts closer first? should we act?
But i'm terrified of the current loud support toward censorship and authoritarian suppression of incorrect ideas. We have a lot of historical evidence of just how bloody that always turns out. So I choose to believe in the power of openness and competition of ideas.
As others have posted above, we will never have a time where it's possible or desirable for each of us to validate the truth of every claim, so that means we will have to find trustworthy arbiters of truth. I think that this should happen by people showing they are trustworthy and earning respect, rather than using authoritarian control to shut down those with differing ideas.
Much of the media today has lost such respect, and deservedly so. You can not fix this by suppression of free-speech, but only by creating honest organizations that aren't afraid to respectfully show the ideas of those who see things differently -- even if it's just refute them. Organizations that _trust_ the viewer to decide between fairly articulated positions.
The contempt for our fellow man when we say that bad ideas must never see the light of day or enjoy the same platform as government-approved ideas is a deeply paternalistic and ultimately anti democratic idea. It's elitism at its worst.
(For example, we need to be able to trust that they have a sincere opinion and aren't paid shills for a corporate lobby on a PR mission to waste our time, emotional energy, column-inches, and attention.)
If you feel a growing sense of dread as it retreats, it's a good time to consider whether you know others who have expressed a similar sense of dread that other things in our world have come unmoored, and whether they could use some help keeping them tied down.
Even society is shown to be untrustworthy, and the social processes of science.
Thus some reactionaries want to replace trust with authority. Or markets, which is another name for social proof, but with much less transparency.
Ultimately the other parts of trust are verification and reputation, which are both not unassailable. (Sybil style attacks, bribery, institutional and social biases.)
But, our saving grace might be simpler: cooperation without trust is possible and might be as efficient if things get bad enough.
The thing is, people do not check information that matches their viewpoint for validity. Because being wrong feels bad.
Maybe I’m being paranoid but it seems that the public is being conditioned to believe deepfakes are so good prior to a certain cache of video recordings being made public
> You have to remember that in democratic societies citizens talking with each other is very important. We've lost a lot of that with the mass media. Now we have an opportunity for citizens to create their own communications with each other. So when these big deals with the big companies and the big governments carve up this new territory, I feel it's very important that we keep a kind of "social green belt", that we keep the ability for citizens to talk amongst each other.
-- Howard Rheingold, https://www.youtube.com/watch?v=U_o8gerare0&t=22m14s
> If everybody always lies to you, the consequence is not that you believe the lies, but rather that nobody believes anything any longer. This is because lies, by their very nature, have to be changed, and a lying government has constantly to rewrite its own history. On the receiving end you get not only one lie — a lie which you could go on for the rest of your days — but you get a great number of lies, depending on how the political wind blows. And a people that no longer can believe anything cannot make up its mind. It is deprived not only of its capacity to act but also of its capacity to think and to judge. And with such a people you can then do what you please.
-- Hannah Arendt, Interview with Roger Errera (1974) https://www.nybooks.com/articles/1978/10/26/hannah-arendt-fr...
https://www.youtube.com/watch?v=bPhUhypV27w
In this case, the body is being entirely ignored by the autoencoder. The way it works is by first doing a machine vision pass to isolate just faces and process on that region for both sets of source imagery.
Uh.. That's what a DeepFake is? Look up the definition.
> Deepfakes (a portmanteau of "deep learning" and "fake"[1]) are media that take a person in an existing image or video and replace them with someone else's likeness using artificial neural networks.
"Likeness" refers to appearance in general, not just the face.
Still, what's remarkable is that a neophyte like me can create fairly convincing video so quickly and for so little money. And there's every reason to think deepfake technology will continue to get better, faster, and cheaper in the coming years."
So essentially you’re training a network how to compress an image down to a very tiny representation, and then uncompress it as accurately to the original as possible.
You train two of these: one for the original face, and one for the target face. Then, you compress with the “source” autoencoder, and then uncompress with the “target” autoencoder. And, voila, ‘source‘ face becomes ‘target’ face.
For example, the canonical way to train deep machine translation systems is to make use of large parallel corpora - large set of translation pairs. In the case where this data may not exist, for structurally similar languages, one approach is to learn unsupervised word embeddings independently (i.e. using word2vec) which only require monolingual data and to find a transformation that aligns the two spaces. In many cases, neural networks still struggle with this task. However, some work in the last few years has demonstrated that a few seed word-translations is all you need to apply simple algorithms that can learn a linear or simple nonlinear transformation that work pretty well!
[1] Here is a method that proposes locally linear transformation maps for alignment: http://nakashole.com/papers/2018-emnlp-norm.pdf
One of my favorite related papers: https://arxiv.org/pdf/1703.00848.pdf
Just look at what Prince Andrew tried to do: He was out whoring around and had photos taken--with the whore--and he has attempted to deny it citing that the photos are faked. But honestly, his own behavior and track record makes it clear that he is lying and that in all likelihood, he did in fact have sex with a 17 year old woman and all the allegations are true.
The worst part of all this is that Prince Andrew's transgressions are the ones they WANT you to see because they are the ones that are more easy for the public to write off (she was 17 and consenting) and it was bad but just his bad judgement or what have you.
My sense is that these "simple" cases are the are the tip of the iceberg, however. The ones they DON'T want you to see haven't been made public yet. And those are truly, pitchforks and torches, bad.
Even better (though I'm not sure this technology exists yet), some some kind of "rolling signature", available running along side the video in metadata, that a media player can use to validate the authenticity of the video at that point in time. Then you don't need the full video to be able to verify the source.
But for now deepfakes seem like a 2018 meme that died out.
> In the long run, the larger risk may be that public attitudes swing too far in the opposite direction: that the possibility of deepfakes completely destroys public trust in video evidence. Certain politicians are already in the habit of dismissing media criticism as "fake news." That tactic will only become more effective as public awareness of deepfake technology grows.
Deepfakes themselves will not disrupt democracies or cause the much anticipated chaos. Deepfakes are in fact pointless for agitprop / disinfo campaigns:
"cheapfakes beat deepfakes" --@thegrugq
https://twitter.com/thegrugq/status/1206404680223358976
https://medium.com/@thegrugq/cheap-fakes-beat-deep-fakes-b1a...
What is fascinating (and uncommon) is, that the damage isn't delivered with any specific deepfake itself. But the mere awareness that the technology exists, and that they could _potentially_ be used, is enough to change our risk perception. Even if the ratio cheapfakes/deepfakes usage in actual disinfo campaigns remains tiny percentage, deepfakes make much better headlines. (in a similar way the infosec industry is obsessed with 0days - but most of the risks are coming from people clicking on links in email)
Maybe one day we will look at deepfakes like "art". If pictures and videos can be art, and if "all art is propaganda" (see Orwell), then deepfakes too should be considered art, no?
Remember, technology to fake voices has already be done. https://www.youtube.com/watch?v=I3l4XLZ59iw
Certainly interesting times ahead.