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Deepdiving into deepfakes to uncover the ramifications of artificial influence
on culture and branding today and into the future. 




Seeing Is No Longer Believing

In the past year, machine learning powered videos known as “deepfakes” are spreading online, misleading people with their life-like renderings. From fun filters to deeply augmented content, it’s not just the rise in adoption of this technology that warrants attention but its rapid sophistication…

“Fake news.” “Don’t trust what you read.” “Beware of clickbait.” The line between truth and fiction has never been more blurred, or faced as much cultural scrutiny. Luckily we’ve always had video evidence to fall back on – after all, if it’s caught on camera it actually happened…right? Well... not exactly, not any more at least.

What Are Deepfakes?

Deepfakes are videos, images and audio that use artificial intelligence to produce incredibly realistic fakes, predominantly used to swap faces on different bodies.

Deepfakes can get very technical, very quickly. Rather than go too deep, we have the option to read further if you wish via our GEEK OUT MORE buttons.






Video Rewrite program launched, using AI to change mouthing of words



Ian Goodfellow invents ‘GAN’ technology, creating AI-generated faces​



Face2Face program allows facial expressions to be transferred between videos​


NOV 2017

Reddit r/deepfakes created, with deepfake porn surfacing on platform  ​


DEC 2017

Vice publishes story about a pornographic deepfake of Gal Godot​


FEB 2018

Reddit bans r/deepfakes thread due to pornography, a rapidly increasing issue​


JAN 2018

Buzzfeed tweets fake Obama & Jordan Peele video in the first truly viral deepfake


APR 2018

FakeApp launched. Users deepfake Nick Cage into other popular films​


AUG 2018

University of Berkley creates fake dancing AI app, expanding to full body fakes​


FEB 2019

AI generates expressive faces, programmers use Opensource software to improve code


SEP 2019

Google releases 3,000 deepfake videos in an open-source database to build detection tools​


JUN 2019

Mark Zuckerberg gets deepfaked using CannyAI’s ‘video dialogue replacement’ tech​


SEP 2019

Chinese app Zao goes viral; creates celebrity deepfakes in seconds​


JAN 2020

ByteDance and TikTok secretly build a deepfake maker​ this space...


APRIL 2020

Budweiser uses deepfakes to recreate a famous 20 year old ad


JUN 2020

Facebook’s Deepfake Detection challenge yields 65.18% accuracy result​



Deepfakes are evolving at a different pace to other technologies. The speed and development of AI powered content will exponentially increase – at a rate never seen before in history.

Typically, any developments in computing power follow a formula known as Moore’s Law. This theory has been around since the 70s and says that the overall processing power for computers will double every two years at dramatically reduced costs. However because of machine learning, Moore’s Law is no longer applying. Instead, graphic processing technology (the kind used to power deepfakes) follows “supercharged” laws of change.  

In 2019, there was 100% growth in the use of deepfake technology. The growth is possible because programmers collaborate to improve the original ‘Faceswap’ code. Software platforms like GitHub allows users to freely download the code and improve it, driving both efficiencies and improvements in quality of fake videos. 


Quicker Than You Think

If you asked this 2 years ago, the answer would’ve been a decade at least. Deepfakes aren’t like an Instagram filter. You need high powered computer processing power and hundreds of images to make one – which is why celebrity faces have been so popular so far. But entrepreneurial programmers are changing this – offering their services to create hyper-realistic splices for as little as $2.99 in under 48hrs. More advanced marketplace services allow users to pay between $30-50 for a higher quality deepfake, including voice cloning for around $10 per 50 words generated.



Also, as we speak apps like Doublicat are gaining cultural velocity. Outputs from this tech are shared further down.


While the price is low, you still need roughly 250 images of a specific subject which is why we aren’t seeing high quality deepfakes of your mates all over the internet yet. That said, as this technology develops the number of source images required will decrease, allowing greater access for everyday internet users.

But as with most things, if we look to the East, we can see the future penetration and popularity of this technology. In September last year a Chinese app called Zao was launched. Zao allowed users to deepfake their face into film clips and movie scenes in around eight seconds. Rather than requiring hundreds of images, the app simply requires a shot of your face which can be seamlessly inserted upon a selection of celebrity bodies. The result? An almost instant rendering of highly shareable deepfake memes. Within a week, Zao became one of the most downloaded apps in China, prompting many to revisit their predictions about the speed by which deepfake technology is progressing.

“Soon, it’s going to get to the point where there is no way that we can actually detect [deepfakes] anymore”  Hao Li - an associate professor of computer science at the University of Southern California.



Another Moral Panic

With the arrival of new technology often comes a wave of hysteria and panic. Apocalyptic claims of destroyed democracy and loss of freedom are the common catchcries of panicked consumers. It’s safe to say deepfakes have not been immune to this. However, whilst there may be some cause for concern, it can be argued the impact to everyday life will be minute, if anything. As Human Computer Interface researcher at The University of Sydney Mike Seymour notes, society does adapt and move forward:


“People ducked at trains in movies when it first happened...and the world didn’t collapse when Photoshop came out”


Industry developers and observers like Seymour claim that we instead need to adapt societal frameworks of checks and balances to embrace new technology rather than simply concede that we are all doomed.


Get Out Of Jail Free

The harm of deepfakes is less about the video footage, rather, the existence of deep fakes altogether. Celebrities and politicians have often been caught out telling the public one thing, only to have ‘video evidence’ come back to prove them wrong. However in the era of “fake content” people have the ability to claim falsehood, even if the case is not magnified. Take for example the below clip of Donald Trump, which shows him confidently classifying the media’s replaying of claims he made about the coronavirus as fake news.

In this instance, the media were able to use direct footage of him to prove him wrong. But if you muddy the waters around edited footage with high-quality deepfake content you accelerate plausible deniability. An increase in “fake videos” only justifies the premise that news and information “isn’t real” allowing politicians, celebrities, and other public figures to deny footage as evidence of any wrongdoing. What was once an empty threat suddenly becomes plausible as our eyes are physically unable to distinguish real and fake evidence, increasing widespread scepticism.


The Illusionary Truth Effect

Videos are more shareable than a news article, and more easily scrolled past without much scrutiny. More frequent production and dissemination of deepfakes will drive the illusory truth effect, that is, a lie becomes a truth the more you say it. In the case of deepfakes, a fake video becomes truth the more times that it is viewed, because for every 9 people that realise it is a fake, there is 1 who believes it to be true. Add the multiplier effect of the internet, and deepfakes very quickly become the most efficient way to spread misinformation. Even if footage is eventually discredited, its impact still stands.




Almost as soon as the technology was available, researchers at The University of Washington produced an infamous series of edited speeches by Barrack Obama to prove the threat of disinformation. Jordan Peele teamed up with Buzzfeed to produce a similar video of Obama saying that President Trump was a “total and complete dipshit.” Experts have identified deepfakes as a key threat to upcoming US elections and more broadly in the spread of misinformation (e.g. Climate change deniers, anti-vaxxers etc), placing a greater onus on verifying ‘real’ footage and sources.

Interestingly, deepfakes have already been used in an Indian election. In February, the Bharatiya Janata Party (BJP) partnered with a political communications firm to use deepfakes to reach different linguistic voter bases. With hundreds of different dialects in India, deepfake technology allowed the party to scale campaign efforts on a whole new level, even when the candidate did not speak the local language. They produced multiple assets, distributed across almost 6,000 Whatsapp groups, reaching close to 15 million people. This example proves the scalability of deepfake technology, especially in combination with dark social messaging, and the potential for falsified footage to spread.

“By using lookalike stand-ins, or relabeling footage of one event as another, media creators can easily manipulate an audience’s interpretations. Britt Paris & Joan Donovan, Deepfakes and Cheap Fakes  



Preventing Future Harm

Deepfakes are not some underground threat. Silicon Valley is clearly alarmed. Tech juggernauts like Google, Facebook and Twitter are investing millions of dollars and resource in proactively seeking solutions to the negatives of a deepfake future. Beyond brand safety concerns, they see defending the trustworthiness of digital platforms as a priority to help their users to see beyond what their eyes tell them (and protect their ad revenue). As part of their efforts Google recently announced that they would release 3,000 deepfake images for detection training, with many Australian journalists already receiving training from Google on how to ‘test’ if videos show signs of being fabricated.

In January, Facebook followed suit, banning all deepfakes bar those intended for parody. Beyond brand safety concerns, Facebook and Google must prioritise defending the trustworthiness of digital platforms to protect their ad revenue and help their users to see beyond what their eyes tell them. Rest assured, it's got everyone's attention and solutions will come soon enough.


“Unless you are breaking stuff, you aren’t moving fast enough”


While Mark Zuckerberg was famously quoted about destruction as the key to success, Facebook has clearly seen deepfakes are a step too far. In January, the company announced that it was putting US $10M to fund a deepfake detection challenge. So far it hasn't been smooth sailing; they revealed last month the resulting technology was only able to detect deepfakes with an accuracy of 65%, with researchers describing the issue as an “unsolved problem.”


Navigating the negative effects of trust-dilution and IP hijacking are going to become much larger industry conversations. However, whilst there are many negatives to overcome as deepfakes penetrate culture, there are equal and opposite opportunities for brands to connect with their consumers better than ever before.

From streamlining production costs via enhanced editing capabilities (avoiding that painful 43rd take on set and reinvesting back into amplification) to artificial influencers, new-wave UGC and curated cultural commerce the potential for brands moving forward is incredible.  

Artificial Influencers

Consumers are already aware that the internet breeds altered realities. The panic around deepfakes often ignores the enduring scepticism of internet imagery. In fact, some brands have acknowledged this and chosen to lean into ‘fake’ rather than distance themselves. Examples span from KFC creating their own virtual Colonel Sanders, generated to poke fun at influencers on Instagram while Balmain released a campaign modelled entirely by virtual models.


“Social media, to date, has largely been the domain of real humans being fake. But Avatars are the future of storytelling.”


Virtual influencers aren’t an entirely new concept. In 1996, a Japanese virtual pop star called Kyoko Date burst onto the scene with her own pop single. Following the success of Japan’s virtual idols, China has created its own raft of virtual pop stars including Luo Tianyi who sells concert tickets worth over AUD$300, and China’s virtual idol industry is expected to grow to $230 million by 2023.   
Many anime and vocaloid influencers thrive on Bilibili - a Chinese entertainment platform known for its animation content. In 2018-19, Nescafe partnered with animated idol  Luo Tianyi to promote Nescafe drinks, launching a branded song and customised messages based on location, weather, mood, horoscope and time of the day. 

While such animated influencers lean into fantasy rather than realism, their commercial use normalises the presence of artificial influence. More life-like virtual influencers were used during Shanghai’s first all-online Fashion week last year, including TMall’s Aimee who modelled Prada and Miu Miu products.  

TMall’s virtual influencer, Aimee. Image: RADII China

In this sense, deepfakes could herald a flood of new ‘remixed’ content; presenting entirely new ways for audiences to challenge, recreate and share cultural moments. Creators such as Cntrl Alt Face herald a new wave of commentary and creativity, where celebrities and film assets are re-shared and re-made. In a world where a Twitter handle is a voice for brands, the potential around virtual influence is endless. Going from some characters brought to life by text to totally malleable, interactive and lifelike brand ambassadors is a genuine reality.

Freed Up By Fakes

In the world of deepfakes, intellectual property is more easily created, remixed and shared. Creative agencies need not pay full price for talent if talent can be artificially cast. Already there are companies such as CannyAI which can transform videos into any language and any new dialogue.

This doesn't just power the future, but helps bring back the past. By remixing old assets, brands can re-use shoots from other times. Budweiser did this during the peak of COVID quarantine, using its iconic 1990 advert to make it more relevant to lockdown. Similarly in May, ESPN recreated a piece of 1998 SportsCenter footage to “predict” The Last Dance’s existence 22 years into the future.

Yet for unowned assets, deepfakes raise new issues for copyright, particularly in the context of re-using footage of deceased actors or talent. Last year, the Dali Museum in Florida brought the surrealist artist back to life from hundreds of photographs and 1,000 hours of footage.


“I believe in general in death, but in the death of Dali, absolutely not.”

Salvador Dali

During a pandemic where full shoots shut down, firms such as CannyAI can offer their services to allow ads and content to be made without a full scale shoot. If talent does not pronounce the brand name correctly, deepfaked vision and audio can fix the problem. This heralds fascinating new territory for production costs, talent pricing and usage rights.

Customised Content

With Netflix already playing with interactive storytelling and choose-your-own-adventure style shows, we can also envisage a world where deepfakes allow consumers to choose the actor they want cast in a production. Similarly, celebrity endorsements could be more accessible to brands, without the fees. This could reduce trust in celebrity endorsements altogether, as human faces and bodies become easily transferrable creative capital.

Imagine logging into Netflix and seeing this

Increased scepticism will potentially limit smaller brands from deriving value from celebrity endorsements, as consumers become familiar with feigned use and only trust existing sponsorships from larger brands who have built capital in an era before fakes. It also means brands will need to be wary of endorsement hacks, with consumers easily generating fake versions of their content using undesirable spokespersons. Finally, brands can take passive virtual influencers and create more life-like brand advocates. Rather than a 24 year old social media intern moderating comments on the Coles Facebook page, the supermarket could use actual deepfaked personas to speak to consumers and engage in community management, literally bringing the brand’s “voice” to life.

Player 1 Enters The Game

In gaming, deepfake technology has obvious and exciting applications. Rather than spend 4 hours building out your own avatar, the technology will allow you to simply insert yourself directly into the game. Just this month, leading game creation platform Unreal Engine rolled out a tool that enables developers to stream high-quality animation in real time from an iPhone directly onto characters in Unreal Engine. The app tracks a performer’s face, transmitting face data directly to Unreal Engine. Imagine the exciting potential for both gaming and cinema.  

New Wave UGC

As deepfake technology becomes more accessible to the masses, it’s not hard to imagine its adoption by fandom communities who are fluent when it comes to remixing culture. This allows consumers greater agency to input their own casting decisions, scripting and messaging, enhancing UGC and allowing consumers to actively contribute to a brand’s story. In some cases, this wave of UGC could add value to brands, much like the NSFW unofficial Skittles ad which was created in jest and without approval, yet was circulated on industry press and YouTube.

In a social context, deepfakes allow complete personalisation of pop culture content – increasing communication through imagery and video instead of words. Recently, an app called Doublicat has been making waves across social media. Rather than send a celebratory GIF of Beyonce dancing into the group chat, you can deepfake yourself into Beyoncé’s body, reducing the reliance on existing GIF/bitmoji/memoji databases and software. We are about to witness a stage in cultural history where deepfake technology becomes accessible to users in the same way that Bitmojis and GIPHY is integrated into messaging. This will both enhance and normalise the already blurred lines between real and fake images on social.  

Our Panellists, Deepfaked

Tegan Jones deepfaked as Jason Statham

Mike Seymour deepfaked as Jennifer Lopez

Sam Geer deepfaked as Dua Lipa

Fans are already actively giving feedback on content, exemplified most recently by their engagement with the latest Lion King film. A fan recreated portions of the film's animation, arguing that the official CGI was too lifelike and destroyed the emotional subtlety of the original cartoon. Similarly, when Paramount released the trailer for its upcoming live action/CGI version of Sonic The Hedgehog in April last year, fans were both amused and outraged at the depiction of their beloved cartoon’s eyes and fur, prompting one fan to produce their own take on Sega’s iconic hedgehog and received significantly more praise and support than the original interpretation. As a result, Paramount revised their creation, delaying the film’s release date by three months.


“...Fan fiction is a way of the culture repairing the damage done in a system where contemporary myths are owned by corporations instead of owned by the folk.”

henry jenkins, media scholar 1997


1. For Brands

As deepfake technology becomes a realistic tool in creative development, brands will be able to overcome casting limitations due to geographic distance, high talent fees, or calendar availabilities. As the talent model extends into image licencing, brands will have access to high-power talent otherwise deemed impossible. This will lend further trust and credibility to brands as long as they, as the talent are not overexposed. This could see brands bringing back legacy assets and even recasting old ambassadors. While trust and transparency will be important areas to watch out for, the opportunities around personalised content and opportunities for consumer participation are endless.

2. For Consumers

Deepfakes herald a new era of remix culture. This eases the total creative control of Hollywood and production houses, by empowering fans to re-create content as they already do through fan fiction. It will also take personalisation to a whole new level – as already seen with Doublicat app. GIFs and meme culture will no longer be an exercise in sharing the same intellectual property. Digital identities (including gaming avatars) will become increasingly synonymous with real life identities while artificial influencers will continue to occupy the same newsfeed as “real” human influencers.

3. For Culture

Deepfakes allow commentators to radically challenge perceptions of authority and power, with ‘real’ looking footage that demands attention and interrogation. Already we’ve seen deepfakes employed as a tool for debate and discussion through parody sketches on talk shows.

On the other hand, deep fakes will allow skeptics to shout louder: for those with the intent of spreading misinformation, deepfakes provide a way to accelerate plausible deniability. This could eventually see video and audio evidence increasingly discredited, or at least until society introduces new checks and balances to understand limits of what can be altered. Leaked footage can be more easily dismissed as ‘fake’ while real fakes have a greater chance of influencing audiences.

Many Thanks to our Contributors and Partners

Adnews, Publishing Partner

Mike Seymour, Researcher, University of Sydney

Tegan Jones, Editor, Gizmodo

Sam Geer, Managing Director, Initiative

Pralay Bajaria, Addressable Activation Executive, Initiative

Camille Gray, Strategist, Initiative

Christopher Colter, Chief Strategy Officer, Initiative

Joshua Hogg, Strategy Manager, Initiative

Renae Joseph, Group Operations Director, Initiative



Sam Geer, Managing Director
M +61 478 034 849


Sarah James, Managing Director
M +61 412 341 367


Luke O'Sullivan, Managing Director
M +61 412 341 367