Even if you don’t know what a deepfake is, you’ve probably encountered them. The next step in altering media, deepfakes are blurring the line between fiction and reality. While altered or fake images aren’t anything new, deepfakes take it to a whole new level, utilizing artificial intelligence (AI) to create images, videos, and audio that appear real – but aren’t.

And they’re making an impact. From Wired to Cosmopolitan, those are just the major publications that have written about deepfakes this week. Deepfakes have been an extremely active conversation topic since their rise to public prominence in 2017, and they’re growing online. The number of deepfakes online increased over 300% from October 2019 to June 2020, and it’s likely that this number has only continued to grow.

In 2021, using only a few images of a person’s face and publicly available software, it is possible to insert a person’s likeness into a video and show them saying or doing almost anything, even if they haven’t. It’s becoming more and more difficult to determine the legitimacy of deepfakes, increasing the potential for misrepresentation and misinformation.

Your reputation stems from what is out there about you, and how others interpret what they see. With the growing number of deepfakes online, people’s opinions can be impacted by events or moments that haven’t even happened. Even if the deepfake is eventually (or quickly) revealed, the initial impact on the audience can be difficult to recover from.

As the prevalence of deepfakes grows, the importance of spreading awareness and passing legislation around them is growing, too. The way that deepfakes can alter reality influences public perception, privacy, and your reputation.

Here, we take a closer look at what a deepfake is, how to spot them, and how they are changing our online world.

What is a deepfake?

Deepfakes – a phrase combining “deep learning” and “fake” – are synthetic media in which a person in an existing image, video, or recording is replaced with someone else’s likeness. Unlike Photoshop or other forms of media alteration, deepfakes leverage machine learning and AI to manipulate media and create content with a high potential for deception. Put a bit more simply: a deepfake is a video, image, or recording that seems real, but isn’t.

The most common examples of deepfakes include:

• face swapping, or replacing one person’s face with another,
• lip-syncing, or replacing the original audio of a video with different audio, and manipulating the video to make the speaker’s lips sync with the new audio,
• and full-body animation, or replacing an image of one person’s body with another, creating the appearance of that person acting however the person in the original video did.

How to Spot a Deepfake

While deepfakes are created to be convincing, they aren’t quite airtight. While AI detection tools are out there to spot deepfakes, there are several indicators that can help you identify a deepfake on your own, such as inconsistent lighting, blurriness around the face or hair, mismatched audio, or something off about the eyes, such as too much or too little blinking.

In fact, when it comes to determining whether or not something is a deepfake, the eyes may be the most valuable factor. In October 2020, a paper was published by a team from the University of Buffalo stating that their technique of using reflections of light in the eyes had a high success rate in detecting deepfakes, even without the use of AI detection tools. In an article published just this week, Syfy Wire noted that eyes may be users’ best chance to identify a deepfake or AI generated image.

Another way of identifying deepfakes is by identifying the origin of the video or media and requiring verification before they will be shown on various social media platforms, or including a watermark. Though this is not strictly identifying deepfakes, the hope is that the verification requirement would reduce the spread of possibly harmful deepfake media.

However, some deepfakes are easier to spot than others, and deepfake technology is iterative, and changing quickly. As reports of the weaknesses of deepfakes come out, more effort is put into remedying those particular issues, requiring deepfake detection to change as well. As a result, the majority of academic research around deepfakes is centered around detection.

Where did deepfakes start?

Of course, the manipulation of images and video has been around almost as long as photography and film have. The technology and practices around visual and auditory manipulation improved over the course of the 20th century, with deepfake technology developing at academic institutions in the early 1990s. Later, amateurs began developing deepfake technology on their own, and, more recently, deepfakes have been used by companies and other organizations as well.

The term “deepfake” itself originated on Reddit. Users shared deepfake videos they had created on the subreddit r/deepfakes, where the majority of videos involved swapping celebrities’ faces onto the bodies of adult actresses in pornographic videos. The subreddit r/deepfakes was shut down on February 7, 2018 for “involuntary pornography” due to the nonconsensual nature of the media, but other online communities continue to share pornography on platforms that have not banned deepfake pornography. On Reddit, there are still communities that share deepfakes, but they depict non-pornographic scenarios.

The Appeal of Deepfakes

Entertainment and Pop Culture

Perhaps one of the first and most popular uses of deepfakes in popular culture was the 2019 Bill Hader impressions video created by YouTube channel Ctrl-Shift-Face. The video took a clip of actor and comedian Bill Hader on David Letterman impersonating Tom Cruise and Seth Rogen. Though the original clip was from 2008, the new video showed Hader’s face morphing into the faces of Cruise and Rogen, depending on who he was imitating.

To date, the video has received nearly 12 million views on YouTube.

In an interview with The Guardian, the YouTuber behind the video stated that he made it to raise awareness of the power of face-swapping and deepfake technology in “the age of fake news and footage,” stating, “People need to learn to be more critical. The general public are aware that photos could be Photoshopped, but they have no idea that this could be done with video.”

In 2021, deepfakes are becoming more and more prominent in popular media. Recent Star Wars films have featured computer-generated versions of Peter Cushing (Grand Moff Tarkin) and Carrie Fisher (Princess Leia) as they appeared in the original 1977 film. Marvel films have also made use of this technology, aging down many characters in several films set in the MCU.

Paul McCartney, in a collaboration with Beck, featured a younger version of himself in the music video for “Find My Way.”

In the video, the current Paul McCartney even makes an appearance, looking over at his younger alter-ego.

Social Media

Social media has been credited with fueling the spread of deepfakes, due in large part to applications and software that allow users to to create their own. Apps like FakeApp, Faceswap, Zao, and, more recently, Impressions, have all become popular for users to swap faces with each other and impose their own faces on images and videos of celebrities with a computer or mobile phone, and has made creating deepfakes much more accessible to the average person.

Memes that utilize deepfake technology have also become more prevalent, the most popular of which being the inclusion of Nicolas Cage in several movies, such as The Sound of Music:

However, the use of deepfakes on social media has not just been fun and games. Several reports indicate that deepfakes have been used to create fake or false social media profiles for non-existent people – called sockpuppets. These fake accounts have been used for propaganda, perpetuating fake news or false narratives, and catfishing or misleading social media users.

Though many social media platforms have begun screening content for deepfakes, it has been reported that only around two-thirds are detected.

The Darker Side of Deepfakes

While these are some of the lighter or more positive applications of deepfakes, deepfakes can be considered controversial to say the least. Some utilization of deepfakes can be a bit more grey, if not downright shady (as we’ve already touched on in regards to the r/deepfakes subreddit, how the fake profiles are used on social media, etc.).

The majority of news and attention around deepfakes centers around celebrity pornographic videos, revenge porn, misinformation and hoaxes, fake news, blackmail, and fraud.

Pornography

It is nearly impossible to talk about the applications of deepfakes without talking about pornography. According to Dutch startup Deeptrace, pornography made up 96% of deepfake videos found online in 2019, with 99% of those featuring the faces of female celebrities. Typically, deepfakes featuring pornography of people uses their likeness without their consent. And this does not just apply to celebrities. Deepfake technology has been used in cases of revenge porn against non-public facing people as well.

In a 2021 study out of Northwestern University, a majority of American adults reported nonconsenually-created pornographic deepfake videos as extremely harmful, and overwhelmingly wanted to impose a criminal sanction on those creating them. Even when the videos were labeled as fictional, there was no impact on the videos’ perceived wrongfulness. Even further, those surveyed judged the creation and dissemination of deepfake pornography to be “as harmful as the dissemination of traditional nonconsensual pornography, otherwise known as revenge porn, and to be slightly more morally blameworthy.”

Politics

Deepfakes have been used playfully in political satire, or to spread awareness for certain political issues, such as in the case of the 2020 Joaquin Oliver PSA. Joaquin Oliver, a victim of the Parkland shooting, was posthumously featured in a gun-safety voting campaign created by his parents with their nonprofit Change the Ref, as well as McCann Health.

But the impact of deepfakes in politics can go much further. Deepfakes have been used to misrepresent politicians and impact public political opinion through this misrepresentation. These videos, though often eventually identified as deepfakes, can have a significant impact on peoples’ opinions and perceptions, particularly on the audiences that they reach prior to being identified as deepfakes.

As mentioned above when talking about social media, false accounts using deepfakes have also impacted political conversations on social media platforms.

Misrepresentation

The misrepresentation of individuals in deepfakes has led to generation of blackmail materials to falsely incriminate people. As these videos and audio recordings can be difficult to verify, the negative impact on reputation can be difficult to recover from, even when verified as a deepfake.

However, the opposite can also be true. As discerning what is true versus a deepfake, people who receive negative press or attention for videos or audio from reputable sources can claim that authentic information is fake or false, granting plausible deniability. This can create a harmful dynamic – if it is difficult to determine the truth of a video, people can get away with saying things they did do, they didn’t.

The Impact of Deepfakes on Privacy, Policy, and Reputation

Privacy Concerns

Obviously, your image being used without your consent, particularly in compromising media, can be a violation of privacy. This can become even more significant when considering the believability of deepfakes.

However, this can be a bit complicated. Unlike authentic images being stolen and used without your permission, the inherent falseness of deepfake images means that victims of deepfakes can run into obstacles when claiming privacy violations, since the person depicted in the media is not them.

There are also privacy concerns involving the apps used to create deepfakes in the first place, with prominent companies like Zao facing public scrutiny for its invasive user data and privacy policy.

While it seems that deepfakes only create issues when it comes to privacy concerns, some make the argument that deepfake technology can remove the need for you to put your real face out there, maintaining your anonymity. But this brings up other concerns about how your identity informs what you say, where your perspective is coming from, and how you are responded to, and brings into question concerns of identity and anonymity.

Legal Considerations

There is growing legal consideration when it comes to how to handle deepfakes. In 2018, the Malicious Deep Fake Prohibition Act was introduced to the US Senate. In 2019, the DEEPFAKES Accountability Act was introduced in the House of Representatives. Several states, including Virginia, Texas, California, and New York, have already passed laws regulating deepfakes, and more will likely follow. Most of these laws are focused on nonconsensual deepfake pornography and malicious deepfake audio or visual media targeting a candidate running for public office.

There is also a push to have nonconsensual deepfake pornography treated “under the First Amendment as prohibitions on tradition nonconsensual pornography rather than being dealt with under the less-protective law of defamation,” and a call for deepfake-specific laws and consequences are on the rise.

Reputation: Loss of Credibility and Authenticity

The impact of deepfakes on reputation, credibility, and authenticity can be substantial and severe.  Several experts fear the impact of deepfakes on public perception, particularly as the rate of growth regarding believability of deepfakes outpaces public awareness of them.

Though some social media platforms have worked to limit the prevalence of deepfakes, such as Twitter banning accounts posting nonconsensual deepfake content, and search engines such as Google adding “involuntary synthetic pornographic imagery” to its ban list, the amount of deepfakes, and convincing deepfakes, available online are growing.

While deepfakes may not be able to stand up completely against reality, the fear regarding their impact on perception stems from impacting smaller groups or single individuals by creating a narrative powerful and convincing enough to influence their opinions.

And it works both ways. While deepfakes do not only act to misrepresent people, they also provide people an opportunity to misrepresent their true actions, by claiming falseness about authentic media. As people become more skeptical of what they see, or, if they don’t, and what they see is false, authenticity is harder to find.

What’s more, the impact on reputation does not only affect public figures. While celebrities and politicians may be more likely to be targeted by deepfakes in the first place, they also have more recognition, resources, and status to help control the narrative. However, an ordinary person may struggle to prove the same about themselves if videos, images, or recordings showing them doing something distasteful, inappropriate, or worse comes to light.

Conclusion

As our lives move more into the digital space, the capabilities of emerging technologies and their applications can have a huge impact on culture, policy, and reputation. The rising prominence of deepfakes over the last few years has influenced an ongoing discussion of authenticity online, and the line between fact and fiction.

When it comes to your reputation, particularly online, the importance of a first impression is immense. In our scrolling culture, the effort deepfakes require from an audience to determine the legitimacy of media, if they even know to do so, can lead deepfakes to impact public opinion despite the fact that they may be misrepresenting, or entirely false.

However, as deepfakes continue to improve in their believability and grow in prominence, their own reputation is growing, too. Desire for authenticity and awareness of deepfakes, as well as policy limiting how they can be used, can help audiences be more discerning about what they see online, which in turn can keep the negative impacts of deepfakes at bay.