Deepfake pornography

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Deepfake pornography, or simply fake pornography, is a type of synthetic pornography that is created via altering already-existing photographs or video by applying deepfake technology to the images of the participants. The use of deepfake pornography has sparked controversy because it involves the making and sharing of realistic videos featuring non-consenting individuals, typically female celebrities, and is sometimes used for revenge porn. Efforts are being made to combat these ethical concerns through legislation and technology-based solutions.

Contents

History

The term "deepfake" was coined in 2017 on a Reddit forum where users shared altered pornographic videos created using machine learning algorithms. It is a combination of the word "deep learning", which refers to the program used to create the videos, and "fake" meaning the videos are not real. [1]

Deepfake pornography was originally created on a small individual scale using a combination of machine learning algorithms, computer vision techniques, and AI software. The process began by gathering a large amount of source material (including both images and videos) of a person's face, and then using a deep learning model to train a Generative Adversarial Network to create a fake video that convincingly swaps the face of the source material onto the body of a pornographic performer. However, the production process has significantly evolved since 2018, with the advent of several public apps that have largely automated the process. [2]

Deepfake pornography is sometimes confused with fake nude photography, but the two are mostly different. Fake nude photography typically uses non-sexual images and merely makes it appear that the people in them are nude.

Notable cases

Deepfake technology has been used to create non-consensual and pornographic images and videos of famous women. One of the earliest examples occurred in 2017 when a deepfake pornographic video of Gal Gadot was created by a Reddit user and quickly spread online. Since then, there have been numerous instances of similar deepfake content targeting other female celebrities, such as Emma Watson, Natalie Portman, and Scarlett Johansson. [3] Johansson spoke publicly on the issue in December 2018, condemning the practice but also refusing legal action because she views the harassment as inevitable. [4]

Rana Ayyub

In 2018, Rana Ayyub, an Indian investigative journalist, was the target of an online hate campaign stemming from her condemnation of the Indian government, specifically her speaking out against the rape of an eight-year-old Kashmiri girl. Ayyub was bombarded with rape and death threats, and had doctored pornographic video of her circulated online. [5] In a Huffington Post article, Ayyub discussed the long-lasting psychological and social effects this experience has had on her. She explained that she continued to struggle with her mental health and how the images and videos continued to resurface whenever she took a high-profile case. [6]

Atrioc controversy

In 2023, Twitch streamer Atrioc stirred controversy when he accidentally revealed deepfake pornographic material featuring female Twitch streamers while on live. The influencer has since admitted to paying for AI generated porn, and apologized to the women and his fans. [7] [8]

Taylor Swift

In January 2024, AI-generated sexually explicit images of American singer Taylor Swift were posted on X (formerly Twitter), and spread to other platforms such as Facebook, Reddit and Instagram. [9] [10] [11] One tweet with the images was viewed over 45 million times before being removed. [12] [10] A report from 404 Media found that the images appeared to have originated from a Telegram group, whose members used tools such as Microsoft Designer to generate the images, using misspellings and keyword hacks to work around Designer's content filters. [13] [14] After the material was posted, Swift's fans posted concert footage and images to bury the deepfake images, and reported the accounts posting the deepfakes. [15] Searches for Swift's name were temporarily disabled on X, returning an error message instead. [16] Graphika, a disinformation research firm, traced the creation of the images back to a 4chan community. [17] [18]

A source close to Swift told the Daily Mail that she would be considering legal action, saying, "Whether or not legal action will be taken is being decided, but there is one thing that is clear: These fake AI-generated images are abusive, offensive, exploitative, and done without Taylor's consent and/or knowledge." [15] [19]

The controversy drew condemnation from White House Press Secretary Karine Jean-Pierre, [20] Microsoft CEO Satya Nadella, [21] the Rape, Abuse & Incest National Network, [22] and SAG-AFTRA. [23] Several US politicians called for federal legislation against deepfake pornography. [24] Later in the month, US senators Dick Durbin, Lindsey Graham, Amy Klobuchar and Josh Hawley introduced a bipartisan bill that would allow victims to sue individuals who produced or possessed "digital forgeries" with intent to distribute, or those who received the material knowing it was made non-consensually. [25]

2024 Telegram deepfake scandal

It emerged in South Korea in August 2024 that many teachers and female students were victims of deepfake images created by users who utilized AI technology. Journalist Ko Narin of Hankyoreh uncovered the deepfake images through Telegram chats. [26] [27] [28] On Telegram, group chats were created specifically for image-based sexual abuse of women, including middle and high school students, teachers, and even family members. Women with photos on social media platforms like KakaoTalk, Instagram, and Facebook are often targeted as well. Perpetrators use AI bots to generate fake images, which are then sold or widely shared, along with the victims’ social media accounts, phone numbers, and KakaoTalk usernames. One Telegram group reportedly drew around 220,000 members, according to a Guardian report.

Investigations revealed numerous chat groups on Telegram where users, mainly teenagers, create and share explicit deepfake images of classmates and teachers. The issue came in the wake of a troubling history of digital sex crimes, notably the notorious Nth Room case in 2019. The Korean Teachers Union estimated that more than 200 schools had been affected by these incidents. Activists called for a "national emergency" declaration to address the problem. [29] South Korean police reported over 800 deepfake sex crime cases by the end of September 2024, a stark rise from just 156 cases in 2021, with most victims and offenders being teenagers. [30]

On September 21, 6,000 people gathered at Marronnier Park in northeastern Seoul to demand stronger legal action against deepfake crimes targeting women. [31] On September 26, following widespread outrage over the Telegram scandal, South Korean lawmakers passed a bill criminalizing the possession or viewing of sexually explicit deepfake images and videos, imposing penalties that include prison terms and fines. Under the new law, those caught buying, saving, or watching such material could face up to three years in prison or fines up to 30 million won ($22,600). At the time the bill was proposed, creating sexually explicit deepfakes for distribution carried a maximum penalty of five years, but the new legislation would increase this to seven years, regardless of intent. [30]

By October 2024 it was estimated that "nudify" deep fake bots on Telegram were up to four million monthly users. [32] [33]

Ethical considerations

Deepfake CSAM

Deepfake technology has made the creation of child sexual abuse material (CSAM), also often referenced to as child pornography, faster, safer and easier than it has ever been. Deepfakes can be used to produce new CSAM from already existing material or creating CSAM from children who have not been subjected to sexual abuse. Deepfake CSAM can, however, have real and direct implications on children including defamation, grooming, extortion, and bullying. [34]

Differences from generative AI pornography

While both deepfake pornography and generative AI pornography utilize synthetic media, they differ in approach and ethical implications. [35] Generative AI pornography is created entirely through algorithms, producing hyper-realistic content unlinked to real individuals. [36] [37] In contrast, Deepfake pornography alters existing footage of real individuals, often without consent, by superimposing faces or modifying scenes. [38] [39] Hany Farid, a digital image analysis expert, has emphasized these distinctions. [40]

Most deepfake pornography is made using the faces of people who did not consent to their image being used in such a sexual way. In 2023, Sensity, an identify verification company, has found that "96% of deepfakes are sexually explicit and feature women who didn’t consent to the creation of the content." [41] Oftentimes, deepfake pornography is used to humiliate and harass primarily women in ways similar to revenge porn.

Combatting deepfake pornography

Technical approach

Deepfake detection has become an increasingly important area of research in recent years as the spread of fake videos and images has become more prevalent. One promising approach to detecting deepfakes is through the use of Convolutional Neural Networks (CNNs), which have shown high accuracy in distinguishing between real and fake images. One CNN-based algorithm that has been developed specifically for deepfake detection is DeepRhythm, which has demonstrated an impressive accuracy score of 0.98 (i.e. successful at detecting deepfake images 98% of the time). This algorithm utilizes a pre-trained CNN to extract features from facial regions of interest and then applies a novel attention mechanism to identify discrepancies between the original and manipulated images. While the development of more sophisticated deepfake technology presents ongoing challenges to detection efforts, the high accuracy of algorithms like DeepRhythm offers a promising tool for identifying and mitigating the spread of harmful deepfakes. [1]

Aside from detection models, there are also video authenticating tools available to the public. In 2019, Deepware launched the first publicly available detection tool which allowed users to easily scan and detect deepfake videos. Similarly, in 2020 Microsoft released a free and user-friendly video authenticator. Users upload a suspected video or input a link, and receive a confidence score to assess the level of manipulation in a deepfake.

As of 2023, there is a lack of legislation that specifically addresses deepfake pornography. Instead, the harm caused by its creation and distribution is being addressed by the courts through existing criminal and civil laws. [42]

Victims of deepfake pornography often have claims for revenge porn, tort claims, and harassment. [43] The legal consequences for revenge porn vary from state to state and country to country. [43] [44] For instance, in Canada, the penalty for publishing non-consensual intimate images is up to 5 years in prison, [45] whereas in Malta it is a fine of up to €5,000. [46]

The "Deepfake Accountability Act" was introduced to the United States Congress in 2019 but died in 2020. [47] It aimed to make the production and distribution of digitally altered visual media that was not disclosed to be such, a criminal offense. The title specifies that making any sexual, non-consensual altered media with the intent of humiliating or otherwise harming the participants, may be fined, imprisoned for up to 5 years or both. [44] A newer version of bill was introduced in 2021 which would have required any "advanced technological false personation records" to contain a watermark and an audiovisual disclosure to identify and explain any altered audio and visual elements. The bill also includes that failure to disclose this information with intent to harass or humiliate a person with an "advanced technological false personation record" containing sexual content "shall be fined under this title, imprisoned for not more than 5 years, or both." However this bill has since died in 2023. [48]

In the United Kingdom, the Law Commission for England and Wales recommended reform to criminalise sharing of deepfake pornography in 2022. [49] In 2023, the government announced amendments to the Online Safety Bill to that end. The Online Safety Act 2023 amends the Sexual Offences Act 2003 to criminalise sharing intimate images that shows or "appears to show" another (thus including deepfake images) without consent. [50] In 2024, the Government announced that an offence criminalising the production of deepfake pornographic images would be included in the Criminal Justice Bill of 2024. [51] [52] The Bill did not pass before Parliament was dissolved before the general election.

Controlling the distribution

While the legal landscape remains undeveloped, victims of deepfake pornography have several tools available to contain and remove content, including securing removal through a court order, intellectual property tools like the DMCA takedown, reporting for terms and conditions violations of the hosting platform, and removal by reporting the content to search engines. [53]

Several major online platforms have taken steps to ban deepfake pornography. As of 2018, gfycat, reddit, Twitter, Discord, and Pornhub have all prohibited the uploading and sharing of deepfake pornographic content on their platforms. [54] [55] In September of that same year, Google also added "involuntary synthetic pornographic imagery" to its ban list, allowing individuals to request the removal of such content from search results. [56]

See also

Related Research Articles

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<span class="mw-page-title-main">Internet Watch Foundation</span> Registered charity in Cambridge, England

The Internet Watch Foundation (IWF) is a global registered charity based in Cambridge, England. It states that its remit is "to minimise the availability of online sexual abuse content, specifically child sexual abuse images and videos hosted anywhere in the world and non-photographic child sexual abuse images hosted in the UK." Content inciting racial hatred was removed from the IWF's remit after a police website was set up for the purpose in April 2011. The IWF used to also take reports of criminally obscene adult content hosted in the UK. This was removed from the IWF's remit in 2017. As part of its function, the IWF says that it will "supply partners with an accurate and current URL list to enable blocking of child sexual abuse content". It has "an excellent and responsive national Hotline reporting service" for receiving reports from the public. In addition to receiving referrals from the public, its agents also proactively search the open web and deep web to identify child sexual abuse images and videos. It can then ask service providers to take down the websites containing the images or to block them if they fall outside UK jurisdiction.

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<span class="mw-page-title-main">Child pornography laws in the United States</span>

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