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Deepfakes[edit]

A sketch originally released in May 2016 by The Tonight Show portrayed host Jimmy Fallon as Donald Trump and actor Dion Flynn as Barack Obama, in which Jimmy Fallon discussed his (Trump’s) latest Indiana primary win. In March 2019, this sketch was altered by superimposing the real Donald Trump and Barack Obama onto Jimmy Fallon and Dion Flynn. [1] In 2019, the number of views for Deepfake videos grew by 2,000% since 2018, and 60% of Deepfakes were found to be related to politics. [2]

Because debunking Deepfakes is a difficult and lengthy process, the growing use of politicians in Deepfakes has raised concerns that political elections will be impacted by these manipulated photos or videos. [3] In January 2019, the Worldwide Threat Assessment of the US Intelligence Community released a statement that future elections will be impacted by Deepfakes as adversaries of the United States are creating Deepfakes targeted towards the political campaigns of the United States and its allies. [4]

Synthetic Audio[edit]

Synthetic audio is often used to deceive companies via phone calls by creating audio through soundwaves to sound exactly like the real voice of an employee. Creating synthetic audio requires many sources of the impersonated person’s real voice, making public figures an easy target as there is footage of them readily available across the internet. According to Nisos, a cyber operating company, there are three things a synthetic audio creator needs to face to create a realistic audio file: finding relevant existing files with uninterrupted speech, being able to create a situation that would sounds authentic and require no further action on the part of the creator, and being able to use a pathway that would avoid in-time conversation as the audio needs to be pre-made. Putting together this audio take an immense amount of time to get as close to perfection as possible with mannerisms and common speech of the subject. [5]

Synthetic Audio Study[edit]

Nisos has used technology to study synthetic audio to see differences between real and fake audio and found that “through the use of Spectrum3d, an audio spectrogram, they were able to analyze voice waves and see how the fake audio replicated consistently strong sounds while natural audio followed the true wave lengths of the speakers voice”. The false audio was found to be deceptive with a lack of outside noises and the traditional robotic voice showing when the audio was played at different speeds. [5]

Concerns and Controversies[edit]

Experiences shape many of human's beliefs and feelings. The recognizable features of synthetic media lead to a more fluent engagement, which therefore increases the believability of the media while we process new information; this is called "metacognition experience". Synthetic media is considered "real-world material" and is known to be more believable than text. Consumers face the risk of losing trust in the media they consume. An increase in uncertainty can carry into other outlets and forms of media that are viable and have no connection to previous deepfake experiences. This can cause online behavior to change to an unhealthy or unsafe culture in the future. The loss of trust can cause a loss of online etiquette in general. [6]

Regulation[edit]

On December 20th 2019, United States President Donald Trump signed the first federal law regarding Deepfakes, the National Defense Authorization Act for Fiscal Year 2020 (NDAA). This law involved three primary aspects. First, it required that the Director of National Intelligence (DNI) provide an annual report on any weaponization made by foreign countries, specifically China and Russia, regarding Deepfake technology. Second, the DNI is also required to report to Congress when it is discovered that a foreign country or individual is using Deepfake technology towards a United States election. Lastly, this law provides that the DNI will run a Deepfakes competition, with up to a $5 million prize, to promote the "research, development, or commercialization of technologies to automatically detect machine-manipulated media.” [7]

Many social media companies have banned the use of synthetic media on their platforms. In February 2020, Twitter updated its general policies to state that users were not allowed to share synthetic or manipulated media that could cause harm. Tweets posted with this intent will be deleted, and continuous posts by a user would result in that user’s account being deleted. [8] In January 2020, Facebook added to their policies that the platform would utilize fact-checkers to remove non-comedic synthetic media as well as flag the photo or video in order to reduce its distribution within news outlets.

Other regulation concerning Synthetic Media include the Identifying Outputs of Generative Adversarial Networks (IOGAN) Act (H.R. 4355) which was approved by the United States House in December 9, 2019 and pending in Senate, requires the National Science Foundation (NSF) and National Institute of Standards and Technology (NIST) to research synthetic media, specifically GANS, as well as standards for this technology. [9]

The Deepfake Report Act of 2019 (S. 2065) passed the Senate on October 24, 2019 and Is pending in the House. This Act requires the Department of Homeland Security to report every year for five years on Deepfake technology. [10]

Potential Uses and Impacts[edit]

Parts inside of triple brackets( [[[ ... ]]] ) already exist in the main article and are copied over to show the change in article structure. This applies to the Potential Uses and Impacts section only.

Benefits[edit]

[[[Synthetic media techniques involve generating, manipulating, and altering data to emulate creative processes on a much faster and more accurate scale. As a result, the potential uses are as wide as human creativity itself, ranging from revolutionizing the entertainment industry to accelerating the research and production of academia. The initial application has been to synchronize lip-movements to increase the engagement of normal dubbing that is growing fast with the rise of OTTs. In the boarder picture, synthetic media will democratize media production cost and limit the need for expensive cameras, recording equipment and visual effects. Big news organizations are already exploring how they can use video synthesis and other synthetic media technologies to become more efficient and engaging.]]]

[[[Deep reinforcement learning-based natural-language generators have the potential to be the first AI systems to pass the Turing Test and potentially be used as advanced chatbots, which may then be used to forge artificial relationships in a manner similar to the 2013 film Her and spam believable comments on news articles.]]]

[[[One use case for natural-language generation is to generate or assist with writing novels and short stories, while other potential developments are that of stylistic editors to emulate professional writers. The same technique could then be used for songwriting, poetry, and technical writing, as well as rewriting old books in other authors' styles and generating conclusions to incomplete series.]]]

[[[Image synthesis tools may be able to streamline or even completely automate the creation of certain aspects of visual illustrations, such as animated cartoons, comic books, and political cartoons. Because the automation process takes away the need for teams of designers, artists, and others involved in the making of entertainment, costs could plunge to virtually nothing and allow for the creation of "bedroom multimedia franchises" where singular people can generate results indistinguishable from the highest budget productions for little more than the cost of running their computer. Character and scene creation tools will no longer be based on premade assets, thematic limitations, or personal skill but instead based on tweaking certain parameters and giving enough input.]]]

[[[A combination of speech synthesis and deepfakes has been used to automatically redub an actor's speech into multiple languages without the need for reshoots or language classes.]]]

[[[There has been speculation about deepfakes being used for creating digital actors for future films. Digitally constructed/altered humans have already been used in films before, and deepfakes could contribute new developments in the near future. Amateur deepfake technology has already been used to insert faces into existing films, such as the insertion of Harrison Ford's young face onto Han Solo's face in Solo: A Star Wars Story, and techniques similar to those used by deepfakes were used for the acting of Princess Leia in Rogue One.]]]

Generative Adversarial Networks, [[[GANs, can be used to create photos of imaginary fashion models, with no need to hire a model, photographer, makeup artist, or pay for a studio and transportation. GANs can be used to create fashion advertising campaigns including more diverse groups of models, which may increase intent to buy among people resembling the models. GANs can also be used to create portraits, landscapes and album covers. The ability for GANs to generate photorealistic human bodies presents a challenge to industries such as fashion modeling, which may be at heightened risk of being automated.]]]

[[[In 2019, Dadabots unveiled an AI-generated stream of death metal which remains ongoing with no pauses.]]]

[[[Musical artists and their respective brands may also conceivably be generated from scratch, including AI-generated music, videos, interviews, and promotional material. Conversely, existing music can be completely altered at will, such as changing lyrics, singers, instrumentation, and composition. In 2018, using a process by WaveNet for timbre musical transfer, researchers were able to shift entire genres from one to another. Through the use of artificial intelligence, old bands and artists may be "revived" to release new material without pause, which may even include "live" concerts and promotional images.]]]

Risks[edit]

[[[ Potential future hazards include the use of a combination of different subfields to generate fake news, natural-language bot swarms generating trends and memes, false evidence being generated, and potentially addiction to personalized content and a retreat into AI-generated fantasy worlds within virtual reality.]]]

Though synthetic media can be used to replicate anyone, it becomes more realistic with the higher amounts of existing data available to the creator. Existing footage and sound clips can be found in abundance for many high-profile individuals online, making it easier to create high quality deepfake images, videos, and audio bits. [6]

[[[ In 2019, Elon Musk warned of the potential use of advanced text-generating bots to manipulate humans on social media platforms. In the future, even more advanced bots may be employed for means of astroturfing or demonizing apps, websites, and political movements, as well as supercharging memes and cultural trends— including those generated for the sole purpose of being promoted by bots until humans perpetuate them without further assistance.]]]

[[[An increase in cyberattacks has also been feared due to methods of phishing, catfishing, and social hacking being automated by new technological methods.]]]

[[[ Natural-language generation bots mixed with image synthesis networks may theoretically be used to clog search results, filling search engines with trillions of otherwise useless but legitimate-seeming blogs, websites, and marketing spam.]]]

[[[ Neural network-powered photo manipulation has the potential to abet the behaviors of totalitarian and absolutist regimes. A sufficiently paranoid totalitarian government or community may engage in a total wipe-out of history using all manner of synthetic technologies, fabricating history and personalities as well as any evidence of their existence at all times. Even in otherwise rational and democratic societies, certain social and political groups may utilize synthetic to craft cultural, political, and scientific cocoons that greatly reduce or even altogether destroy the ability of the public to agree on basic objective facts. Conversely, the existence of synthetic media will be used to discredit factual news sources and scientific facts as "potentially fabricated."]]]

References[edit]

  1. ^ "The rise of the deepfake and the threat to democracy". the Guardian. Retrieved 2020-10-11.
  2. ^ Koetsier, John. "Fake Video Election? Deepfake Videos 'Grew 20X' Since 2019". Forbes. Retrieved 2020-10-11.
  3. ^ Chesney, Bobby; Citron, Danielle (2019). "Deep Fakes: A Looming Challenge for Privacy". California Law Review. 107 (6). doi:10.15779/z38rv0d15j.
  4. ^ Coats, Daniel (2019-01-29). "Worldwide Threat Assessment of the US Intelligence Community" (PDF). Retrieved 2020-10-11.{{cite web}}: CS1 maint: url-status (link)
  5. ^ a b Franceschi-Bicchierai, Lorenzo (19 July 2020). "The Rise of Synthetic Audio Deepfakes". Nisos. Retrieved 9 October 2020.{{cite web}}: CS1 maint: url-status (link)
  6. ^ a b Vaccari, Cristian; Chadwick, Andrew (January 2020). "Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News". Social Media + Society. 6 (1): 205630512090340. doi:10.1177/2056305120903408. ISSN 2056-3051.
  7. ^ "First Federal Legislation on Deepfakes Signed Into Law". JD Supra. Retrieved 2020-10-11.
  8. ^ "Synthetic and manipulated media policy". help.twitter.com. Retrieved 2020-10-11.
  9. ^ Gonzalez, Anthony (2019-12-10). "H.R.4355 - 116th Congress (2019-2020): Identifying Outputs of Generative Adversarial Networks Act". www.congress.gov. Retrieved 2020-10-14.
  10. ^ Portman, Rob (2019-10-29). "S.2065 - 116th Congress (2019-2020): Deepfake Report Act of 2019". www.congress.gov. Retrieved 2020-10-14.