Facebook recently promised that it would increase efforts to remove so-called "deepfake" videos, including content that included "misleading manipulated media."
In addition to fears that deepfakes -- altered videos that appear to be authentic -- could impact the upcoming 2020 general election in the United States, there are growing concerns that they could ruin reputations and impact businesses.
A manipulated video that looks real could convince viewers to believe that the subjects in the video said things they didn't say, or did things they didn't do.
Deepfakes have become more sophisticated and easier to produce, thanks to artificial intelligence and machine learning, which can be applied to existing videos quickly and easily, achieving results that took professional special effects teams and digital artists hours or days to achieve in the past.
"Deepfake technology is being weaponized for political misinformation and cybercrime," said Robert Prigge, CEO of Jumio.
In one high profile case, criminals last year used AI-based software to impersonate a chief executive's voice and demand a fraudulent transfer of US$243,000, Prigge told TechNewsWorld.
"Unfortunately, deepfakes can also be used to bypass many biometric-based identity verification systems, which have rapidly grown in popularity in response to impersonation attacks, identity theft and social engineering," he added.
Facing Off Against Deepfakes
Given the potential for damage, both Facebook and Twitter have banned such content. However, it's not clear what the bans cover. For its part Facebook will utilize third-party fact-checkers, reportedly including more than 50 partners working worldwide in more than 40 languages.
"They're banning videos created through machine learning that are intended to be deceptive," explained Paul Bischoff, privacy advocate at Comparitech.
"The videos must have both audio and video that the average person wouldn't reasonably assume is fake," he told TechNewsWorld.
"A deepfake superimposes existing video footage of a face onto a source head and body using advanced neural network-powered AI to create increasingly realistic doctored videos," noted Prigge. "In other words, a deepfake looks to be a real person's recorded face and voice, but the words they appear to be speaking were never really uttered by them."
Defining Deepfakes
One troubling issue with deepfakes is simply determining what is a deepfake and what is just edited video. In many cases deepfakes are built by utilizing the latest technology to edit or manipulate video. News outlets regularly edit interviews, press conferences and other events when crafting news stories, as way to highlight certain elements and get juicy sound bites.
Of course, there have been plenty of criticisms of mainstream news media for manipulating video footage to change the context without AI or machine learning, simply using the tools of the editing suite.
Deepfakes generally are viewed as far more dangerous because it isn't just context that is altered.
"At its heart, a deepfake is when someone uses sophisticated technology -- artificial intelligence -- to blend multiple images or audio together in order to change its original meaning and convey something that is not true or valid," said Chris Olson, CEO of The Media Trust.
"From manipulating audio to creating misleading images, deepfakes foster the spread of disinformation as the end user typically doesn't know that the content or message is not real," he told TechNewsWorld.
"To varying degrees, social platforms have issued policies prohibiting the posting of highly manipulated videos that are not clearly labeled or readily apparent to consumers as fake," added Olson.
Still, "while these policies are a step in the right direction, they do not explicitly ban manipulated video or audio," he pointed out. "Having your account blocked isn't much of a deterrent."
Manipulation Without Malice
Facebook's ban and other efforts to ban or otherwise curb deepfakes do not apply to political speech or parodies.
Consent may be another issue that needs to be addressed.
"This is a great point -- fake videos and images can be defined broadly -- for example, anything that is manipulated," said Shuman Ghosemajumder, CTO of Shape Security and former fraud czar at Google.
"But most media created is, to some extent, manipulated," he told TechNewsWorld.
Manipulations include automatic digital enhancements to photos taken using modern cameras -- those equipped with HDR settings or other AI-based enhancement -- as well as filters, and aesthetic editing and retouching, noted Ghosemajumder.
"If most media is thus automatically marked on a platform as 'synthetic' or 'manipulated,' this will reduce the benefit of such a tag," he remarked.
The next step will be to figure out objective criteria to exclude that type of editing and focus on "maliciously manipulated" media, which could be an inherently subjective standard.
However, "it can't be a question of individuals consenting to be in videos, because no such consent is generally required of public figures or of videos and images that are taken in public places," observed Ghosemajumder, "and public figures are the ones that are most likely to be targeted by malicious users of these technologies."
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