AI is Changing the Reality—Revealing the History of Deepfakes

In 2017, a Reddit user found a change by inventing ‘deepfake,’ a new but disturbing type of AI-generated media. The moderator of the subreddit was dedicated to spreading deepfake porn while using photos and face-swapping systems of celebrities. This explicit deep fake spread rapidly in no time before it could be banned; however, its influence became unrepairable and turned out to be a dark point in the history of deepfakes. 

Deepfake AI originated from the terms ‘deep learning’ and ‘fake’ utilizing the latest machine learning and AI to generate extremely realistic but fake videos or multimedia. This technology hides the thin line between reality and exploitation raises serious issues, and may become a cause of misleading, spreading exploitation, and the manipulation of identities. Deepfake has many advantages related to entertainment, research, and face swapping skills that it lead to an important societal dilemma that threatens privacy and public trust.

Deepfakes Origin—Exploring the Technology’s Early Days

Deepfakes use the latest artificial intelligence to generate convincing but fake media, which gained attention since 2010 with machine learning advancement and computing power. In 2014, Ian Goodfellow developed Generative Adversarial Networks, a form of creating highly realistic and convincing deepfakes. One notable example dates back to 1997 when the Video Rewrite Program, developed by Bregler, Covell, and Slaney, synthesized new facial animations from audio. 

Although furor over deepfakes hit the world in the 2010s with the growth of sophisticated AI and machine learning, it originated in the 1990s. Researchers were then using CGI to render pictures of humans; however, since the achievement of the invention of Generative Adversarial Networks (GANs) by Ian Goodfellow in 2014, deepfakes have more significantly developed, providing unparalleled quality in fake media production. 

Early synthetic media were seen long ago in the form of CGI. However, modern deepfakes, more so the GAN-powered advanced AI-based deepfakes, have been able to create fake content that is far more convincing and available for public access. Deepfake technology is now being used not only for entertainment but even for criminal goals, including the creation of fake pornography, false political information, and victimization through forged media. Even celebrities and a common person have been targeted by the deepfakes to date. Pope Francis and Queen Elizabeth along with other political leaders are famous examples of viral deepfakes. 

How Deepfake Technology Progressed Eventually

The change in deepfake technology has an important part in its broadening to average internet users. However, in 2017, free deepfake availability creation tools provided the chance for experts and users to try something new with technology. Some use it for dangerous fun, for instance, memes or actor face-swapping in movies but others take it to the darker path, utilizing it for wrong purposes such as deepfake pornography. The bold contribution of average regular users has enhanced this system’s huge adoption and development, making it more experienced and difficult to detect.  

Impact of Open-Source Tools and User Participation

Deepfake tools have become more widely available because they allow everyone, from experts to fraudsters to generate and distribute. The modification of this technology provides more growth chances that can be the cause of serious misuse. The more access will be easy to these tools, the more harmful deepfakes will be created, for instance, celebrity deepfake videos or exploited political content—which is a growing issue. 

Regulatory Concerns and Slow Response

2018 was a year when experts started showing their concerns regarding the rapid deepfake technology’s advancement. Besides, tech companies also introduced new policies to stop deepfake misuse, while the U.S. initiated exploring the laws to regulate the generation and spread. The response has been slow, with glaring gaps for misuse. Companies, governments, and institutions still struggle to meet the challenge that this fast-changing technology presents: faster, more effective regulatory and technological countermeasures are needed. 

Deepfake Attacks vs. Deepfakes

Deepfakes are a huge grouping of artificially generated media that can start from dangerous fun, for instance, face morphing or swapping in movies. Also, it is being used in the regular memes on social media and for the wrong purposes. Common deepfake usually involves AI usage and ML algorithms to generate realistic yet fake images, videos, or audio. They are usually created for entertainment or educational purposes and have no negative results. There are some milestones in deepfake development involving advancements in artificial intelligence and machine learning that made it easy for inexperienced people to generate realistic fabricated media. 

Deepfake Attacks

More dangerous, however, is this use of the technology to commit deepfake attacks. These are deliberately applied to target people for crimes like fraud, identity theft, misinformation, and blackmail. In these attacks, deepfakes often impersonate individuals, manipulate public opinion, or create a scandal against public figures or organizations. The end can be the manufacture of fake speeches or statements from politicians or company CEOs to manipulate the public or to create instability in financial markets. Such malicious intent makes deepfakes attacks different from harmless deepfakes as they aim to exploit, deceive, and harm.

Solutions to Deepfake Attacks

Besides, the ever-emerging deepfakes offer more alternatives to mitigate such attacks. The most discussed one is the advancement of deepfake detection. Such AI-powered tools would inspect video and audio patterns, like pixel inconsistency or unnatural movement within a face, to identify if the content is already manipulated. Indeed, deepfake detection development is a landmark in the world of deepfakes. They are critical to identifying fake media more efficiently.

Another innovation that’s now quite popular includes blockchain technology, which helps in the development of an open, tamper-proof record of where and when a video or image was created, making it possible to trace the content back to its source and verify legitimacy.

Moreover, legal frameworks are being designed in countries regarding the legal issues involved with deepfakes. Governments are drafting laws that punish malicious use of deepfakes, most especially fraud and identity theft, or non-consensual deepfake pornography. With this, improving techniques for the detection of deepfakes is critical in curbing the harm concerning the impact of deepfake attacks by providing a multi-layered approach to combating the misuse of this technology.

Governments vs. Deepfakes—Can Laws Keep Up with AI?

Several countries are taking part in setting the deepfake regulations including the U.S., the European Union, and China are making efforts to reduce such cases. However, in the U.S., some states like California and Texas have initiated laws picking out deepfakes in elections and non-consensual porn. Furthermore, European Unions spotlighted wrong information via its Digita Service Act. Also, China is working to regulate artificially created content, meanwhile, California Governor Gavin Newsom has taken further actions, enacting a series of laws to address the rising deepfakes threat in political campaigns. 

AB 2655: As introduced, authors will label or remove false or misleading election-related AI-created content on online sites and give officials the authority to take civil action if not complied with. AB 2839: Election materials created with the help of artificial intelligence are deemed unlawful for a longer time frame and open up to civil action, sponsored by Assemblymember Gail Pellerin. AB 2355—-political ads using AI-generated materials must have clear disclosure, signed by Assemblymember Wendy Carrillo. These deepfake law efforts indicate California’s energetic methods to prevent the election’s honesty while handling free speech and AI development as the state stays a leader in artificial progress.

Securing Digital Platforms from Deepfake Threats

Deepfakes and faked photography are becoming rational, and saving online forums from such threats is becoming essential. Deepfakes are created by the use of AI to exploit audio, video, and images to spread wrong information and destroy someone’s reputation or disrupt elections. Every social forum must execute the latest detection tools, enhance strict content policies, and combine with artificial experts to protect the deepfake technology’s misuse and fabricated photos. 

The incorporation of authentication systems, checking the content closely, and being vigilant to evolve artificial abilities enable online forums to make better prevention users and balance digital information honesty. 

Protect the Society with FACIA

In their history over time, deepfakes are ultra-realistic yet carry subtle indications that may help identify their artificial nature. Facia’s advanced detection software pans out all the minute details, such as eye and lip movements, facial shadows, and reflections that work to pop the deepfakes. All our technology is built on seamless API integration, so it is easy for any platform to add our solution. 

Additionally, since deepfakes are not geographically or demographically bound, Facia detection models are prepared against the complete range of datasets so that they have actual precision across these groups. Our deepfake detection consistently outperforms competitors with industry-leading precision in its multiple uses; it can be operated on its own or as part of a system for ongoing analysis.