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Artificial intelligence isn't going away. This game-changing technology has the potential to improve efficiency by simply simulating human thought and can be trained to solve specific problems. According to
The landscape for artificial intelligence advancements is limitless and rapid, with new breakthroughs occurring daily. For example, in terms of AI videos and voices, we can anticipate new features being added and video generations becoming more
In many ways, this is a new frontier for ethics and risk assessment just as much as it is for other growing technologies. This has given rise to organizations adopting AI codes of ethics to formally specify the role of artificial intelligence in advancing humanity. An AI code of ethics' objective is to offer stakeholders with much-needed direction when faced with an ethical decision surrounding the use of artificial intelligence.
The term "deepfake" was first used in late 2017 by a Reddit user of the same name, who shared pornographic videos using open-source face-swapping technology on the Reddit site. The term has since been expanded to include "Synthetic Media Applications" that existed prior to the Reddit page, as well as new creations such as STYLE-GAN – "realistic-looking still images of people that don't exist."
Deepfake technology uses someone's behaviour – such as voice, face, common facial expressions, or bodily movements – to generate new audio or video content that is barely distinguishable from what is real. This technology could also be used to make people in the real world appear in videos and audios that say or do things they never said or did, to replace people in existing videos, or to create video content with completely non-existent characters, celebrities, or important prominent politicians; and this has raised numerous concerns about the ethics of deepfakes.
Deepfake effects used to take at least a year to create for experts in high-tech studios, but with the use of machine learning, the rapid development of deepfake technology over the years has made the creation of truly convincing fake content much easier and faster.
Deepfakes began with the development of Artificial Neural Networks (ANNs). An ANN is a machine learning model that is built on a network of neurons that is remarkably similar to the human brain. It differs, though, in that the AI does not make predictions about new data supplied to it; instead, it creates new data. These algorithms are known as Generative Adversarial Networks (GANs), and recent breakthroughs have fueled research and development, resulting in the emergence of deepfakes.
Convolutional Neural Networks (CNNs), which are based on ANNs, simulate how the visual cortex processes images in order to perform computer image recognition. Artificial and Convolutional Neural Networks lay the basis for deep learning programs and underlie the algorithms that generate deepfakes today: Generative Adversarial Networks.
Face-swapping apps, such as Zao and Faceapp (one of the earliest deepfake successes), for example, allow users to swap their faces with another person's, occasionally a celebrity's, to create a deepfake or
This new technology has justifiably aroused worries about privacy and identity. But, if an algorithm can build our looks, will it be possible to replicate even more characteristics of our own digital identity, such as our voice – or perhaps create a full-body double?
Deepfakes pose a significant threat to our community, political system, and business because they put pressure on journalists who are struggling to distinguish between real and fake news, endanger national security by publishing propaganda and disrupting elections, undermine citizen trust in authorities, and raise cybersecurity concerns for individuals and organizations.
Deepfakes are most likely posing the greatest danger to the journalistic business as they are more dangerous than "conventional" fake news since they are more difficult to detect, and consumers are more likely to assume the fake is real. In addition, the technology enables the creation of ostensibly credible news videos, putting journalists' and the media's reputations in danger.
It is enough for intelligence agencies to have some fear, as deepfakes can be used to endanger national security by propagating political propaganda and interfering with election campaigns.
US intelligence authorities have often warned of the dangers of foreign involvement in American politics, particularly in the run-up to elections.
A continuous stream of such recordings is also likely to impede digital literacy and citizens' trust in authority-provided information. Phoney recordings, which can easily be generated with a text to speech feature like Synthesys'
Another problem offered by deepfakes is cybersecurity vulnerabilities. Deepfakes could also be used to influence the market and stocks, for instance, by depicting a CEO speaking racist obscenities, announcing a fake merger, or presenting them as though they committed a crime. Furthermore, deepfake porn or product announcements could be used to harm a company's brand, blackmail, or humiliate management. Deepfake technology can also allow the digitalized impersonation of an executive, for example, to request an urgent cash transfer or private information from an employee.
Despite the potential hazards presented by deepfake technology, it can have
For example, in movies where actors' voices have been lost due to disease, deepfake technology can assist in creating synthetic voices or updating film footage rather than remaking it. As a result, moviemakers will be able to reproduce old movie scenes, create new films that can star long-dead actors,
Deepfake technology also enables natural voice dubbing for films in any language, letting various audiences enjoy films and educational materials more effectively. A
Deepfakes technology provides improved telepresence in online games and virtual chat worlds, natural-sounding and -looking smart assistants, and virtual replicas of individuals. This contributes to the development of better human relationships and online engagement.
Businesses also have much to benefit from the possibilities of brand-applicable deepfake technology because it has the ability to significantly revolutionize e-commerce and advertising.
For example, Deepfake technology can enable virtual fittings to give customers the ability to preview how an outfit would appear on them before purchasing and may make personalized fashion commercials that vary depending on time, weather, and viewer, as well as create
Broad-scale innovation is an ethical issue since ethics is basically concerned with anything that can enhance or hinder human well-being. As a result, ethics is important in judging the goals of innovation, such as deepfakes, as well as the process by which it is carried out and the outcomes that result from it. The fundamental question is, "Who are deepfakes designed for?"
"What is the purpose of their creation?" "How can the most severe consequences be mitigated?" Answering these questions can help organizations and individuals align with the following