Deepfake | Sociamonials Blog

Faux-semblant

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Deepfake technology, a rapidly progressing field, specializes in generating forged yet extremely convincing images, videos, or audio clips. With its roots tracing back to the 19th-century photo alteration, the technology took a significant leap forward in the vidéo numérique^[1] era of the 1990s. Through the application of techniques such as Generative Adversarial Networks (GANs), deepfakes have reached an unprecedented level of realism. Yet, they come with their share of disputes, including ethical concerns, particularly in the realm of pornography, and the risk of being utilized for spreading désinformation^[2], leading to discussions about regulatory measures. Despite the controversies, deepfakes have found commendable uses in sectors like entertainment, where they’re employed for visual effects and de-ageing roles, and in corporate training, where they enable the creation of customized videos. However, as the evolution of deepfakes persists, the dialogue about their societal influence and the potential for exploitation remains ongoing.

Définitions des termes

1. ↑ vidéo numérique. Le sujet principal de ce passage, la vidéo numérique, est une méthode d'enregistrement numérique qui utilise un signal numérique au lieu d'un signal vidéo analogique. Cette technologie a vu le jour lorsque des capteurs d'image MOS ont été incorporés dans les caméras vidéo numériques. Depuis sa création, elle a évolué de manière significative, marquée par la création du premier capteur d'image à semi-conducteur, le CCD, et par la transition de l'industrie du divertissement vers l'imagerie numérique. À l'heure actuelle, la vidéo numérique est largement utilisée dans divers secteurs, tels que le divertissement, l'éducation et la recherche. Elle est également utilisée dans diverses applications telles que la surveillance, le stockage et le contrôle des signes vitaux dans l'industrie des soins de santé. L'une des caractéristiques de la vidéo numérique est sa capacité à être dupliquée et distribuée sans effort et sans perte de qualité. Elle offre également diverses possibilités de stockage, notamment les disques Blu-ray, les dispositifs de stockage de données et la diffusion en continu sur l'internet. Ses éléments techniques comprennent l'utilisation de la bande passante pour les vidéos en direct et l'utilisation du stockage pour les vidéos enregistrées, la compression réduisant considérablement l'utilisation des données. Il existe également des formats vidéo distincts pour les consommateurs et les professionnels. La résolution la plus élevée de la vidéo numérique présentée jusqu'à présent est de 132,7 mégapixels.

2. ↑ désinformation. Disinformation, a term rooted in the Proto-Indo-European language family, is the deliberate propagation of inaccurate or misleading data, typically for political or sociocultural manipulation. This practice gained prominence in the 1980s and has been the focus of comprehensive research to decipher its origins, techniques, and effects. Disinformation is frequently employed in deceptive strategies on social platforms and is distinct from misinformation and malinformation. It's prevalent in political contexts, often muddling citizens and disheartening their participation. Disinformation has worldwide consequences, utilized by governments, NGOs, and global businesses. It poses a threat to the integrity of elections and can instigate societal rifts. Entities like NATO and the EU have implemented various strategies to tackle this problem. The exploration of disinformation also encompasses ethical aspects and its application in warfare. Despite these initiatives, disinformation continues to be a persistent issue due to its ubiquitous presence and the challenge in gauging its real impact.

Faux-semblant (Wikipedia)

It has been suggested that this article be merged avec Synthetic media. (Discuss) Proposed since January 2024.

Deepfakes (portmanteau de "deep learning" and "fake") are synthetic media that have been digitally manipulated to replace one person's likeness convincingly with that of another. It can also refer to computer-generated images of human subjects that do not exist in real life. While the act of creating fake content is not new, deepfakes leverage tools and techniques from apprentissage automatique et intelligence artificielle, y compris facial recognition algorithms and artificial neural networks tels que variational autoencoders (VAEs) and generative adversarial networks (GANs). In turn the field of image forensics develops techniques to detect manipulated images.

Deepfakes have garnered widespread attention for their potential use in creating child sexual abuse material, celebrity pornographic videos, revenge porn, fake news, canulars, bullyinget financial fraud. The spreading of disinformation and hate speech through deepfakes has a potential to undermine core functions and norms of democratic systems by interfering with people's ability to participate in decisions that affect them, determine collective agendas and express political will through informed decision-making. This has elicited responses from both industry and government to detect and limit their use.

From traditional entertainment à jeux, deepfake technology has evolved to be increasingly convincing and available to the public, allowing the disruption of the entertainment and médias industries.