EspañolWhat is it and how has the concept of “deepfakes” proliferated?
Deepfakes are faked images or videos created through the use of artificial intelligence (AI) and machine learning techniques. The term is derived from the combination of “deep learning” (deep learning) and “fake” (false). These techniques make it possible to manipulate and alter existing visual content to create visually compelling but fake material, where one person’s face in a video is swapped for another’s.
The proliferation of deepfakes is due to advances in AI technology and the availability of vast amounts of visual data online. These AI systems can automatically learn from these images and videos to generate new, realistic renderings.
Why are these practices carried out? What are your most common formats?
Deepfake creation practices are carried out for various reasons. Some people use them for satire, entertainment, or artistic content creation. However, there are also more worrying cases, where they are used to defame, extort, harass or manipulate public figures or ordinary individuals.
The most common formats of deepfakes are fake videos where a person’s face is swapped into an existing recording, although they can also include fake voice and text generation. Furthermore, deepfakes can vary in quality and level of realism, from those easily detectable to those that are almost indistinguishable from real video.
What emblematic cases of public figures have been victims of deepfakes?
Several public figures have been victims of deepfakes. For example, politicians, celebrities, and journalists (Pope Francis, Donald Trump, among others) have been targeted by fake videos that show them saying things they never said or engaging in compromising situations that didn’t happen. These cases can have serious repercussions on the reputation and privacy of the people affected.
What is the impact they entail, and how could this phenomenon be better regulated?
The impact of deepfakes is worrying because they can generate confusion and misinformation in society, eroding trust in visual media and information in general. In addition, deepfakes can be used for malicious purposes, such as rigging elections, smearing people, or generating conflict.
Regulating the phenomenon of deepfakes is a complex challenge due to the rapid evolution of technology and the difficulties in detecting them. A combination of technical and legal approaches is required to address the problem. Some potential solutions include developing more sophisticated deepfake detection tools, promoting standards and best practices for visual media authenticity, educating the public about the risks of deepfakes, and implementing specific laws and regulations that address the malicious use of this technology.
Image from rawpixel.com on Freepik
