Computer Vision and Algorithmic Ethics: Challenges in the Recognition and Detection of Deepfakes
Computer Vision and Algorithmic Ethics: Challenges in the Recognition and Detection of Deepfakes
DOI:
https://doi.org/10.51473/rcmos.v2i2.2022.1865Keywords:
computer vision; algorithmic ethics; deepfake; artificial intelligence; detection.Abstract
The rise of deepfakes represents one of the greatest ethical and technological challenges of the 21st century. Based on computer vision and deep learning techniques, these manipulated contents challenge the limits of digital trust and the very notion of truth in contemporary media. This scientific paper examines the intersections between computer vision evolution and algorithmic ethics, highlighting how advances in convolutional neural networks and generative adversarial models (GANs) affect digital forgery detection and recognition. The analysis covers not only the technical dimension but also the social, legal, and moral implications involved in the dissemination of deepfakes, pointing out pathways for developing ethical and transparent systems.
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