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Deepfakes & Algorithmes: Menace ou Opportunité ?

Authors: Rannou, Emilie; Benichoux, Alexis; Forgeas, Rémi; Gaillard, Simon; Mary, Jérémie; Trinh, Minh; TURINICI, Gabriel; +1 Authors

Deepfakes & Algorithmes: Menace ou Opportunité ?

Abstract

Les deepfakes apparaissent désormais comme un outil de manipulation dont l'impact sur la société est encore peu maîtrisé. Leur existence et utilisation soulèvent de nombreuses questions d’ordre légal et éthique. Mais, au-delà des lois et règles de gouvernance susceptibles d’être mises en place, un problème fondamental demeure, celui de l’incapacité à détecter un deepfake. Alors que la technologie évolue, il s’avère de plus en plus compliqué d’identifier un faux. Développer une connaissance européenne des outils de détection de faux et aussi de reconnaissance du vrai apparaît urgent. Face à l’ensemble de ces enjeux, le dernier rapport Praxis, Deepfakes & Algorithme, formule douze recommandations autour de quatre grand axes stratégiques : Faire de l’Europe un leader dans la lutte contre les deepfakes Renforcer la responsabilité des plateformes au niveau européen Construire un environnement réglementaire adapté à une lutte efficace contre les deepfakes Protéger les citoyens de l’impact des deepfakes

Country
France
Keywords

fake news, deep fakes, variational auto-encoders, deep learning, 006.3, Intelligence artificielle, generative adversarial networks, artificial intelligence, algorithms, neural networks, GAN

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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0
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83
169
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