Jan. 31, 2024, 2:10 a.m. | Mikihiro Kasahara, Taiki Oka, Vincent Taschereau-Dumouchel, Mitsuo Kawato, Hiroki Takakura, Aurelio Cortese

cs.CR updates on arXiv.org arxiv.org

While generative AI is now widespread and useful in society, there are
potential risks of misuse, e.g., unconsciously influencing cognitive processes
or decision-making. Although this causes a security problem in the cognitive
domain, there has been no research about neural and computational mechanisms
counteracting the impact of malicious generative AI in humans. We propose
DecNefGAN, a novel framework that combines a generative adversarial system and
a neural reinforcement model. More specifically, DecNefGAN bridges human and
generative AI in a closed-loop …

arxiv computational decision domain generative generative ai humans impact loop making malicious problem processes research risks security society system

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