This bill directs the National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST) to support research on generative adversarial networks. A generative adversarial network is a software system designed to be trained with authentic inputs (e.g., photographs) to generate similar, but artificial, outputs (e.g., deepfakes).

Specifically, the NSF must support research on the science and ethics of material produced by generative adversarial networks and NIST must support research to accelerate the development of tools to examine the function and outputs of generative adversarial networks.

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