IB 
Union Calendar No. 213 
116TH CONGRESS 
1ST SESSION H. R. 4355 
[Report No. 116–268] 
To direct the Director of the National Science Foundation to support research 
on the outputs that may be generated by generative adversarial networks, 
otherwise known as deepfakes, and other comparable techniques that 
may be developed in the future, and for other purposes. 
IN THE HOUSE OF REPRESENTATIVES 
SEPTEMBER 17, 2019 
Mr. GONZALEZ of Ohio (for himself, Ms. STEVENS, Mr. BAIRD, and Ms. HILL 
of California) introduced the following bill; which was referred to the 
Committee on Science, Space, and Technology 
NOVEMBER 5, 2019 
Additional sponsors: Ms. SHERRILL, Ms. WEXTON, Miss GONZA´LEZ-COLO´N of 
Puerto Rico, Ms. SLOTKIN, Mr. LUCAS, and Ms. SPANBERGER 
Reported with an amendment, committed to the Committee of the Whole 
House on the State of the Union, and ordered to be printed 
[Strike out all after the enacting clause and insert the part printed in italic] 
[For text of introduced bill, see copy of bill as introduced on September 17, 2019] 
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A BILL 
To direct the Director of the National Science Foundation 
to support research on the outputs that may be gen-
erated by generative adversarial networks, otherwise 
known as deepfakes, and other comparable techniques 
that may be developed in the future, and for other pur-
poses. 
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Be it enacted by the Senate and House of Representa-
tives of the United States of America in Congress assembled, 
SECTION 1. SHORT TITLE. 
This Act may be cited as the ‘‘Identifying Outputs of 
Generative Adversarial Networks Act’’ or the ‘‘IOGAN Act’’. 
SEC. 2. FINDINGS. 
Congress finds the following: 
(1) Research gaps currently exist on the under-
lying technology needed to develop tools to identify 
authentic videos, voice reproduction, or photos from 
manipulated or synthesized content, including those 
generated by generative adversarial networks. 
(2) The National Science Foundation’s focus to 
support research in artificial intelligence through 
computer and information science and engineering, 
cognitive science and psychology, economics and game 
theory, control theory, linguistics, mathematics, and 
philosophy, is building a better understanding of how 
new technologies are shaping the society and economy 
of the United States. 
(3) The National Science Foundation has identi-
fied the ‘‘10 Big Ideas for NSF Future Investment’’ 
including ‘‘Harnessing the Data Revolution’’ and the 
‘‘Future of Work at the Human-Technology Frontier’’, 
in with artificial intelligence is a critical component. 
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(4) The outputs generated by generative adver-
sarial networks should be included under the umbrella 
of research described in paragraph (3) given the grave 
national security and societal impact potential of 
such networks. 
(5) Generative adversarial networks are not like-
ly to be utilized as the sole technique of artificial in-
telligence or machine learning capable of creating 
credible deepfakes and other comparable techniques 
may be developed in the future to produce similar 
outputs. 
SEC. 3. NSF SUPPORT OF RESEARCH ON MANIPULATED OR 
SYNTHESIZED CONTENT AND INFORMATION 
SECURITY. 
The Director of the National Science Foundation, in 
consultation with other relevant Federal agencies, shall sup-
port merit-reviewed and competitively awarded research on 
manipulated or synthesized content and information au-
thenticity, which may include— 
(1) fundamental research on digital forensic tools 
or other technologies for verifying the authenticity of 
information and detection of manipulated or syn-
thesized content, including content generated by gen-
erative adversarial networks; 
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(2) fundamental research on technical tools for 
identifying manipulated or synthesized content, such 
as watermarking systems for generated media; 
(3) social and behavioral research related to ma-
nipulated or synthesized content, including the ethics 
of the technology and human engagement with the 
content; 
(4) research on public understanding and aware-
ness of manipulated and synthesized content, includ-
ing research on best practices for educating the public 
to discern authenticity of digital content; and 
(5) research awards coordinated with other fed-
eral agencies and programs including the Networking 
and Information Technology Research and Develop-
ment Program, the Defense Advanced Research 
Projects Agency and the Intelligence Advanced Re-
search Projects Agency. 
SEC. 4. NIST SUPPORT FOR RESEARCH AND STANDARDS ON 
GENERATIVE ADVERSARIAL NETWORKS. 
(a) IN GENERAL.—The Director of the National Insti-
tute of Standards and Technology shall support research for 
the development of measurements and standards necessary 
to accelerate the development of the technological tools to 
examine the function and outputs of generative adversarial 
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