Text: S.2904 — 116th Congress (2019-2020)All Information (Except Text)

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Public Law No: 116-258 (12/23/2020)

 
[116th Congress Public Law 258]
[From the U.S. Government Publishing Office]



[[Page 1149]]

                   IDENTIFYING OUTPUTS OF GENERATIVE 
                        ADVERSARIAL NETWORKS ACT

[[Page 134 STAT. 1150]]

Public Law 116-258
116th Congress

                                 An Act


 
  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. <<NOTE: Dec. 23, 2020 -  [S. 2904]>> 

    Be it enacted by the Senate and House of Representatives of the 
United States of America in Congress assembled, <<NOTE: Identifying 
Outputs of Generative Adversarial Networks Act. 15 USC 9101 note. 15 USC 
9101.>> 
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) Gaps currently exist on the underlying research needed 
        to develop tools that detect videos, audio files, or photos that 
        have manipulated or synthesized content, including those 
        generated by generative adversarial networks. Research on 
        digital forensics is also needed to identify, preserve, recover, 
        and analyze the provenance of digital artifacts.
            (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 identified the ``10 
        Big Ideas for NSF Future Investment'' including ``Harnessing the 
        Data Revolution'' and the ``Future of Work at the Human-
        Technology Frontier'', with artificial intelligence is a 
        critical component.
            (4) The outputs generated by generative adversarial 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 likely to be 
        utilized as the sole technique of artificial intelligence or 
        machine learning capable of creating credible deepfakes. Other 
        techniques may be developed in the future to produce similar 
        outputs.

[[Page 134 STAT. 1151]]

SEC. 3. <<NOTE: 15 USC 9102.>>  NSF SUPPORT OF RESEARCH ON 
                    MANIPULATED OR SYNTHESIZED CONTENT AND 
                    INFORMATION SECURITY.

    The Director <<NOTE: Consultation.>>  of the National Science 
Foundation, in consultation with other relevant Federal agencies, shall 
support merit-reviewed and competitively awarded research on manipulated 
or synthesized content and information authenticity, which may include--
            (1) fundamental research on digital forensic tools or other 
        technologies for verifying the authenticity of information and 
        detection of manipulated or synthesized content, including 
        content generated by generative adversarial networks;
            (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 manipulated or 
        synthesized content, including human engagement with the 
        content;
            (4) research on public understanding and awareness of 
        manipulated and synthesized content, including research on best 
        practices for educating the public to discern authenticity of 
        digital content; and
            (5) <<NOTE: Coordination.>>  research awards coordinated 
        with other federal agencies and programs, including the Defense 
        Advanced Research Projects Agency and the Intelligence Advanced 
        Research Projects Agency, with coordination enabled by the 
        Networking and Information Technology Research and Development 
        Program.
SEC. 4. <<NOTE: 15 USC 9103.>>  NIST SUPPORT FOR RESEARCH AND 
                    STANDARDS ON GENERATIVE ADVERSARIAL NETWORKS.

    (a) In General.--The Director of the National Institute 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 networks or other technologies that synthesize or 
manipulate content.
    (b) Outreach.--The Director of the National Institute of Standards 
and Technology shall conduct outreach--
            (1) to receive input from private, public, and academic 
        stakeholders on fundamental measurements and standards research 
        necessary to examine the function and outputs of generative 
        adversarial networks; and
            (2) to consider the feasibility of an ongoing public and 
        private sector engagement to develop voluntary standards for the 
        function and outputs of generative adversarial networks or other 
        technologies that synthesize or manipulate content.
SEC. 5. REPORT ON FEASIBILITY OF PUBLIC-PRIVATE PARTNERSHIP TO 
                    DETECT MANIPULATED OR SYNTHESIZED CONTENT.

    Not later than 1 year after the date of enactment of this Act, the 
Director of the National Science Foundation and the Director of the 
National Institute of Standards and Technology shall jointly submit to 
the Committee on Science, Space, and Technology of the House of 
Representatives, the Subcommittee on Commerce, Justice, Science, and 
Related Agencies of the Committee on Appropriations of the House of 
Representatives, the Committee on Commerce, Science, and Transportation 
of the Senate, and the

[[Page 134 STAT. 1152]]

Subcommittee on Commerce, Justice, Science, and Related Agencies of the 
Committee on Appropriations of the Senate a report containing--
            (1) the Directors' findings with respect to the feasibility 
        for research opportunities with the private sector, including 
        digital media companies to detect the function and outputs of 
        generative adversarial networks or other technologies that 
        synthesize or manipulate content; and
            (2) <<NOTE: Recommenda- tions.>>  any policy recommendations 
        of the Directors that could facilitate and improve communication 
        and coordination between the private sector, the National 
        Science Foundation, and relevant Federal agencies through the 
        implementation of innovative approaches to detect digital 
        content produced by generative adversarial networks or other 
        technologies that synthesize or manipulate content.
SEC. 6. <<NOTE: 15 USC 9104.>>  GENERATIVE ADVERSARIAL NETWORK 
                    DEFINED.

     In this Act, the term ``generative adversarial network'' means, 
with respect to artificial intelligence, the machine learning process of 
attempting to cause a generator artificial neural network (referred to 
in this paragraph as the ``generator'' and a discriminator artificial 
neural network (referred to in this paragraph as a ``discriminator'') to 
compete against each other to become more accurate in their function and 
outputs, through which the generator and discriminator create a feedback 
loop, causing the generator to produce increasingly higher-quality 
artificial outputs and the discriminator to increasingly improve in 
detecting such artificial outputs.

    Approved December 23, 2020.

LEGISLATIVE HISTORY--S. 2904 (H.R. 4355):
---------------------------------------------------------------------------

HOUSE REPORTS: No. 116-268 (Comm. on Science, Space, and Technology) 
accompanying H.R. 4355.
SENATE REPORTS: No. 116-289 (Comm. on Commerce, Science, and 
Transportation).
CONGRESSIONAL RECORD, Vol. 166 (2020):
            Nov. 18, considered and passed Senate.
            Dec. 8, considered and passed House.

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