IOGAN Act

Bill: 116-s-2904
Sponsor: Sen. Cortez Masto, Catherine [D-NV]
Introduced: 2019-11-20 in the Senate
Policy area: Science, Technology, Communications
Subjects: Advanced technology and technological innovations
Computers and information technology
Congressional oversight
Digital media
Government studies and investigations
Intergovernmental relations
Photography and imaging
Research administration and funding
Research and development
Research ethics
Technology assessment

Summary:
action_date: 2019-11-20
text: 

Identifying Outputs of Generative Adversarial Networks Act or the IOGAN Act

 
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 manipulated or synthesized content and information authenticity and NIST must 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. 

action_date: 2020-11-09
text: 

Identifying Outputs of Generative Adversarial Networks Act or the IOGAN Act

 
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 manipulated or synthesized content and information authenticity and the NIST must 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. 

action_date: 2020-11-18
text: 

Identifying Outputs of Generative Adversarial Networks Act or the IOGAN Act

 
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 manipulated or synthesized content and information authenticity and the NIST must 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. 

action_date: 2020-12-08
text: 

Identifying Outputs of Generative Adversarial Networks Act or the IOGAN Act

 
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 manipulated or synthesized content and information authenticity and the NIST must 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. 

action_date: 2020-12-23
text: 

Identifying Outputs of Generative Adversarial Networks Act or the IOGAN Act

 
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 manipulated or synthesized content and information authenticity and the NIST must 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. 


Legislative actions:
action_date: 2020-12-23
text: Became Public Law No: 116-258.
action_date: 2020-12-23
text: Became Public Law No: 116-258.
action_date: 2020-12-23
text: Signed by President.
action_date: 2020-12-23
text: Signed by President.
action_date: 2020-12-11
text: Presented to President.
action_date: 2020-12-11
text: Presented to President.
action_date: 2020-12-08
text: Motion to reconsider laid on the table Agreed to without objection.
action_date: 2020-12-08
text: On passage Passed without objection. (text: CR H7022-7023)
action_date: 2020-12-08
text: Passed/agreed to in House: On passage Passed without objection.
action_date: 2020-12-08
text: Mr. Tonko asked unanimous consent to take from the Speaker's table and consider.
action_date: 2020-12-08
text: Considered by unanimous consent. (consideration: CR H7022-7023)
action_date: 2020-11-19
text: Held at the desk.
action_date: 2020-11-19
text: Received in the House.
action_date: 2020-11-19
text: Message on Senate action sent to the House.
action_date: 2020-11-18
text: Passed Senate with an amendment by Unanimous Consent. (consideration: CR S7082-7083; text of amendment in the nature of a substitute: CR S7082-7083)
action_date: 2020-11-18
text: Passed/agreed to in Senate: Passed Senate with an amendment by Unanimous Consent.(consideration: CR S7082-7083; text of amendment in the nature of a substitute: CR S7082-7083)
action_date: 2020-11-09
text: Placed on Senate Legislative Calendar under General Orders. Calendar No. 580.
action_date: 2020-11-09
text: Committee on Commerce, Science, and Transportation. Reported by Senator Wicker with an amendment in the nature of a substitute. With written report No. 116-289.
action_date: 2020-11-09
text: Committee on Commerce, Science, and Transportation. Reported by Senator Wicker with an amendment in the nature of a substitute. With written report No. 116-289.
action_date: 2020-05-20
text: Committee on Commerce, Science, and Transportation. Ordered to be reported with an amendment in the nature of a substitute favorably.
action_date: 2019-11-20
text: Read twice and referred to the Committee on Commerce, Science, and Transportation.
action_date: 2019-11-20
text: Introduced in Senate

Enacted as: number: 116-258