,i #aafth ,,congress #ast ,session ,h4 ,r4 #dcee ,,in ,,the ,,house ,,of ,,representatives ,september #ag1 #bjai,mr4 ,gonzalez of ,ohio 7for himself1 ,ms4 ,stevens1 ,mr4 ,baird1 and ,ms4 ,hill of ,california7 introduced the following bill2 which was referred to the ,committee on ,science1 ,space1 and ,technology ,a ,,bill ,to direct the ,director of the ,national ,science ,foundation to support research on the outputs that may be generated by generative adversarial networks1 otherwise known as deepfakes1 and other comparable techniques that may be developed in the future1 and for other purposes4 #a4 ,short title ,this ,act may be cited as the ,identifying ,outputs of ,generative ,adversarial ,networks ,act or the ,,iogan ,act4 #b4 ,findings ,congress finds the following3 7#a7 ,research gaps currently exist on the underlying technology needed to develop tools to identify authentic videos1 voice reproduction1 or photos from those generated by generative adversarial networks4 7#b7 ,the ,national ,science ,foundation's focus to support research in artificial intelligence through computer and information science and engineering1 cognitive science and psychology1 economics and game theory1 control theory1 linguistics1 mathematics1 and philosophy1 is building a better understanding of how new technologies are shaping the society and economy of the ,united ,states4 7#c7 ,the ,national ,science ,foundation has identified the #aj ,big ,ideas for ,,nsf ,future ,investment including ,harnessing the ,data ,revolution and the ,future of ,work at the ,human-,technology ,frontier1 in with artificial intelligence is a critical component4 7#d7 ,the outputs generated by generative adversarial networks should be included under the umbrella of research described in paragraph 7#c7 given the grave national security and societal impact potential of such networks4 7#e7 ,generative adversarial networks are not likely to be utilized as the sole technique of artificial intelligence or machine learning capable of creating credible deepfakes and other comparable techniques may be developed in the future to produce similar outputs4 #c4 ,,nsf support of research for outputs of generative adversarial networks ,the ,director of the ,national ,science ,foundation1 in consultation with other relevant ,federal agencies1 shall support merit-reviewed and competitively awarded research on the science and ethics of material produced by generative adversarial networks1 which may include-- 7#a7 supplementing fundamental research on digital media forensic tools or comparable technologies for detection of the outputs of generative adversarial networks completed by the ,defense ,advanced ,research ,projects ,agency and the ,intelligence ,advanced ,research ,projects ,activity2 7#b7 fundamental research on developing constraint aware generative adversarial networks2 and 7#c7 social and behavioral research on the ethics of the technology1 and human engagement with the networks4 #d4 ,,nist support for research and standards on generative adversarial networks 7a7 ,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 networks4 7b7 ,outreach ,the ,director of the ,national ,institute of ,standards and ,technology shall conduct outreach-- 7#a7 to receive input from private1 public1 and academic stakeholders on fundamental measurements and standards research necessary to examine the function and outputs of generative of generative adversarial networks or to develop constraint aware generative adversarial networks2 and 7#b7 to consider the feasibility of an ongoing public and private sector engagement to develop voluntary standards for the outputs of generative adversarial networks or comparable technologies4 #e4 ,report on feasibility of public-private partnership to detect outputs of generative adversarial networks and comparable technologies ,not later than one year after the date of the enactment of this ,act1 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 ,science1 ,space1 and ,technology of the ,house of ,representatives and the ,committee on ,commerce1 ,science1 and ,transportation a report containing-- 7#a7 the ,directors' findings with respect to the feasibility for research opportunities with the private sector1 including digital media companies to detect the outputs of generative adversarial networks or comparable technologies2 and 7#b7 any policy recommendations of the ,directors that could facilitate and improve communication and coordination between the private sector1 the ,national ,science ,foundation1 and relevant ,federal agencies through the implementation of innovative approaches to detect media products produced by generative adversarial networks or comparable technologies4 #f4 ,definitions ,in this ,act3 7#a7 ,generative adversarial network ,the term generative adversarial network means1 with respect to artificial intelligence1 the machine learning process of attempting to cause a generator artificial neural network 7referred to in this paragraph as the generator and a discriminator artificial neural network 7referred to in this paragraph as a discriminator77 to compete against each other to become more accurate in their function and outputs1 through which the generator and discriminator create a feedback loop1 causing the generator to produce increasingly higher-quality artificial outputs and the discriminator to increasingly improve in detecting such artificial outputs4 7#b7 ,comparable technology ,the term comparable technology means technology that utilizes similar techniques to achieve the same outputs as a generative adversarial network4 7#c7 ,constraint aware ,the term constraint aware means1 with respect to artificial intelligence1 the generation of realistic relational data by a machine with constraint on the modules generated by an adversarial network4